system

Abstract

We provide the system. [Solution] A means of generating digital works using a generation device, A means of comparing generated digital works between content creators and content providers and recommending the most suitable creator, A means for registering the generated digital works on multiple sales platforms and managing their sales, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the production of digital content, although many creators carry out creative activities, it is difficult to monetize the produced works and expose them in the market. As a result, there is a problem that the potential capabilities of the creators are not fully exerted. In addition, since it is difficult to match between content providers and appropriate creators, a situation has arisen where the talents of the creators are not fully utilized. There is a need for a solution to improve such a current situation, generate digital works efficiently and effectively, perform an appropriate matching between creators, and maximize the sales opportunities of the generated works.

Means for Solving the Problems

[0005] This invention provides a means for generating digital works based on themes and styles entered by users, utilizing a generation device. Furthermore, it provides a means for comparing content creators and content providers based on these generated works and recommending the most suitable creator. This recommendation aims to ensure the best possible match. In addition, it provides a means for efficiently managing sales activities by registering the generated digital works on multiple sales platforms, allowing logged-in users to easily obtain sales opportunities. In this way, the invention solves the problem by supporting the entire process from the generation of digital works to matching creators and sales.

[0006] A "generation device" is a device that has the function of creating digital works based on themes and styles entered by the user.

[0007] "Digital works" refer to electronic content such as images, videos, and text created using a generation device.

[0008] A "content creator" is an individual or group that creates digital works and provides value through the publication or sale of those works.

[0009] A "content provider" is a person or organization that commissions the creation of a digital work or has a need for such a work.

[0010] "Matching" is the process of forming an appropriate collaborative relationship between content creators and content providers.

[0011] A "sales platform" is a system that provides generated digital works to the market and distributes them in a form that can be purchased. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the 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.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0026] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] The present invention aims to maximize the market exposure of digital works by utilizing a generation device to generate digital works, efficiently matching content creators with content providers, and registering the generated works on multiple sales platforms.

[0034] This system operates on a platform accessible to the user. When a user logs into the system as an entry point, the generator first determines the theme and style of the target content based on the user's requests. For example, a user can specify a theme they want to use for illustrations in a fantasy novel.

[0035] User: After logging in, start a new project on the menu screen and enter various parameters (e.g., theme, style, type of work) to inform the generator.

[0036] Terminal: Receives user input information and sends it to the generation device. This generation device uses an AI-powered model to generate initial works based on a specified theme.

[0037] Server: Stores the generated artwork data and provides it to users in a viewable format. It also receives continuous feedback and supports the process of regenerating artwork in response to user requests for corrections.

[0038] After a work is created, the system performs a process to match content creators with content providers. At this stage, a mechanism is in place to recommend creators who are a good fit for the style and purpose of the digital work. For example, if a user is writing an adventure fantasy plot, an illustrator with experience in this theme will be recommended.

[0039] Ultimately, the system registers completed digital works on multiple sales platforms. This sales functionality facilitates access to marketplaces and helps users pursue revenue potential. Users can monitor the performance and revenue status of their works on each sales platform in real time through a dashboard.

[0040] In this way, the system provides an integrated solution for generating creative content, establishing appropriate collaborative systems, and gaining market exposure.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] User: Enter your username and password on the login screen and press the login button. This will initiate user authentication.

[0044] Step 2:

[0045] Server: The server verifies the received username and password against the information in the database. If the verification is successful, it sends a notification of successful authentication to the device.

[0046] Step 3:

[0047] Terminal: Receives authentication results from the server, displays a successful login message to the user, and redirects them to the dashboard screen.

[0048] Step 4:

[0049] User: On the project creation screen, enter the theme and style for the new content and request project creation.

[0050] Step 5:

[0051] Terminal: Sends user input information to the server and instructs it to start the generation process.

[0052] Step 6:

[0053] Server: Selects an AI model and generates an initial digital artwork based on the theme and style specified by the user.

[0054] Step 7:

[0055] Terminal: Displays the generated work as a preview to the user and provides an option to receive feedback.

[0056] Step 8:

[0057] User: Review the preview of the artwork and request a regeneration if necessary.

[0058] Step 9:

[0059] Server: Modifies or regenerates the artwork based on user feedback and saves the final version to the project folder.

[0060] Step 10:

[0061] Server: Based on the style and content of the work, it selects suitable content creators as recommended candidates and sends matching information to the terminal.

[0062] Step 11:

[0063] Terminal: Presents users with information on recommended content creators and provides them with the option to submit a matching request.

[0064] Step 12:

[0065] User: Review the presented information and send matching requests to creators who wish to collaborate.

[0066] Step 13:

[0067] Server: Registers the completed work on the selected sales platform and initiates the sales process.

[0068] Step 14:

[0069] User: Check the sales status and revenue of registered works in real time on the dashboard.

[0070] The above describes the specific actions taken in each processing step.

[0071] (Example 1)

[0072] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0073] In generating digital content, it is necessary to provide a system that efficiently produces high-quality works based on specific user requests, builds collaborative relationships with appropriate creators, registers with a wide range of sales platforms to maximize market exposure, and allows users to efficiently understand sales status in real time.

[0074] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0075] In this invention, the server includes means for generating digital works according to a theme and style using a generation device based on user input, means for storing the generated digital works in a data storage unit and making them available for the user to view, and means for modifying and regenerating the generated digital works based on user feedback. This enables the user to manage the entire process from the generation of digital works to sales and monitoring in an integrated manner.

[0076] A "generation device" is hardware or software that generates digital works by considering themes and styles based on user input information.

[0077] A "digital work" is an electronic work that includes text, images, audio, video, and other content created by a generating device.

[0078] A "content creator" refers to an individual or organization that is involved in the creation of digital works and provides creative input.

[0079] A "content provider" is an individual or organization that provides generated digital works to the market and is responsible for their distribution.

[0080] A "sales platform" is an online or offline platform for selling generated digital works.

[0081] A "generative AI model" is a program model that uses artificial intelligence to generate, analyze, or improve content.

[0082] A "prompt" is text used as a command or instruction when a generative AI model generates a digital work.

[0083] "Feedback" refers to opinions and requests for revisions provided by users regarding their created works.

[0084] A "dashboard" is an interface that allows users to visually check and manage the progress and sales status of their generated digital works.

[0085] This invention aims to generate digital works tailored to user needs using a computer-based system, facilitate collaboration with appropriate content creators, and widely publish the works in the market. Specific embodiments of this system are described below.

[0086] First, users access the platform from their device via the internet and log in to the system using their username and password. Once logged in, users can access a dashboard to create new projects.

[0087] When creating a project, users enter detailed information such as the theme, style, and type of work. For example, if a user wants to generate illustrations for a fantasy novel with the theme of "magic school," they would fill in this information in the project form. This information is recorded as a prompt and used in the next stage. A concrete example of this prompt might be, "Generate illustrations for a fantasy novel with the theme of a magic school. The style should be fantastical and include futuristic elements."

[0088] The terminal sends information entered by the user to the server. Based on this information, the server activates a generation device and uses a generative AI model to generate digital artwork according to the specified theme and style. The generative AI model used here is a general-purpose AI software that is highly regarded in the market.

[0089] The generated digital artwork is stored in the data storage area by the server and simultaneously reflected on the dashboard in a format viewable by the user. Users can review the artwork and provide feedback if necessary. For example, if a particular character in an illustration differs from the user's image, they can request a correction. The server receives this feedback and instructs the generation AI model to regenerate the artwork.

[0090] The system also matches content creators and content providers based on the generated digital works. The server recommends the most suitable creator for the work's theme and style, and supports collaboration.

[0091] Ultimately, the content is registered on multiple sales platforms, which are automatically managed by a server, allowing users to view sales status and revenue in real time through a dashboard. This process enables users to improve how their content is presented and optimize access to the market.

[0092] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0093] Step 1:

[0094] Users access the platform from their devices and log in to the system by entering their username and password. Login is performed by verifying user information against a database through an authentication system. The input is user information, and the output is a user-specific dashboard screen.

[0095] Step 2:

[0096] The user clicks the "Start a New Project" button on the dashboard to display the project creation screen. Here, they enter details such as the theme, style, and type of the project. The inputs are project parameters, and the output is a prompt message containing this data.

[0097] Step 3:

[0098] The terminal sends the project information entered by the user to the server. The server then uses this information to prepare to start the generator. The input consists of project parameters, and the output consists of prepared data to be passed to the generator.

[0099] Step 4:

[0100] The server generates prompt statements for the AI ​​model. These prompt statements serve as specific instructions for the AI ​​model when generating the digital artwork. The input is the data prepared by the generation device, and the output is the prompt statements passed to the AI ​​model.

[0101] Step 5:

[0102] The generation device uses an AI model to generate digital artwork based on prompt messages received from the server. The AI ​​performs data calculations to generate artwork based on a specified theme and style. The input is the prompt message, and the output is the generated digital artwork data.

[0103] Step 6:

[0104] The server stores the generated digital artwork data in its data storage unit and simultaneously reflects it on the user's dashboard, making it viewable. The input is the generated artwork data, and the output is the artwork data in a format viewable by the user.

[0105] Step 7:

[0106] Users review the generated work on the dashboard and provide feedback as needed. User input consists of revision requests and opinions, while output is feedback data.

[0107] Step 8:

[0108] The server analyzes the user feedback data and instructs the AI ​​model to regenerate. The server then updates the database and regenerates the corrected prompt text. The input is the feedback data, and the output is the corrected artwork data.

[0109] Step 9:

[0110] The system matches content creators and content providers based on the generated digital works. The server recommends the most suitable creator from the database and notifies the user. The input is the work data, and the output is creator information.

[0111] Step 10:

[0112] The server initiates the process of registering the completed artwork with multiple sales platforms. During this process, it uses the sales platform's API to send artwork data and begin sales. The input is the artwork data, and the output is a notification that registration is complete with the sales platform.

[0113] Step 11:

[0114] Users monitor the sales and revenue status of their works in real time on a dashboard. The server aggregates feedback from the sales platform and presents it to users as a report. The input is sales data, and the output is a revenue report.

[0115] (Application Example 1)

[0116] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0117] In today's world, the process of creating, matching, and marketing digital works is complex, and efficient methods are needed. Furthermore, there is a lack of systems that allow users to intuitively specify themes and styles and easily create and distribute content. Solving this challenge will allow both content creators and providers to maximize profits and expand the scope of their creative activities.

[0118] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0119] In this invention, the server includes means for generating digital works using a generation device, means for comparing the generated digital works between content creators and content providers and recommending the most suitable creator, means for registering the generated digital works on multiple sales platforms and managing sales, means for specifying the theme and style that the user aims for and automatically generating art content using artificial intelligence, and means for directly uploading the generated digital works to a content distribution service. This makes it possible for users to efficiently and easily generate and distribute digital works.

[0120] A "generation device" is a device or system for automatically generating digital works using artificial intelligence or other technologies.

[0121] "Digital works" refer to digital content such as images, illustrations, videos, and music that are generated using computer technology.

[0122] A "content creator" is an individual or group that is responsible for creating or generating digital works.

[0123] A "content provider" is an individual or organization that markets, sells, or distributes digitally generated works.

[0124] A "sales platform" refers to the online platforms and marketplaces used to sell digital works.

[0125] "Theme" refers to the fundamental concept or subject matter of the digital work being created.

[0126] "Style" is a concept that describes a specific method or characteristic of visuals and expression in digital works.

[0127] An "artificial intelligence model" is a computational model developed to perform a specific task using machine learning or deep learning techniques.

[0128] A "prompt message" is a word or phrase used by a user to give instructions to a generator.

[0129] The system based on this invention is a platform that utilizes a generation device to generate digital works based on user-specified themes and styles. The server hosts a generation system equipped with AI technology and automatically generates digital works upon receiving input information from the user. The hardware uses a server with a high-performance processor, and the software includes machine learning libraries for running AI models (e.g., a generation AI model).

[0130] The terminal acts as a user interface, transmitting themes and style information entered by the user to the server. Users can give detailed instructions to the AI ​​by entering specific prompts, such as "an illustration of a dragon with a fantasy theme." These prompts are used by the generator to produce a unique digital artwork according to the specifications.

[0131] The generated digital works are also used as data to efficiently match content creators with content providers. The server automatically registers works to multiple sales platforms, making sales and revenue management easy and enabling seamless market access for users. Users can utilize these functions to quickly create, distribute, and sell digital works in the market.

