System

Abstract

A system is provided.SOLUTION: A system including means for inputting target information and a product description, means for transmitting the input information to a generation model, means for generating a proposed advertisement using the generation model, means for receiving and displaying the generated proposed advertisement, means for selecting the displayed proposed advertisement, means for generating a presentation material on the basis of the selected proposed advertisement, means for generating a presentation video by adding audio to the presentation material, means for approving the generated presentation video, and means for uploading the approved presentation video onto a web.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] Traditionally, advertising designers and public relations personnel have spent a great deal of time and effort creating advertising proposals and preparing presentation materials. To solve this problem, an efficient and fast method for generating advertising proposals and creating presentation materials is required. However, with previous systems, it was difficult to achieve efficiency while maintaining a consistent quality of advertising proposals and presentation materials.

[0005] In addition, the approval process for the generated advertising proposals and presentation materials was cumbersome, and there was a need to automate certain approval steps. Therefore, a system was needed that would consistently streamline the entire process from advertising creation to approval and publication. [Means for solving the problem]

[0006] The present invention solves the above-mentioned problems by providing the following means.

[0007] A system is constructed that provides a means for inputting target information and product descriptions and a means for sending the input information to a generative model. A means for generating advertising proposals using the generative model is provided, and a means for receiving and displaying the generated advertising proposals is provided. A means for selecting the displayed advertising proposals is provided, and a means for generating presentation materials based on the selected advertising proposal is provided. A means for generating a presentation video by adding audio to the presentation materials is provided, and a means for approving the generated presentation video is provided. A system is constructed that provides a means for uploading the approved presentation video to the web.

[0008] This system allows advertising designers and public relations personnel to efficiently create advertising proposals with simple operations of "selection" and "approval," generate presentation videos, and finally publish them online all in one go.

[0009] "Target information" is information that indicates the characteristics of the customer base or market segment that is the target of the advertisement.

[0010] "Product description" is information that explains the features, functions, and benefits of the product or service being advertised.

[0011] A "generative model" is a machine learning algorithm or AI system that automatically generates advertising ideas based on input information.

[0012] An "advertising proposal" is an advertising proposal that includes a catchy slogan, advertising copy, and effectiveness predictions created by the generative model.

[0013] "Presentation materials" are slides and documents for presentations created based on the selected advertising proposal.

[0014] A "presentation video" is video content for presentations that includes audio and video.

[0015] "Approval" refers to the act of a user checking the content of the generated presentation materials or presentation video and ultimately agreeing to use them.

[0016] "Uploading to the web" means publishing an approved presentation video on an internet platform, website, or cloud service. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. Specific embodiments of the system are described below.

[0039] System configuration

[0040] The system consists of three main components:

[0041] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0042] 2. Server: This is the server that hosts the generative model and the presentation creation tool.

[0043] 3. Web platform: Web services and cloud storage for publishing the final presentation video.

[0044] Program processing explanation

[0045] The specific operations of each component of the system will be described below.

[0046] 1. Enter target information and product description

[0047] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[0048] 2. Generate advertising ideas

[0049] The device sends the input information to a server, which then uses a generative model to generate a large number of ad ideas based on the received information. The generative model uses machine learning algorithms and AI systems to propose new ad ideas based on past success stories.

[0050] 3. Select an ad idea

[0051] The server sends the generated advertisement suggestions to the user terminal and displays them on the user interface. The user selects the most suitable one from the proposed advertisement suggestions. The selected advertisement suggestion is then sent back to the server.

[0052] 4. Automatic generation of presentation materials and videos

[0053] The server activates a "presentation material generation module" based on the selected advertising proposal. The presentation material generation module converts the selected advertising proposal into slides for presentation. Next, the server uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[0054] 5. Approval and automatic upload

[0055] The generated presentation video is sent from the server to the user's device, where the user can review it and click the "Approve" button. Once approved, the server automatically uploads the video to the web platform.

[0056] Specific examples

[0057] Example: Advertisement for a new coffee maker

[0058] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[0059] 2. The server uses the generative model to generate a large number of ad ideas, including taglines such as "Start your day on a new level."

[0060] 3. The user selects the most attractive ad from the proposed ads.

[0061] 4. The server creates presentation materials based on the selected advertising proposal, and uses an automatic voice generation system to add audio such as "The latest coffee maker will change your mornings" to generate a presentation video.

[0062] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0063] Using this system, advertising designers and public relations personnel can efficiently create advertising proposals, generate presentation videos, and publish them online.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] The user enters target information and product description on the client terminal, entering detailed information such as target demographic, product features, and keywords through input fields in a web form or dedicated application.

[0067] Step 2:

[0068] The device sends the entered information to the server, and passes target information and product description data to the server using an API request.

[0069] Step 3:

[0070] The server then uses the received information to launch a generative model, which generates a large number of ad ideas. The generative model uses machine learning algorithms and AI systems, and references a database of past success stories.

[0071] Step 4:

[0072] The server sends the generated ad proposal to the user's device and returns the generated ad proposal and related data as an API response.

[0073] Step 5:

[0074] The device displays the received ad proposals on the user interface, along with a list of each proposal's catchphrase and predicted performance.

[0075] Step 6:

[0076] The user selects the most suitable ad from the displayed ad suggestions by clicking on the best ad suggestion from the options and then clicking on the "Select" button.

[0077] Step 7:

[0078] The device sends the selected ad proposal to the server again, and sends an API request including the identification information of the selected ad proposal.

[0079] Step 8:

[0080] The server starts the "presentation material generation module" and generates presentation materials based on the selected advertisement proposals. The server converts the text and images of the advertisement proposals into the required format to create slides for the presentation.

[0081] Step 9:

[0082] The server uses an automatic speech generation system to generate audio for each slide in the presentation, and a text-to-speech tool to convert the content of each slide into audio.

[0083] Step 10:

[0084] The server combines the generated audio with the slides to generate a video presentation. A video generation tool is used to add audio to the slides and create a video file.

[0085] Step 11:

[0086] The server sends the generated presentation video to the user's device and returns the completed video file as an API response.

[0087] Step 12:

[0088] The device displays the received presentation video on the user interface, and the user can view the video using a video player.

[0089] Step 13:

[0090] The user checks the presentation video and clicks the "Approve" button if there are no problems. If there are no problems with the presentation content, the approval operation is performed.

[0091] Step 14:

[0092] The device notifies the server of the approval operation and sends an API request including the approval information to the server.

[0093] Step 15:

[0094] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[0095] Example 1

[0096] 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."

[0097] The process of advertising designers and public relations personnel efficiently generating advertising proposals, creating presentation videos, and finally publishing them online is extremely time-consuming and labor-intensive when done manually. A system that automates and efficiently performs this process is needed. In particular, technology that can smoothly integrate each step, such as data entry, generating advertising proposals, creating presentation materials, generating audio, and creating and publishing the final presentation video, is needed.

[0098] 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.

[0099] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, and means for automating the generation and uploading of the presentation video. This makes it possible to efficiently perform processes from creating advertising proposals to generating the presentation video and publishing it on the web.

[0100] "Targeted Information" refers to information about a specific audience or group for advertising or marketing purposes.

[0101] "Product description" refers to information that explains the features, benefits, and usage of the products or services you offer.

[0102] "Generative modeling" refers to the technique of using machine learning algorithms and AI systems to generate new ideas and data.

[0103] "Advertising Proposal" refers to a proposal for a catchy slogan or visual content generated for the purpose of promoting a product or service.

[0104] "Presentation materials" refer to slides and documents created based on advertising proposals, and are materials used to visually convey information about products and services.

[0105] "Presentation video" refers to video content that adds audio and animation to presentation materials to dynamically convey information to viewers.

[0106] "Approval" refers to the act of finally reviewing the generated presentation video and giving permission before it is made public.

[0107] "Uploading to the web" refers to the act of publishing generated content on an internet platform or website.

[0108] "Automating the process of generating and uploading presentation videos" refers to a series of processes in which the system automatically creates presentation videos and publishes them on the web, without the need for manual work.

[0109] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. A specific embodiment of this system will be described below.

[0110] System configuration

[0111] The system consists of three main components:

[0112] 1. User devices: Computers and smart devices operated by advertising designers and public relations personnel. Specifically, these include personal computers, tablets, and smartphones.

[0113] 2. Server: A computer system that hosts the generative model and the presentation creation tool. The server must have high-performance processing power and sufficient storage capacity. A cloud-based server can also be used.

[0114] 3. Web Platform: Web services and cloud storage for publishing the final presentation video. Specifically, this includes the company's official website and video sharing services such as YouTube and Vimeo.

[0115] Program processing

[0116] The system program executes processing in the following manner.

[0117] 1. Enter target information and product description

[0118] A user inputs target information and a product description using a client terminal. The user inputs target information (e.g., "young professionals") and a product description (e.g., "coffee brewed with the latest technology, special design"), for example, through a web form or a dedicated application.

[0119] 2. Generate advertising ideas

[0120] The device sends the input information to a server. The server uses the received information to run a generative AI model to generate a large number of ad ideas. The generative AI model learns from past success stories and marketing data, and uses this data to propose new ad ideas.

[0121] 3. Select an ad idea

[0122] The server sends the generated advertisement suggestions to the user's terminal, which displays them through a user interface. The user selects the most suitable one from the presented advertisement suggestions and sends the selection result to the server via the terminal.

[0123] 4. Automatic generation of presentation materials and videos

[0124] The server automatically generates presentation materials based on the selected advertising proposals. The presentation material generation module converts the advertising proposals into slide format. The server then uses an automatic audio generation system to generate audio corresponding to each slide, thereby completing a presentation video with audio.

[0125] 5. Approval and automatic upload

[0126] The server sends the generated presentation video to the user's device, where the user can review and approve it. After approval, the server automatically uploads the presentation video to the web platform. This process reduces manual errors and greatly improves efficiency.

[0127] Specific examples

[0128] Example: Advertisement for a new coffee maker

[0129] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[0130] 2. The device sends the input data to the server, which uses the generative model to generate ad ideas including slogans such as "Start your day on a new level."

[0131] 3. The server sends the proposed advertisements to the user's terminal, and the user selects the most attractive one from the proposed advertisements.

[0132] 4. The server creates presentation materials based on the selected advertising proposal, uses an automatic voice generation system to generate audio such as "The latest coffee maker will change your morning," and creates a presentation video.

[0133] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0134] This system allows advertising designers and public relations personnel to efficiently create advertising proposals, generate presentation videos, and publish them online.

[0135] Example prompts for generative AI models

[0136] "To advertise coffee brewed using the latest technology, target information: young professionals. Product description: A coffee maker with a special design that uses the latest technology. Please create an ad proposal based on this information."

[0137] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0138] Step 1:

[0139] The user inputs target information and product description. The user inputs target information (e.g., "young professionals") and product description (e.g., "coffee brewed with the latest technology, special design") using a web form in a browser or a dedicated application. The input data is stored in a built-in data structure.

[0140] (Input) Target information, product description

[0141] (Output) Save the entered data

[0142] Step 2:

[0143] The device sends the entered information to the server, where the data is encrypted and securely transferred to the server.

[0144] (Input) Data entered

[0145] (Output) Data sent to the server

[0146] Step 3:

[0147] The server analyzes the target information and product description it receives. Based on the analysis results, the server creates a prompt for the generative AI model. The generative AI model is used to generate multiple ad proposals.

[0148] (Input) Data sent to the server

[0149] (Output) Generated ad ideas

[0150] Step 4:

[0151] The server sends the generated advertisement proposal to the user terminal, which temporarily stores the generated advertisement proposal in an internal database and sends it to the terminal for display through the user interface.

[0152] (Input) Generated ad ideas

[0153] (Output) Advertisement proposals sent to the device

[0154] Step 5:

[0155] The user selects the most suitable advertisement from the presented advertisements, and the information selected by the user is sent back to the server via the terminal.

[0156] (Input) Advertisement proposal selection information

[0157] (Output) Selection information sent to the server

[0158] Step 6:

[0159] The server generates presentation materials based on the selected advertisement proposals. A "presentation material generation module" in the server operates and converts the selected advertisement proposals into presentation slides.

[0160] (Input) Selected ad idea

[0161] (Output) Generated presentation materials

[0162] Step 7:

[0163] The server uses an automatic voice generation system to generate voice corresponding to the generated presentation materials. The generated voice data and slide data are integrated to complete the presentation video.

[0164] (Input) Presentation materials

[0165] (Output) Generated presentation video

[0166] Step 8:

[0167] The server sends the generated presentation video to the user's terminal, where the user can view the presentation video and click the approval button to generate approval information.

[0168] (Input) Generated presentation video

[0169] (Output) Presentation video sent to user device

[0170] Step 9:

[0171] The server uploads the approved presentation video to a web platform, which makes the video available on the company's official website or video sharing service.

[0172] (Input) Approval information, presentation video

[0173] (Output) Presentation video uploaded to the web platform

[0174] (Application example 1)

[0175] 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."

[0176] The traditional process of creating ad proposals and video presentations was time-consuming and inefficient. It often required expensive software and specialized knowledge, making it difficult for small teams or individual ad designers to access. Furthermore, publishing the resulting ads and presentations online required multiple steps, which was time-consuming and laborious.

[0177] 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.

[0178] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, means for an advertising designer to generate advertising proposals on a smartphone, create a presentation video, and publish it on the web, means for presenting the generated advertising proposals on the server, means for automatically generating a presentation video with audio based on the selected advertising proposal, and means for automatically uploading the generated presentation video to a web platform. This enables advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and instantly publish them on the web.

[0179] "Target information" refers to information such as the attributes, preferences, and behavioral patterns of consumers targeted by an advertising campaign.

[0180] "Product description" is information that provides detailed explanations of the characteristics, functions, advantages, specifications, etc. of the advertised product.

[0181] A "generative model" is a model that uses machine learning algorithms or AI systems to generate advertising ideas from input data.

[0182] "Advertising Proposal" means a proposal or concept created to promote a product or service.

[0183] A "server" is a computer system for receiving and processing data and hosting generative models.

[0184] "Presentation materials" are slides and documents created based on advertising proposals and used for explanations and presentations.

[0185] A "video presentation with audio" is a video presentation that is created with audio explanations corresponding to the presentation materials.

[0186] "Auto-uploading" is the process of publishing system-generated content to the web without manual intervention.

[0187] A "web platform" is an internet service or cloud storage that allows generated presentation videos and advertisements to be published and made viewable.

[0188] A "smartphone" is a mobile phone and is a device used by a user to generate and manage advertising proposals.

[0189] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web using smartphones. Specific embodiments for carrying out the invention are described below.

[0190] The system mainly consists of the following components:

[0191] Smartphone terminal: A device where users can input target information and product descriptions and view generated advertising proposals.

[0192] Server: This is the central system that receives and sends data, runs generative models, generates presentations and videos, and automatically uploads them.

[0193] Web Platform: An online service for publishing the final presentation video and making it widely accessible.

[0194] Technology used

[0195] The system consists of the following key technologies:

[0196] Generative AI models: Use advanced generative algorithms, such as OpenAI's GPT-3, to generate ad suggestions based on input.

[0197] Video generation software: Tools to generate video from presentations and add audio, for example using the Google Text-to-Speech engine.

[0198] Servers and cloud storage: Infrastructure for processing and storing data, typically using cloud services such as AWS or Google Cloud.

[0199] Program processing

[0200] Step 1: Enter target information and product description

[0201] The user enters target information and product description using a dedicated application form on their smartphone, and the entered data is sent to the server via an HTTP request.

[0202] Step 2: Generate ad proposals

[0203] The server runs a generative AI model based on the received information to generate a large number of ad ideas, incorporating past advertising success stories and target behavior patterns into the model.

[0204] Step 3: Select your ad idea

[0205] The generated ad proposals are sent from the server to the smartphone device and displayed on the user interface. The user selects the most suitable ad proposal from multiple proposals, and the selection result is sent back to the server.

[0206] Step 4: Generate a video of your presentation

[0207] The server creates presentation materials based on the selected advertising proposal and adds audio using an automatic voice generation system (e.g., Google Text-to-Speech), generating a presentation video that appeals to both the eyes and the ears.

[0208] Step 5: Approval and Auto Upload

[0209] The generated presentation video is sent from the server to the user's device, where the user can review the content and approve it by clicking the approval button. Approved videos are automatically uploaded to the web platform and made publicly available.

[0210] Specific examples

[0211] For example, consider an advertising designer creating an advertisement for a new smartphone.

[0212] 1. The user enters the target information as "young people interested in technology" and the product description as "a smartphone equipped with the latest camera technology and a high-performance battery."

[0213] 2. The server uses the generative AI model to generate a large number of advertising ideas, including catchy slogans such as "Enrich your smartphone life with the latest technology."

[0214] 3. The user selects the most attractive ad from the proposed ads.

[0215] 4. The server creates presentation materials based on the selected advertising proposal and uses an automatic voice generation system to add audio such as "This smartphone will revolutionize your daily life" to generate a presentation video.

[0216] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0217] Prompt Sentence Examples

[0218] "Target: Younger generations interested in technology, Product description: Generate ad ideas for a smartphone with the latest camera technology and a powerful battery."

[0219] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0220] Step 1:

[0221] The user inputs target information and product description on their smartphone. This is done through a form in a dedicated application. The input target information and product description are sent to the server as an HTTP request. The input data is structured and includes target information such as age and hobbies, and product description information such as function details.

[0222] Step 2:

[0223] The server generates a prompt for the generative AI model based on the target information and product description received. This prompt is appropriately constructed for generating ad proposals, for example, "Target: Young generation interested in technology, Product description: Please generate an ad proposal for a smartphone equipped with the latest camera technology and a high-performance battery." This prompt is sent to the generative AI model to generate ad proposals. The generated ad proposals are output in multiple text formats.

[0224] Step 3:

[0225] The server sends the generated ad proposals to the smartphone device. Multiple ad proposals are displayed on the user interface. The user visually reviews these ad proposals and selects the most suitable one. The user's selection is then sent back to the server.

[0226] Step 4:

[0227] The server automatically generates presentation materials based on the selected advertising proposal. The presentation materials are created in a slide format such as PowerPoint, with each slide displaying the main message and visuals of the advertising proposal. In addition, a voice generation engine (e.g., Google Text-to-Speech) is used to generate narration audio corresponding to each slide. This audio data is combined with the slides to generate a presentation video.

[0228] Step 5:

[0229] The server sends the generated presentation video to the smartphone device so that the user can review it. The user plays the presentation video, checks the content, and if satisfied, clicks the "Approve" button. This approval information is sent to the server.

[0230] Step 6:

[0231] The server automatically uploads the approved presentation video to a web platform (e.g., YouTube or the company's website). Once the upload is complete, the user is notified and the generated video is made public. This allows advertising designers to efficiently create requested advertising proposals and widely publish them in a short time.

[0232] 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.

[0233] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. Furthermore, by combining this with an emotion engine that recognizes user emotions, it is possible to propose and optimize advertising proposals that take user emotions into consideration. A specific embodiment of the system is described below.

[0234] System configuration

[0235] The system consists of four main components:

[0236] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0237] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[0238] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[0239] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[0240] Program processing explanation

[0241] The specific operations of each component of the system will be described below.

[0242] 1. Enter target information and product description

[0243] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[0244] 2. Generate advertising ideas

[0245] The device sends the input information to a server, which then uses the received information to activate a generative model that generates a large number of ad ideas. This generative model uses machine learning algorithms and AI systems and references a database of past success stories.