[0132] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0133] Step 1:

[0134] The user logs into the system via their terminal and enters prompt text to specify a theme and style. This prompt text is prepared as input data and sent to the next process. For example, the user might enter the prompt text "An illustration of a dragon with a fantasy theme." This information is then sent from the terminal to the server.

[0135] Step 2:

[0136] The server uses a generative AI model to generate digital artwork, taking the prompt text received from the user as input data. This AI model analyzes the prompt text using machine learning algorithms and generates artwork data based on the results. Natural language processing is performed as data processing and computation, and the output is a pictorial representation. Specifically, the AI ​​model generates a new image based on the input theme and outputs it as a digital file.

[0137] Step 3:

[0138] The generated digital works are stored on a server in a database that matches content creators with providers. Here, data processing is performed to recommend the most suitable providers based on the style and theme of the generated works. Specifically, the system uses each provider's work history and rating data to list relevant providers for the user.

[0139] Step 4:

[0140] The server performs the necessary format conversions and delivers information to register generated digital works on multiple sales platforms. It takes digital works and their metadata as input and uploads them to the specified platform as output. Specifically, it communicates with the marketplace API and uploads the works and their sales information.

[0141] Step 5:

[0142] On the dashboard, users can view the performance and revenue status of their works across sales platforms in real time. The information entered is sales data collected from each sales platform, which is displayed visually as graphs and tables. Specifically, the device periodically receives updated data from the server and visualizes it as part of the user interface.

[0143] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0144] This invention is a system that utilizes an emotion engine to recognize a user's emotions and reflect those emotions in the creation of digital works. The system includes a generation device, an emotion engine, a user interface, and a data storage unit.

[0145] When the system starts, the user logs in and specifies the theme and style of the digital artwork to be generated in the project settings screen. Additionally, data related to the user's emotions is collected by the emotion engine through multiple methods (e.g., text input, voice input, facial recognition).

[0146] Terminal: Analyzes emotional data received from the user in real time and sends it to the server. This emotional data is used to reflect the emotional intentions the user wants to convey in their artwork. For example, if the user expresses joy, the emotional engine will use corresponding colors and positive elements to compose the artwork.

[0147] Server: Analyzes the received emotional data and determines the specific elements of the digital artwork (color, style, tone, etc.) based on the generation device. The generation device receives instructions from the emotional engine and uses an AI model to generate artwork that matches the user's emotional state.

[0148] The generated artwork reflects emotional elements, resulting in a piece that better aligns with the user's intentions. After final adjustments to content and style, this artwork is stored in the data storage unit.

[0149] The saved digital works are used in a matching process that connects content creators and providers. In this process, the system recommends suitable creators based on the style and emotional elements of the generated works, and ultimately, sales begin by registering them on multiple sales platforms.

[0150] For example, if a user inputs a sad emotion via voice input, the emotion engine analyzes the tone of the voice and the choice of words, and generates a digital artwork that reflects that emotion. This artwork may use dark colors and subdued tones, demonstrating how emotional nuances can be translated into digital art.

[0151] In this way, by using emotional information, we can create a system that efficiently generates and supplies digital works tailored to individual needs to the market.

[0152] The following describes the processing flow.

[0153] Step 1:

[0154] User: On the login screen, enter your username and password to authenticate. This login information will grant the user access to use the system.

[0155] Step 2:

[0156] Terminal: The terminal collects the theme, style, and desired emotional state of the digital artwork specified by the user via an input screen, and sends this information to the server.

[0157] Step 3:

[0158] Server: Activates a generator based on the user's theme and style, and prepares the emotion engine to analyze the user's emotional information.

[0159] Step 4:

[0160] Device: Collects user facial expressions and voice data through the camera and microphone, and transmits them to the emotion engine in real time.

[0161] Step 5:

[0162] Server: Analyzes facial expressions and voice data received by the emotion engine to identify the user's current emotional state. Based on this analysis, it provides appropriate instructions to the generation device.

[0163] Step 6:

[0164] Server: Using the analysis results from the emotion engine, the generator determines the color scheme, tone, and style of the artwork and generates an initial version of the digital artwork that corresponds to the emotion.

[0165] Step 7:

[0166] Terminal: Provides users with a preview of the generated digital artwork, allowing them to review the content and provide feedback.

[0167] Step 8:

[0168] User: View the preview and, if necessary, request revisions to the generated work or re-enter emotions.

[0169] Step 9:

[0170] Server: After receiving user feedback and making necessary corrections, the server saves the final digital artwork to the data storage unit.

[0171] Step 10:

[0172] Server: Based on the generated works, it matches content creators with providers and recommends appropriate creators.

[0173] Step 11:

[0174] Server: Finally, the completed work is registered on multiple sales platforms, and the sales process begins.

[0175] In this way, by utilizing emotional information, it becomes possible to efficiently generate digital works that better meet individual needs.

[0176] (Example 2)

[0177] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0178] There is a need to provide a system that efficiently generates digital content that reflects user emotions, optimally matches content creators and providers, and quickly delivers it to the market. Furthermore, it is necessary to accurately recognize the emotions of individual users and reflect them in digital works to enhance personalized product value and provide a better user experience.

[0179] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0180] In this invention, the server includes emotion analysis means that recognize the user's emotions and reflect those emotions in the generation of digital works; terminal means that analyze emotion data in real time and transmit it to the server; and server means that analyze the received emotion data and instruct the generation device to determine specific elements. This makes it possible to generate and optimize digital content that reflects the user's emotions.

[0181] An "emotion analysis tool" is a device that recognizes a user's emotions and analyzes those emotions in order to utilize the data for generating digital works.

[0182] A "terminal device" is a device or system that analyzes emotional data based on user input and transmits it to a server.

[0183] A "server device" is a device that analyzes emotional data received from a terminal and issues instructions to the generation device to determine the specific elements of the work.

[0184] A "generation device" is a device or system that has the function of generating digital content based on user input data and sentiment analysis.

[0185] "Digital content" refers to works or products in digital format that are generated based on the user's emotions or input themes.

[0186] "Content creator" refers to a professional or user who creates digital content.

[0187] A "content provider" refers to an organization or individual that is responsible for providing generated digital content to the market or platform.

[0188] "Supplying to the market" refers to the process of making generated digital content accessible to the general public.

[0189] This invention realizes a system that recognizes user emotions and generates digital content that reflects them. This system provides users with a personalized experience by consistently performing the processes of emotion analysis, digital content generation, and market supply.

[0190] First, the user logs in as the entry point to the system and specifies the theme and style of the digital content on the project settings screen. The user then inputs their emotions using text, voice, or facial expressions. This provides initial data for emotion analysis.

[0191] The device analyzes emotional data acquired from the user in real time. Specific software used includes a natural language processing engine, speech analysis tools, and image processing algorithms. This analysis extracts detailed emotions such as "joy," "sadness," and "surprise." For example, if a user inputs an emotion like "happy" via voice, that voice data is converted to text by a speech recognition tool and classified as "joy" by the emotion analysis engine.

[0192] The server uses emotional data transmitted from the terminal to generate digital works using a generation device. Generation AI models are used for this process, specifically models such as "DALL-E" and "Midjourney." These models automatically generate intuitive visual content based on emotional, thematic, and style information. The server stores the generated content in a data storage unit and provides a preview to the user as needed.

[0193] For example, when a user requests artwork based on "sad feelings," a prompt is used to generate a "calm landscape painting using dark tones." This prompt is given to the generation AI model and means something like, "Generate digital art that reflects the user's sad feelings. Use dark colors and calm tones."

[0194] Through the above process, this system accurately captures user emotions and enables the efficient delivery of unique, custom content to the market.

[0195] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0196] Step 1:

[0197] The user logs into the system and accesses the project settings screen. Here, the user enters input specifying the theme and style of the digital content they want to generate. This setting information is then sent to the terminal as output.

[0198] Step 2:

[0199] The user inputs their emotions. This input is done through text, voice, or facial recognition. For example, if the user voice-inputs "I'm happy today," the device converts that voice into text. This converted data is then recorded as input data on the device.

[0200] Step 3:

[0201] The device analyzes emotional data received from the user in real time. By processing the input data with a natural language processing engine and speech analysis tools, it performs calculations to identify the type of emotion (joy, sadness, etc.). The output of this analysis is sent to the server as analyzed emotional data.

[0202] Step 4:

[0203] The server activates the generation device based on the analyzed emotion data received from the terminal. The server sends the input emotion data as a prompt to the AI ​​model (e.g., DALL-E or Midjourney) to generate digital content that matches the user's emotions. An example of such a prompt message would be, "Please generate a bright-toned digital art piece that reflects the user's happy feelings."

[0204] Step 5:

[0205] The generation device receives prompts from the server and generates digital content based on them. The generation device utilizes an AI model to output works with visual elements (color tone, shape, etc.) corresponding to specified emotions and themes. The generated digital content is stored in the data storage unit.

[0206] Step 6:

[0207] The server utilizes stored digital content to match content creators with providers. A program recommends suitable creators based on the style and emotional elements of the work. As a result, the digital content is registered on the sales platform and market distribution begins.

[0208] (Application Example 2)

[0209] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0210] In today's digital content market, there is a demand for personalized experiences based on users' emotions and individual needs. However, existing systems struggle to accurately recognize and analyze users' emotions and provide appropriate digital experiences based on them. A system is needed to solve this problem and to quickly and efficiently generate and deliver more personalized digital content.

[0211] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0212] In this invention, the server includes means for generating digital representations using a generation device, means for creating digital information that provides a personalized experience to the user using an emotion recognition engine that recognizes and analyzes the user's emotions, and means for recommending the most suitable creator to connect the user and the creator based on the generated digital representations. This makes it possible to provide digital representations based on the individual emotions and needs of the user.

[0213] A "generation device" refers to a device or system for automatically generating digital representations.

[0214] "Digital expression" refers to all works and content created using digital technology.

[0215] An "emotion recognition engine" refers to software or a system used to detect and analyze a user's emotions.

[0216] A "personalized experience" refers to providing an experience that is customized according to the individual user's emotions and preferences.

[0217] "Digital information" refers to any information that is expressed in digital format.

[0218] An "e-commerce platform" refers to a platform for trading digital products and services online.

[0219] An "automated intelligent model" refers to a model that uses machine learning and artificial intelligence technologies to automatically perform various tasks.

[0220] The "data storage unit" refers to the storage system or database used to save the generated information.

[0221] To implement this invention, the system comprises a smartphone, a server, and an emotion recognition engine. Users can input emotion data using the smartphone. This emotion data is collected using methods such as voice input or facial recognition. The terminal analyzes the collected emotion data in real time and transmits the information to the server.

[0222] The server generates digital representations using generative AI models based on the received emotion data. The emotion recognition engine analyzes the user's emotional state and creates digital information with a style and content appropriate to the corresponding emotion. The generated digital representations are further optimized to provide a personalized experience when they are delivered to the user. This process utilizes AI models (e.g., GPT family) running on Google Cloud Platform (GCP), as well as TENSORFLOW® for emotion recognition and OpenCV.

[0223] As a concrete example, a server can use an emotion recognition engine to generate and provide music playlists and visual content suitable for relaxation based on voice information entered by the user when they want to relax. In this way, it becomes easy to create digital experiences that match the user's emotions.

[0224] In this regard, the following prompts can be used with the generative AI model: "Generate music that promotes a relaxed mood," and "Suggest videos that evoke a travel-like feeling."

[0225] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0226] Step 1:

[0227] The user launches a smartphone application and inputs emotion data. Input is performed using voice input or facial recognition. The device collects audio and video data using the microphone and camera. This input data is temporarily stored on the smartphone.

[0228] Step 2:

[0229] The device processes collected audio and video data in real time to recognize emotions. This process uses TensorFlow to analyze audio data and OpenCV to analyze facial expressions in video data. The results of these analyses are output as the user's emotional state and sent to the server.

[0230] Step 3:

[0231] The server receives emotion data from the terminal and uses a generative AI model to generate digital representations. In this step, content that matches the user's emotions is generated based on pre-configured prompts. The server uses an AI model such as the GPT family to materialize the digital information and generates the result as a digital representation.

[0232] Step 4:

[0233] Based on the generated digital representations, the server optimizes and delivers them to the user. Specifically, it adjusts the generated content to match the user's preferences in order to create a personalized experience. When these digital representations are sent to the user's device, the user can receive a digital experience that responds to their emotions.

[0234] Step 5:

[0235] Users can experience the provided digital representations and provide feedback on their results. Additional emotional data can be provided through the application. This creates a consistent data feedback loop throughout the system, contributing to the optimization of future experiences.

[0236] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0237] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0238] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0239] [Second Embodiment]

[0240] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0241] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0242] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0243] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0244] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0245] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0246] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0247] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0248] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0249] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0250] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0251] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0252] The present invention aims to maximize the market exposure of digital works by utilizing a generation device to generate digital works, efficiently matching content creators with content providers, and registering the generated works on multiple sales platforms.

[0253] This system operates on a platform accessible to the user. When a user logs into the system as an entry point, the generator first determines the theme and style of the target content based on the user's requests. For example, a user can specify a theme they want to use for illustrations in a fantasy novel.

[0254] User: After logging in, start a new project on the menu screen and enter various parameters (e.g., theme, style, type of work) to inform the generator.

[0255] Terminal: Receives user input information and sends it to the generation device. This generation device uses an AI-powered model to generate initial works based on a specified theme.

[0256] Server: Stores the generated artwork data and provides it to users in a viewable format. It also receives continuous feedback and supports the process of regenerating artwork in response to user requests for corrections.

[0257] After a work is created, the system performs a process to match content creators with content providers. At this stage, a mechanism is in place to recommend creators who are a good fit for the style and purpose of the digital work. For example, if a user is writing an adventure fantasy plot, an illustrator with experience in this theme will be recommended.

[0258] Ultimately, the system registers completed digital works on multiple sales platforms. This sales functionality facilitates access to marketplaces and helps users pursue revenue potential. Users can monitor the performance and revenue status of their works on each sales platform in real time through a dashboard.

[0259] In this way, the system provides an integrated solution for generating creative content, establishing appropriate collaborative systems, and gaining market exposure.

[0260] The following describes the processing flow.

[0261] Step 1:

[0262] User: Enter your username and password on the login screen and press the login button. This will initiate user authentication.

[0263] Step 2:

[0264] Server: The server verifies the received username and password against the information in the database. If the verification is successful, it sends a notification of successful authentication to the device.

[0265] Step 3:

[0266] Terminal: Receives authentication results from the server, displays a successful login message to the user, and redirects them to the dashboard screen.

[0267] Step 4:

[0268] User: On the project creation screen, enter the theme and style for the new content and request project creation.

[0269] Step 5:

[0270] Terminal: Sends user input information to the server and instructs it to start the generation process.

[0271] Step 6:

[0272] Server: Selects an AI model and generates an initial digital artwork based on the theme and style specified by the user.

[0273] Step 7:

[0274] Terminal: Displays the generated work as a preview to the user and provides an option to receive feedback.

[0275] Step 8:

[0276] User: Review the preview of the artwork and request a regeneration if necessary.

[0277] Step 9:

[0278] Server: Modify or regenerate the work based on the user's feedback and save the final version to the project folder.

[0279] Step 10:

[0280] Server: Based on the style and content of the work, select suitable content generators as recommended candidates and send the matching information to the terminal.

[0281] Step 11:

[0282] Terminal: Present the information of the recommended content generators to the user and provide an option to submit a matching application.

[0283] Step 12:

[0284] User: Review the presented information and send a matching request to the generator who wishes to cooperate.

[0285] Step 13:

[0286] Server: Register the completed work on the selected sales platform and start the sales process.

[0287] Step 14:

[0288] User: Check the sales status and revenue of the registered work in real time on the dashboard.

[0289] The above are the specific operations in each processing step.

[0290] (Example 1)

[0291] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0292] In generating digital content, it is necessary to provide a system that efficiently produces high-quality works based on specific user requests, builds collaborative relationships with appropriate creators, registers with a wide range of sales platforms to maximize market exposure, and allows users to efficiently understand sales status in real time.

[0293] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0294] In this invention, the server includes means for generating digital works according to a theme and style using a generation device based on user input, means for storing the generated digital works in a data storage unit and making them available for the user to view, and means for modifying and regenerating the generated digital works based on user feedback. This enables the user to manage the entire process from the generation of digital works to sales and monitoring in an integrated manner.

[0295] A "generation device" is hardware or software that generates digital works by considering themes and styles based on user input information.

[0296] A "digital work" is an electronic work that includes text, images, audio, video, and other content created by a generating device.

[0297] A "content creator" refers to an individual or organization that is involved in the creation of digital works and provides creative input.

[0298] A "content provider" is an individual or organization that provides generated digital works to the market and is responsible for their distribution.

[0299] A "sales platform" is an online or offline platform for selling generated digital works.

[0300] A "generative AI model" is a program model that uses artificial intelligence to generate, analyze, or improve content.

[0301] A "prompt" is text used as a command or instruction when a generative AI model generates a digital work.

[0302] "Feedback" refers to opinions and requests for revisions provided by users regarding their created works.

[0303] A "dashboard" is an interface that allows users to visually check and manage the progress and sales status of their generated digital works.

[0304] This invention aims to generate digital works tailored to user needs using a computer-based system, facilitate collaboration with appropriate content creators, and widely publish the works in the market. Specific embodiments of this system are described below.

[0305] First, users access the platform from their device via the internet and log in to the system using their username and password. Once logged in, users can access a dashboard to create new projects.

[0306] When creating a project, users enter detailed information such as the theme, style, and type of work. For example, if a user wants to generate illustrations for a fantasy novel with the theme of "magic school," they would fill in this information in the project form. This information is recorded as a prompt and used in the next stage. A concrete example of this prompt might be, "Generate illustrations for a fantasy novel with the theme of a magic school. The style should be fantastical and include futuristic elements."

[0307] The terminal sends the information input by the user to the server. Based on this information, the server starts the generation device and uses the generation AI model to generate a digital work according to the specified theme and style. The general-purpose AI software with high market evaluation is used as the generation AI model here.

[0308] The generated digital work is stored in the data storage department by the server and at the same time is reflected on the dashboard in a format that can be viewed by the user. The user can view this work and provide feedback if necessary. For example, if a specific character in the illustration is different from the user's image, the modification can be requested. The server receives such feedback and instructs the generation AI model to regenerate the work.

[0309] The system also performs matching between the content generator and the content provider based on the generated digital work. The server recommends the most suitable generator for the theme and style of the work and supports the cooperation.

[0310] Finally, the work is registered on multiple sales platforms, and the server automatically manages this, enabling the user to check the sales status and revenue in real time through the dashboard. Through this process, the user can improve the appearance of the content and optimize access to the market.

[0311] The flow of the specific process in Example 1 will be described using FIG. 11. <000098​​​​​​​​​​

[0315] The user clicks the "Start a New Project" button on the dashboard to display the project creation screen. Here, they enter details such as the theme, style, and type of the project. The inputs are project parameters, and the output is a prompt message containing this data.

[0316] Step 3:

[0317] The terminal sends the project information entered by the user to the server. The server then uses this information to prepare to start the generator. The input consists of project parameters, and the output consists of prepared data to be passed to the generator.

[0318] Step 4:

[0319] The server generates prompt statements for the AI ​​model. These prompt statements serve as specific instructions for the AI ​​model when generating the digital artwork. The input is the data prepared by the generation device, and the output is the prompt statements passed to the AI ​​model.

[0320] Step 5:

[0321] The generation device uses an AI model to generate digital artwork based on prompt messages received from the server. The AI ​​performs data calculations to generate artwork based on a specified theme and style. The input is the prompt message, and the output is the generated digital artwork data.

[0322] Step 6:

[0323] The server stores the generated digital artwork data in its data storage unit and simultaneously reflects it on the user's dashboard, making it viewable. The input is the generated artwork data, and the output is the artwork data in a format viewable by the user.

[0324] Step 7:

[0325] Users review the generated work on the dashboard and provide feedback as needed. User input consists of revision requests and opinions, while output is feedback data.

[0326] Step 8:

[0327] The server analyzes the user feedback data and instructs the AI ​​model to regenerate. The server then updates the database and regenerates the corrected prompt text. The input is the feedback data, and the output is the corrected artwork data.

[0328] Step 9:

[0329] The system matches content creators and content providers based on the generated digital works. The server recommends the most suitable creator from the database and notifies the user. The input is the work data, and the output is creator information.

[0330] Step 10:

[0331] The server initiates the process of registering the completed artwork with multiple sales platforms. During this process, it uses the sales platform's API to send artwork data and begin sales. The input is the artwork data, and the output is a notification that registration is complete with the sales platform.

[0332] Step 11:

[0333] Users monitor the sales and revenue status of their works in real time on a dashboard. The server aggregates feedback from the sales platform and presents it to users as a report. The input is sales data, and the output is a revenue report.

[0334] (Application Example 1)

[0335] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0336] In today's world, the process of creating, matching, and marketing digital works is complex, and efficient methods are needed. Furthermore, there is a lack of systems that allow users to intuitively specify themes and styles and easily create and distribute content. Solving this challenge will allow both content creators and providers to maximize profits and expand the scope of their creative activities.

[0337] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0338] In this invention, the server includes means for generating digital works using a generation device, means for comparing the generated digital works between content creators and content providers and recommending the most suitable creator, means for registering the generated digital works on multiple sales platforms and managing sales, means for specifying the theme and style that the user aims for and automatically generating art content using artificial intelligence, and means for directly uploading the generated digital works to a content distribution service. This makes it possible for users to efficiently and easily generate and distribute digital works.

[0339] A "generation device" is a device or system for automatically generating digital works using artificial intelligence or other technologies.

[0340] "Digital works" refer to digital content such as images, illustrations, videos, and music that are generated using computer technology.

[0341] A "content creator" is an individual or group that is responsible for creating or generating digital works.

[0342] A "content provider" is an individual or organization that markets, sells, or distributes digitally generated works.

[0343] A "sales platform" refers to the online platforms and marketplaces used to sell digital works.

[0344] "Theme" refers to the fundamental concept or subject matter of the digital work being created.

[0345] "Style" is a concept that describes a specific method or characteristic of visuals and expression in digital works.

[0346] An "artificial intelligence model" is a computational model developed to perform a specific task using machine learning or deep learning techniques.

[0347] A "prompt message" is a word or phrase used by a user to give instructions to a generator.

[0348] The system based on this invention is a platform that utilizes a generation device to generate digital works based on user-specified themes and styles. The server hosts a generation system equipped with AI technology and automatically generates digital works upon receiving input information from the user. The hardware uses a server with a high-performance processor, and the software includes machine learning libraries for running AI models (e.g., a generation AI model).

[0349] The terminal acts as a user interface, transmitting themes and style information entered by the user to the server. Users can give detailed instructions to the AI ​​by entering specific prompts, such as "an illustration of a dragon with a fantasy theme." These prompts are used by the generator to produce a unique digital artwork according to the specifications.

[0350] The generated digital works are also used as data to efficiently match content creators with content providers. The server automatically registers works to multiple sales platforms, making sales and revenue management easy and enabling seamless market access for users. Users can utilize these functions to quickly create, distribute, and sell digital works in the market.

[0351] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0352] Step 1:

[0353] The user logs into the system via their terminal and enters prompt text to specify a theme and style. This prompt text is prepared as input data and sent to the next process. For example, the user might enter the prompt text "An illustration of a dragon with a fantasy theme." This information is then sent from the terminal to the server.

[0354] Step 2:

[0355] The server uses a generative AI model to generate digital artwork, taking the prompt text received from the user as input data. This AI model analyzes the prompt text using machine learning algorithms and generates artwork data based on the results. Natural language processing is performed as data processing and computation, and the output is a pictorial representation. Specifically, the AI ​​model generates a new image based on the input theme and outputs it as a digital file.

[0356] Step 3:

[0357] The generated digital works are stored on a server in a database that matches content creators with providers. Here, data processing is performed to recommend the most suitable providers based on the style and theme of the generated works. Specifically, the system uses each provider's work history and rating data to list relevant providers for the user.

[0358] Step 4:

[0359] The server performs the necessary format conversions and delivers information to register generated digital works on multiple sales platforms. It takes digital works and their metadata as input and uploads them to the specified platform as output. Specifically, it communicates with the marketplace API and uploads the works and their sales information.

[0360] Step 5:

[0361] On the dashboard, users can view the performance and revenue status of their works across sales platforms in real time. The information entered is sales data collected from each sales platform, which is displayed visually as graphs and tables. Specifically, the device periodically receives updated data from the server and visualizes it as part of the user interface.