[0246] 3. Selecting advertising ideas and collecting emotional data

[0247] The server transmits the generated advertisement proposal to the user terminal and displays it on the user interface, and the emotion engine is activated to collect the user's emotions regarding the displayed advertisement proposal.

[0248] The user selects an ad suggestion, which is then retransmitted to the server along with the emotion data collected by the emotion engine.

[0249] 4. Automatic generation of presentation materials and videos

[0250] The server activates a "presentation material generation module" based on the selected advertising proposal. The presentation material generation module converts the selected advertising proposal into slides for presentation. Next, the server uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[0251] 5. Optimize and approve your presentation video

[0252] The server sends the generated presentation video to the user's device. When the user reviews the presentation video, the emotion engine is reactivated and analyzes the user's emotions. Based on the analysis results, the server optimizes the presentation video. For example, it may edit out parts the user dislikes.

[0253] The user checks the presentation video and, if there are no problems, clicks the "Approve" button. This operation causes the device to notify the server of the approval operation.

[0254] 6. Automatic upload

[0255] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[0256] Specific examples

[0257] Example: Advertisement for a new coffee maker

[0258] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[0259] 2. The server uses the generative model to generate a large number of ad ideas, including taglines such as "Start your day on a new level."

[0260] 3. The user browses the generated ad suggestions, and the emotion engine collects the user's emotional data in the process. It then selects the most attractive ad from the suggested suggestions.

[0261] 4. The server creates presentation materials based on the selected advertising proposal, and uses an automatic voice generation system to add audio such as "The latest coffee maker will change your mornings" to generate a presentation video.

[0262] 5. The user reviews the presentation video, and the emotion engine analyzes the user's emotions again. Based on the analysis results, the presentation video is optimized.

[0263] 6. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0264] This system allows advertising designers and public relations personnel to efficiently generate advertising proposals, and also allows them to create and publish presentation videos optimized based on user emotional data.

[0265] The processing flow will be explained below.

[0266] Step 1:

[0267] The user inputs target information and product description on the client terminal. For example, the user inputs the target demographic (e.g., "young professionals") and product description (e.g., "coffee brewed with the latest technology, special design") using a web form or dedicated application.

[0268] Step 2:

[0269] The device sends the entered information to the server, which then uses an API request to pass target information and product description data to the server.

[0270] Step 3:

[0271] The server then uses the received information to activate a generative model, which then generates a large number of ad ideas. The generative model uses machine learning algorithms and AI systems and references a database of past success stories. For example, it generates ad ideas with catchphrases such as "Start your day on a new level" or "Your special drink, creative."

[0272] Step 4:

[0273] The server sends the generated ad proposal to the user terminal, and returns the generated ad proposal and related data to the user terminal as an API response.

[0274] Step 5:

[0275] The device displays the received ad proposals on the user interface, along with a list of each proposal's catchphrase and predicted performance.

[0276] Step 6:

[0277] The emotion engine is activated and collects user emotion data when ad proposals are displayed, for example, by analyzing emotions from the user's facial expressions and voice.

[0278] Step 7:

[0279] The user selects the most suitable ad from the displayed suggestions. The emotion engine continues to analyze the user's reactions and emotions during the selection process, and finally clicks the "Select" button to confirm the ad suggestion.

[0280] Step 8:

[0281] The device transmits the selected ad proposal and emotion data to the server again, and sends an API request to the server including the identification information of the selected ad proposal and the associated emotion data.

[0282] Step 9:

[0283] The server starts a "presentation material generation module" to generate presentation materials based on the selected advertisement proposal, creating slides for the presentation and converting the text and images of the advertisement proposal into the required format.

[0284] Step 10:

[0285] The server uses an automatic speech generation system to generate audio for each slide in the presentation, and a text-to-speech tool to convert the content of each slide into audio.

[0286] Step 11:

[0287] The server combines the generated audio with the slides to generate a video presentation. A video generation tool is used to add audio to the slides and create a video file.

[0288] Step 12:

[0289] The server sends the generated presentation video to the user's device, and returns the completed video file to the user's device as an API response.

[0290] Step 13:

[0291] The device displays the received presentation video on the user interface, and the user can view the video using a video player.

[0292] Step 14:

[0293] The emotion engine is then reactivated to analyze the emotions of the user as they watch the presentation video. While the user is watching the video, the emotion engine analyzes their facial expressions and voice.

[0294] Step 15:

[0295] The server optimizes the presentation video based on the analysis results of the emotion engine. For example, it edits out parts where the user expressed dissatisfaction or boredom, and generates an improved version.

[0296] Step 16:

[0297] The user checks the optimized presentation video again and, if there are no problems, clicks the "Approve" button. If there are no problems with the presentation content, the approval operation is performed.

[0298] Step 17:

[0299] The device notifies the server of the approval operation and sends an API request including the approval information to the server.

[0300] Step 18:

[0301] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[0302] This specific processing flow enables the generation and optimization of advertising proposals that take user emotions into consideration, allowing advertising designers and public relations personnel to work efficiently.

[0303] Example 2

[0304] 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."

[0305] With current technology, the process for advertising designers and public relations personnel to efficiently generate advertising proposals, optimize the proposals and presentation videos taking user emotions into account, and finally publish them on the web requires a great deal of time and effort. Furthermore, adjusting the proposals based on user emotions is difficult, making it difficult to create advertisements that attract users' attention. Therefore, there is a need for a system that can easily and efficiently generate and optimize advertising proposals, create presentation videos that reflect user emotions, and quickly publish them.

[0306] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0307] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for displaying the advertising proposals on a user interface, means for collecting user emotion data regarding the displayed advertising proposals, means for generating presentation materials based on selected advertising proposals, means for generating audio corresponding to the presentation materials and creating a presentation video, means for optimizing the generated presentation video based on emotion analysis, means for approving the optimized presentation video, and means for uploading the approved presentation video to the web. This enables advertising designers and public relations personnel to efficiently generate advertising proposals and create and quickly publish optimal presentation videos that reflect user emotions.

[0308] "Target information" is information about specific people or groups to whom advertising is intended to be directed.

[0309] "Product description" is information detailing the features, performance, price, benefits, etc. of the advertised product.

[0310] "Transmission means" refers to the technical mechanism for sending data from the user terminal to the server.

[0311] A "generative model" is an algorithm that automatically generates advertising ideas based on input information.

[0312] "Ad Proposals" are a set of draft ad content suggested by a generative model.

[0313] A "user interface" is an interactive screen or operating means for a user to interact with a system.

[0314] "Emotion data" is information about emotions obtained by analyzing the user's facial expressions and voice.

[0315] "Presentation materials" are slides and documents used for presentations that are based on advertising proposals.

[0316] The "means for generating voice" is a technology that automatically generates voice based on text information.

[0317] A "presentation video" is a video presentation that combines audio corresponding to the presentation materials.

[0318] "Emotion analysis" is the process of analyzing collected emotion data to understand a user's emotional state.

[0319] "Optimization methods" are technologies for improving and adjusting advertising proposals and presentation videos based on the results of sentiment analysis.

[0320] The "means of approval" is a mechanism that allows the user to check the final generated presentation video and approve it if they determine that there are no problems.

[0321] "Means of uploading" refers to the technology used to transmit and save data in order to publish the generated presentation video on the web.

[0322] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. By combining this system with an emotion engine that recognizes user emotions, the system can propose and optimize advertising proposals taking user emotions into consideration.

[0323] System configuration

[0324] The system consists of four components:

[0325] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0326] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[0327] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[0328] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[0329] Program processing explanation

[0330] Enter target information and product description

[0331] The user inputs target information and product description on the client terminal. This is done, for example, through a dedicated application or a web form. Specifically, the user starts the dedicated application and inputs target information and product description such as "young professionals" or "coffee brewed with the latest technology, special design" into the form.

[0332] Generate advertising proposals

[0333] The device sends the information entered to the server, where secure communication takes place using the HTTPS protocol. The server analyzes the received information and activates a generative AI model (e.g., a natural language generation algorithm built in Python). This generative AI model references a database of past success stories and generates a large number of ad suggestions based on the entered information. For example, ad suggestions may be generated that include a catchphrase such as "Start your day on a new level."

[0334] Advertisement selection and emotional data collection

[0335] The server sends the generated ad ideas to the user's device and displays them in an interactive dashboard format using HTML and JavaScript. At this time, an emotion engine is activated and collects user emotional data via a webcam and microphone. The emotional data is analyzed by an AI algorithm. The user selects the most attractive ad idea, and the selection is sent to the server.

[0336] Automatic generation of presentation materials and videos

[0337] The server activates a "presentation material generation module" based on the selected advertising proposal. This module converts the advertising proposal into presentation slides using, for example, Microsoft PowerPoint. Next, the server uses an automatic speech generation system (for example, Google Text-to-Speech API) to generate audio corresponding to each slide, and combines the generated audio with the slides to generate a presentation video using Adobe Premiere Pro.

[0338] Presentation video optimization and approval

[0339] The server sends the generated presentation video to the user's device. The user then views the presentation video using a dedicated viewer. At this time, the emotion engine is reactivated and collects and analyzes the user's emotional data via the webcam and microphone. Based on the analysis results, the server optimizes the presentation video to reflect the user's preferences. The user reviews the final presentation video, and if there are no problems, clicks the "Approve" button to notify the server of the approval operation.

[0340] Automatic Upload

[0341] The server automatically uploads the approved presentation video to the web using the YouTube Data API or other cloud storage APIs, and notifies the user after the upload is complete.

[0342] Specific examples

[0343] Example: Advertisement for a new coffee maker

[0344] 1. The user enters the target information "young professionals" and the product description "coffee brewed with the latest technology, special design" into a form in a dedicated application.

[0345] 2. The device sends this information to a server, which uses a generative AI model to generate ad suggestions, including taglines like "Start your day on a new level."

[0346] 3. The user browses the generated ad suggestions on the web dashboard, and the emotion engine collects the user's emotional data via the webcam and microphone. The user then selects the most appealing ad suggestion.

[0347] 4. The server creates a presentation using Microsoft PowerPoint based on the selected ad proposal, and then combines the audio generated by the Google Text-to-Speech API with the slides in Adobe Premiere Pro to generate a video presentation.

[0348] 5. The user reviews the presentation video, and the emotion engine again collects and analyzes the emotion data. The server optimizes the video based on the analysis results.

[0349] 6. The user approves the optimized presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel via API.

[0350] This system enables advertising designers and public relations personnel to efficiently generate advertising proposals and create and publish presentation videos optimized based on user emotional data.

[0351] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0352] Step 1:

[0353] The user inputs target information and product description on the client device. The user launches a dedicated application or web form and inputs target information (e.g., young professionals) and product description (e.g., coffee brewed with the latest technology, special design). This input data is structured in JSON format and sent to the server.

[0354] Step 2:

[0355] The device sends the input information to the server. Communication is secure using the HTTPS protocol. The server analyzes the received information and passes target information and product descriptions to the generative model. This activates a natural language generation algorithm written in Python to generate ad suggestions based on the input data. Multiple ad suggestions are generated as output.

[0356] Step 3:

[0357] The server sends the generated ad suggestions to the user's device. The ad suggestions are displayed on an interactive dashboard using HTML and JavaScript. At the same time, an emotion engine is activated to collect the user's emotional data through a webcam and microphone. The input emotional data is analyzed by an AI algorithm to determine the user's emotional state. Based on this, multiple ad suggestions are displayed to the user.

[0358] Step 4:

[0359] The user selects the most attractive advertising proposal. The selection is made through an interface operation such as clicking, and the data is sent to the server. The server then starts a presentation generation module based on the selected advertising proposal, and automatically generates a slide-format presentation using, for example, Microsoft PowerPoint. The presentation is then created as the output.

[0360] Step 5:

[0361] The server uses an automatic speech generation system (e.g., Google Text-to-Speech API) to generate audio corresponding to the presentation materials. Audio corresponding to each slide in the presentation materials is generated. The generated audio data and slide data are used to generate a presentation video using Adobe Premiere Pro. The presentation video is generated as the output.

[0362] Step 6:

[0363] The server sends the generated presentation video to the user's device. The user then watches the presentation video using a dedicated viewer. At this time, the emotion engine is activated again to collect and analyze the user's emotional data via the webcam and microphone. Based on the analysis results, the server optimizes the presentation video. For example, it edits out unattractive parts based on the user's emotional data. The optimized presentation video is generated as the output.

[0364] Step 7:

[0365] The user reviews the optimized presentation video and gives final approval by clicking the "Approve" button. This approval operation is notified to the server from the device. Finally, the server uses the approved presentation video and automatically uploads it to the web using the YouTube Data API or cloud storage API. The presentation video is then made public as an output.

[0366] By performing such specific processing at each step, advertising designers and public relations personnel can efficiently generate advertising proposals and quickly create and publish optimized presentation videos.

[0367] (Application example 2)

[0368] 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."

[0369] Conventional advertising production systems have difficulty reflecting user sentiment in the generation and optimization of ad ideas, and have limited means to maximize the effectiveness of ad ideas. Furthermore, they lack a comprehensive system for improving the efficiency of the ad production process. This has resulted in advertising designers and public relations personnel having to expend a great deal of effort and time.

[0370] The identification process by the identification 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 target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, means for recognizing user emotions and analyzing data, and means for optimizing the advertising proposals based on the recognized emotion data. This makes it possible to efficiently perform a series of processes from generating advertising proposals to publishing the presentation video, and to create optimized advertising proposals that reflect user emotions.

[0371] "Target information" is information about the user profile or customer segment that is the target of the advertisement.

[0372] "Product description" refers to information about the detailed features and specifications of the product or service being advertised.

[0373] A "generative model" is a system that uses machine learning algorithms and artificial intelligence to generate advertising ideas based on input data.

[0374] "Advertising Proposals" are advertising ideas or suggestions created by a generative model.

[0375] "Presentation materials" are slides and documents used for presentations created based on advertising proposals.

[0376] A "presentation video" is a video presentation that adds audio and animation to presentation materials.

[0377] The "emotion engine" is a system that recognizes the user's emotions and analyzes the data.

[0378] "Optimization" is the process of improving and adjusting advertising proposals and presentation videos based on collected data in accordance with user emotions.

[0379] "Upload" refers to the transfer of generated and approved content to a web service or cloud storage on the Internet.

[0380] This invention provides a system that enables advertising designers and public relations personnel to efficiently generate advertising proposals, and also creates and publishes presentation videos that are optimized based on user emotion data.

[0381] The system includes the following components:

[0382] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0383] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[0384] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[0385] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[0386] Program processing explanation

[0387] Enter target information and product description

[0388] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[0389] Generate advertising proposals

[0390] The device sends the input information to a server, which then uses the received information to activate a generative model that generates a large number of ad ideas. This generative model uses machine learning algorithms and AI systems and references a database of past success stories.

[0391] Advertisement selection and emotional data collection

[0392] The server transmits the generated advertisement proposals to the user terminal and displays them on the user interface. At this time, the emotion engine is activated to collect the user's emotions regarding the displayed advertisement proposals. The user selects an advertisement proposal. The selected advertisement proposal is retransmitted to the server together with the emotion data collected by the emotion engine.

[0393] Automatic generation of presentation materials and videos

[0394] The server activates a presentation material generation module based on the selected advertising proposals. The presentation material generation module converts the selected advertising proposals into presentation slides. The server then uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[0395] Presentation video optimization and approval

[0396] The server sends the generated presentation video to the user's device. When the user reviews the presentation video, the emotion engine is reactivated and analyzes the user's emotions. Based on the analysis results, the server optimizes the presentation video. For example, it may edit out parts the user dislikes. The user reviews the presentation video and, if there are no problems, clicks the "Approve" button. This operation causes the device to notify the server of the approval operation.

[0397] Automatic Upload

[0398] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or video sharing platform.

[0399] Hardware and software used

[0400] Hardware: smartphones, computers, servers

[0401] Software: Python3, requests library, transformers library, emotion_recognition library

[0402] Specific examples

[0403] For example, to create an advertisement for a new coffee maker, a user might enter the following information:

[0404] Brand Name: "Latest Coffee Maker"

[0405] Target Audience: "Young Professionals"

[0406] Product Description: "Coffee brewed with the latest technology, special design"

[0407] Image file path for emotion recognition: " / path / to / user / image.jpg"

[0408] Based on this information, the generative model generates ad ideas with taglines such as "Start your day on a new level." The emotion engine collects emotional data as users view the ad ideas.

[0409] Based on the collected emotional data, the server generates optimized presentation materials and videos, and once the user approves the presentation video, the server automatically uploads the video to the company's official website and YouTube channel.

[0410] Prompt Sentence Examples

[0411] Enter your brand name: Latest Coffee Maker

[0412] Enter your target audience: Young Professionals

[0413] Enter your product description: Latest technology, special design

[0414] Enter the image file path for emotion recognition: / path / to / user / image.jpg

[0415] This system allows advertising designers and public relations personnel to efficiently generate advertising proposals, and also allows them to create and publish presentation videos optimized based on user emotional data.

[0416] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0417] Step 1:

[0418] The user inputs target information and product description on the client terminal, for example, using input fields in the dedicated application to input information such as brand name, target audience, product description, etc. The input data is used for subsequent processes.

[0419] Input: Brand name, target audience, product description

[0420] Output: Input target information and product description data

[0421] Step 2:

[0422] The device sends the target information and product description entered by the user to the server, which then activates the generative AI model based on the received information.

[0423] Input: Target information and product description data

[0424] Output: Sending input data to the server

[0425] Step 3:

[0426] The server generates advertising proposals using a generative AI model. The server references a database of past success stories and automatically generates multiple advertising proposals. The generated advertising proposals are sent to the user's device.

[0427] Input: Target information and product description data

[0428] Output: Multiple ad proposal data

[0429] Step 4:

[0430] The user terminal displays the generated advertising proposals. The user browses the displayed multiple advertising proposals and selects the most suitable one. At this time, the emotion engine is activated and collects the user's emotion data.

[0431] Input: Multiple ad proposal data

[0432] Output: Displayed ad suggestions, user sentiment data

[0433] Step 5:

[0434] The device retransmits the advertisement proposal selected by the user to the server. The emotion data collected by the emotion engine is also sent to the server at the same time. The server then generates the optimal presentation materials based on this information.

[0435] Input: Selected ad proposal data, user emotion data

[0436] Output: Sending selection data and emotion data to the server

[0437] Step 6:

[0438] The server activates a presentation material generation module based on the selected advertisement proposal and the user's emotion data, and the presentation material generation module converts the selected advertisement proposal into slides for presentation.

[0439] Input: Selected ad proposal data, user emotion data

[0440] Output: Generated presentation slides

[0441] Step 7:

[0442] The server uses an automatic voice generation system to generate voice corresponding to the presentation slides, and combines the generated voice with the slides to generate a presentation video.

[0443] Input: Generated presentation slides

[0444] Output: Generated presentation video

[0445] Step 8:

[0446] The server sends the generated presentation video to the user's device. When the user views the presentation video, the emotion engine is activated again to analyze the user's emotions.

[0447] Input: Generated presentation video

[0448] Output: Sending the presentation video to the user, user emotion data

[0449] Step 9:

[0450] The server optimizes the presentation video based on the analysis results. For example, it may edit out parts the user dislikes. The user then checks the optimized presentation video and clicks the "Approve" button if there are no problems.