[0362] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0363] This invention is a system that utilizes an emotion engine to recognize a user's emotions and reflect those emotions in the creation of digital works. The system includes a generation device, an emotion engine, a user interface, and a data storage unit.

[0364] When the system starts, the user logs in and specifies the theme and style of the digital artwork to be generated in the project settings screen. Additionally, data related to the user's emotions is collected by the emotion engine through multiple methods (e.g., text input, voice input, facial recognition).

[0365] Terminal: Analyzes emotional data received from the user in real time and sends it to the server. This emotional data is used to reflect the emotional intentions the user wants to convey in their artwork. For example, if the user expresses joy, the emotional engine will use corresponding colors and positive elements to compose the artwork.

[0366] Server: Analyzes the received emotional data and determines the specific elements of the digital artwork (color, style, tone, etc.) based on the generation device. The generation device receives instructions from the emotional engine and uses an AI model to generate artwork that matches the user's emotional state.

[0367] The generated artwork reflects emotional elements, resulting in a piece that better aligns with the user's intentions. After final adjustments to content and style, this artwork is stored in the data storage unit.

[0368] The saved digital works are used in a matching process that connects content creators and providers. In this process, the system recommends suitable creators based on the style and emotional elements of the generated works, and ultimately, sales begin by registering them on multiple sales platforms.

[0369] For example, if a user inputs a sad emotion via voice input, the emotion engine analyzes the tone of the voice and the choice of words, and generates a digital artwork that reflects that emotion. This artwork may use dark colors and subdued tones, demonstrating how emotional nuances can be translated into digital art.

[0370] In this way, by using emotional information, we can create a system that efficiently generates and supplies digital works tailored to individual needs to the market.

[0371] The following describes the processing flow.

[0372] Step 1:

[0373] User: On the login screen, enter your username and password to authenticate. This login information will grant the user access to use the system.

[0374] Step 2:

[0375] Terminal: The terminal collects the theme, style, and desired emotional state of the digital artwork specified by the user via an input screen, and sends this information to the server.

[0376] Step 3:

[0377] Server: Activates a generator based on the user's theme and style, and prepares the emotion engine to analyze the user's emotional information.

[0378] Step 4:

[0379] Device: Collects user facial expressions and voice data through the camera and microphone, and transmits them to the emotion engine in real time.

[0380] Step 5:

[0381] Server: Analyzes facial expressions and voice data received by the emotion engine to identify the user's current emotional state. Based on this analysis, it provides appropriate instructions to the generation device.

[0382] Step 6:

[0383] Server: Using the analysis results from the emotion engine, the generator determines the color scheme, tone, and style of the artwork and generates an initial version of the digital artwork that corresponds to the emotion.

[0384] Step 7:

[0385] Terminal: Provides users with a preview of the generated digital artwork, allowing them to review the content and provide feedback.

[0386] Step 8:

[0387] User: View the preview and, if necessary, request revisions to the generated work or re-enter emotions.

[0388] Step 9:

[0389] Server: After receiving user feedback and making necessary corrections, the server saves the final digital artwork to the data storage unit.

[0390] Step 10:

[0391] Server: Based on the generated works, it matches content creators with providers and recommends appropriate creators.

[0392] Step 11:

[0393] Server: Finally, the completed work is registered on multiple sales platforms, and the sales process begins.

[0394] In this way, by utilizing emotional information, it becomes possible to efficiently generate digital works that better meet individual needs.

[0395] (Example 2)

[0396] Next, we will describe Example 2. 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".

[0397] There is a need to provide a system that efficiently generates digital content that reflects user emotions, optimally matches content creators and providers, and quickly delivers it to the market. Furthermore, it is necessary to accurately recognize the emotions of individual users and reflect them in digital works to enhance personalized product value and provide a better user experience.

[0398] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0399] In this invention, the server includes emotion analysis means that recognize the user's emotions and reflect those emotions in the generation of digital works; terminal means that analyze emotion data in real time and transmit it to the server; and server means that analyze the received emotion data and instruct the generation device to determine specific elements. This makes it possible to generate and optimize digital content that reflects the user's emotions.

[0400] An "emotion analysis tool" is a device that recognizes a user's emotions and analyzes those emotions in order to utilize the data for generating digital works.

[0401] A "terminal device" is a device or system that analyzes emotional data based on user input and transmits it to a server.

[0402] A "server device" is a device that analyzes emotional data received from a terminal and issues instructions to the generation device to determine the specific elements of the work.

[0403] A "generation device" is a device or system that has the function of generating digital content based on user input data and sentiment analysis.

[0404] "Digital content" refers to works or products in digital format that are generated based on the user's emotions or input themes.

[0405] "Content creator" refers to a professional or user who creates digital content.

[0406] A "content provider" refers to an organization or individual that is responsible for providing generated digital content to the market or platform.

[0407] "Supplying to the market" refers to the process of making generated digital content accessible to the general public.

[0408] This invention realizes a system that recognizes user emotions and generates digital content that reflects them. This system provides users with a personalized experience by consistently performing the processes of emotion analysis, digital content generation, and market supply.

[0409] First, the user logs in as the entry point to the system and specifies the theme and style of the digital content on the project settings screen. The user then inputs their emotions using text, voice, or facial expressions. This provides initial data for emotion analysis.

[0410] The device analyzes emotional data acquired from the user in real time. Specific software used includes a natural language processing engine, speech analysis tools, and image processing algorithms. This analysis extracts detailed emotions such as "joy," "sadness," and "surprise." For example, if a user inputs an emotion like "happy" via voice, that voice data is converted to text by a speech recognition tool and classified as "joy" by the emotion analysis engine.

[0411] The server uses emotional data transmitted from the terminal to generate digital works using a generation device. Generation AI models are used for this process, specifically models such as "DALL-E" and "Midjourney." These models automatically generate intuitive visual content based on emotional, thematic, and style information. The server stores the generated content in a data storage unit and provides a preview to the user as needed.

[0412] For example, when a user requests artwork based on "sad feelings," a prompt is used to generate a "calm landscape painting using dark tones." This prompt is given to the generation AI model and means something like, "Generate digital art that reflects the user's sad feelings. Use dark colors and calm tones."

[0413] Through the above process, this system accurately captures user emotions and enables the efficient delivery of unique, custom content to the market.

[0414] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0415] Step 1:

[0416] The user logs into the system and accesses the project settings screen. Here, the user enters input specifying the theme and style of the digital content they want to generate. This setting information is then sent to the terminal as output.

[0417] Step 2:

[0418] The user inputs their emotions. This input is done through text, voice, or facial recognition. For example, if the user voice-inputs "I'm happy today," the device converts that voice into text. This converted data is then recorded as input data on the device.

[0419] Step 3:

[0420] The device analyzes emotional data received from the user in real time. By processing the input data with a natural language processing engine and speech analysis tools, it performs calculations to identify the type of emotion (joy, sadness, etc.). The output of this analysis is sent to the server as analyzed emotional data.

[0421] Step 4:

[0422] The server activates the generation device based on the analyzed emotion data received from the terminal. The server sends the input emotion data as a prompt to the AI ​​model (e.g., DALL-E or Midjourney) to generate digital content that matches the user's emotions. An example of such a prompt message would be, "Please generate a bright-toned digital art piece that reflects the user's happy feelings."

[0423] Step 5:

[0424] The generation device receives prompts from the server and generates digital content based on them. The generation device utilizes an AI model to output works with visual elements (color tone, shape, etc.) corresponding to specified emotions and themes. The generated digital content is stored in the data storage unit.

[0425] Step 6:

[0426] The server utilizes stored digital content to match content creators with providers. A program recommends suitable creators based on the style and emotional elements of the work. As a result, the digital content is registered on the sales platform and market distribution begins.

[0427] (Application Example 2)

[0428] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0429] In today's digital content market, there is a demand for personalized experiences based on users' emotions and individual needs. However, existing systems struggle to accurately recognize and analyze users' emotions and provide appropriate digital experiences based on them. A system is needed to solve this problem and to quickly and efficiently generate and deliver more personalized digital content.

[0430] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0431] In this invention, the server includes means for generating digital representations using a generation device, means for creating digital information that provides a personalized experience to the user using an emotion recognition engine that recognizes and analyzes the user's emotions, and means for recommending the most suitable creator to connect the user and the creator based on the generated digital representations. This makes it possible to provide digital representations based on the individual emotions and needs of the user.

[0432] A "generation device" refers to a device or system for automatically generating digital representations.

[0433] "Digital expression" refers to all works and content created using digital technology.

[0434] An "emotion recognition engine" refers to software or a system used to detect and analyze a user's emotions.

[0435] A "personalized experience" refers to providing an experience that is customized according to the individual user's emotions and preferences.

[0436] "Digital information" refers to any information that is expressed in digital format.

[0437] An "e-commerce platform" refers to a platform for trading digital products and services online.

[0438] An "automated intelligent model" refers to a model that uses machine learning and artificial intelligence technologies to automatically perform various tasks.

[0439] The "data storage unit" refers to the storage system or database used to save the generated information.

[0440] To implement this invention, the system comprises a smartphone, a server, and an emotion recognition engine. Users can input emotion data using the smartphone. This emotion data is collected using methods such as voice input or facial recognition. The terminal analyzes the collected emotion data in real time and transmits the information to the server.

[0441] The server generates digital representations using generative AI models based on the received emotion data. The emotion recognition engine analyzes the user's emotional state and creates digital information with a style and content appropriate to the corresponding emotion. The generated digital representations are further optimized to provide a personalized experience when they are delivered to the user. This process utilizes AI models running on Google Cloud Platform (GCP) (e.g., the GPT family), as well as TensorFlow and OpenCV for emotion recognition.

[0442] As a concrete example, a server can use an emotion recognition engine to generate and provide music playlists and visual content suitable for relaxation based on voice information entered by the user when they want to relax. In this way, it becomes easy to create digital experiences that match the user's emotions.

[0443] In this regard, the following prompts can be used with the generative AI model: "Generate music that promotes a relaxed mood," and "Suggest videos that evoke a travel-like feeling."

[0444] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0445] Step 1:

[0446] The user launches a smartphone application and inputs emotion data. Input is performed using voice input or facial recognition. The device collects audio and video data using the microphone and camera. This input data is temporarily stored on the smartphone.

[0447] Step 2:

[0448] The device processes collected audio and video data in real time to recognize emotions. This process uses TensorFlow to analyze audio data and OpenCV to analyze facial expressions in video data. The results of these analyses are output as the user's emotional state and sent to the server.

[0449] Step 3:

[0450] The server receives emotion data from the terminal and uses a generative AI model to generate digital representations. In this step, content that matches the user's emotions is generated based on pre-configured prompts. The server uses an AI model such as the GPT family to materialize the digital information and generates the result as a digital representation.

[0451] Step 4:

[0452] Based on the generated digital representations, the server optimizes and delivers them to the user. Specifically, it adjusts the generated content to match the user's preferences in order to create a personalized experience. When these digital representations are sent to the user's device, the user can receive a digital experience that responds to their emotions.

[0453] Step 5:

[0454] Users can experience the provided digital representations and provide feedback on their results. Additional emotional data can be provided through the application. This creates a consistent data feedback loop throughout the system, contributing to the optimization of future experiences.

[0455] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0456] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0457] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0458] [Third Embodiment]

[0459] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0460] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0461] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0462] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0463] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0464] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0465] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0466] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0467] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0468] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0469] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0470] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0471] The present invention aims to maximize the market exposure of digital works by utilizing a generation device to generate digital works, efficiently matching content creators with content providers, and registering the generated works on multiple sales platforms.

[0472] This system operates on a platform accessible to the user. When a user logs into the system as an entry point, the generator first determines the theme and style of the target content based on the user's requests. For example, a user can specify a theme they want to use for illustrations in a fantasy novel.

[0473] User: After logging in, start a new project on the menu screen and enter various parameters (e.g., theme, style, type of work) to inform the generator.

[0474] Terminal: Receives user input information and sends it to the generation device. This generation device uses an AI-powered model to generate initial works based on a specified theme.

[0475] Server: Stores the generated artwork data and provides it to users in a viewable format. It also receives continuous feedback and supports the process of regenerating artwork in response to user requests for corrections.

[0476] After a work is created, the system performs a process to match content creators with content providers. At this stage, a mechanism is in place to recommend creators who are a good fit for the style and purpose of the digital work. For example, if a user is writing an adventure fantasy plot, an illustrator with experience in this theme will be recommended.

[0477] Ultimately, the system registers completed digital works on multiple sales platforms. This sales functionality facilitates access to marketplaces and helps users pursue revenue potential. Users can monitor the performance and revenue status of their works on each sales platform in real time through a dashboard.

[0478] In this way, the system provides an integrated solution for generating creative content, establishing appropriate collaborative systems, and gaining market exposure.

[0479] The following describes the processing flow.

[0480] Step 1:

[0481] User: Enter your username and password on the login screen and press the login button. This will initiate user authentication.

[0482] Step 2:

[0483] Server: The server verifies the received username and password against the information in the database. If the verification is successful, it sends a notification of successful authentication to the device.

[0484] Step 3:

[0485] Terminal: Receives authentication results from the server, displays a successful login message to the user, and redirects them to the dashboard screen.

[0486] Step 4:

[0487] User: On the project creation screen, enter the theme and style for the new content and request project creation.

[0488] Step 5:

[0489] Terminal: Sends user input information to the server and instructs it to start the generation process.

[0490] Step 6:

[0491] Server: Selects an AI model and generates an initial digital artwork based on the theme and style specified by the user.

[0492] Step 7:

[0493] Terminal: Displays the generated work as a preview to the user and provides an option to receive feedback.

[0494] Step 8:

[0495] User: Review the preview of the artwork and request a regeneration if necessary.

[0496] Step 9:

[0497] Server: Modifies or regenerates the artwork based on user feedback and saves the final version to the project folder.

[0498] Step 10:

[0499] Server: Based on the style and content of the work, it selects suitable content creators as recommended candidates and sends matching information to the terminal.

[0500] Step 11:

[0501] Terminal: Presents users with information on recommended content creators and provides them with the option to submit a matching request.

[0502] Step 12:

[0503] User: Review the presented information and send matching requests to creators who wish to collaborate.

[0504] Step 13:

[0505] Server: Registers the completed work on the selected sales platform and initiates the sales process.

[0506] Step 14:

[0507] User: Check the sales status and revenue of registered works in real time on the dashboard.

[0508] The above describes the specific actions taken in each processing step.

[0509] (Example 1)

[0510] Next, we will describe Example 1. 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."

[0511] In generating digital content, it is necessary to provide a system that efficiently produces high-quality works based on specific user requests, builds collaborative relationships with appropriate creators, registers with a wide range of sales platforms to maximize market exposure, and allows users to efficiently understand sales status in real time.

[0512] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0513] In this invention, the server includes means for generating digital works according to a theme and style using a generation device based on user input, means for storing the generated digital works in a data storage unit and making them available for the user to view, and means for modifying and regenerating the generated digital works based on user feedback. This enables the user to manage the entire process from the generation of digital works to sales and monitoring in an integrated manner.

[0514] A "generation device" is hardware or software that generates digital works by considering themes and styles based on user input information.

[0515] A "digital work" is an electronic work that includes text, images, audio, video, and other content created by a generating device.

[0516] A "content creator" refers to an individual or organization that is involved in the creation of digital works and provides creative input.

[0517] A "content provider" is an individual or organization that provides generated digital works to the market and is responsible for their distribution.

[0518] A "sales platform" is an online or offline platform for selling generated digital works.

[0519] A "generative AI model" is a program model that uses artificial intelligence to generate, analyze, or improve content.

[0520] A "prompt" is text used as a command or instruction when a generative AI model generates a digital work.

[0521] "Feedback" refers to opinions and requests for revisions provided by users regarding their created works.

[0522] A "dashboard" is an interface that allows users to visually check and manage the progress and sales status of their generated digital works.

[0523] This invention aims to generate digital works tailored to user needs using a computer-based system, facilitate collaboration with appropriate content creators, and widely publish the works in the market. Specific embodiments of this system are described below.

[0524] First, users access the platform from their device via the internet and log in to the system using their username and password. Once logged in, users can access a dashboard to create new projects.

[0525] When creating a project, users enter detailed information such as the theme, style, and type of work. For example, if a user wants to generate illustrations for a fantasy novel with the theme of "magic school," they would fill in this information in the project form. This information is recorded as a prompt and used in the next stage. A concrete example of this prompt might be, "Generate illustrations for a fantasy novel with the theme of a magic school. The style should be fantastical and include futuristic elements."

[0526] The terminal sends information entered by the user to the server. Based on this information, the server activates a generation device and uses a generative AI model to generate digital artwork according to the specified theme and style. The generative AI model used here is a general-purpose AI software that is highly regarded in the market.

[0527] The generated digital artwork is stored in the data storage area by the server and simultaneously reflected on the dashboard in a format viewable by the user. Users can review the artwork and provide feedback if necessary. For example, if a particular character in an illustration differs from the user's image, they can request a correction. The server receives this feedback and instructs the generation AI model to regenerate the artwork.

[0528] The system also matches content creators and content providers based on the generated digital works. The server recommends the most suitable creator for the work's theme and style, and supports collaboration.

[0529] Ultimately, the content is registered on multiple sales platforms, which are automatically managed by a server, allowing users to view sales status and revenue in real time through a dashboard. This process enables users to improve how their content is presented and optimize access to the market.

[0530] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0531] Step 1:

[0532] Users access the platform from their devices and log in to the system by entering their username and password. Login is performed by verifying user information against a database through an authentication system. The input is user information, and the output is a user-specific dashboard screen.

[0533] Step 2:

[0534] The user clicks the "Start a New Project" button on the dashboard to display the project creation screen. Here, they enter details such as the theme, style, and type of the project. The inputs are project parameters, and the output is a prompt message containing this data.

[0535] Step 3:

[0536] The terminal sends the project information entered by the user to the server. The server then uses this information to prepare to start the generator. The input consists of project parameters, and the output consists of prepared data to be passed to the generator.

[0537] Step 4:

[0538] The server generates prompt statements for the AI ​​model. These prompt statements serve as specific instructions for the AI ​​model when generating the digital artwork. The input is the data prepared by the generation device, and the output is the prompt statements passed to the AI ​​model.

[0539] Step 5:

[0540] The generation device uses an AI model to generate digital artwork based on prompt messages received from the server. The AI ​​performs data calculations to generate artwork based on a specified theme and style. The input is the prompt message, and the output is the generated digital artwork data.

[0541] Step 6:

[0542] The server stores the generated digital artwork data in its data storage unit and simultaneously reflects it on the user's dashboard, making it viewable. The input is the generated artwork data, and the output is the artwork data in a format viewable by the user.

[0543] Step 7:

[0544] Users review the generated work on the dashboard and provide feedback as needed. User input consists of revision requests and opinions, while output is feedback data.

[0545] Step 8:

[0546] The server analyzes the user feedback data and instructs the AI ​​model to regenerate. The server then updates the database and regenerates the corrected prompt text. The input is the feedback data, and the output is the corrected artwork data.

[0547] Step 9:

[0548] The system matches content creators and content providers based on the generated digital works. The server recommends the most suitable creator from the database and notifies the user. The input is the work data, and the output is creator information.

[0549] Step 10:

[0550] The server initiates the process of registering the completed artwork with multiple sales platforms. During this process, it uses the sales platform's API to send artwork data and begin sales. The input is the artwork data, and the output is a notification that registration is complete with the sales platform.

[0551] Step 11:

[0552] Users monitor the sales and revenue status of their works in real time on a dashboard. The server aggregates feedback from the sales platform and presents it to users as a report. The input is sales data, and the output is a revenue report.

[0553] (Application Example 1)

[0554] Next, we will explain Application Example 1. In the following explanation, 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."

[0555] In today's world, the process of creating, matching, and marketing digital works is complex, and efficient methods are needed. Furthermore, there is a lack of systems that allow users to intuitively specify themes and styles and easily create and distribute content. Solving this challenge will allow both content creators and providers to maximize profits and expand the scope of their creative activities.

[0556] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0557] In this invention, the server includes means for generating digital works using a generation device, means for comparing the generated digital works between content creators and content providers and recommending the most suitable creator, means for registering the generated digital works on multiple sales platforms and managing sales, means for specifying the theme and style that the user aims for and automatically generating art content using artificial intelligence, and means for directly uploading the generated digital works to a content distribution service. This makes it possible for users to efficiently and easily generate and distribute digital works.

[0558] A "generation device" is a device or system for automatically generating digital works using artificial intelligence or other technologies.

[0559] "Digital works" refer to digital content such as images, illustrations, videos, and music that are generated using computer technology.

[0560] A "content creator" is an individual or group that is responsible for creating or generating digital works.

[0561] A "content provider" is an individual or organization that markets, sells, or distributes digitally generated works.

[0562] A "sales platform" refers to the online platforms and marketplaces used to sell digital works.

[0563] "Theme" refers to the fundamental concept or subject matter of the digital work being created.

[0564] "Style" is a concept that describes a specific method or characteristic of visuals and expression in digital works.

[0565] An "artificial intelligence model" is a computational model developed to perform a specific task using machine learning or deep learning techniques.

[0566] A "prompt message" is a word or phrase used by a user to give instructions to a generator.

[0567] The system based on this invention is a platform that utilizes a generation device to generate digital works based on user-specified themes and styles. The server hosts a generation system equipped with AI technology and automatically generates digital works upon receiving input information from the user. The hardware uses a server with a high-performance processor, and the software includes machine learning libraries for running AI models (e.g., a generation AI model).

[0568] The terminal acts as a user interface, transmitting themes and style information entered by the user to the server. Users can give detailed instructions to the AI ​​by entering specific prompts, such as "an illustration of a dragon with a fantasy theme." These prompts are used by the generator to produce a unique digital artwork according to the specifications.

[0569] The generated digital works are also used as data to efficiently match content creators with content providers. The server automatically registers works to multiple sales platforms, making sales and revenue management easy and enabling seamless market access for users. Users can utilize these functions to quickly create, distribute, and sell digital works in the market.

[0570] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0571] Step 1:

[0572] The user logs into the system via their terminal and enters prompt text to specify a theme and style. This prompt text is prepared as input data and sent to the next process. For example, the user might enter the prompt text "An illustration of a dragon with a fantasy theme." This information is then sent from the terminal to the server.

[0573] Step 2:

[0574] The server uses a generative AI model to generate digital artwork, taking the prompt text received from the user as input data. This AI model analyzes the prompt text using machine learning algorithms and generates artwork data based on the results. Natural language processing is performed as data processing and computation, and the output is a pictorial representation. Specifically, the AI ​​model generates a new image based on the input theme and outputs it as a digital file.

[0575] Step 3:

[0576] The generated digital works are stored on a server in a database that matches content creators with providers. Here, data processing is performed to recommend the most suitable providers based on the style and theme of the generated works. Specifically, the system uses each provider's work history and rating data to list relevant providers for the user.

[0577] Step 4:

[0578] The server performs the necessary format conversions and delivers information to register generated digital works on multiple sales platforms. It takes digital works and their metadata as input and uploads them to the specified platform as output. Specifically, it communicates with the marketplace API and uploads the works and their sales information.

[0579] Step 5:

[0580] On the dashboard, users can view the performance and revenue status of their works across sales platforms in real time. The information entered is sales data collected from each sales platform, which is displayed visually as graphs and tables. Specifically, the device periodically receives updated data from the server and visualizes it as part of the user interface.

[0581] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0582] This invention is a system that utilizes an emotion engine to recognize a user's emotions and reflect those emotions in the creation of digital works. The system includes a generation device, an emotion engine, a user interface, and a data storage unit.

[0583] When the system starts, the user logs in and specifies the theme and style of the digital artwork to be generated in the project settings screen. Additionally, data related to the user's emotions is collected by the emotion engine through multiple methods (e.g., text input, voice input, facial recognition).

[0584] Terminal: Analyzes emotional data received from the user in real time and sends it to the server. This emotional data is used to reflect the emotional intentions the user wants to convey in their artwork. For example, if the user expresses joy, the emotional engine will use corresponding colors and positive elements to compose the artwork.

[0585] Server: Analyzes the received emotional data and determines the specific elements of the digital artwork (color, style, tone, etc.) based on the generation device. The generation device receives instructions from the emotional engine and uses an AI model to generate artwork that matches the user's emotional state.

[0586] The generated artwork reflects emotional elements, resulting in a piece that better aligns with the user's intentions. After final adjustments to content and style, this artwork is stored in the data storage unit.

[0587] The saved digital works are used in a matching process that connects content creators and providers. In this process, the system recommends suitable creators based on the style and emotional elements of the generated works, and ultimately, sales begin by registering them on multiple sales platforms.