[0451] Input: User emotion data

[0452] Output: Optimized presentation video, user approval

[0453] Step 10:

[0454] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or video sharing platform.

[0455] Input: Approved presentation video

[0456] Output: Upload video to the web

[0457] 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.

[0458] 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.

[0459] 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.

[0460] [Second embodiment]

[0461] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0462] 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.

[0463] 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).

[0464] 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.

[0465] 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.

[0466] 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).

[0467] 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.

[0468] 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.

[0469] 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.

[0470] 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.

[0471] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0472] 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."

[0473] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. Specific embodiments of the system are described below.

[0474] System configuration

[0475] The system consists of three main components:

[0476] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0477] 2. Server: This is the server that hosts the generative model and the presentation creation tool.

[0478] 3. Web platform: Web services and cloud storage for publishing the final presentation video.

[0479] Program processing explanation

[0480] The specific operations of each component of the system will be described below.

[0481] 1. Enter target information and product description

[0482] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[0483] 2. Generate advertising ideas

[0484] The device sends the input information to a server, which then uses a generative model to generate a large number of ad ideas based on the received information. The generative model uses machine learning algorithms and AI systems to propose new ad ideas based on past success stories.

[0485] 3. Select an ad idea

[0486] The server sends the generated advertisement suggestions to the user terminal and displays them on the user interface. The user selects the most suitable one from the proposed advertisement suggestions. The selected advertisement suggestion is then sent back to the server.

[0487] 4. Automatic generation of presentation materials and videos

[0488] The server activates a "presentation material generation module" based on the selected advertising proposal. The presentation material generation module converts the selected advertising proposal into slides for presentation. Next, the server uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[0489] 5. Approval and automatic upload

[0490] The generated presentation video is sent from the server to the user's device, where the user can review it and click the "Approve" button. Once approved, the server automatically uploads the video to the web platform.

[0491] Specific examples

[0492] Example: Advertisement for a new coffee maker

[0493] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[0494] 2. The server uses the generative model to generate a large number of ad ideas, including taglines such as "Start your day on a new level."

[0495] 3. The user selects the most attractive ad from the proposed ads.

[0496] 4. The server creates presentation materials based on the selected advertising proposal, and uses an automatic voice generation system to add audio such as "The latest coffee maker will change your mornings" to generate a presentation video.

[0497] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0498] Using this system, advertising designers and public relations personnel can efficiently create advertising proposals, generate presentation videos, and publish them online.

[0499] The processing flow will be explained below.

[0500] Step 1:

[0501] The user enters target information and product description on the client terminal, entering detailed information such as target demographic, product features, and keywords through input fields in a web form or dedicated application.

[0502] Step 2:

[0503] The device sends the entered information to the server, and passes target information and product description data to the server using an API request.

[0504] Step 3:

[0505] The server then uses the received information to launch a generative model, which generates a large number of ad ideas. The generative model uses machine learning algorithms and AI systems, and references a database of past success stories.

[0506] Step 4:

[0507] The server sends the generated ad proposal to the user's device and returns the generated ad proposal and related data as an API response.

[0508] Step 5:

[0509] The device displays the received ad proposals on the user interface, along with a list of each proposal's catchphrase and predicted performance.

[0510] Step 6:

[0511] The user selects the most suitable ad from the displayed ad suggestions by clicking on the best ad suggestion from the options and then clicking on the "Select" button.

[0512] Step 7:

[0513] The device sends the selected ad proposal to the server again, and sends an API request including the identification information of the selected ad proposal.

[0514] Step 8:

[0515] The server starts the "presentation material generation module" and generates presentation materials based on the selected advertisement proposals. The server converts the text and images of the advertisement proposals into the required format to create slides for the presentation.

[0516] Step 9:

[0517] The server uses an automatic speech generation system to generate audio for each slide in the presentation, and a text-to-speech tool to convert the content of each slide into audio.

[0518] Step 10:

[0519] The server combines the generated audio with the slides to generate a video presentation. A video generation tool is used to add audio to the slides and create a video file.

[0520] Step 11:

[0521] The server sends the generated presentation video to the user's device and returns the completed video file as an API response.

[0522] Step 12:

[0523] The device displays the received presentation video on the user interface, and the user can view the video using a video player.

[0524] Step 13:

[0525] The user checks the presentation video and clicks the "Approve" button if there are no problems. If there are no problems with the presentation content, the approval operation is performed.

[0526] Step 14:

[0527] The device notifies the server of the approval operation and sends an API request including the approval information to the server.

[0528] Step 15:

[0529] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[0530] Example 1

[0531] 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."

[0532] The process of advertising designers and public relations personnel efficiently generating advertising proposals, creating presentation videos, and finally publishing them online is extremely time-consuming and labor-intensive when done manually. A system that automates and efficiently performs this process is needed. In particular, technology that can smoothly integrate each step, such as data entry, generating advertising proposals, creating presentation materials, generating audio, and creating and publishing the final presentation video, is needed.

[0533] 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.

[0534] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, and means for automating the generation and uploading of the presentation video. This makes it possible to efficiently perform processes from creating advertising proposals to generating the presentation video and publishing it on the web.

[0535] "Targeted Information" refers to information about a specific audience or group for advertising or marketing purposes.

[0536] "Product description" refers to information that explains the features, benefits, and usage of the products or services you offer.

[0537] "Generative modeling" refers to the technique of using machine learning algorithms and AI systems to generate new ideas and data.

[0538] "Advertising Proposal" refers to a proposal for a catchy slogan or visual content generated for the purpose of promoting a product or service.

[0539] "Presentation materials" refer to slides and documents created based on advertising proposals, and are materials used to visually convey information about products and services.

[0540] "Presentation video" refers to video content that adds audio and animation to presentation materials to dynamically convey information to viewers.

[0541] "Approval" refers to the act of finally reviewing the generated presentation video and giving permission before it is made public.

[0542] "Uploading to the web" refers to the act of publishing generated content on an internet platform or website.

[0543] "Automating the process of generating and uploading presentation videos" refers to a series of processes in which the system automatically creates presentation videos and publishes them on the web, without the need for manual work.

[0544] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. A specific embodiment of this system will be described below.

[0545] System configuration

[0546] The system consists of three main components:

[0547] 1. User devices: Computers and smart devices operated by advertising designers and public relations personnel. Specifically, these include personal computers, tablets, and smartphones.

[0548] 2. Server: A computer system that hosts the generative model and the presentation creation tool. The server must have high-performance processing power and sufficient storage capacity. A cloud-based server can also be used.

[0549] 3. Web Platform: Web services and cloud storage for publishing the final presentation video. Specifically, this includes the company's official website and video sharing services such as YouTube and Vimeo.

[0550] Program processing

[0551] The system program executes processing in the following manner.

[0552] 1. Enter target information and product description

[0553] A user inputs target information and a product description using a client terminal. The user inputs target information (e.g., "young professionals") and a product description (e.g., "coffee brewed with the latest technology, special design"), for example, through a web form or a dedicated application.

[0554] 2. Generate advertising ideas

[0555] The device sends the input information to a server. The server uses the received information to run a generative AI model to generate a large number of ad ideas. The generative AI model learns from past success stories and marketing data, and uses this data to propose new ad ideas.

[0556] 3. Select an ad idea

[0557] The server sends the generated advertisement suggestions to the user's terminal, which displays them through a user interface. The user selects the most suitable one from the presented advertisement suggestions and sends the selection result to the server via the terminal.

[0558] 4. Automatic generation of presentation materials and videos

[0559] The server automatically generates presentation materials based on the selected advertising proposals. The presentation material generation module converts the advertising proposals into slide format. The server then uses an automatic audio generation system to generate audio corresponding to each slide, thereby completing a presentation video with audio.

[0560] 5. Approval and automatic upload

[0561] The server sends the generated presentation video to the user's device, where the user can review and approve it. After approval, the server automatically uploads the presentation video to the web platform. This process reduces manual errors and greatly improves efficiency.

[0562] Specific examples

[0563] Example: Advertisement for a new coffee maker

[0564] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[0565] 2. The device sends the input data to the server, which uses the generative model to generate ad ideas including slogans such as "Start your day on a new level."

[0566] 3. The server sends the proposed advertisements to the user's terminal, and the user selects the most attractive one from the proposed advertisements.

[0567] 4. The server creates presentation materials based on the selected advertising proposal, uses an automatic voice generation system to generate audio such as "The latest coffee maker will change your morning," and creates a presentation video.

[0568] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0569] This system allows advertising designers and public relations personnel to efficiently create advertising proposals, generate presentation videos, and publish them online.

[0570] Example prompts for generative AI models

[0571] "To advertise coffee brewed using the latest technology, target information: young professionals. Product description: A coffee maker with a special design that uses the latest technology. Please create an ad proposal based on this information."

[0572] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0573] Step 1:

[0574] The user inputs target information and product description. The user inputs target information (e.g., "young professionals") and product description (e.g., "coffee brewed with the latest technology, special design") using a web form in a browser or a dedicated application. The input data is stored in a built-in data structure.

[0575] (Input) Target information, product description

[0576] (Output) Save the entered data

[0577] Step 2:

[0578] The device sends the entered information to the server, where the data is encrypted and securely transferred to the server.

[0579] (Input) Data entered

[0580] (Output) Data sent to the server

[0581] Step 3:

[0582] The server analyzes the target information and product description it receives. Based on the analysis results, the server creates a prompt for the generative AI model. The generative AI model is used to generate multiple ad proposals.

[0583] (Input) Data sent to the server

[0584] (Output) Generated ad ideas

[0585] Step 4:

[0586] The server sends the generated advertisement proposal to the user terminal, which temporarily stores the generated advertisement proposal in an internal database and sends it to the terminal for display through the user interface.

[0587] (Input) Generated ad ideas

[0588] (Output) Advertisement proposals sent to the device

[0589] Step 5:

[0590] The user selects the most suitable advertisement from the presented advertisements, and the information selected by the user is sent back to the server via the terminal.

[0591] (Input) Advertisement proposal selection information

[0592] (Output) Selection information sent to the server

[0593] Step 6:

[0594] The server generates presentation materials based on the selected advertisement proposals. A "presentation material generation module" in the server operates and converts the selected advertisement proposals into presentation slides.

[0595] (Input) Selected ad idea

[0596] (Output) Generated presentation materials

[0597] Step 7:

[0598] The server uses an automatic voice generation system to generate voice corresponding to the generated presentation materials. The generated voice data and slide data are integrated to complete the presentation video.

[0599] (Input) Presentation materials

[0600] (Output) Generated presentation video

[0601] Step 8:

[0602] The server sends the generated presentation video to the user's terminal, where the user can view the presentation video and click the approval button to generate approval information.

[0603] (Input) Generated presentation video

[0604] (Output) Presentation video sent to user device

[0605] Step 9:

[0606] The server uploads the approved presentation video to a web platform, which makes the video available on the company's official website or video sharing service.

[0607] (Input) Approval information, presentation video

[0608] (Output) Presentation video uploaded to the web platform

[0609] (Application example 1)

[0610] 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."

[0611] The traditional process of creating ad proposals and video presentations was time-consuming and inefficient. It often required expensive software and specialized knowledge, making it difficult for small teams or individual ad designers to access. Furthermore, publishing the resulting ads and presentations online required multiple steps, which was time-consuming and laborious.

[0612] 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.

[0613] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, means for an advertising designer to generate advertising proposals on a smartphone, create a presentation video, and publish it on the web, means for presenting the generated advertising proposals on the server, means for automatically generating a presentation video with audio based on the selected advertising proposal, and means for automatically uploading the generated presentation video to a web platform. This enables advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and instantly publish them on the web.

[0614] "Target information" refers to information such as the attributes, preferences, and behavioral patterns of consumers targeted by an advertising campaign.

[0615] "Product description" is information that provides detailed explanations of the characteristics, functions, advantages, specifications, etc. of the advertised product.

[0616] A "generative model" is a model that uses machine learning algorithms or AI systems to generate advertising ideas from input data.

[0617] "Advertising Proposal" means a proposal or concept created to promote a product or service.

[0618] A "server" is a computer system for receiving and processing data and hosting generative models.

[0619] "Presentation materials" are slides and documents created based on advertising proposals and used for explanations and presentations.

[0620] A "video presentation with audio" is a video presentation that is created with audio explanations corresponding to the presentation materials.

[0621] "Auto-uploading" is the process of publishing system-generated content to the web without manual intervention.

[0622] A "web platform" is an internet service or cloud storage that allows generated presentation videos and advertisements to be published and made viewable.

[0623] A "smartphone" is a mobile phone and is a device used by a user to generate and manage advertising proposals.

[0624] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web using smartphones. Specific embodiments for carrying out the invention are described below.

[0625] The system mainly consists of the following components:

[0626] Smartphone terminal: A device where users can input target information and product descriptions and view generated advertising proposals.

[0627] Server: This is the central system that receives and sends data, runs generative models, generates presentations and videos, and automatically uploads them.

[0628] Web Platform: An online service for publishing the final presentation video and making it widely accessible.

[0629] Technology used

[0630] The system consists of the following key technologies:

[0631] Generative AI models: Use advanced generative algorithms, such as OpenAI's GPT-3, to generate ad suggestions based on input.

[0632] Video generation software: Tools to generate video from presentations and add audio, for example using the Google Text-to-Speech engine.

[0633] Servers and cloud storage: Infrastructure for processing and storing data, typically using cloud services such as AWS or Google Cloud.

[0634] Program processing

[0635] Step 1: Enter target information and product description

[0636] The user enters target information and product description using a dedicated application form on their smartphone, and the entered data is sent to the server via an HTTP request.

[0637] Step 2: Generate ad proposals

[0638] The server runs a generative AI model based on the received information to generate a large number of ad ideas, incorporating past advertising success stories and target behavior patterns into the model.

[0639] Step 3: Select your ad idea

[0640] The generated ad proposals are sent from the server to the smartphone device and displayed on the user interface. The user selects the most suitable ad proposal from multiple proposals, and the selection result is sent back to the server.

[0641] Step 4: Generate a video of your presentation

[0642] The server creates presentation materials based on the selected advertising proposal and adds audio using an automatic voice generation system (e.g., Google Text-to-Speech), generating a presentation video that appeals to both the eyes and the ears.

[0643] Step 5: Approval and Auto Upload

[0644] The generated presentation video is sent from the server to the user's device, where the user can review the content and approve it by clicking the approval button. Approved videos are automatically uploaded to the web platform and made publicly available.

[0645] Specific examples

[0646] For example, consider an advertising designer creating an advertisement for a new smartphone.

[0647] 1. The user enters the target information as "young people interested in technology" and the product description as "a smartphone equipped with the latest camera technology and a high-performance battery."

[0648] 2. The server uses the generative AI model to generate a large number of advertising ideas, including catchy slogans such as "Enrich your smartphone life with the latest technology."

[0649] 3. The user selects the most attractive ad from the proposed ads.

[0650] 4. The server creates presentation materials based on the selected advertising proposal and uses an automatic voice generation system to add audio such as "This smartphone will revolutionize your daily life" to generate a presentation video.

[0651] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0652] Prompt Sentence Examples

[0653] "Target: Younger generations interested in technology, Product description: Generate ad ideas for a smartphone with the latest camera technology and a powerful battery."

[0654] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0655] Step 1:

[0656] The user inputs target information and product description on their smartphone. This is done through a form in a dedicated application. The input target information and product description are sent to the server as an HTTP request. The input data is structured and includes target information such as age and hobbies, and product description information such as function details.

[0657] Step 2:

[0658] The server generates a prompt for the generative AI model based on the target information and product description received. This prompt is appropriately constructed for generating ad proposals, for example, "Target: Young generation interested in technology, Product description: Please generate an ad proposal for a smartphone equipped with the latest camera technology and a high-performance battery." This prompt is sent to the generative AI model to generate ad proposals. The generated ad proposals are output in multiple text formats.

[0659] Step 3:

[0660] The server sends the generated ad proposals to the smartphone device. Multiple ad proposals are displayed on the user interface. The user visually reviews these ad proposals and selects the most suitable one. The user's selection is then sent back to the server.

[0661] Step 4:

[0662] The server automatically generates presentation materials based on the selected advertising proposal. The presentation materials are created in a slide format such as PowerPoint, with each slide displaying the main message and visuals of the advertising proposal. In addition, a voice generation engine (e.g., Google Text-to-Speech) is used to generate narration audio corresponding to each slide. This audio data is combined with the slides to generate a presentation video.

[0663] Step 5:

[0664] The server sends the generated presentation video to the smartphone device so that the user can review it. The user plays the presentation video, checks the content, and if satisfied, clicks the "Approve" button. This approval information is sent to the server.

[0665] Step 6:

[0666] The server automatically uploads the approved presentation video to a web platform (e.g., YouTube or the company's website). Once the upload is complete, the user is notified and the generated video is made public. This allows advertising designers to efficiently create requested advertising proposals and widely publish them in a short time.

[0667] 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.

[0668] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. Furthermore, by combining this with an emotion engine that recognizes user emotions, it is possible to propose and optimize advertising proposals that take user emotions into consideration. A specific embodiment of the system is described below.

[0669] System configuration

[0670] The system consists of four main components:

[0671] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0672] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[0673] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[0674] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[0675] Program processing explanation

[0676] The specific operations of each component of the system will be described below.

[0677] 1. Enter target information and product description

[0678] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[0679] 2. Generate advertising ideas

[0680] The device sends the input information to a server, which then uses the received information to activate a generative model that generates a large number of ad ideas. This generative model uses machine learning algorithms and AI systems and references a database of past success stories.

[0681] 3. Selecting advertising ideas and collecting emotional data

[0682] The server transmits the generated advertisement proposal to the user terminal and displays it on the user interface, and the emotion engine is activated to collect the user's emotions regarding the displayed advertisement proposal.

[0683] The user selects an ad suggestion, which is then retransmitted to the server along with the emotion data collected by the emotion engine.

[0684] 4. Automatic generation of presentation materials and videos

[0685] The server activates a "presentation material generation module" based on the selected advertising proposal. The presentation material generation module converts the selected advertising proposal into slides for presentation. Next, the server uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[0686] 5. Optimize and approve your presentation video

[0687] The server sends the generated presentation video to the user's device. When the user reviews the presentation video, the emotion engine is reactivated and analyzes the user's emotions. Based on the analysis results, the server optimizes the presentation video. For example, it may edit out parts the user dislikes.

[0688] The user checks the presentation video and, if there are no problems, clicks the "Approve" button. This operation causes the device to notify the server of the approval operation.

[0689] 6. Automatic upload

[0690] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[0691] Specific examples

[0692] Example: Advertisement for a new coffee maker

[0693] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[0694] 2. The server uses the generative model to generate a large number of ad ideas, including taglines such as "Start your day on a new level."

[0695] 3. The user browses the generated ad suggestions, and the emotion engine collects the user's emotional data in the process. It then selects the most attractive ad from the suggested suggestions.

[0696] 4. The server creates presentation materials based on the selected advertising proposal, and uses an automatic voice generation system to add audio such as "The latest coffee maker will change your mornings" to generate a presentation video.

[0697] 5. The user reviews the presentation video, and the emotion engine analyzes the user's emotions again. Based on the analysis results, the presentation video is optimized.

[0698] 6. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0699] This system allows advertising designers and public relations personnel to efficiently generate advertising proposals, and also allows them to create and publish presentation videos optimized based on user emotional data.

[0700] The processing flow will be explained below.

[0701] Step 1:

[0702] The user inputs target information and product description on the client terminal. For example, the user inputs the target demographic (e.g., "young professionals") and product description (e.g., "coffee brewed with the latest technology, special design") using a web form or dedicated application.

[0703] Step 2:

[0704] The device sends the entered information to the server, which then uses an API request to pass target information and product description data to the server.

[0705] Step 3:

[0706] The server then uses the received information to activate a generative model, which then generates a large number of ad ideas. The generative model uses machine learning algorithms and AI systems and references a database of past success stories. For example, it generates ad ideas with catchphrases such as "Start your day on a new level" or "Your special drink, creative."

[0707] Step 4:

[0708] The server sends the generated ad proposal to the user terminal, and returns the generated ad proposal and related data to the user terminal as an API response.

[0709] Step 5:

[0710] The device displays the received ad proposals on the user interface, along with a list of each proposal's catchphrase and predicted performance.

[0711] Step 6:

[0712] The emotion engine is activated and collects user emotion data when ad proposals are displayed, for example, by analyzing emotions from the user's facial expressions and voice.

[0713] Step 7:

[0714] The user selects the most suitable ad from the displayed suggestions. The emotion engine continues to analyze the user's reactions and emotions during the selection process, and finally clicks the "Select" button to confirm the ad suggestion.

[0715] Step 8:

[0716] The device transmits the selected ad proposal and emotion data to the server again, and sends an API request to the server including the identification information of the selected ad proposal and the associated emotion data.

[0717] Step 9:

[0718] The server starts a "presentation material generation module" to generate presentation materials based on the selected advertisement proposal, creating slides for the presentation and converting the text and images of the advertisement proposal into the required format.

[0719] Step 10:

[0720] The server uses an automatic speech generation system to generate audio for each slide in the presentation, and a text-to-speech tool to convert the content of each slide into audio.

[0721] Step 11:

[0722] The server combines the generated audio with the slides to generate a video presentation. A video generation tool is used to add audio to the slides and create a video file.

[0723] Step 12:

[0724] The server sends the generated presentation video to the user's device, and returns the completed video file to the user's device as an API response.

[0725] Step 13:

[0726] The device displays the received presentation video on the user interface, and the user can view the video using a video player.

[0727] Step 14:

[0728] The emotion engine is then reactivated to analyze the emotions of the user as they watch the presentation video. While the user is watching the video, the emotion engine analyzes their facial expressions and voice.

[0729] Step 15:

[0730] The server optimizes the presentation video based on the analysis results of the emotion engine. For example, it edits out parts where the user expressed dissatisfaction or boredom, and generates an improved version.

[0731] Step 16:

[0732] The user checks the optimized presentation video again and, if there are no problems, clicks the "Approve" button. If there are no problems with the presentation content, the approval operation is performed.

[0733] Step 17:

[0734] The device notifies the server of the approval operation and sends an API request including the approval information to the server.

[0735] Step 18:

[0736] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[0737] This specific processing flow enables the generation and optimization of advertising proposals that take user emotions into consideration, allowing advertising designers and public relations personnel to work efficiently.

[0738] Example 2

[0739] 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."

[0740] With current technology, the process for advertising designers and public relations personnel to efficiently generate advertising proposals, optimize the proposals and presentation videos taking user emotions into account, and finally publish them on the web requires a great deal of time and effort. Furthermore, adjusting the proposals based on user emotions is difficult, making it difficult to create advertisements that attract users' attention. Therefore, there is a need for a system that can easily and efficiently generate and optimize advertising proposals, create presentation videos that reflect user emotions, and quickly publish them.

[0741] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0742] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for displaying the advertising proposals on a user interface, means for collecting user emotion data regarding the displayed advertising proposals, means for generating presentation materials based on selected advertising proposals, means for generating audio corresponding to the presentation materials and creating a presentation video, means for optimizing the generated presentation video based on emotion analysis, means for approving the optimized presentation video, and means for uploading the approved presentation video to the web. This enables advertising designers and public relations personnel to efficiently generate advertising proposals and create and quickly publish optimal presentation videos that reflect user emotions.

[0743] "Target information" is information about specific people or groups to whom advertising is intended to be directed.

[0744] "Product description" is information detailing the features, performance, price, benefits, etc. of the advertised product.

[0745] "Transmission means" refers to the technical mechanism for sending data from the user terminal to the server.

[0746] A "generative model" is an algorithm that automatically generates advertising ideas based on input information.

[0747] "Ad Proposals" are a set of draft ad content suggested by a generative model.

[0748] A "user interface" is an interactive screen or operating means for a user to interact with a system.

[0749] "Emotion data" is information about emotions obtained by analyzing the user's facial expressions and voice.

[0750] "Presentation materials" are slides and documents used for presentations that are based on advertising proposals.

[0751] The "means for generating voice" is a technology that automatically generates voice based on text information.

[0752] A "presentation video" is a video presentation that combines audio corresponding to the presentation materials.

[0753] "Emotion analysis" is the process of analyzing collected emotion data to understand a user's emotional state.

[0754] "Optimization methods" are technologies for improving and adjusting advertising proposals and presentation videos based on the results of sentiment analysis.

[0755] The "means of approval" is a mechanism that allows the user to check the final generated presentation video and approve it if they determine that there are no problems.

[0756] "Means of uploading" refers to the technology used to transmit and save data in order to publish the generated presentation video on the web.

[0757] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. By combining this system with an emotion engine that recognizes user emotions, the system can propose and optimize advertising proposals taking user emotions into consideration.

[0758] System configuration

[0759] The system consists of four components:

[0760] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0761] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[0762] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[0763] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[0764] Program processing explanation

[0765] Enter target information and product description

[0766] The user inputs target information and product description on the client terminal. This is done, for example, through a dedicated application or a web form. Specifically, the user starts the dedicated application and inputs target information and product description such as "young professionals" or "coffee brewed with the latest technology, special design" into the form.

[0767] Generate advertising proposals

[0768] The device sends the information entered to the server, where secure communication takes place using the HTTPS protocol. The server analyzes the received information and activates a generative AI model (e.g., a natural language generation algorithm built in Python). This generative AI model references a database of past success stories and generates a large number of ad suggestions based on the entered information. For example, ad suggestions may be generated that include a catchphrase such as "Start your day on a new level."

[0769] Advertisement selection and emotional data collection

[0770] The server sends the generated ad ideas to the user's device and displays them in an interactive dashboard format using HTML and JavaScript. At this time, an emotion engine is activated and collects user emotional data via a webcam and microphone. The emotional data is analyzed by an AI algorithm. The user selects the most attractive ad idea, and the selection is sent to the server.

[0771] Automatic generation of presentation materials and videos

[0772] The server activates a "presentation material generation module" based on the selected advertising proposal. This module converts the advertising proposal into presentation slides using, for example, Microsoft PowerPoint. Next, the server uses an automatic speech generation system (for example, Google Text-to-Speech API) to generate audio corresponding to each slide, and combines the generated audio with the slides to generate a presentation video using Adobe Premiere Pro.

[0773] Presentation video optimization and approval

[0774] The server sends the generated presentation video to the user's device. The user then views the presentation video using a dedicated viewer. At this time, the emotion engine is reactivated and collects and analyzes the user's emotional data via the webcam and microphone. Based on the analysis results, the server optimizes the presentation video to reflect the user's preferences. The user reviews the final presentation video, and if there are no problems, clicks the "Approve" button to notify the server of the approval operation.

[0775] Automatic Upload

[0776] The server automatically uploads the approved presentation video to the web using the YouTube Data API or other cloud storage APIs, and notifies the user after the upload is complete.

[0777] Specific examples

[0778] Example: Advertisement for a new coffee maker

[0779] 1. The user enters the target information "young professionals" and the product description "coffee brewed with the latest technology, special design" into a form in a dedicated application.

[0780] 2. The device sends this information to a server, which uses a generative AI model to generate ad suggestions, including taglines like "Start your day on a new level."

[0781] 3. The user browses the generated ad suggestions on the web dashboard, and the emotion engine collects the user's emotional data via the webcam and microphone. The user then selects the most appealing ad suggestion.

[0782] 4. The server creates a presentation using Microsoft PowerPoint based on the selected ad proposal, and then combines the audio generated by the Google Text-to-Speech API with the slides in Adobe Premiere Pro to generate a video presentation.

[0783] 5. The user reviews the presentation video, and the emotion engine again collects and analyzes the emotion data. The server optimizes the video based on the analysis results.

[0784] 6. The user approves the optimized presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel via API.

[0785] This system enables advertising designers and public relations personnel to efficiently generate advertising proposals and create and publish presentation videos optimized based on user emotional data.

[0786] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0787] Step 1:

[0788] The user inputs target information and product description on the client device. The user launches a dedicated application or web form and inputs target information (e.g., young professionals) and product description (e.g., coffee brewed with the latest technology, special design). This input data is structured in JSON format and sent to the server.

[0789] Step 2:

[0790] The device sends the input information to the server. Communication is secure using the HTTPS protocol. The server analyzes the received information and passes target information and product descriptions to the generative model. This activates a natural language generation algorithm written in Python to generate ad suggestions based on the input data. Multiple ad suggestions are generated as output.

[0791] Step 3:

[0792] The server sends the generated ad suggestions to the user's device. The ad suggestions are displayed on an interactive dashboard using HTML and JavaScript. At the same time, an emotion engine is activated to collect the user's emotional data through a webcam and microphone. The input emotional data is analyzed by an AI algorithm to determine the user's emotional state. Based on this, multiple ad suggestions are displayed to the user.

[0793] Step 4:

[0794] The user selects the most attractive advertising proposal. The selection is made through an interface operation such as clicking, and the data is sent to the server. The server then starts a presentation generation module based on the selected advertising proposal, and automatically generates a slide-format presentation using, for example, Microsoft PowerPoint. The presentation is then created as the output.

[0795] Step 5:

[0796] The server uses an automatic speech generation system (e.g., Google Text-to-Speech API) to generate audio corresponding to the presentation materials. Audio corresponding to each slide in the presentation materials is generated. The generated audio data and slide data are used to generate a presentation video using Adobe Premiere Pro. The presentation video is generated as the output.

[0797] Step 6:

[0798] The server sends the generated presentation video to the user's device. The user then watches the presentation video using a dedicated viewer. At this time, the emotion engine is activated again to collect and analyze the user's emotional data via the webcam and microphone. Based on the analysis results, the server optimizes the presentation video. For example, it edits out unattractive parts based on the user's emotional data. The optimized presentation video is generated as the output.

[0799] Step 7:

[0800] The user reviews the optimized presentation video and gives final approval by clicking the "Approve" button. This approval operation is notified to the server from the device. Finally, the server uses the approved presentation video and automatically uploads it to the web using the YouTube Data API or cloud storage API. The presentation video is then made public as an output.

[0801] By performing such specific processing at each step, advertising designers and public relations personnel can efficiently generate advertising proposals and quickly create and publish optimized presentation videos.

[0802] (Application example 2)

[0803] 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."

[0804] Conventional advertising production systems have difficulty reflecting user sentiment in the generation and optimization of ad ideas, and have limited means to maximize the effectiveness of ad ideas. Furthermore, they lack a comprehensive system for improving the efficiency of the ad production process. This has resulted in advertising designers and public relations personnel having to expend a great deal of effort and time.

[0805] The identification process by the identification 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 target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, means for recognizing user emotions and analyzing data, and means for optimizing the advertising proposals based on the recognized emotion data. This makes it possible to efficiently perform a series of processes from generating advertising proposals to publishing the presentation video, and to create optimized advertising proposals that reflect user emotions.

[0806] "Target information" is information about the user profile or customer segment that is the target of the advertisement.

[0807] "Product description" refers to information about the detailed features and specifications of the product or service being advertised.

[0808] A "generative model" is a system that uses machine learning algorithms and artificial intelligence to generate advertising ideas based on input data.

[0809] "Advertising Proposals" are advertising ideas or suggestions created by a generative model.

[0810] "Presentation materials" are slides and documents used for presentations created based on advertising proposals.

[0811] A "presentation video" is a video presentation that adds audio and animation to presentation materials.

[0812] The "emotion engine" is a system that recognizes the user's emotions and analyzes the data.

[0813] "Optimization" is the process of improving and adjusting advertising proposals and presentation videos based on collected data in accordance with user emotions.

[0814] "Upload" refers to the transfer of generated and approved content to a web service or cloud storage on the Internet.

[0815] This invention provides a system that enables advertising designers and public relations personnel to efficiently generate advertising proposals, and also creates and publishes presentation videos that are optimized based on user emotion data.

[0816] The system includes the following components:

[0817] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0818] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[0819] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[0820] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[0821] Program processing explanation

[0822] Enter target information and product description

[0823] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[0824] Generate advertising proposals

[0825] The device sends the input information to a server, which then uses the received information to activate a generative model that generates a large number of ad ideas. This generative model uses machine learning algorithms and AI systems and references a database of past success stories.

[0826] Advertisement selection and emotional data collection

[0827] The server transmits the generated advertisement proposals to the user terminal and displays them on the user interface. At this time, the emotion engine is activated to collect the user's emotions regarding the displayed advertisement proposals. The user selects an advertisement proposal. The selected advertisement proposal is retransmitted to the server together with the emotion data collected by the emotion engine.

[0828] Automatic generation of presentation materials and videos

[0829] The server activates a presentation material generation module based on the selected advertising proposals. The presentation material generation module converts the selected advertising proposals into presentation slides. The server then uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[0830] Presentation video optimization and approval

[0831] The server sends the generated presentation video to the user's device. When the user reviews the presentation video, the emotion engine is reactivated and analyzes the user's emotions. Based on the analysis results, the server optimizes the presentation video. For example, it may edit out parts the user dislikes. The user reviews the presentation video and, if there are no problems, clicks the "Approve" button. This operation causes the device to notify the server of the approval operation.

[0832] Automatic Upload

[0833] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or video sharing platform.

[0834] Hardware and software used

[0835] Hardware: smartphones, computers, servers

[0836] Software: Python3, requests library, transformers library, emotion_recognition library

[0837] Specific examples

[0838] For example, to create an advertisement for a new coffee maker, a user might enter the following information:

[0839] Brand Name: "Latest Coffee Maker"

[0840] Target Audience: "Young Professionals"

[0841] Product Description: "Coffee brewed with the latest technology, special design"

[0842] Image file path for emotion recognition: " / path / to / user / image.jpg"

[0843] Based on this information, the generative model generates ad ideas with taglines such as "Start your day on a new level." The emotion engine collects emotional data as users view the ad ideas.

[0844] Based on the collected emotional data, the server generates optimized presentation materials and videos, and once the user approves the presentation video, the server automatically uploads the video to the company's official website and YouTube channel.

[0845] Prompt Sentence Examples

[0846] Enter your brand name: Latest Coffee Maker

[0847] Enter your target audience: Young Professionals

[0848] Enter your product description: Latest technology, special design

[0849] Enter the image file path for emotion recognition: / path / to / user / image.jpg

[0850] This system allows advertising designers and public relations personnel to efficiently generate advertising proposals, and also allows them to create and publish presentation videos optimized based on user emotional data.

[0851] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0852] Step 1:

[0853] The user inputs target information and product description on the client terminal, for example, using input fields in the dedicated application to input information such as brand name, target audience, product description, etc. The input data is used for subsequent processes.

[0854] Input: Brand name, target audience, product description

[0855] Output: Input target information and product description data

[0856] Step 2:

[0857] The device sends the target information and product description entered by the user to the server, which then activates the generative AI model based on the received information.

[0858] Input: Target information and product description data

[0859] Output: Sending input data to the server

[0860] Step 3:

[0861] The server generates advertising proposals using a generative AI model. The server references a database of past success stories and automatically generates multiple advertising proposals. The generated advertising proposals are sent to the user's device.

[0862] Input: Target information and product description data

[0863] Output: Multiple ad proposal data

[0864] Step 4:

[0865] The user terminal displays the generated advertising proposals. The user browses the displayed multiple advertising proposals and selects the most suitable one. At this time, the emotion engine is activated and collects the user's emotion data.

[0866] Input: Multiple ad proposal data

[0867] Output: Displayed ad suggestions, user sentiment data

[0868] Step 5:

[0869] The device retransmits the advertisement proposal selected by the user to the server. The emotion data collected by the emotion engine is also sent to the server at the same time. The server then generates the optimal presentation materials based on this information.

[0870] Input: Selected ad proposal data, user emotion data

[0871] Output: Sending selection data and emotion data to the server

[0872] Step 6:

[0873] The server activates a presentation material generation module based on the selected advertisement proposal and the user's emotion data, and the presentation material generation module converts the selected advertisement proposal into slides for presentation.

[0874] Input: Selected ad proposal data, user emotion data

[0875] Output: Generated presentation slides

[0876] Step 7:

[0877] The server uses an automatic voice generation system to generate voice corresponding to the presentation slides, and combines the generated voice with the slides to generate a presentation video.

[0878] Input: Generated presentation slides

[0879] Output: Generated presentation video

[0880] Step 8:

[0881] The server sends the generated presentation video to the user's device. When the user views the presentation video, the emotion engine is activated again to analyze the user's emotions.

[0882] Input: Generated presentation video

[0883] Output: Sending the presentation video to the user, user emotion data

[0884] Step 9:

[0885] The server optimizes the presentation video based on the analysis results. For example, it may edit out parts the user dislikes. The user then checks the optimized presentation video and clicks the "Approve" button if there are no problems.

[0886] Input: User emotion data

[0887] Output: Optimized presentation video, user approval

[0888] Step 10:

[0889] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or video sharing platform.

[0890] Input: Approved presentation video

[0891] Output: Upload video to the web

[0892] 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.

[0893] 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.

[0894] 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.

[0895] [Third embodiment]

[0896] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0897] 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.

[0898] 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).

[0899] 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.

[0900] 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.

[0901] 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).

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] 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."

[0908] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. Specific embodiments of the system are described below.

[0909] System configuration

[0910] The system consists of three main components:

[0911] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[0912] 2. Server: This is the server that hosts the generative model and the presentation creation tool.

[0913] 3. Web platform: Web services and cloud storage for publishing the final presentation video.

[0914] Program processing explanation

[0915] The specific operations of each component of the system will be described below.

[0916] 1. Enter target information and product description

[0917] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[0918] 2. Generate advertising ideas

[0919] The device sends the input information to a server, which then uses a generative model to generate a large number of ad ideas based on the received information. The generative model uses machine learning algorithms and AI systems to propose new ad ideas based on past success stories.

[0920] 3. Select an ad idea

[0921] The server sends the generated advertisement suggestions to the user terminal and displays them on the user interface. The user selects the most suitable one from the proposed advertisement suggestions. The selected advertisement suggestion is then sent back to the server.

[0922] 4. Automatic generation of presentation materials and videos

[0923] The server activates a "presentation material generation module" based on the selected advertising proposal. The presentation material generation module converts the selected advertising proposal into slides for presentation. Next, the server uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[0924] 5. Approval and automatic upload

[0925] The generated presentation video is sent from the server to the user's device, where the user can review it and click the "Approve" button. Once approved, the server automatically uploads the video to the web platform.