[0588] For example, if a user inputs a sad emotion via voice input, the emotion engine analyzes the tone of the voice and the choice of words, and generates a digital artwork that reflects that emotion. This artwork may use dark colors and subdued tones, demonstrating how emotional nuances can be translated into digital art.

[0589] In this way, by using emotional information, we can create a system that efficiently generates and supplies digital works tailored to individual needs to the market.

[0590] The following describes the processing flow.

[0591] Step 1:

[0592] User: On the login screen, enter your username and password to authenticate. This login information will grant the user access to use the system.

[0593] Step 2:

[0594] Terminal: The terminal collects the theme, style, and desired emotional state of the digital artwork specified by the user via an input screen, and sends this information to the server.

[0595] Step 3:

[0596] Server: Activates a generator based on the user's theme and style, and prepares the emotion engine to analyze the user's emotional information.

[0597] Step 4:

[0598] Device: Collects user facial expressions and voice data through the camera and microphone, and transmits them to the emotion engine in real time.

[0599] Step 5:

[0600] Server: Analyzes facial expressions and voice data received by the emotion engine to identify the user's current emotional state. Based on this analysis, it provides appropriate instructions to the generation device.

[0601] Step 6:

[0602] Server: Using the analysis results from the emotion engine, the generator determines the color scheme, tone, and style of the artwork and generates an initial version of the digital artwork that corresponds to the emotion.

[0603] Step 7:

[0604] Terminal: Provides users with a preview of the generated digital artwork, allowing them to review the content and provide feedback.

[0605] Step 8:

[0606] User: View the preview and, if necessary, request revisions to the generated work or re-enter emotions.

[0607] Step 9:

[0608] Server: After receiving user feedback and making necessary corrections, the server saves the final digital artwork to the data storage unit.

[0609] Step 10:

[0610] Server: Based on the generated works, it matches content creators with providers and recommends appropriate creators.

[0611] Step 11:

[0612] Server: Finally, the completed work is registered on multiple sales platforms, and the sales process begins.

[0613] In this way, by utilizing emotional information, it becomes possible to efficiently generate digital works that better meet individual needs.

[0614] (Example 2)

[0615] Next, we will describe Example 2. 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."

[0616] There is a need to provide a system that efficiently generates digital content that reflects user emotions, optimally matches content creators and providers, and quickly delivers it to the market. Furthermore, it is necessary to accurately recognize the emotions of individual users and reflect them in digital works to enhance personalized product value and provide a better user experience.

[0617] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0618] In this invention, the server includes emotion analysis means that recognize the user's emotions and reflect those emotions in the generation of digital works; terminal means that analyze emotion data in real time and transmit it to the server; and server means that analyze the received emotion data and instruct the generation device to determine specific elements. This makes it possible to generate and optimize digital content that reflects the user's emotions.

[0619] An "emotion analysis tool" is a device that recognizes a user's emotions and analyzes those emotions in order to utilize the data for generating digital works.

[0620] A "terminal device" is a device or system that analyzes emotional data based on user input and transmits it to a server.

[0621] A "server device" is a device that analyzes emotional data received from a terminal and issues instructions to the generation device to determine the specific elements of the work.

[0622] A "generation device" is a device or system that has the function of generating digital content based on user input data and sentiment analysis.

[0623] "Digital content" refers to works or products in digital format that are generated based on the user's emotions or input themes.

[0624] "Content creator" refers to a professional or user who creates digital content.

[0625] A "content provider" refers to an organization or individual that is responsible for providing generated digital content to the market or platform.

[0626] "Supplying to the market" refers to the process of making generated digital content accessible to the general public.

[0627] This invention realizes a system that recognizes user emotions and generates digital content that reflects them. This system provides users with a personalized experience by consistently performing the processes of emotion analysis, digital content generation, and market supply.

[0628] First, the user logs in as the entry point to the system and specifies the theme and style of the digital content on the project settings screen. The user then inputs their emotions using text, voice, or facial expressions. This provides initial data for emotion analysis.

[0629] The device analyzes emotional data acquired from the user in real time. Specific software used includes a natural language processing engine, speech analysis tools, and image processing algorithms. This analysis extracts detailed emotions such as "joy," "sadness," and "surprise." For example, if a user inputs an emotion like "happy" via voice, that voice data is converted to text by a speech recognition tool and classified as "joy" by the emotion analysis engine.

[0630] The server uses emotional data transmitted from the terminal to generate digital works using a generation device. Generation AI models are used for this process, specifically models such as "DALL-E" and "Midjourney." These models automatically generate intuitive visual content based on emotional, thematic, and style information. The server stores the generated content in a data storage unit and provides a preview to the user as needed.

[0631] For example, when a user requests artwork based on "sad feelings," a prompt is used to generate a "calm landscape painting using dark tones." This prompt is given to the generation AI model and means something like, "Generate digital art that reflects the user's sad feelings. Use dark colors and calm tones."

[0632] Through the above process, this system accurately captures user emotions and enables the efficient delivery of unique, custom content to the market.

[0633] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0634] Step 1:

[0635] The user logs into the system and accesses the project settings screen. Here, the user enters input specifying the theme and style of the digital content they want to generate. This setting information is then sent to the terminal as output.

[0636] Step 2:

[0637] The user inputs their emotions. This input is done through text, voice, or facial recognition. For example, if the user voice-inputs "I'm happy today," the device converts that voice into text. This converted data is then recorded as input data on the device.

[0638] Step 3:

[0639] The device analyzes emotional data received from the user in real time. By processing the input data with a natural language processing engine and speech analysis tools, it performs calculations to identify the type of emotion (joy, sadness, etc.). The output of this analysis is sent to the server as analyzed emotional data.

[0640] Step 4:

[0641] The server activates the generation device based on the analyzed emotion data received from the terminal. The server sends the input emotion data as a prompt to the AI ​​model (e.g., DALL-E or Midjourney) to generate digital content that matches the user's emotions. An example of such a prompt message would be, "Please generate a bright-toned digital art piece that reflects the user's happy feelings."

[0642] Step 5:

[0643] The generation device receives prompts from the server and generates digital content based on them. The generation device utilizes an AI model to output works with visual elements (color tone, shape, etc.) corresponding to specified emotions and themes. The generated digital content is stored in the data storage unit.

[0644] Step 6:

[0645] The server utilizes stored digital content to match content creators with providers. A program recommends suitable creators based on the style and emotional elements of the work. As a result, the digital content is registered on the sales platform and market distribution begins.

[0646] (Application Example 2)

[0647] Next, we will explain application example 2. In the following explanation, 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."

[0648] In today's digital content market, there is a demand for personalized experiences based on users' emotions and individual needs. However, existing systems struggle to accurately recognize and analyze users' emotions and provide appropriate digital experiences based on them. A system is needed to solve this problem and to quickly and efficiently generate and deliver more personalized digital content.

[0649] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0650] In this invention, the server includes means for generating digital representations using a generation device, means for creating digital information that provides a personalized experience to the user using an emotion recognition engine that recognizes and analyzes the user's emotions, and means for recommending the most suitable creator to connect the user and the creator based on the generated digital representations. This makes it possible to provide digital representations based on the individual emotions and needs of the user.

[0651] A "generation device" refers to a device or system for automatically generating digital representations.

[0652] "Digital expression" refers to all works and content created using digital technology.

[0653] An "emotion recognition engine" refers to software or a system used to detect and analyze a user's emotions.

[0654] A "personalized experience" refers to providing an experience that is customized according to the individual user's emotions and preferences.

[0655] "Digital information" refers to any information that is expressed in digital format.

[0656] An "e-commerce platform" refers to a platform for trading digital products and services online.

[0657] An "automated intelligent model" refers to a model that uses machine learning and artificial intelligence technologies to automatically perform various tasks.

[0658] The "data storage unit" refers to the storage system or database used to save the generated information.

[0659] To implement this invention, the system comprises a smartphone, a server, and an emotion recognition engine. Users can input emotion data using the smartphone. This emotion data is collected using methods such as voice input or facial recognition. The terminal analyzes the collected emotion data in real time and transmits the information to the server.

[0660] The server generates digital representations using generative AI models based on the received emotion data. The emotion recognition engine analyzes the user's emotional state and creates digital information with a style and content appropriate to the corresponding emotion. The generated digital representations are further optimized to provide a personalized experience when they are delivered to the user. This process utilizes AI models running on Google Cloud Platform (GCP) (e.g., the GPT family), as well as TensorFlow and OpenCV for emotion recognition.

[0661] As a concrete example, a server can use an emotion recognition engine to generate and provide music playlists and visual content suitable for relaxation based on voice information entered by the user when they want to relax. In this way, it becomes easy to create digital experiences that match the user's emotions.

[0662] In this regard, the following prompts can be used with the generative AI model: "Generate music that promotes a relaxed mood," and "Suggest videos that evoke a travel-like feeling."

[0663] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0664] Step 1:

[0665] The user launches a smartphone application and inputs emotion data. Input is performed using voice input or facial recognition. The device collects audio and video data using the microphone and camera. This input data is temporarily stored on the smartphone.

[0666] Step 2:

[0667] The device processes collected audio and video data in real time to recognize emotions. This process uses TensorFlow to analyze audio data and OpenCV to analyze facial expressions in video data. The results of these analyses are output as the user's emotional state and sent to the server.

[0668] Step 3:

[0669] The server receives emotion data from the terminal and uses a generative AI model to generate digital representations. In this step, content that matches the user's emotions is generated based on pre-configured prompts. The server uses an AI model such as the GPT family to materialize the digital information and generates the result as a digital representation.

[0670] Step 4:

[0671] Based on the generated digital representations, the server optimizes and delivers them to the user. Specifically, it adjusts the generated content to match the user's preferences in order to create a personalized experience. When these digital representations are sent to the user's device, the user can receive a digital experience that responds to their emotions.

[0672] Step 5:

[0673] Users can experience the provided digital representations and provide feedback on their results. Additional emotional data can be provided through the application. This creates a consistent data feedback loop throughout the system, contributing to the optimization of future experiences.

[0674] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0675] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0676] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0677] [Fourth Embodiment]

[0678] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0679] As shown in Figure 7, the 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.

[0680] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0681] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0682] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0683] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0684] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0685] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0686] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0687] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0688] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0689] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0690] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0691] The present invention aims to maximize the market exposure of digital works by utilizing a generation device to generate digital works, efficiently matching content creators with content providers, and registering the generated works on multiple sales platforms.

[0692] This system operates on a platform accessible to the user. When a user logs into the system as an entry point, the generator first determines the theme and style of the target content based on the user's requests. For example, a user can specify a theme they want to use for illustrations in a fantasy novel.

[0693] User: After logging in, start a new project on the menu screen and enter various parameters (e.g., theme, style, type of work) to inform the generator.

[0694] Terminal: Receives user input information and sends it to the generation device. This generation device uses an AI-powered model to generate initial works based on a specified theme.

[0695] Server: Stores the generated artwork data and provides it to users in a viewable format. It also receives continuous feedback and supports the process of regenerating artwork in response to user requests for corrections.

[0696] After a work is created, the system performs a process to match content creators with content providers. At this stage, a mechanism is in place to recommend creators who are a good fit for the style and purpose of the digital work. For example, if a user is writing an adventure fantasy plot, an illustrator with experience in this theme will be recommended.

[0697] Ultimately, the system registers completed digital works on multiple sales platforms. This sales functionality facilitates access to marketplaces and helps users pursue revenue potential. Users can monitor the performance and revenue status of their works on each sales platform in real time through a dashboard.

[0698] In this way, the system provides an integrated solution for generating creative content, establishing appropriate collaborative systems, and gaining market exposure.

[0699] The following describes the processing flow.

[0700] Step 1:

[0701] User: Enter your username and password on the login screen and press the login button. This will initiate user authentication.

[0702] Step 2:

[0703] Server: The server verifies the received username and password against the information in the database. If the verification is successful, it sends a notification of successful authentication to the device.

[0704] Step 3:

[0705] Terminal: Receives authentication results from the server, displays a successful login message to the user, and redirects them to the dashboard screen.

[0706] Step 4:

[0707] User: On the project creation screen, enter the theme and style for the new content and request project creation.

[0708] Step 5:

[0709] Terminal: Sends user input information to the server and instructs it to start the generation process.

[0710] Step 6:

[0711] Server: Selects an AI model and generates an initial digital artwork based on the theme and style specified by the user.

[0712] Step 7:

[0713] Terminal: Displays the generated work as a preview to the user and provides an option to receive feedback.