[0926] Specific examples

[0927] Example: Advertisement for a new coffee maker

[0928] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[0929] 2. The server uses the generative model to generate a large number of ad ideas, including taglines such as "Start your day on a new level."

[0930] 3. The user selects the most attractive ad from the proposed ads.

[0931] 4. The server creates presentation materials based on the selected advertising proposal, and uses an automatic voice generation system to add audio such as "The latest coffee maker will change your mornings" to generate a presentation video.

[0932] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[0933] Using this system, advertising designers and public relations personnel can efficiently create advertising proposals, generate presentation videos, and publish them online.

[0934] The processing flow will be explained below.

[0935] Step 1:

[0936] The user enters target information and product description on the client terminal, entering detailed information such as target demographic, product features, and keywords through input fields in a web form or dedicated application.

[0937] Step 2:

[0938] The device sends the entered information to the server, and passes target information and product description data to the server using an API request.

[0939] Step 3:

[0940] The server then uses the received information to launch a generative model, which generates a large number of ad ideas. The generative model uses machine learning algorithms and AI systems, and references a database of past success stories.

[0941] Step 4:

[0942] The server sends the generated ad proposal to the user's device and returns the generated ad proposal and related data as an API response.

[0943] Step 5:

[0944] The device displays the received ad proposals on the user interface, along with a list of each proposal's catchphrase and predicted performance.

[0945] Step 6:

[0946] The user selects the most suitable ad from the displayed ad suggestions by clicking on the best ad suggestion from the options and then clicking on the "Select" button.

[0947] Step 7:

[0948] The device sends the selected ad proposal to the server again, and sends an API request including the identification information of the selected ad proposal.

[0949] Step 8:

[0950] The server starts the "presentation material generation module" and generates presentation materials based on the selected advertisement proposals. The server converts the text and images of the advertisement proposals into the required format to create slides for the presentation.

[0951] Step 9:

[0952] The server uses an automatic speech generation system to generate audio for each slide in the presentation, and a text-to-speech tool to convert the content of each slide into audio.

[0953] Step 10:

[0954] The server combines the generated audio with the slides to generate a video presentation. A video generation tool is used to add audio to the slides and create a video file.

[0955] Step 11:

[0956] The server sends the generated presentation video to the user's device and returns the completed video file as an API response.

[0957] Step 12:

[0958] The device displays the received presentation video on the user interface, and the user can view the video using a video player.

[0959] Step 13:

[0960] The user checks the presentation video and clicks the "Approve" button if there are no problems. If there are no problems with the presentation content, the approval operation is performed.

[0961] Step 14:

[0962] The device notifies the server of the approval operation and sends an API request including the approval information to the server.

[0963] Step 15:

[0964] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[0965] Example 1

[0966] 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."

[0967] The process of advertising designers and public relations personnel efficiently generating advertising proposals, creating presentation videos, and finally publishing them online is extremely time-consuming and labor-intensive when done manually. A system that automates and efficiently performs this process is needed. In particular, technology that can smoothly integrate each step, such as data entry, generating advertising proposals, creating presentation materials, generating audio, and creating and publishing the final presentation video, is needed.

[0968] 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.

[0969] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, and means for automating the generation and uploading of the presentation video. This makes it possible to efficiently perform processes from creating advertising proposals to generating the presentation video and publishing it on the web.

[0970] "Targeted Information" refers to information about a specific audience or group for advertising or marketing purposes.

[0971] "Product description" refers to information that explains the features, benefits, and usage of the products or services you offer.

[0972] "Generative modeling" refers to the technique of using machine learning algorithms and AI systems to generate new ideas and data.

[0973] "Advertising Proposal" refers to a proposal for a catchy slogan or visual content generated for the purpose of promoting a product or service.

[0974] "Presentation materials" refer to slides and documents created based on advertising proposals, and are materials used to visually convey information about products and services.

[0975] "Presentation video" refers to video content that adds audio and animation to presentation materials to dynamically convey information to viewers.

[0976] "Approval" refers to the act of finally reviewing the generated presentation video and giving permission before it is made public.

[0977] "Uploading to the web" refers to the act of publishing generated content on an internet platform or website.

[0978] "Automating the process of generating and uploading presentation videos" refers to a series of processes in which the system automatically creates presentation videos and publishes them on the web, without the need for manual work.

[0979] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. A specific embodiment of this system will be described below.

[0980] System configuration

[0981] The system consists of three main components:

[0982] 1. User devices: Computers and smart devices operated by advertising designers and public relations personnel. Specifically, these include personal computers, tablets, and smartphones.

[0983] 2. Server: A computer system that hosts the generative model and the presentation creation tool. The server must have high-performance processing power and sufficient storage capacity. A cloud-based server can also be used.

[0984] 3. Web Platform: Web services and cloud storage for publishing the final presentation video. Specifically, this includes the company's official website and video sharing services such as YouTube and Vimeo.

[0985] Program processing

[0986] The system program executes processing in the following manner.

[0987] 1. Enter target information and product description

[0988] A user inputs target information and a product description using a client terminal. The user inputs target information (e.g., "young professionals") and a product description (e.g., "coffee brewed with the latest technology, special design"), for example, through a web form or a dedicated application.

[0989] 2. Generate advertising ideas

[0990] The device sends the input information to a server. The server uses the received information to run a generative AI model to generate a large number of ad ideas. The generative AI model learns from past success stories and marketing data, and uses this data to propose new ad ideas.

[0991] 3. Select an ad idea

[0992] The server sends the generated advertisement suggestions to the user's terminal, which displays them through a user interface. The user selects the most suitable one from the presented advertisement suggestions and sends the selection result to the server via the terminal.

[0993] 4. Automatic generation of presentation materials and videos

[0994] The server automatically generates presentation materials based on the selected advertising proposals. The presentation material generation module converts the advertising proposals into slide format. The server then uses an automatic audio generation system to generate audio corresponding to each slide, thereby completing a presentation video with audio.

[0995] 5. Approval and automatic upload

[0996] The server sends the generated presentation video to the user's device, where the user can review and approve it. After approval, the server automatically uploads the presentation video to the web platform. This process reduces manual errors and greatly improves efficiency.

[0997] Specific examples

[0998] Example: Advertisement for a new coffee maker

[0999] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[1000] 2. The device sends the input data to the server, which uses the generative model to generate ad ideas including slogans such as "Start your day on a new level."

[1001] 3. The server sends the proposed advertisements to the user's terminal, and the user selects the most attractive one from the proposed advertisements.

[1002] 4. The server creates presentation materials based on the selected advertising proposal, uses an automatic voice generation system to generate audio such as "The latest coffee maker will change your morning," and creates a presentation video.

[1003] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[1004] This system allows advertising designers and public relations personnel to efficiently create advertising proposals, generate presentation videos, and publish them online.

[1005] Example prompts for generative AI models

[1006] "To advertise coffee brewed using the latest technology, target information: young professionals. Product description: A coffee maker with a special design that uses the latest technology. Please create an ad proposal based on this information."

[1007] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1008] Step 1:

[1009] The user inputs target information and product description. The user inputs target information (e.g., "young professionals") and product description (e.g., "coffee brewed with the latest technology, special design") using a web form in a browser or a dedicated application. The input data is stored in a built-in data structure.

[1010] (Input) Target information, product description

[1011] (Output) Save the entered data

[1012] Step 2:

[1013] The device sends the entered information to the server, where the data is encrypted and securely transferred to the server.

[1014] (Input) Data entered

[1015] (Output) Data sent to the server

[1016] Step 3:

[1017] The server analyzes the target information and product description it receives. Based on the analysis results, the server creates a prompt for the generative AI model. The generative AI model is used to generate multiple ad proposals.

[1018] (Input) Data sent to the server

[1019] (Output) Generated ad ideas

[1020] Step 4:

[1021] The server sends the generated advertisement proposal to the user terminal, which temporarily stores the generated advertisement proposal in an internal database and sends it to the terminal for display through the user interface.

[1022] (Input) Generated ad ideas

[1023] (Output) Advertisement proposals sent to the device

[1024] Step 5:

[1025] The user selects the most suitable advertisement from the presented advertisements, and the information selected by the user is sent back to the server via the terminal.

[1026] (Input) Advertisement proposal selection information

[1027] (Output) Selection information sent to the server

[1028] Step 6:

[1029] The server generates presentation materials based on the selected advertisement proposals. A "presentation material generation module" in the server operates and converts the selected advertisement proposals into presentation slides.

[1030] (Input) Selected ad idea

[1031] (Output) Generated presentation materials

[1032] Step 7:

[1033] The server uses an automatic voice generation system to generate voice corresponding to the generated presentation materials. The generated voice data and slide data are integrated to complete the presentation video.

[1034] (Input) Presentation materials

[1035] (Output) Generated presentation video

[1036] Step 8:

[1037] The server sends the generated presentation video to the user's terminal, where the user can view the presentation video and click the approval button to generate approval information.

[1038] (Input) Generated presentation video

[1039] (Output) Presentation video sent to user device

[1040] Step 9:

[1041] The server uploads the approved presentation video to a web platform, which makes the video available on the company's official website or video sharing service.

[1042] (Input) Approval information, presentation video

[1043] (Output) Presentation video uploaded to the web platform

[1044] (Application example 1)

[1045] 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."

[1046] The traditional process of creating ad proposals and video presentations was time-consuming and inefficient. It often required expensive software and specialized knowledge, making it difficult for small teams or individual ad designers to access. Furthermore, publishing the resulting ads and presentations online required multiple steps, which was time-consuming and laborious.

[1047] 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.

[1048] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, means for an advertising designer to generate advertising proposals on a smartphone, create a presentation video, and publish it on the web, means for presenting the generated advertising proposals on the server, means for automatically generating a presentation video with audio based on the selected advertising proposal, and means for automatically uploading the generated presentation video to a web platform. This enables advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and instantly publish them on the web.

[1049] "Target information" refers to information such as the attributes, preferences, and behavioral patterns of consumers targeted by an advertising campaign.

[1050] "Product description" is information that provides detailed explanations of the characteristics, functions, advantages, specifications, etc. of the advertised product.

[1051] A "generative model" is a model that uses machine learning algorithms or AI systems to generate advertising ideas from input data.

[1052] "Advertising Proposal" means a proposal or concept created to promote a product or service.

[1053] A "server" is a computer system for receiving and processing data and hosting generative models.

[1054] "Presentation materials" are slides and documents created based on advertising proposals and used for explanations and presentations.

[1055] A "video presentation with audio" is a video presentation that is created with audio explanations corresponding to the presentation materials.

[1056] "Auto-uploading" is the process of publishing system-generated content to the web without manual intervention.

[1057] A "web platform" is an internet service or cloud storage that allows generated presentation videos and advertisements to be published and made viewable.

[1058] A "smartphone" is a mobile phone and is a device used by a user to generate and manage advertising proposals.

[1059] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web using smartphones. Specific embodiments for carrying out the invention are described below.

[1060] The system mainly consists of the following components:

[1061] Smartphone terminal: A device where users can input target information and product descriptions and view generated advertising proposals.

[1062] Server: This is the central system that receives and sends data, runs generative models, generates presentations and videos, and automatically uploads them.

[1063] Web Platform: An online service for publishing the final presentation video and making it widely accessible.

[1064] Technology used

[1065] The system consists of the following key technologies:

[1066] Generative AI models: Use advanced generative algorithms, such as OpenAI's GPT-3, to generate ad suggestions based on input.

[1067] Video generation software: Tools to generate video from presentations and add audio, for example using the Google Text-to-Speech engine.

[1068] Servers and cloud storage: Infrastructure for processing and storing data, typically using cloud services such as AWS or Google Cloud.

[1069] Program processing

[1070] Step 1: Enter target information and product description

[1071] The user enters target information and product description using a dedicated application form on their smartphone, and the entered data is sent to the server via an HTTP request.

[1072] Step 2: Generate ad proposals

[1073] The server runs a generative AI model based on the received information to generate a large number of ad ideas, incorporating past advertising success stories and target behavior patterns into the model.

[1074] Step 3: Select your ad idea

[1075] The generated ad proposals are sent from the server to the smartphone device and displayed on the user interface. The user selects the most suitable ad proposal from multiple proposals, and the selection result is sent back to the server.

[1076] Step 4: Generate a video of your presentation

[1077] The server creates presentation materials based on the selected advertising proposal and adds audio using an automatic voice generation system (e.g., Google Text-to-Speech), generating a presentation video that appeals to both the eyes and the ears.

[1078] Step 5: Approval and Auto Upload

[1079] The generated presentation video is sent from the server to the user's device, where the user can review the content and approve it by clicking the approval button. Approved videos are automatically uploaded to the web platform and made publicly available.

[1080] Specific examples

[1081] For example, consider an advertising designer creating an advertisement for a new smartphone.

[1082] 1. The user enters the target information as "young people interested in technology" and the product description as "a smartphone equipped with the latest camera technology and a high-performance battery."

[1083] 2. The server uses the generative AI model to generate a large number of advertising ideas, including catchy slogans such as "Enrich your smartphone life with the latest technology."

[1084] 3. The user selects the most attractive ad from the proposed ads.

[1085] 4. The server creates presentation materials based on the selected advertising proposal and uses an automatic voice generation system to add audio such as "This smartphone will revolutionize your daily life" to generate a presentation video.

[1086] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[1087] Prompt Sentence Examples

[1088] "Target: Younger generations interested in technology, Product description: Generate ad ideas for a smartphone with the latest camera technology and a powerful battery."

[1089] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1090] Step 1:

[1091] The user inputs target information and product description on their smartphone. This is done through a form in a dedicated application. The input target information and product description are sent to the server as an HTTP request. The input data is structured and includes target information such as age and hobbies, and product description information such as function details.

[1092] Step 2:

[1093] The server generates a prompt for the generative AI model based on the target information and product description received. This prompt is appropriately constructed for generating ad proposals, for example, "Target: Young generation interested in technology, Product description: Please generate an ad proposal for a smartphone equipped with the latest camera technology and a high-performance battery." This prompt is sent to the generative AI model to generate ad proposals. The generated ad proposals are output in multiple text formats.

[1094] Step 3:

[1095] The server sends the generated ad proposals to the smartphone device. Multiple ad proposals are displayed on the user interface. The user visually reviews these ad proposals and selects the most suitable one. The user's selection is then sent back to the server.

[1096] Step 4:

[1097] The server automatically generates presentation materials based on the selected advertising proposal. The presentation materials are created in a slide format such as PowerPoint, with each slide displaying the main message and visuals of the advertising proposal. In addition, a voice generation engine (e.g., Google Text-to-Speech) is used to generate narration audio corresponding to each slide. This audio data is combined with the slides to generate a presentation video.

[1098] Step 5:

[1099] The server sends the generated presentation video to the smartphone device so that the user can review it. The user plays the presentation video, checks the content, and if satisfied, clicks the "Approve" button. This approval information is sent to the server.

[1100] Step 6:

[1101] The server automatically uploads the approved presentation video to a web platform (e.g., YouTube or the company's website). Once the upload is complete, the user is notified and the generated video is made public. This allows advertising designers to efficiently create requested advertising proposals and widely publish them in a short time.

[1102] 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.

[1103] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. Furthermore, by combining this with an emotion engine that recognizes user emotions, it is possible to propose and optimize advertising proposals that take user emotions into consideration. A specific embodiment of the system is described below.

[1104] System configuration

[1105] The system consists of four main components:

[1106] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[1107] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[1108] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[1109] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[1110] Program processing explanation

[1111] The specific operations of each component of the system will be described below.

[1112] 1. Enter target information and product description

[1113] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[1114] 2. Generate advertising ideas

[1115] The device sends the input information to a server, which then uses the received information to activate a generative model that generates a large number of ad ideas. This generative model uses machine learning algorithms and AI systems and references a database of past success stories.

[1116] 3. Selecting advertising ideas and collecting emotional data

[1117] The server transmits the generated advertisement proposal to the user terminal and displays it on the user interface, and the emotion engine is activated to collect the user's emotions regarding the displayed advertisement proposal.

[1118] The user selects an ad suggestion, which is then retransmitted to the server along with the emotion data collected by the emotion engine.

[1119] 4. Automatic generation of presentation materials and videos

[1120] The server activates a "presentation material generation module" based on the selected advertising proposal. The presentation material generation module converts the selected advertising proposal into slides for presentation. Next, the server uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[1121] 5. Optimize and approve your presentation video

[1122] The server sends the generated presentation video to the user's device. When the user reviews the presentation video, the emotion engine is reactivated and analyzes the user's emotions. Based on the analysis results, the server optimizes the presentation video. For example, it may edit out parts the user dislikes.

[1123] The user checks the presentation video and, if there are no problems, clicks the "Approve" button. This operation causes the device to notify the server of the approval operation.

[1124] 6. Automatic upload

[1125] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[1126] Specific examples

[1127] Example: Advertisement for a new coffee maker

[1128] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[1129] 2. The server uses the generative model to generate a large number of ad ideas, including taglines such as "Start your day on a new level."

[1130] 3. The user browses the generated ad suggestions, and the emotion engine collects the user's emotional data in the process. It then selects the most attractive ad from the suggested suggestions.

[1131] 4. The server creates presentation materials based on the selected advertising proposal, and uses an automatic voice generation system to add audio such as "The latest coffee maker will change your mornings" to generate a presentation video.

[1132] 5. The user reviews the presentation video, and the emotion engine analyzes the user's emotions again. Based on the analysis results, the presentation video is optimized.

[1133] 6. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[1134] This system allows advertising designers and public relations personnel to efficiently generate advertising proposals, and also allows them to create and publish presentation videos optimized based on user emotional data.

[1135] The processing flow will be explained below.

[1136] Step 1:

[1137] The user inputs target information and product description on the client terminal. For example, the user inputs the target demographic (e.g., "young professionals") and product description (e.g., "coffee brewed with the latest technology, special design") using a web form or dedicated application.

[1138] Step 2:

[1139] The device sends the entered information to the server, which then uses an API request to pass target information and product description data to the server.

[1140] Step 3:

[1141] The server then uses the received information to activate a generative model, which then generates a large number of ad ideas. The generative model uses machine learning algorithms and AI systems and references a database of past success stories. For example, it generates ad ideas with catchphrases such as "Start your day on a new level" or "Your special drink, creative."

[1142] Step 4:

[1143] The server sends the generated ad proposal to the user terminal, and returns the generated ad proposal and related data to the user terminal as an API response.

[1144] Step 5:

[1145] The device displays the received ad proposals on the user interface, along with a list of each proposal's catchphrase and predicted performance.

[1146] Step 6:

[1147] The emotion engine is activated and collects user emotion data when ad proposals are displayed, for example, by analyzing emotions from the user's facial expressions and voice.

[1148] Step 7:

[1149] The user selects the most suitable ad from the displayed suggestions. The emotion engine continues to analyze the user's reactions and emotions during the selection process, and finally clicks the "Select" button to confirm the ad suggestion.

[1150] Step 8:

[1151] The device transmits the selected ad proposal and emotion data to the server again, and sends an API request to the server including the identification information of the selected ad proposal and the associated emotion data.

[1152] Step 9:

[1153] The server starts a "presentation material generation module" to generate presentation materials based on the selected advertisement proposal, creating slides for the presentation and converting the text and images of the advertisement proposal into the required format.