[0714] Step 8:

[0715] User: Review the preview of the artwork and request a regeneration if necessary.

[0716] Step 9:

[0717] Server: Modifies or regenerates the artwork based on user feedback and saves the final version to the project folder.

[0718] Step 10:

[0719] Server: Based on the style and content of the work, it selects suitable content creators as recommended candidates and sends matching information to the terminal.

[0720] Step 11:

[0721] Terminal: Presents users with information on recommended content creators and provides them with the option to submit a matching request.

[0722] Step 12:

[0723] User: Review the presented information and send matching requests to creators who wish to collaborate.

[0724] Step 13:

[0725] Server: Registers the completed work on the selected sales platform and initiates the sales process.

[0726] Step 14:

[0727] User: Check the sales status and revenue of registered works in real time on the dashboard.

[0728] The above describes the specific actions taken in each processing step.

[0729] (Example 1)

[0730] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0731] In generating digital content, it is necessary to provide a system that efficiently produces high-quality works based on specific user requests, builds collaborative relationships with appropriate creators, registers with a wide range of sales platforms to maximize market exposure, and allows users to efficiently understand sales status in real time.

[0732] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0733] In this invention, the server includes means for generating digital works according to a theme and style using a generation device based on user input, means for storing the generated digital works in a data storage unit and making them available for the user to view, and means for modifying and regenerating the generated digital works based on user feedback. This enables the user to manage the entire process from the generation of digital works to sales and monitoring in an integrated manner.

[0734] A "generation device" is hardware or software that generates digital works by considering themes and styles based on user input information.

[0735] A "digital work" is an electronic work that includes text, images, audio, video, and other content created by a generating device.

[0736] A "content creator" refers to an individual or organization that is involved in the creation of digital works and provides creative input.

[0737] A "content provider" is an individual or organization that provides generated digital works to the market and is responsible for their distribution.

[0738] A "sales platform" is an online or offline platform for selling generated digital works.

[0739] A "generative AI model" is a program model that uses artificial intelligence to generate, analyze, or improve content.

[0740] A "prompt" is text used as a command or instruction when a generative AI model generates a digital work.

[0741] "Feedback" refers to opinions and requests for revisions provided by users regarding their created works.

[0742] A "dashboard" is an interface that allows users to visually check and manage the progress and sales status of their generated digital works.

[0743] This invention aims to generate digital works tailored to user needs using a computer-based system, facilitate collaboration with appropriate content creators, and widely publish the works in the market. Specific embodiments of this system are described below.

[0744] First, users access the platform from their device via the internet and log in to the system using their username and password. Once logged in, users can access a dashboard to create new projects.

[0745] When creating a project, users enter detailed information such as the theme, style, and type of work. For example, if a user wants to generate illustrations for a fantasy novel with the theme of "magic school," they would fill in this information in the project form. This information is recorded as a prompt and used in the next stage. A concrete example of this prompt might be, "Generate illustrations for a fantasy novel with the theme of a magic school. The style should be fantastical and include futuristic elements."

[0746] The terminal sends information entered by the user to the server. Based on this information, the server activates a generation device and uses a generative AI model to generate digital artwork according to the specified theme and style. The generative AI model used here is a general-purpose AI software that is highly regarded in the market.

[0747] The generated digital artwork is stored in the data storage area by the server and simultaneously reflected on the dashboard in a format viewable by the user. Users can review the artwork and provide feedback if necessary. For example, if a particular character in an illustration differs from the user's image, they can request a correction. The server receives this feedback and instructs the generation AI model to regenerate the artwork.

[0748] The system also matches content creators and content providers based on the generated digital works. The server recommends the most suitable creator for the work's theme and style, and supports collaboration.

[0749] Ultimately, the content is registered on multiple sales platforms, which are automatically managed by a server, allowing users to view sales status and revenue in real time through a dashboard. This process enables users to improve how their content is presented and optimize access to the market.

[0750] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0751] Step 1:

[0752] Users access the platform from their devices and log in to the system by entering their username and password. Login is performed by verifying user information against a database through an authentication system. The input is user information, and the output is a user-specific dashboard screen.

[0753] Step 2:

[0754] The user clicks the "Start a New Project" button on the dashboard to display the project creation screen. Here, they enter details such as the theme, style, and type of the project. The inputs are project parameters, and the output is a prompt message containing this data.

[0755] Step 3:

[0756] The terminal sends the project information entered by the user to the server. The server then uses this information to prepare to start the generator. The input consists of project parameters, and the output consists of prepared data to be passed to the generator.

[0757] Step 4:

[0758] The server generates prompt statements for the AI ​​model. These prompt statements serve as specific instructions for the AI ​​model when generating the digital artwork. The input is the data prepared by the generation device, and the output is the prompt statements passed to the AI ​​model.

[0759] Step 5:

[0760] The generation device uses an AI model to generate digital artwork based on prompt messages received from the server. The AI ​​performs data calculations to generate artwork based on a specified theme and style. The input is the prompt message, and the output is the generated digital artwork data.

[0761] Step 6:

[0762] The server stores the generated digital artwork data in its data storage unit and simultaneously reflects it on the user's dashboard, making it viewable. The input is the generated artwork data, and the output is the artwork data in a format viewable by the user.

[0763] Step 7:

[0764] Users review the generated work on the dashboard and provide feedback as needed. User input consists of revision requests and opinions, while output is feedback data.

[0765] Step 8:

[0766] The server analyzes the user feedback data and instructs the AI ​​model to regenerate. The server then updates the database and regenerates the corrected prompt text. The input is the feedback data, and the output is the corrected artwork data.

[0767] Step 9:

[0768] The system matches content creators and content providers based on the generated digital works. The server recommends the most suitable creator from the database and notifies the user. The input is the work data, and the output is creator information.

[0769] Step 10:

[0770] The server initiates the process of registering the completed artwork with multiple sales platforms. During this process, it uses the sales platform's API to send artwork data and begin sales. The input is the artwork data, and the output is a notification that registration is complete with the sales platform.

[0771] Step 11:

[0772] Users monitor the sales and revenue status of their works in real time on a dashboard. The server aggregates feedback from the sales platform and presents it to users as a report. The input is sales data, and the output is a revenue report.

[0773] (Application Example 1)

[0774] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0775] In today's world, the process of creating, matching, and marketing digital works is complex, and efficient methods are needed. Furthermore, there is a lack of systems that allow users to intuitively specify themes and styles and easily create and distribute content. Solving this challenge will allow both content creators and providers to maximize profits and expand the scope of their creative activities.

[0776] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0777] In this invention, the server includes means for generating digital works using a generation device, means for comparing the generated digital works between content creators and content providers and recommending the most suitable creator, means for registering the generated digital works on multiple sales platforms and managing sales, means for specifying the theme and style that the user aims for and automatically generating art content using artificial intelligence, and means for directly uploading the generated digital works to a content distribution service. This makes it possible for users to efficiently and easily generate and distribute digital works.

[0778] A "generation device" is a device or system for automatically generating digital works using artificial intelligence or other technologies.

[0779] "Digital works" refer to digital content such as images, illustrations, videos, and music that are generated using computer technology.

[0780] A "content creator" is an individual or group that is responsible for creating or generating digital works.

[0781] A "content provider" is an individual or organization that markets, sells, or distributes digitally generated works.

[0782] A "sales platform" refers to the online platforms and marketplaces used to sell digital works.

[0783] "Theme" refers to the fundamental concept or subject matter of the digital work being created.

[0784] "Style" is a concept that describes a specific method or characteristic of visuals and expression in digital works.

[0785] An "artificial intelligence model" is a computational model developed to perform a specific task using machine learning or deep learning techniques.

[0786] A "prompt message" is a word or phrase used by a user to give instructions to a generator.

[0787] The system based on this invention is a platform that utilizes a generation device to generate digital works based on user-specified themes and styles. The server hosts a generation system equipped with AI technology and automatically generates digital works upon receiving input information from the user. The hardware uses a server with a high-performance processor, and the software includes machine learning libraries for running AI models (e.g., a generation AI model).

[0788] The terminal acts as a user interface, transmitting themes and style information entered by the user to the server. Users can give detailed instructions to the AI ​​by entering specific prompts, such as "an illustration of a dragon with a fantasy theme." These prompts are used by the generator to produce a unique digital artwork according to the specifications.

[0789] The generated digital works are also used as data to efficiently match content creators with content providers. The server automatically registers works to multiple sales platforms, making sales and revenue management easy and enabling seamless market access for users. Users can utilize these functions to quickly create, distribute, and sell digital works in the market.

[0790] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0791] Step 1:

[0792] The user logs into the system via their terminal and enters prompt text to specify a theme and style. This prompt text is prepared as input data and sent to the next process. For example, the user might enter the prompt text "An illustration of a dragon with a fantasy theme." This information is then sent from the terminal to the server.

[0793] Step 2:

[0794] The server uses a generative AI model to generate digital artwork, taking the prompt text received from the user as input data. This AI model analyzes the prompt text using machine learning algorithms and generates artwork data based on the results. Natural language processing is performed as data processing and computation, and the output is a pictorial representation. Specifically, the AI ​​model generates a new image based on the input theme and outputs it as a digital file.

[0795] Step 3:

[0796] The generated digital works are stored on a server in a database that matches content creators with providers. Here, data processing is performed to recommend the most suitable providers based on the style and theme of the generated works. Specifically, the system uses each provider's work history and rating data to list relevant providers for the user.

[0797] Step 4:

[0798] The server performs the necessary format conversions and delivers information to register generated digital works on multiple sales platforms. It takes digital works and their metadata as input and uploads them to the specified platform as output. Specifically, it communicates with the marketplace API and uploads the works and their sales information.

[0799] Step 5:

[0800] On the dashboard, users can view the performance and revenue status of their works across sales platforms in real time. The information entered is sales data collected from each sales platform, which is displayed visually as graphs and tables. Specifically, the device periodically receives updated data from the server and visualizes it as part of the user interface.

[0801] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0802] This invention is a system that utilizes an emotion engine to recognize a user's emotions and reflect those emotions in the creation of digital works. The system includes a generation device, an emotion engine, a user interface, and a data storage unit.

[0803] When the system starts, the user logs in and specifies the theme and style of the digital artwork to be generated in the project settings screen. Additionally, data related to the user's emotions is collected by the emotion engine through multiple methods (e.g., text input, voice input, facial recognition).

[0804] Terminal: Analyzes emotional data received from the user in real time and sends it to the server. This emotional data is used to reflect the emotional intentions the user wants to convey in their artwork. For example, if the user expresses joy, the emotional engine will use corresponding colors and positive elements to compose the artwork.

[0805] Server: Analyzes the received emotional data and determines the specific elements of the digital artwork (color, style, tone, etc.) based on the generation device. The generation device receives instructions from the emotional engine and uses an AI model to generate artwork that matches the user's emotional state.

[0806] The generated artwork reflects emotional elements, resulting in a piece that better aligns with the user's intentions. After final adjustments to content and style, this artwork is stored in the data storage unit.

[0807] The saved digital works are used in a matching process that connects content creators and providers. In this process, the system recommends suitable creators based on the style and emotional elements of the generated works, and ultimately, sales begin by registering them on multiple sales platforms.

[0808] For example, if a user inputs a sad emotion via voice input, the emotion engine analyzes the tone of the voice and the choice of words, and generates a digital artwork that reflects that emotion. This artwork may use dark colors and subdued tones, demonstrating how emotional nuances can be translated into digital art.

[0809] In this way, by using emotional information, we can create a system that efficiently generates and supplies digital works tailored to individual needs to the market.

[0810] The following describes the processing flow.

[0811] Step 1:

[0812] User: On the login screen, enter your username and password to authenticate. This login information will grant the user access to use the system.

[0813] Step 2:

[0814] Terminal: The terminal collects the theme, style, and desired emotional state of the digital artwork specified by the user via an input screen, and sends this information to the server.

[0815] Step 3:

[0816] Server: Activates a generator based on the user's theme and style, and prepares the emotion engine to analyze the user's emotional information.

[0817] Step 4:

[0818] Device: Collects user facial expressions and voice data through the camera and microphone, and transmits them to the emotion engine in real time.

[0819] Step 5:

[0820] Server: Analyzes facial expressions and voice data received by the emotion engine to identify the user's current emotional state. Based on this analysis, it provides appropriate instructions to the generation device.