[1154] Step 10:

[1155] The server uses an automatic speech generation system to generate audio for each slide in the presentation, and a text-to-speech tool to convert the content of each slide into audio.

[1156] Step 11:

[1157] The server combines the generated audio with the slides to generate a video presentation. A video generation tool is used to add audio to the slides and create a video file.

[1158] Step 12:

[1159] The server sends the generated presentation video to the user's device, and returns the completed video file to the user's device as an API response.

[1160] Step 13:

[1161] The device displays the received presentation video on the user interface, and the user can view the video using a video player.

[1162] Step 14:

[1163] The emotion engine is then reactivated to analyze the emotions of the user as they watch the presentation video. While the user is watching the video, the emotion engine analyzes their facial expressions and voice.

[1164] Step 15:

[1165] The server optimizes the presentation video based on the analysis results of the emotion engine. For example, it edits out parts where the user expressed dissatisfaction or boredom, and generates an improved version.

[1166] Step 16:

[1167] The user checks the optimized presentation video again and, if there are no problems, clicks the "Approve" button. If there are no problems with the presentation content, the approval operation is performed.

[1168] Step 17:

[1169] The device notifies the server of the approval operation and sends an API request including the approval information to the server.

[1170] Step 18:

[1171] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[1172] This specific processing flow enables the generation and optimization of advertising proposals that take user emotions into consideration, allowing advertising designers and public relations personnel to work efficiently.

[1173] Example 2

[1174] 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."

[1175] With current technology, the process for advertising designers and public relations personnel to efficiently generate advertising proposals, optimize the proposals and presentation videos taking user emotions into account, and finally publish them on the web requires a great deal of time and effort. Furthermore, adjusting the proposals based on user emotions is difficult, making it difficult to create advertisements that attract users' attention. Therefore, there is a need for a system that can easily and efficiently generate and optimize advertising proposals, create presentation videos that reflect user emotions, and quickly publish them.

[1176] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1177] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for displaying the advertising proposals on a user interface, means for collecting user emotion data regarding the displayed advertising proposals, means for generating presentation materials based on selected advertising proposals, means for generating audio corresponding to the presentation materials and creating a presentation video, means for optimizing the generated presentation video based on emotion analysis, means for approving the optimized presentation video, and means for uploading the approved presentation video to the web. This enables advertising designers and public relations personnel to efficiently generate advertising proposals and create and quickly publish optimal presentation videos that reflect user emotions.

[1178] "Target information" is information about specific people or groups to whom advertising is intended to be directed.

[1179] "Product description" is information detailing the features, performance, price, benefits, etc. of the advertised product.

[1180] "Transmission means" refers to the technical mechanism for sending data from the user terminal to the server.

[1181] A "generative model" is an algorithm that automatically generates advertising ideas based on input information.

[1182] "Ad Proposals" are a set of draft ad content suggested by a generative model.

[1183] A "user interface" is an interactive screen or operating means for a user to interact with a system.

[1184] "Emotion data" is information about emotions obtained by analyzing the user's facial expressions and voice.

[1185] "Presentation materials" are slides and documents used for presentations that are based on advertising proposals.

[1186] The "means for generating voice" is a technology that automatically generates voice based on text information.

[1187] A "presentation video" is a video presentation that combines audio corresponding to the presentation materials.

[1188] "Emotion analysis" is the process of analyzing collected emotion data to understand a user's emotional state.

[1189] "Optimization methods" are technologies for improving and adjusting advertising proposals and presentation videos based on the results of sentiment analysis.

[1190] The "means of approval" is a mechanism that allows the user to check the final generated presentation video and approve it if they determine that there are no problems.

[1191] "Means of uploading" refers to the technology used to transmit and save data in order to publish the generated presentation video on the web.

[1192] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. By combining this system with an emotion engine that recognizes user emotions, the system can propose and optimize advertising proposals taking user emotions into consideration.

[1193] System configuration

[1194] The system consists of four components:

[1195] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[1196] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[1197] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[1198] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[1199] Program processing explanation

[1200] Enter target information and product description

[1201] The user inputs target information and product description on the client terminal. This is done, for example, through a dedicated application or a web form. Specifically, the user starts the dedicated application and inputs target information and product description such as "young professionals" or "coffee brewed with the latest technology, special design" into the form.

[1202] Generate advertising proposals

[1203] The device sends the information entered to the server, where secure communication takes place using the HTTPS protocol. The server analyzes the received information and activates a generative AI model (e.g., a natural language generation algorithm built in Python). This generative AI model references a database of past success stories and generates a large number of ad suggestions based on the entered information. For example, ad suggestions may be generated that include a catchphrase such as "Start your day on a new level."

[1204] Advertisement selection and emotional data collection

[1205] The server sends the generated ad ideas to the user's device and displays them in an interactive dashboard format using HTML and JavaScript. At this time, an emotion engine is activated and collects user emotional data via a webcam and microphone. The emotional data is analyzed by an AI algorithm. The user selects the most attractive ad idea, and the selection is sent to the server.

[1206] Automatic generation of presentation materials and videos

[1207] The server activates a "presentation material generation module" based on the selected advertising proposal. This module converts the advertising proposal into presentation slides using, for example, Microsoft PowerPoint. Next, the server uses an automatic speech generation system (for example, Google Text-to-Speech API) to generate audio corresponding to each slide, and combines the generated audio with the slides to generate a presentation video using Adobe Premiere Pro.

[1208] Presentation video optimization and approval

[1209] The server sends the generated presentation video to the user's device. The user then views the presentation video using a dedicated viewer. At this time, the emotion engine is reactivated and collects and analyzes the user's emotional data via the webcam and microphone. Based on the analysis results, the server optimizes the presentation video to reflect the user's preferences. The user reviews the final presentation video, and if there are no problems, clicks the "Approve" button to notify the server of the approval operation.

[1210] Automatic Upload

[1211] The server automatically uploads the approved presentation video to the web using the YouTube Data API or other cloud storage APIs, and notifies the user after the upload is complete.

[1212] Specific examples

[1213] Example: Advertisement for a new coffee maker

[1214] 1. The user enters the target information "young professionals" and the product description "coffee brewed with the latest technology, special design" into a form in a dedicated application.

[1215] 2. The device sends this information to a server, which uses a generative AI model to generate ad suggestions, including taglines like "Start your day on a new level."

[1216] 3. The user browses the generated ad suggestions on the web dashboard, and the emotion engine collects the user's emotional data via the webcam and microphone. The user then selects the most appealing ad suggestion.

[1217] 4. The server creates a presentation using Microsoft PowerPoint based on the selected ad proposal, and then combines the audio generated by the Google Text-to-Speech API with the slides in Adobe Premiere Pro to generate a video presentation.

[1218] 5. The user reviews the presentation video, and the emotion engine again collects and analyzes the emotion data. The server optimizes the video based on the analysis results.

[1219] 6. The user approves the optimized presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel via API.

[1220] This system enables advertising designers and public relations personnel to efficiently generate advertising proposals and create and publish presentation videos optimized based on user emotional data.

[1221] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1222] Step 1:

[1223] The user inputs target information and product description on the client device. The user launches a dedicated application or web form and inputs target information (e.g., young professionals) and product description (e.g., coffee brewed with the latest technology, special design). This input data is structured in JSON format and sent to the server.

[1224] Step 2:

[1225] The device sends the input information to the server. Communication is secure using the HTTPS protocol. The server analyzes the received information and passes target information and product descriptions to the generative model. This activates a natural language generation algorithm written in Python to generate ad suggestions based on the input data. Multiple ad suggestions are generated as output.

[1226] Step 3:

[1227] The server sends the generated ad suggestions to the user's device. The ad suggestions are displayed on an interactive dashboard using HTML and JavaScript. At the same time, an emotion engine is activated to collect the user's emotional data through a webcam and microphone. The input emotional data is analyzed by an AI algorithm to determine the user's emotional state. Based on this, multiple ad suggestions are displayed to the user.

[1228] Step 4:

[1229] The user selects the most attractive advertising proposal. The selection is made through an interface operation such as clicking, and the data is sent to the server. The server then starts a presentation generation module based on the selected advertising proposal, and automatically generates a slide-format presentation using, for example, Microsoft PowerPoint. The presentation is then created as the output.

[1230] Step 5:

[1231] The server uses an automatic speech generation system (e.g., Google Text-to-Speech API) to generate audio corresponding to the presentation materials. Audio corresponding to each slide in the presentation materials is generated. The generated audio data and slide data are used to generate a presentation video using Adobe Premiere Pro. The presentation video is generated as the output.

[1232] Step 6:

[1233] The server sends the generated presentation video to the user's device. The user then watches the presentation video using a dedicated viewer. At this time, the emotion engine is activated again to collect and analyze the user's emotional data via the webcam and microphone. Based on the analysis results, the server optimizes the presentation video. For example, it edits out unattractive parts based on the user's emotional data. The optimized presentation video is generated as the output.

[1234] Step 7:

[1235] The user reviews the optimized presentation video and gives final approval by clicking the "Approve" button. This approval operation is notified to the server from the device. Finally, the server uses the approved presentation video and automatically uploads it to the web using the YouTube Data API or cloud storage API. The presentation video is then made public as an output.

[1236] By performing such specific processing at each step, advertising designers and public relations personnel can efficiently generate advertising proposals and quickly create and publish optimized presentation videos.

[1237] (Application example 2)

[1238] 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."

[1239] Conventional advertising production systems have difficulty reflecting user sentiment in the generation and optimization of ad ideas, and have limited means to maximize the effectiveness of ad ideas. Furthermore, they lack a comprehensive system for improving the efficiency of the ad production process. This has resulted in advertising designers and public relations personnel having to expend a great deal of effort and time.

[1240] The identification process by the identification 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 target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, means for recognizing user emotions and analyzing data, and means for optimizing the advertising proposals based on the recognized emotion data. This makes it possible to efficiently perform a series of processes from generating advertising proposals to publishing the presentation video, and to create optimized advertising proposals that reflect user emotions.

[1241] "Target information" is information about the user profile or customer segment that is the target of the advertisement.

[1242] "Product description" refers to information about the detailed features and specifications of the product or service being advertised.

[1243] A "generative model" is a system that uses machine learning algorithms and artificial intelligence to generate advertising ideas based on input data.

[1244] "Advertising Proposals" are advertising ideas or suggestions created by a generative model.

[1245] "Presentation materials" are slides and documents used for presentations created based on advertising proposals.

[1246] A "presentation video" is a video presentation that adds audio and animation to presentation materials.

[1247] The "emotion engine" is a system that recognizes the user's emotions and analyzes the data.

[1248] "Optimization" is the process of improving and adjusting advertising proposals and presentation videos based on collected data in accordance with user emotions.

[1249] "Upload" refers to the transfer of generated and approved content to a web service or cloud storage on the Internet.

[1250] This invention provides a system that enables advertising designers and public relations personnel to efficiently generate advertising proposals, and also creates and publishes presentation videos that are optimized based on user emotion data.

[1251] The system includes the following components:

[1252] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[1253] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[1254] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[1255] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[1256] Program processing explanation

[1257] Enter target information and product description

[1258] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[1259] Generate advertising proposals

[1260] The device sends the input information to a server, which then uses the received information to activate a generative model that generates a large number of ad ideas. This generative model uses machine learning algorithms and AI systems and references a database of past success stories.

[1261] Advertisement selection and emotional data collection

[1262] The server transmits the generated advertisement proposals to the user terminal and displays them on the user interface. At this time, the emotion engine is activated to collect the user's emotions regarding the displayed advertisement proposals. The user selects an advertisement proposal. The selected advertisement proposal is retransmitted to the server together with the emotion data collected by the emotion engine.

[1263] Automatic generation of presentation materials and videos

[1264] The server activates a presentation material generation module based on the selected advertising proposals. The presentation material generation module converts the selected advertising proposals into presentation slides. The server then uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[1265] Presentation video optimization and approval

[1266] The server sends the generated presentation video to the user's device. When the user reviews the presentation video, the emotion engine is reactivated and analyzes the user's emotions. Based on the analysis results, the server optimizes the presentation video. For example, it may edit out parts the user dislikes. The user reviews the presentation video and, if there are no problems, clicks the "Approve" button. This operation causes the device to notify the server of the approval operation.

[1267] Automatic Upload

[1268] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or video sharing platform.

[1269] Hardware and software used

[1270] Hardware: smartphones, computers, servers

[1271] Software: Python3, requests library, transformers library, emotion_recognition library

[1272] Specific examples

[1273] For example, to create an advertisement for a new coffee maker, a user might enter the following information:

[1274] Brand Name: "Latest Coffee Maker"

[1275] Target Audience: "Young Professionals"

[1276] Product Description: "Coffee brewed with the latest technology, special design"

[1277] Image file path for emotion recognition: " / path / to / user / image.jpg"

[1278] Based on this information, the generative model generates ad ideas with taglines such as "Start your day on a new level." The emotion engine collects emotional data as users view the ad ideas.

[1279] Based on the collected emotional data, the server generates optimized presentation materials and videos, and once the user approves the presentation video, the server automatically uploads the video to the company's official website and YouTube channel.

[1280] Prompt Sentence Examples

[1281] Enter your brand name: Latest Coffee Maker

[1282] Enter your target audience: Young Professionals

[1283] Enter your product description: Latest technology, special design

[1284] Enter the image file path for emotion recognition: / path / to / user / image.jpg

[1285] This system allows advertising designers and public relations personnel to efficiently generate advertising proposals, and also allows them to create and publish presentation videos optimized based on user emotional data.

[1286] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1287] Step 1:

[1288] The user inputs target information and product description on the client terminal, for example, using input fields in the dedicated application to input information such as brand name, target audience, product description, etc. The input data is used for subsequent processes.

[1289] Input: Brand name, target audience, product description

[1290] Output: Input target information and product description data

[1291] Step 2:

[1292] The device sends the target information and product description entered by the user to the server, which then activates the generative AI model based on the received information.

[1293] Input: Target information and product description data

[1294] Output: Sending input data to the server

[1295] Step 3:

[1296] The server generates advertising proposals using a generative AI model. The server references a database of past success stories and automatically generates multiple advertising proposals. The generated advertising proposals are sent to the user's device.

[1297] Input: Target information and product description data

[1298] Output: Multiple ad proposal data

[1299] Step 4:

[1300] The user terminal displays the generated advertising proposals. The user browses the displayed multiple advertising proposals and selects the most suitable one. At this time, the emotion engine is activated and collects the user's emotion data.

[1301] Input: Multiple ad proposal data

[1302] Output: Displayed ad suggestions, user sentiment data

[1303] Step 5:

[1304] The device retransmits the advertisement proposal selected by the user to the server. The emotion data collected by the emotion engine is also sent to the server at the same time. The server then generates the optimal presentation materials based on this information.

[1305] Input: Selected ad proposal data, user emotion data

[1306] Output: Sending selection data and emotion data to the server

[1307] Step 6:

[1308] The server activates a presentation material generation module based on the selected advertisement proposal and the user's emotion data, and the presentation material generation module converts the selected advertisement proposal into slides for presentation.

[1309] Input: Selected ad proposal data, user emotion data

[1310] Output: Generated presentation slides

[1311] Step 7:

[1312] The server uses an automatic voice generation system to generate voice corresponding to the presentation slides, and combines the generated voice with the slides to generate a presentation video.

[1313] Input: Generated presentation slides

[1314] Output: Generated presentation video

[1315] Step 8:

[1316] The server sends the generated presentation video to the user's device. When the user views the presentation video, the emotion engine is activated again to analyze the user's emotions.

[1317] Input: Generated presentation video

[1318] Output: Sending the presentation video to the user, user emotion data

[1319] Step 9:

[1320] The server optimizes the presentation video based on the analysis results. For example, it may edit out parts the user dislikes. The user then checks the optimized presentation video and clicks the "Approve" button if there are no problems.

[1321] Input: User emotion data

[1322] Output: Optimized presentation video, user approval

[1323] Step 10:

[1324] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or video sharing platform.

[1325] Input: Approved presentation video

[1326] Output: Upload video to the web

[1327] 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.

[1328] 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.

[1329] 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.

[1330] [Fourth embodiment]

[1331] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1332] 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.

[1333] 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).

[1334] 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.

[1335] 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.

[1336] 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).

[1337] 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.

[1338] 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.

[1339] 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.

[1340] 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.

[1341] 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.

[1342] 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.

[1343] 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."

[1344] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. Specific embodiments of the system are described below.

[1345] System configuration

[1346] The system consists of three main components:

[1347] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[1348] 2. Server: This is the server that hosts the generative model and the presentation creation tool.

[1349] 3. Web platform: Web services and cloud storage for publishing the final presentation video.

[1350] Program processing explanation

[1351] The specific operations of each component of the system will be described below.

[1352] 1. Enter target information and product description

[1353] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[1354] 2. Generate advertising ideas

[1355] The device sends the input information to a server, which then uses a generative model to generate a large number of ad ideas based on the received information. The generative model uses machine learning algorithms and AI systems to propose new ad ideas based on past success stories.

[1356] 3. Select an ad idea

[1357] The server sends the generated advertisement suggestions to the user terminal and displays them on the user interface. The user selects the most suitable one from the proposed advertisement suggestions. The selected advertisement suggestion is then sent back to the server.

[1358] 4. Automatic generation of presentation materials and videos

[1359] The server activates a "presentation material generation module" based on the selected advertising proposal. The presentation material generation module converts the selected advertising proposal into slides for presentation. Next, the server uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[1360] 5. Approval and automatic upload

[1361] The generated presentation video is sent from the server to the user's device, where the user can review it and click the "Approve" button. Once approved, the server automatically uploads the video to the web platform.

[1362] Specific examples

[1363] Example: Advertisement for a new coffee maker

[1364] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[1365] 2. The server uses the generative model to generate a large number of ad ideas, including taglines such as "Start your day on a new level."

[1366] 3. The user selects the most attractive ad from the proposed ads.

[1367] 4. The server creates presentation materials based on the selected advertising proposal, and uses an automatic voice generation system to add audio such as "The latest coffee maker will change your mornings" to generate a presentation video.

[1368] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[1369] Using this system, advertising designers and public relations personnel can efficiently create advertising proposals, generate presentation videos, and publish them online.

[1370] The processing flow will be explained below.

[1371] Step 1:

[1372] The user enters target information and product description on the client terminal, entering detailed information such as target demographic, product features, and keywords through input fields in a web form or dedicated application.

[1373] Step 2:

[1374] The device sends the entered information to the server, and passes target information and product description data to the server using an API request.

[1375] Step 3:

[1376] The server then uses the received information to launch a generative model, which generates a large number of ad ideas. The generative model uses machine learning algorithms and AI systems, and references a database of past success stories.

[1377] Step 4:

[1378] The server sends the generated ad proposal to the user's device and returns the generated ad proposal and related data as an API response.

[1379] Step 5:

[1380] The device displays the received ad proposals on the user interface, along with a list of each proposal's catchphrase and predicted performance.

[1381] Step 6:

[1382] The user selects the most suitable ad from the displayed ad suggestions by clicking on the best ad suggestion from the options and then clicking on the "Select" button.

[1383] Step 7:

[1384] The device sends the selected ad proposal to the server again, and sends an API request including the identification information of the selected ad proposal.

[1385] Step 8:

[1386] The server starts the "presentation material generation module" and generates presentation materials based on the selected advertisement proposals. The server converts the text and images of the advertisement proposals into the required format to create slides for the presentation.

[1387] Step 9:

[1388] The server uses an automatic speech generation system to generate audio for each slide in the presentation, and a text-to-speech tool to convert the content of each slide into audio.

[1389] Step 10:

[1390] The server combines the generated audio with the slides to generate a video presentation. A video generation tool is used to add audio to the slides and create a video file.

[1391] Step 11:

[1392] The server sends the generated presentation video to the user's device and returns the completed video file as an API response.

[1393] Step 12:

[1394] The device displays the received presentation video on the user interface, and the user can view the video using a video player.

[1395] Step 13:

[1396] The user checks the presentation video and clicks the "Approve" button if there are no problems. If there are no problems with the presentation content, the approval operation is performed.

[1397] Step 14:

[1398] The device notifies the server of the approval operation and sends an API request including the approval information to the server.

[1399] Step 15:

[1400] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[1401] Example 1

[1402] 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."

[1403] The process of advertising designers and public relations personnel efficiently generating advertising proposals, creating presentation videos, and finally publishing them online is extremely time-consuming and labor-intensive when done manually. A system that automates and efficiently performs this process is needed. In particular, technology that can smoothly integrate each step, such as data entry, generating advertising proposals, creating presentation materials, generating audio, and creating and publishing the final presentation video, is needed.

[1404] 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.

[1405] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, and means for automating the generation and uploading of the presentation video. This makes it possible to efficiently perform processes from creating advertising proposals to generating the presentation video and publishing it on the web.

[1406] "Targeted Information" refers to information about a specific audience or group for advertising or marketing purposes.

[1407] "Product description" refers to information that explains the features, benefits, and usage of the products or services you offer.

[1408] "Generative modeling" refers to the technique of using machine learning algorithms and AI systems to generate new ideas and data.

[1409] "Advertising Proposal" refers to a proposal for a catchy slogan or visual content generated for the purpose of promoting a product or service.

[1410] "Presentation materials" refer to slides and documents created based on advertising proposals, and are materials used to visually convey information about products and services.

[1411] "Presentation video" refers to video content that adds audio and animation to presentation materials to dynamically convey information to viewers.

[1412] "Approval" refers to the act of finally reviewing the generated presentation video and giving permission before it is made public.

[1413] "Uploading to the web" refers to the act of publishing generated content on an internet platform or website.

[1414] "Automating the process of generating and uploading presentation videos" refers to a series of processes in which the system automatically creates presentation videos and publishes them on the web, without the need for manual work.

[1415] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. A specific embodiment of this system will be described below.

[1416] System configuration

[1417] The system consists of three main components:

[1418] 1. User devices: Computers and smart devices operated by advertising designers and public relations personnel. Specifically, these include personal computers, tablets, and smartphones.

[1419] 2. Server: A computer system that hosts the generative model and the presentation creation tool. The server must have high-performance processing power and sufficient storage capacity. A cloud-based server can also be used.

[1420] 3. Web Platform: Web services and cloud storage for publishing the final presentation video. Specifically, this includes the company's official website and video sharing services such as YouTube and Vimeo.

[1421] Program processing

[1422] The system program executes processing in the following manner.

[1423] 1. Enter target information and product description

[1424] A user inputs target information and a product description using a client terminal. The user inputs target information (e.g., "young professionals") and a product description (e.g., "coffee brewed with the latest technology, special design"), for example, through a web form or a dedicated application.

[1425] 2. Generate advertising ideas

[1426] The device sends the input information to a server. The server uses the received information to run a generative AI model to generate a large number of ad ideas. The generative AI model learns from past success stories and marketing data, and uses this data to propose new ad ideas.

[1427] 3. Select an ad idea

[1428] The server sends the generated advertisement suggestions to the user's terminal, which displays them through a user interface. The user selects the most suitable one from the presented advertisement suggestions and sends the selection result to the server via the terminal.

[1429] 4. Automatic generation of presentation materials and videos

[1430] The server automatically generates presentation materials based on the selected advertising proposals. The presentation material generation module converts the advertising proposals into slide format. The server then uses an automatic audio generation system to generate audio corresponding to each slide, thereby completing a presentation video with audio.

[1431] 5. Approval and automatic upload

[1432] The server sends the generated presentation video to the user's device, where the user can review and approve it. After approval, the server automatically uploads the presentation video to the web platform. This process reduces manual errors and greatly improves efficiency.

[1433] Specific examples

[1434] Example: Advertisement for a new coffee maker

[1435] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[1436] 2. The device sends the input data to the server, which uses the generative model to generate ad ideas including slogans such as "Start your day on a new level."

[1437] 3. The server sends the proposed advertisements to the user's terminal, and the user selects the most attractive one from the proposed advertisements.

[1438] 4. The server creates presentation materials based on the selected advertising proposal, uses an automatic voice generation system to generate audio such as "The latest coffee maker will change your morning," and creates a presentation video.

[1439] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[1440] This system allows advertising designers and public relations personnel to efficiently create advertising proposals, generate presentation videos, and publish them online.

[1441] Example prompts for generative AI models

[1442] "To advertise coffee brewed using the latest technology, target information: young professionals. Product description: A coffee maker with a special design that uses the latest technology. Please create an ad proposal based on this information."

[1443] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1444] Step 1:

[1445] The user inputs target information and product description. The user inputs target information (e.g., "young professionals") and product description (e.g., "coffee brewed with the latest technology, special design") using a web form in a browser or a dedicated application. The input data is stored in a built-in data structure.

[1446] (Input) Target information, product description

[1447] (Output) Save the entered data

[1448] Step 2:

[1449] The device sends the entered information to the server, where the data is encrypted and securely transferred to the server.

[1450] (Input) Data entered

[1451] (Output) Data sent to the server

[1452] Step 3:

[1453] The server analyzes the target information and product description it receives. Based on the analysis results, the server creates a prompt for the generative AI model. The generative AI model is used to generate multiple ad proposals.

[1454] (Input) Data sent to the server

[1455] (Output) Generated ad ideas

[1456] Step 4:

[1457] The server sends the generated advertisement proposal to the user terminal, which temporarily stores the generated advertisement proposal in an internal database and sends it to the terminal for display through the user interface.

[1458] (Input) Generated ad ideas

[1459] (Output) Advertisement proposals sent to the device

[1460] Step 5:

[1461] The user selects the most suitable advertisement from the presented advertisements, and the information selected by the user is sent back to the server via the terminal.

[1462] (Input) Advertisement proposal selection information

[1463] (Output) Selection information sent to the server

[1464] Step 6:

[1465] The server generates presentation materials based on the selected advertisement proposals. A "presentation material generation module" in the server operates and converts the selected advertisement proposals into presentation slides.

[1466] (Input) Selected ad idea

[1467] (Output) Generated presentation materials

[1468] Step 7:

[1469] The server uses an automatic voice generation system to generate voice corresponding to the generated presentation materials. The generated voice data and slide data are integrated to complete the presentation video.

[1470] (Input) Presentation materials

[1471] (Output) Generated presentation video

[1472] Step 8:

[1473] The server sends the generated presentation video to the user's terminal, where the user can view the presentation video and click the approval button to generate approval information.

[1474] (Input) Generated presentation video

[1475] (Output) Presentation video sent to user device

[1476] Step 9:

[1477] The server uploads the approved presentation video to a web platform, which makes the video available on the company's official website or video sharing service.

[1478] (Input) Approval information, presentation video

[1479] (Output) Presentation video uploaded to the web platform

[1480] (Application example 1)

[1481] 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."

[1482] The traditional process of creating ad proposals and video presentations was time-consuming and inefficient. It often required expensive software and specialized knowledge, making it difficult for small teams or individual ad designers to access. Furthermore, publishing the resulting ads and presentations online required multiple steps, which was time-consuming and laborious.

[1483] 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.

[1484] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, means for an advertising designer to generate advertising proposals on a smartphone, create a presentation video, and publish it on the web, means for presenting the generated advertising proposals on the server, means for automatically generating a presentation video with audio based on the selected advertising proposal, and means for automatically uploading the generated presentation video to a web platform. This enables advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and instantly publish them on the web.

[1485] "Target information" refers to information such as the attributes, preferences, and behavioral patterns of consumers targeted by an advertising campaign.

[1486] "Product description" is information that provides detailed explanations of the characteristics, functions, advantages, specifications, etc. of the advertised product.

[1487] A "generative model" is a model that uses machine learning algorithms or AI systems to generate advertising ideas from input data.

[1488] "Advertising Proposal" means a proposal or concept created to promote a product or service.

[1489] A "server" is a computer system for receiving and processing data and hosting generative models.

[1490] "Presentation materials" are slides and documents created based on advertising proposals and used for explanations and presentations.

[1491] A "video presentation with audio" is a video presentation that is created with audio explanations corresponding to the presentation materials.

[1492] "Auto-uploading" is the process of publishing system-generated content to the web without manual intervention.

[1493] A "web platform" is an internet service or cloud storage that allows generated presentation videos and advertisements to be published and made viewable.

[1494] A "smartphone" is a mobile phone and is a device used by a user to generate and manage advertising proposals.

[1495] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web using smartphones. Specific embodiments for carrying out the invention are described below.

[1496] The system mainly consists of the following components:

[1497] Smartphone terminal: A device where users can input target information and product descriptions and view generated advertising proposals.

[1498] Server: This is the central system that receives and sends data, runs generative models, generates presentations and videos, and automatically uploads them.

[1499] Web Platform: An online service for publishing the final presentation video and making it widely accessible.

[1500] Technology used

[1501] The system consists of the following key technologies:

[1502] Generative AI models: Use advanced generative algorithms, such as OpenAI's GPT-3, to generate ad suggestions based on input.

[1503] Video generation software: Tools to generate video from presentations and add audio, for example using the Google Text-to-Speech engine.

[1504] Servers and cloud storage: Infrastructure for processing and storing data, typically using cloud services such as AWS or Google Cloud.

[1505] Program processing

[1506] Step 1: Enter target information and product description

[1507] The user enters target information and product description using a dedicated application form on their smartphone, and the entered data is sent to the server via an HTTP request.

[1508] Step 2: Generate ad proposals

[1509] The server runs a generative AI model based on the received information to generate a large number of ad ideas, incorporating past advertising success stories and target behavior patterns into the model.

[1510] Step 3: Select your ad idea

[1511] The generated ad proposals are sent from the server to the smartphone device and displayed on the user interface. The user selects the most suitable ad proposal from multiple proposals, and the selection result is sent back to the server.

[1512] Step 4: Generate a video of your presentation

[1513] The server creates presentation materials based on the selected advertising proposal and adds audio using an automatic voice generation system (e.g., Google Text-to-Speech), generating a presentation video that appeals to both the eyes and the ears.

[1514] Step 5: Approval and Auto Upload

[1515] The generated presentation video is sent from the server to the user's device, where the user can review the content and approve it by clicking the approval button. Approved videos are automatically uploaded to the web platform and made publicly available.

[1516] Specific examples

[1517] For example, consider an advertising designer creating an advertisement for a new smartphone.

[1518] 1. The user enters the target information as "young people interested in technology" and the product description as "a smartphone equipped with the latest camera technology and a high-performance battery."

[1519] 2. The server uses the generative AI model to generate a large number of advertising ideas, including catchy slogans such as "Enrich your smartphone life with the latest technology."

[1520] 3. The user selects the most attractive ad from the proposed ads.

[1521] 4. The server creates presentation materials based on the selected advertising proposal and uses an automatic voice generation system to add audio such as "This smartphone will revolutionize your daily life" to generate a presentation video.

[1522] 5. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[1523] Prompt Sentence Examples

[1524] "Target: Younger generations interested in technology, Product description: Generate ad ideas for a smartphone with the latest camera technology and a powerful battery."

[1525] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1526] Step 1:

[1527] The user inputs target information and product description on their smartphone. This is done through a form in a dedicated application. The input target information and product description are sent to the server as an HTTP request. The input data is structured and includes target information such as age and hobbies, and product description information such as function details.

[1528] Step 2:

[1529] The server generates a prompt for the generative AI model based on the target information and product description received. This prompt is appropriately constructed for generating ad proposals, for example, "Target: Young generation interested in technology, Product description: Please generate an ad proposal for a smartphone equipped with the latest camera technology and a high-performance battery." This prompt is sent to the generative AI model to generate ad proposals. The generated ad proposals are output in multiple text formats.

[1530] Step 3:

[1531] The server sends the generated ad proposals to the smartphone device. Multiple ad proposals are displayed on the user interface. The user visually reviews these ad proposals and selects the most suitable one. The user's selection is then sent back to the server.

[1532] Step 4:

[1533] The server automatically generates presentation materials based on the selected advertising proposal. The presentation materials are created in a slide format such as PowerPoint, with each slide displaying the main message and visuals of the advertising proposal. In addition, a voice generation engine (e.g., Google Text-to-Speech) is used to generate narration audio corresponding to each slide. This audio data is combined with the slides to generate a presentation video.

[1534] Step 5:

[1535] The server sends the generated presentation video to the smartphone device so that the user can review it. The user plays the presentation video, checks the content, and if satisfied, clicks the "Approve" button. This approval information is sent to the server.

[1536] Step 6:

[1537] The server automatically uploads the approved presentation video to a web platform (e.g., YouTube or the company's website). Once the upload is complete, the user is notified and the generated video is made public. This allows advertising designers to efficiently create requested advertising proposals and widely publish them in a short time.

[1538] 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.

[1539] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. Furthermore, by combining this with an emotion engine that recognizes user emotions, it is possible to propose and optimize advertising proposals that take user emotions into consideration. A specific embodiment of the system is described below.

[1540] System configuration

[1541] The system consists of four main components:

[1542] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[1543] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[1544] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[1545] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[1546] Program processing explanation

[1547] The specific operations of each component of the system will be described below.

[1548] 1. Enter target information and product description

[1549] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[1550] 2. Generate advertising ideas

[1551] The device sends the input information to a server, which then uses the received information to activate a generative model that generates a large number of ad ideas. This generative model uses machine learning algorithms and AI systems and references a database of past success stories.

[1552] 3. Selecting advertising ideas and collecting emotional data

[1553] The server transmits the generated advertisement proposal to the user terminal and displays it on the user interface, and the emotion engine is activated to collect the user's emotions regarding the displayed advertisement proposal.

[1554] The user selects an ad suggestion, which is then retransmitted to the server along with the emotion data collected by the emotion engine.

[1555] 4. Automatic generation of presentation materials and videos

[1556] The server activates a "presentation material generation module" based on the selected advertising proposal. The presentation material generation module converts the selected advertising proposal into slides for presentation. Next, the server uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[1557] 5. Optimize and approve your presentation video

[1558] The server sends the generated presentation video to the user's device. When the user reviews the presentation video, the emotion engine is reactivated and analyzes the user's emotions. Based on the analysis results, the server optimizes the presentation video. For example, it may edit out parts the user dislikes.

[1559] The user checks the presentation video and, if there are no problems, clicks the "Approve" button. This operation causes the device to notify the server of the approval operation.

[1560] 6. Automatic upload

[1561] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[1562] Specific examples

[1563] Example: Advertisement for a new coffee maker

[1564] 1. The user enters the target information as "young professionals" and the product description as "coffee brewed with the latest technology, special design."

[1565] 2. The server uses the generative model to generate a large number of ad ideas, including taglines such as "Start your day on a new level."

[1566] 3. The user browses the generated ad suggestions, and the emotion engine collects the user's emotional data in the process. It then selects the most attractive ad from the suggested suggestions.

[1567] 4. The server creates presentation materials based on the selected advertising proposal, and uses an automatic voice generation system to add audio such as "The latest coffee maker will change your mornings" to generate a presentation video.

[1568] 5. The user reviews the presentation video, and the emotion engine analyzes the user's emotions again. Based on the analysis results, the presentation video is optimized.

[1569] 6. The user approves the presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel.

[1570] This system allows advertising designers and public relations personnel to efficiently generate advertising proposals, and also allows them to create and publish presentation videos optimized based on user emotional data.

[1571] The processing flow will be explained below.

[1572] Step 1:

[1573] The user inputs target information and product description on the client terminal. For example, the user inputs the target demographic (e.g., "young professionals") and product description (e.g., "coffee brewed with the latest technology, special design") using a web form or dedicated application.

[1574] Step 2:

[1575] The device sends the entered information to the server, which then uses an API request to pass target information and product description data to the server.

[1576] Step 3:

[1577] The server then uses the received information to activate a generative model, which then generates a large number of ad ideas. The generative model uses machine learning algorithms and AI systems and references a database of past success stories. For example, it generates ad ideas with catchphrases such as "Start your day on a new level" or "Your special drink, creative."

[1578] Step 4:

[1579] The server sends the generated ad proposal to the user terminal, and returns the generated ad proposal and related data to the user terminal as an API response.

[1580] Step 5:

[1581] The device displays the received ad proposals on the user interface, along with a list of each proposal's catchphrase and predicted performance.

[1582] Step 6:

[1583] The emotion engine is activated and collects user emotion data when ad proposals are displayed, for example, by analyzing emotions from the user's facial expressions and voice.

[1584] Step 7:

[1585] The user selects the most suitable ad from the displayed suggestions. The emotion engine continues to analyze the user's reactions and emotions during the selection process, and finally clicks the "Select" button to confirm the ad suggestion.

[1586] Step 8:

[1587] The device transmits the selected ad proposal and emotion data to the server again, and sends an API request to the server including the identification information of the selected ad proposal and the associated emotion data.

[1588] Step 9:

[1589] The server starts a "presentation material generation module" to generate presentation materials based on the selected advertisement proposal, creating slides for the presentation and converting the text and images of the advertisement proposal into the required format.

[1590] Step 10:

[1591] The server uses an automatic speech generation system to generate audio for each slide in the presentation, and a text-to-speech tool to convert the content of each slide into audio.

[1592] Step 11:

[1593] The server combines the generated audio with the slides to generate a video presentation. A video generation tool is used to add audio to the slides and create a video file.

[1594] Step 12:

[1595] The server sends the generated presentation video to the user's device, and returns the completed video file to the user's device as an API response.

[1596] Step 13:

[1597] The device displays the received presentation video on the user interface, and the user can view the video using a video player.

[1598] Step 14:

[1599] The emotion engine is then reactivated to analyze the emotions of the user as they watch the presentation video. While the user is watching the video, the emotion engine analyzes their facial expressions and voice.

[1600] Step 15:

[1601] The server optimizes the presentation video based on the analysis results of the emotion engine. For example, it edits out parts where the user expressed dissatisfaction or boredom, and generates an improved version.

[1602] Step 16:

[1603] The user checks the optimized presentation video again and, if there are no problems, clicks the "Approve" button. If there are no problems with the presentation content, the approval operation is performed.

[1604] Step 17:

[1605] The device notifies the server of the approval operation and sends an API request including the approval information to the server.

[1606] Step 18:

[1607] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or YouTube channel.

[1608] This specific processing flow enables the generation and optimization of advertising proposals that take user emotions into consideration, allowing advertising designers and public relations personnel to work efficiently.

[1609] Example 2

[1610] 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."

[1611] With current technology, the process for advertising designers and public relations personnel to efficiently generate advertising proposals, optimize the proposals and presentation videos taking user emotions into account, and finally publish them on the web requires a great deal of time and effort. Furthermore, adjusting the proposals based on user emotions is difficult, making it difficult to create advertisements that attract users' attention. Therefore, there is a need for a system that can easily and efficiently generate and optimize advertising proposals, create presentation videos that reflect user emotions, and quickly publish them.

[1612] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1613] In this invention, the server includes means for inputting target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for displaying the advertising proposals on a user interface, means for collecting user emotion data regarding the displayed advertising proposals, means for generating presentation materials based on selected advertising proposals, means for generating audio corresponding to the presentation materials and creating a presentation video, means for optimizing the generated presentation video based on emotion analysis, means for approving the optimized presentation video, and means for uploading the approved presentation video to the web. This enables advertising designers and public relations personnel to efficiently generate advertising proposals and create and quickly publish optimal presentation videos that reflect user emotions.

[1614] "Target information" is information about specific people or groups to whom advertising is intended to be directed.

[1615] "Product description" is information detailing the features, performance, price, benefits, etc. of the advertised product.

[1616] "Transmission means" refers to the technical mechanism for sending data from the user terminal to the server.

[1617] A "generative model" is an algorithm that automatically generates advertising ideas based on input information.

[1618] "Ad Proposals" are a set of draft ad content suggested by a generative model.

[1619] A "user interface" is an interactive screen or operating means for a user to interact with a system.

[1620] "Emotion data" is information about emotions obtained by analyzing the user's facial expressions and voice.

[1621] "Presentation materials" are slides and documents used for presentations that are based on advertising proposals.

[1622] The "means for generating voice" is a technology that automatically generates voice based on text information.

[1623] A "presentation video" is a video presentation that combines audio corresponding to the presentation materials.

[1624] "Emotion analysis" is the process of analyzing collected emotion data to understand a user's emotional state.

[1625] "Optimization methods" are technologies for improving and adjusting advertising proposals and presentation videos based on the results of sentiment analysis.

[1626] The "means of approval" is a mechanism that allows the user to check the final generated presentation video and approve it if they determine that there are no problems.

[1627] "Means of uploading" refers to the technology used to transmit and save data in order to publish the generated presentation video on the web.

[1628] The system of the present invention provides a comprehensive process for advertising designers and public relations personnel to efficiently generate advertising proposals, create presentation videos, and finally publish them on the web. By combining this system with an emotion engine that recognizes user emotions, the system can propose and optimize advertising proposals taking user emotions into consideration.

[1629] System configuration

[1630] The system consists of four components:

[1631] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[1632] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[1633] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[1634] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[1635] Program processing explanation

[1636] Enter target information and product description

[1637] The user inputs target information and product description on the client terminal. This is done, for example, through a dedicated application or a web form. Specifically, the user starts the dedicated application and inputs target information and product description such as "young professionals" or "coffee brewed with the latest technology, special design" into the form.

[1638] Generate advertising proposals

[1639] The device sends the information entered to the server, where secure communication takes place using the HTTPS protocol. The server analyzes the received information and activates a generative AI model (e.g., a natural language generation algorithm built in Python). This generative AI model references a database of past success stories and generates a large number of ad suggestions based on the entered information. For example, ad suggestions may be generated that include a catchphrase such as "Start your day on a new level."

[1640] Advertisement selection and emotional data collection

[1641] The server sends the generated ad ideas to the user's device and displays them in an interactive dashboard format using HTML and JavaScript. At this time, an emotion engine is activated and collects user emotional data via a webcam and microphone. The emotional data is analyzed by an AI algorithm. The user selects the most attractive ad idea, and the selection is sent to the server.

[1642] Automatic generation of presentation materials and videos

[1643] The server activates a "presentation material generation module" based on the selected advertising proposal. This module converts the advertising proposal into presentation slides using, for example, Microsoft PowerPoint. Next, the server uses an automatic speech generation system (for example, Google Text-to-Speech API) to generate audio corresponding to each slide, and combines the generated audio with the slides to generate a presentation video using Adobe Premiere Pro.

[1644] Presentation video optimization and approval

[1645] The server sends the generated presentation video to the user's device. The user then views the presentation video using a dedicated viewer. At this time, the emotion engine is reactivated and collects and analyzes the user's emotional data via the webcam and microphone. Based on the analysis results, the server optimizes the presentation video to reflect the user's preferences. The user reviews the final presentation video, and if there are no problems, clicks the "Approve" button to notify the server of the approval operation.

[1646] Automatic Upload

[1647] The server automatically uploads the approved presentation video to the web using the YouTube Data API or other cloud storage APIs, and notifies the user after the upload is complete.

[1648] Specific examples

[1649] Example: Advertisement for a new coffee maker

[1650] 1. The user enters the target information "young professionals" and the product description "coffee brewed with the latest technology, special design" into a form in a dedicated application.

[1651] 2. The device sends this information to a server, which uses a generative AI model to generate ad suggestions, including taglines like "Start your day on a new level."

[1652] 3. The user browses the generated ad suggestions on the web dashboard, and the emotion engine collects the user's emotional data via the webcam and microphone. The user then selects the most appealing ad suggestion.

[1653] 4. The server creates a presentation using Microsoft PowerPoint based on the selected ad proposal, and then combines the audio generated by the Google Text-to-Speech API with the slides in Adobe Premiere Pro to generate a video presentation.

[1654] 5. The user reviews the presentation video, and the emotion engine again collects and analyzes the emotion data. The server optimizes the video based on the analysis results.

[1655] 6. The user approves the optimized presentation video, and the server automatically uploads the final presentation video to the company website or YouTube channel via API.

[1656] This system enables advertising designers and public relations personnel to efficiently generate advertising proposals and create and publish presentation videos optimized based on user emotional data.

[1657] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1658] Step 1:

[1659] The user inputs target information and product description on the client device. The user launches a dedicated application or web form and inputs target information (e.g., young professionals) and product description (e.g., coffee brewed with the latest technology, special design). This input data is structured in JSON format and sent to the server.

[1660] Step 2:

[1661] The device sends the input information to the server. Communication is secure using the HTTPS protocol. The server analyzes the received information and passes target information and product descriptions to the generative model. This activates a natural language generation algorithm written in Python to generate ad suggestions based on the input data. Multiple ad suggestions are generated as output.

[1662] Step 3:

[1663] The server sends the generated ad suggestions to the user's device. The ad suggestions are displayed on an interactive dashboard using HTML and JavaScript. At the same time, an emotion engine is activated to collect the user's emotional data through a webcam and microphone. The input emotional data is analyzed by an AI algorithm to determine the user's emotional state. Based on this, multiple ad suggestions are displayed to the user.

[1664] Step 4:

[1665] The user selects the most attractive advertising proposal. The selection is made through an interface operation such as clicking, and the data is sent to the server. The server then starts a presentation generation module based on the selected advertising proposal, and automatically generates a slide-format presentation using, for example, Microsoft PowerPoint. The presentation is then created as the output.

[1666] Step 5:

[1667] The server uses an automatic speech generation system (e.g., Google Text-to-Speech API) to generate audio corresponding to the presentation materials. Audio corresponding to each slide in the presentation materials is generated. The generated audio data and slide data are used to generate a presentation video using Adobe Premiere Pro. The presentation video is generated as the output.

[1668] Step 6:

[1669] The server sends the generated presentation video to the user's device. The user then watches the presentation video using a dedicated viewer. At this time, the emotion engine is activated again to collect and analyze the user's emotional data via the webcam and microphone. Based on the analysis results, the server optimizes the presentation video. For example, it edits out unattractive parts based on the user's emotional data. The optimized presentation video is generated as the output.

[1670] Step 7:

[1671] The user reviews the optimized presentation video and gives final approval by clicking the "Approve" button. This approval operation is notified to the server from the device. Finally, the server uses the approved presentation video and automatically uploads it to the web using the YouTube Data API or cloud storage API. The presentation video is then made public as an output.

[1672] By performing such specific processing at each step, advertising designers and public relations personnel can efficiently generate advertising proposals and quickly create and publish optimized presentation videos.

[1673] (Application example 2)

[1674] 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."

[1675] Conventional advertising production systems have difficulty reflecting user sentiment in the generation and optimization of ad ideas, and have limited means to maximize the effectiveness of ad ideas. Furthermore, they lack a comprehensive system for improving the efficiency of the ad production process. This has resulted in advertising designers and public relations personnel having to expend a great deal of effort and time.

[1676] The identification process by the identification 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 target information and product descriptions, means for transmitting the input information to a generative model, means for generating advertising proposals using the generative model, means for receiving and displaying the generated advertising proposals, means for selecting the displayed advertising proposals, means for generating presentation materials based on the selected advertising proposals, means for generating a presentation video by adding audio to the presentation materials, means for approving the generated presentation video, means for uploading the approved presentation video to the web, means for recognizing user emotions and analyzing data, and means for optimizing the advertising proposals based on the recognized emotion data. This makes it possible to efficiently perform a series of processes from generating advertising proposals to publishing the presentation video, and to create optimized advertising proposals that reflect user emotions.

[1677] "Target information" is information about the user profile or customer segment that is the target of the advertisement.

[1678] "Product description" refers to information about the detailed features and specifications of the product or service being advertised.

[1679] A "generative model" is a system that uses machine learning algorithms and artificial intelligence to generate advertising ideas based on input data.

[1680] "Advertising Proposals" are advertising ideas or suggestions created by a generative model.

[1681] "Presentation materials" are slides and documents used for presentations created based on advertising proposals.

[1682] A "presentation video" is a video presentation that adds audio and animation to presentation materials.

[1683] The "emotion engine" is a system that recognizes the user's emotions and analyzes the data.

[1684] "Optimization" is the process of improving and adjusting advertising proposals and presentation videos based on collected data in accordance with user emotions.

[1685] "Upload" refers to the transfer of generated and approved content to a web service or cloud storage on the Internet.

[1686] This invention provides a system that enables advertising designers and public relations personnel to efficiently generate advertising proposals, and also creates and publishes presentation videos that are optimized based on user emotion data.

[1687] The system includes the following components:

[1688] 1. User terminal: A computer or smart device operated by advertising designers or public relations personnel.

[1689] 2. Server: This is the server that hosts the generative model, the presentation creation tool, and the emotion engine.

[1690] 3. Emotion Engine: A system that recognizes user emotions and analyzes data.

[1691] 4. Web platform: Web services and cloud storage for publishing the final presentation video.

[1692] Program processing explanation

[1693] Enter target information and product description

[1694] The user inputs target information and product description on the client terminal, for example, using input fields in a web form or a dedicated application.

[1695] Generate advertising proposals

[1696] The device sends the input information to a server, which then uses the received information to activate a generative model that generates a large number of ad ideas. This generative model uses machine learning algorithms and AI systems and references a database of past success stories.

[1697] Advertisement selection and emotional data collection

[1698] The server transmits the generated advertisement proposals to the user terminal and displays them on the user interface. At this time, the emotion engine is activated to collect the user's emotions regarding the displayed advertisement proposals. The user selects an advertisement proposal. The selected advertisement proposal is retransmitted to the server together with the emotion data collected by the emotion engine.

[1699] Automatic generation of presentation materials and videos

[1700] The server activates a presentation material generation module based on the selected advertising proposals. The presentation material generation module converts the selected advertising proposals into presentation slides. The server then uses an automatic audio generation system to generate audio corresponding to each slide. The generated audio and the slides are combined to generate a presentation video.

[1701] Presentation video optimization and approval

[1702] The server sends the generated presentation video to the user's device. When the user reviews the presentation video, the emotion engine is reactivated and analyzes the user's emotions. Based on the analysis results, the server optimizes the presentation video. For example, it may edit out parts the user dislikes. The user reviews the presentation video and, if there are no problems, clicks the "Approve" button. This operation causes the device to notify the server of the approval operation.

[1703] Automatic Upload

[1704] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or video sharing platform.

[1705] Hardware and software used

[1706] Hardware: smartphones, computers, servers

[1707] Software: Python3, requests library, transformers library, emotion_recognition library

[1708] Specific examples

[1709] For example, to create an advertisement for a new coffee maker, a user might enter the following information:

[1710] Brand Name: "Latest Coffee Maker"

[1711] Target Audience: "Young Professionals"

[1712] Product Description: "Coffee brewed with the latest technology, special design"

[1713] Image file path for emotion recognition: " / path / to / user / image.jpg"

[1714] Based on this information, the generative model generates ad ideas with taglines such as "Start your day on a new level." The emotion engine collects emotional data as users view the ad ideas.

[1715] Based on the collected emotional data, the server generates optimized presentation materials and videos, and once the user approves the presentation video, the server automatically uploads the video to the company's official website and YouTube channel.

[1716] Prompt Sentence Examples

[1717] Enter your brand name: Latest Coffee Maker

[1718] Enter your target audience: Young Professionals

[1719] Enter your product description: Latest technology, special design

[1720] Enter the image file path for emotion recognition: / path / to / user / image.jpg

[1721] This system allows advertising designers and public relations personnel to efficiently generate advertising proposals, and also allows them to create and publish presentation videos optimized based on user emotional data.

[1722] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1723] Step 1:

[1724] The user inputs target information and product description on the client terminal, for example, using input fields in the dedicated application to input information such as brand name, target audience, product description, etc. The input data is used for subsequent processes.

[1725] Input: Brand name, target audience, product description

[1726] Output: Input target information and product description data

[1727] Step 2:

[1728] The device sends the target information and product description entered by the user to the server, which then activates the generative AI model based on the received information.

[1729] Input: Target information and product description data

[1730] Output: Sending input data to the server

[1731] Step 3:

[1732] The server generates advertising proposals using a generative AI model. The server references a database of past success stories and automatically generates multiple advertising proposals. The generated advertising proposals are sent to the user's device.

[1733] Input: Target information and product description data

[1734] Output: Multiple ad proposal data

[1735] Step 4:

[1736] The user terminal displays the generated advertising proposals. The user browses the displayed multiple advertising proposals and selects the most suitable one. At this time, the emotion engine is activated and collects the user's emotion data.

[1737] Input: Multiple ad proposal data

[1738] Output: Displayed ad suggestions, user sentiment data

[1739] Step 5:

[1740] The device retransmits the advertisement proposal selected by the user to the server. The emotion data collected by the emotion engine is also sent to the server at the same time. The server then generates the optimal presentation materials based on this information.

[1741] Input: Selected ad proposal data, user emotion data

[1742] Output: Sending selection data and emotion data to the server

[1743] Step 6:

[1744] The server activates a presentation material generation module based on the selected advertisement proposal and the user's emotion data, and the presentation material generation module converts the selected advertisement proposal into slides for presentation.

[1745] Input: Selected ad proposal data, user emotion data

[1746] Output: Generated presentation slides

[1747] Step 7:

[1748] The server uses an automatic voice generation system to generate voice corresponding to the presentation slides, and combines the generated voice with the slides to generate a presentation video.

[1749] Input: Generated presentation slides

[1750] Output: Generated presentation video

[1751] Step 8:

[1752] The server sends the generated presentation video to the user's device. When the user views the presentation video, the emotion engine is activated again to analyze the user's emotions.

[1753] Input: Generated presentation video

[1754] Output: Sending the presentation video to the user, user emotion data

[1755] Step 9:

[1756] The server optimizes the presentation video based on the analysis results. For example, it may edit out parts the user dislikes. The user then checks the optimized presentation video and clicks the "Approve" button if there are no problems.

[1757] Input: User emotion data

[1758] Output: Optimized presentation video, user approval

[1759] Step 10:

[1760] The server automatically uploads the approved presentation video to the web, calling an API to upload the video to the company's official website or video sharing platform.

[1761] Input: Approved presentation video

[1762] Output: Upload video to the web

[1763] 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.

[1764] 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.

[1765] 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.

[1766] 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.

[1767] 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.

[1768] 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.

[1769] 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).

[1770] 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.

[1771] 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."

[1772] 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.

[1773] 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).

[1774] 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.

[1775] 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.

[1776] 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.

[1777] 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.

[1778] 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.

[1779] 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.

[1780] 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.

[1781] 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.

[1782] 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.

[1783] 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.

[1784] The following is further disclosed regarding the above embodiment.

[1785] (Claim 1)

[1786] A means for inputting target information and product description;

[1787] a means for transmitting the input information to a generative model;

[1788] means for generating advertising proposals using the generative model;

[1789] means for receiving and displaying the generated advertising proposals;

[1790] means for selecting the displayed advertising suggestions;

[1791] A means for generating presentation materials based on the selected advertising proposal;

[1792] A means to generate a presentation video by adding audio to presentation materials,

[1793] A means for approving the generated presentation video;

[1794] A means to upload the approved presentation video to the web,

[1795] A system including:

[1796] (Claim 2)

[1797] The system according to claim 1, which generates a structured advertising proposal (including a catchy slogan and a predicted effect) based on the input information.

[1798] (Claim 3)

[1799] 10. The system of claim 1, wherein the audio generating means generates audio corresponding to the presentation material.

[1800] (Claim 4)

[1801] 10. The system of claim 1, further comprising means for automatically uploading the generated presentation video to a project management tool.

[1802] (Claim 5)

[1803] 10. The system of claim 1, further comprising means for generating presentation materials in different formats (slides, video, PDF, etc.) based on the selected advertising proposal.

[1804] (Claim 6)

[1805] The system of claim 1, further comprising means for providing an interface for a user to review and approve the presentation video.

[1806] "Example 1"

[1807] (Claim 1)

[1808] A means for inputting target information and product description;

[1809] a means for transmitting the input information to a generative model;

[1810] means for generating advertising proposals using the generative model;

[1811] means for receiving and displaying the generated advertising proposals;

[1812] means for selecting the displayed advertising suggestions;

[1813] A means for generating presentation materials based on the selected advertising proposal;

[1814] A means to generate a presentation video by adding audio to presentation materials,

[1815] A means for approving the generated presentation video;

[1816] A means to upload the approved presentation video to the web,

[1817] A means for automating the process of generating and uploading presentation videos;

[1818] A system including:

[1819] (Claim 2)

[1820] The system according to claim 1, which generates a structured advertising proposal (including a catchy slogan and a predicted effect) based on the input information.

[1821] (Claim 3)

[1822] 10. The system of claim 1, wherein the audio generating means generates audio corresponding to the presentation material.

[1823] "Application Example 1"

[1824] (Claim 1)

[1825] A means for inputting target information and product description;

[1826] a means for transmitting the input information to a generative model;

[1827] means for generating advertising proposals using the generative model;

[1828] means for receiving and displaying the generated advertising proposals;

[1829] ...

Claims

1. A means for inputting target information and product description; a means for transmitting the input information to a generative model; means for generating advertising proposals using the generative model; means for receiving and displaying the generated advertising proposals; means for selecting the displayed advertising suggestions; A means for generating presentation materials based on the selected advertising proposal; A means to generate a presentation video by adding audio to presentation materials, A means for approving the generated presentation video; A means to upload the approved presentation video to the web, A system including:

2. The system according to claim 1, wherein a structured advertising proposal (including a catch phrase and a predicted effect) is generated based on the input information.

3. The system of claim 1 , wherein the audio generating means generates audio corresponding to the presentation material.

4. The system of claim 1 , further comprising means for automatically uploading the generated presentation video to a project management tool.

5. The system of claim 1 , further comprising means for generating presentation materials in different formats (slides, video, PDF, etc.) based on the selected advertising proposal.

6. The system according to claim 1 , further comprising means for providing an interface for a user to perform an operation of reviewing and approving the presentation video.

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