[0821] Step 6:

[0822] Server: Using the analysis results from the emotion engine, the generator determines the color scheme, tone, and style of the artwork and generates an initial version of the digital artwork that corresponds to the emotion.

[0823] Step 7:

[0824] Terminal: Provides users with a preview of the generated digital artwork, allowing them to review the content and provide feedback.

[0825] Step 8:

[0826] User: View the preview and, if necessary, request revisions to the generated work or re-enter emotions.

[0827] Step 9:

[0828] Server: After receiving user feedback and making necessary corrections, the server saves the final digital artwork to the data storage unit.

[0829] Step 10:

[0830] Server: Based on the generated works, it matches content creators with providers and recommends appropriate creators.

[0831] Step 11:

[0832] Server: Finally, the completed work is registered on multiple sales platforms, and the sales process begins.

[0833] In this way, by utilizing emotional information, it becomes possible to efficiently generate digital works that better meet individual needs.

[0834] (Example 2)

[0835] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0836] There is a need to provide a system that efficiently generates digital content that reflects user emotions, optimally matches content creators and providers, and quickly delivers it to the market. Furthermore, it is necessary to accurately recognize the emotions of individual users and reflect them in digital works to enhance personalized product value and provide a better user experience.

[0837] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0838] In this invention, the server includes emotion analysis means that recognize the user's emotions and reflect those emotions in the generation of digital works; terminal means that analyze emotion data in real time and transmit it to the server; and server means that analyze the received emotion data and instruct the generation device to determine specific elements. This makes it possible to generate and optimize digital content that reflects the user's emotions.

[0839] An "emotion analysis tool" is a device that recognizes a user's emotions and analyzes those emotions in order to utilize the data for generating digital works.

[0840] A "terminal device" is a device or system that analyzes emotional data based on user input and transmits it to a server.

[0841] A "server device" is a device that analyzes emotional data received from a terminal and issues instructions to the generation device to determine the specific elements of the work.

[0842] A "generation device" is a device or system that has the function of generating digital content based on user input data and sentiment analysis.

[0843] "Digital content" refers to works or products in digital format that are generated based on the user's emotions or input themes.

[0844] "Content creator" refers to a professional or user who creates digital content.

[0845] A "content provider" refers to an organization or individual that is responsible for providing generated digital content to the market or platform.

[0846] "Supplying to the market" refers to the process of making generated digital content accessible to the general public.

[0847] This invention realizes a system that recognizes user emotions and generates digital content that reflects them. This system provides users with a personalized experience by consistently performing the processes of emotion analysis, digital content generation, and market supply.

[0848] First, the user logs in as the entry point to the system and specifies the theme and style of the digital content on the project settings screen. The user then inputs their emotions using text, voice, or facial expressions. This provides initial data for emotion analysis.

[0849] The device analyzes emotional data acquired from the user in real time. Specific software used includes a natural language processing engine, speech analysis tools, and image processing algorithms. This analysis extracts detailed emotions such as "joy," "sadness," and "surprise." For example, if a user inputs an emotion like "happy" via voice, that voice data is converted to text by a speech recognition tool and classified as "joy" by the emotion analysis engine.

[0850] The server uses emotional data transmitted from the terminal to generate digital works using a generation device. Generation AI models are used for this process, specifically models such as "DALL-E" and "Midjourney." These models automatically generate intuitive visual content based on emotional, thematic, and style information. The server stores the generated content in a data storage unit and provides a preview to the user as needed.

[0851] For example, when a user requests artwork based on "sad feelings," a prompt is used to generate a "calm landscape painting using dark tones." This prompt is given to the generation AI model and means something like, "Generate digital art that reflects the user's sad feelings. Use dark colors and calm tones."

[0852] Through the above process, this system accurately captures user emotions and enables the efficient delivery of unique, custom content to the market.

[0853] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0854] Step 1:

[0855] The user logs into the system and accesses the project settings screen. Here, the user enters input specifying the theme and style of the digital content they want to generate. This setting information is then sent to the terminal as output.

[0856] Step 2:

[0857] The user inputs their emotions. This input is done through text, voice, or facial recognition. For example, if the user voice-inputs "I'm happy today," the device converts that voice into text. This converted data is then recorded as input data on the device.

[0858] Step 3:

[0859] The device analyzes emotional data received from the user in real time. By processing the input data with a natural language processing engine and speech analysis tools, it performs calculations to identify the type of emotion (joy, sadness, etc.). The output of this analysis is sent to the server as analyzed emotional data.

[0860] Step 4:

[0861] The server activates the generation device based on the analyzed emotion data received from the terminal. The server sends the input emotion data as a prompt to the AI ​​model (e.g., DALL-E or Midjourney) to generate digital content that matches the user's emotions. An example of such a prompt message would be, "Please generate a bright-toned digital art piece that reflects the user's happy feelings."

[0862] Step 5:

[0863] The generation device receives prompts from the server and generates digital content based on them. The generation device utilizes an AI model to output works with visual elements (color tone, shape, etc.) corresponding to specified emotions and themes. The generated digital content is stored in the data storage unit.

[0864] Step 6:

[0865] The server utilizes stored digital content to match content creators with providers. A program recommends suitable creators based on the style and emotional elements of the work. As a result, the digital content is registered on the sales platform and market distribution begins.

[0866] (Application Example 2)

[0867] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0868] In today's digital content market, there is a demand for personalized experiences based on users' emotions and individual needs. However, existing systems struggle to accurately recognize and analyze users' emotions and provide appropriate digital experiences based on them. A system is needed to solve this problem and to quickly and efficiently generate and deliver more personalized digital content.

[0869] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0870] In this invention, the server includes means for generating digital representations using a generation device, means for creating digital information that provides a personalized experience to the user using an emotion recognition engine that recognizes and analyzes the user's emotions, and means for recommending the most suitable creator to connect the user and the creator based on the generated digital representations. This makes it possible to provide digital representations based on the individual emotions and needs of the user.

[0871] A "generation device" refers to a device or system for automatically generating digital representations.

[0872] "Digital expression" refers to all works and content created using digital technology.

[0873] An "emotion recognition engine" refers to software or a system used to detect and analyze a user's emotions.

[0874] A "personalized experience" refers to providing an experience that is customized according to the individual user's emotions and preferences.

[0875] "Digital information" refers to any information that is expressed in digital format.

[0876] An "e-commerce platform" refers to a platform for trading digital products and services online.

[0877] An "automated intelligent model" refers to a model that uses machine learning and artificial intelligence technologies to automatically perform various tasks.

[0878] The "data storage unit" refers to the storage system or database used to save the generated information.

[0879] To implement this invention, the system comprises a smartphone, a server, and an emotion recognition engine. Users can input emotion data using the smartphone. This emotion data is collected using methods such as voice input or facial recognition. The terminal analyzes the collected emotion data in real time and transmits the information to the server.

[0880] The server generates digital representations using generative AI models based on the received emotion data. The emotion recognition engine analyzes the user's emotional state and creates digital information with a style and content appropriate to the corresponding emotion. The generated digital representations are further optimized to provide a personalized experience when they are delivered to the user. This process utilizes AI models running on Google Cloud Platform (GCP) (e.g., the GPT family), as well as TensorFlow and OpenCV for emotion recognition.

[0881] As a concrete example, a server can use an emotion recognition engine to generate and provide music playlists and visual content suitable for relaxation based on voice information entered by the user when they want to relax. In this way, it becomes easy to create digital experiences that match the user's emotions.

[0882] In this regard, the following prompts can be used with the generative AI model: "Generate music that promotes a relaxed mood," and "Suggest videos that evoke a travel-like feeling."

[0883] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0884] Step 1:

[0885] The user launches a smartphone application and inputs emotion data. Input is performed using voice input or facial recognition. The device collects audio and video data using the microphone and camera. This input data is temporarily stored on the smartphone.

[0886] Step 2:

[0887] The device processes collected audio and video data in real time to recognize emotions. This process uses TensorFlow to analyze audio data and OpenCV to analyze facial expressions in video data. The results of these analyses are output as the user's emotional state and sent to the server.

[0888] Step 3:

[0889] The server receives emotion data from the terminal and uses a generative AI model to generate digital representations. In this step, content that matches the user's emotions is generated based on pre-configured prompts. The server uses an AI model such as the GPT family to materialize the digital information and generates the result as a digital representation.

[0890] Step 4:

[0891] Based on the generated digital representations, the server optimizes and delivers them to the user. Specifically, it adjusts the generated content to match the user's preferences in order to create a personalized experience. When these digital representations are sent to the user's device, the user can receive a digital experience that responds to their emotions.

[0892] Step 5:

[0893] Users can experience the provided digital representations and provide feedback on their results. Additional emotional data can be provided through the application. This creates a consistent data feedback loop throughout the system, contributing to the optimization of future experiences.

[0894] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0895] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0896] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0897] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0898] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0899] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0900] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0901] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0902] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0903] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0904] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0905] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0906] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0907] 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.

[0908] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0909] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0910] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0911] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0912] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0913] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0914] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0915] The following is further disclosed regarding the embodiments described above.

[0916] (Claim 1)

[0917] A means of generating digital works using a generation device,

[0918] A means of comparing generated digital works between content creators and content providers and recommending the most suitable creator,

[0919] A means for registering the generated digital works on multiple sales platforms and managing their sales,

[0920] A system that includes this.

[0921] (Claim 2)

[0922] The system according to claim 1, wherein the generation device creates content based on a theme and style input by the user.

[0923] (Claim 3)

[0924] The system according to claim 1, wherein the generation device generates digital works using at least a plurality of artificial intelligence models and stores them in a data storage unit.

[0925] "Example 1"

[0926] (Claim 1)

[0927] A means for generating digital works according to a theme and style using a generation device based on user input,

[0928] A means for storing the generated digital works in a data storage unit and making them available for users to view,

[0929] A means of modifying and regenerating the generated digital works based on user feedback,

[0930] A means of comparing generated digital works between content creators and content providers and recommending the most suitable creator,

[0931] A means for registering the generated digital works on multiple sales platforms and managing their sales,

[0932] A system that includes this.

[0933] (Claim 2)

[0934] The system according to claim 1, wherein the generation device generates digital works using at least a plurality of artificial intelligence models.

[0935] (Claim 3)

[0936] The system according to claim 1, which allows users to check the sales status and revenue information of digital works generated through a dashboard in real time.

[0937] "Application Example 1"

[0938] (Claim 1)

[0939] A means of generating digital works using a generation device,

[0940] A means of comparing generated digital works between content creators and content providers and recommending the most suitable creator,

[0941] A means for registering the generated digital works on multiple sales platforms and managing their sales,

[0942] A method for automatically generating art content using artificial intelligence, based on the user's desired theme and style.

[0943] A method for directly uploading generated digital works to content distribution services,

[0944] A system that includes this.

[0945] (Claim 2)

[0946] The system according to claim 1, wherein the generation device creates content based on a theme and style input by the user, and provides the content to a content distribution service.

[0947] (Claim 3)

[0948] The system according to claim 1, wherein the generation device generates digital works using at least a plurality of artificial intelligence models and stores the generated data in a data storage unit based on prompt sentences specified by the user.

[0949] "Example 2 of combining an emotion engine"

[0950] (Claim 1)

[0951] A means of emotional analysis that recognizes the user's emotions and reflects those emotions in the creation of digital works,

[0952] A terminal device that analyzes emotional data in real time and sends it to a server,

[0953] A server means that analyzes the received emotional data and instructs the generation device to determine specific elements,

[0954] A means of generating digital content using a generation device,

[0955] A means of comparing generated digital content between content creators and content providers and recommending the most suitable creator,

[0956] A means for registering the generated digital content on multiple sales platforms and managing sales,

[0957] A system that includes this.

[0958] (Claim 2)

[0959] The system according to claim 1, wherein the generation device creates content based on themes and styles input by the user and reflects the user's emotional state.

[0960] (Claim 3)

[0961] The system according to claim 1, wherein the generation device generates digital content using at least a plurality of artificial intelligence models and stores it in a data storage unit.

[0962] "Application example 2 when combining with an emotional engine"

[0963] (Claim 1)

[0964] A means of generating digital representations using a generation device,

[0965] A means of creating digital information that provides a personalized experience to the user by using an emotion recognition engine that recognizes and analyzes the user's emotions from the generated digital representations,

[0966] A means of recommending the most suitable creator to connect users and creators with the generated digital expressions,

[0967] A means for registering the generated digital representations on multiple e-commerce platforms and managing transactions,

[0968] A system that includes this.

[0969] (Claim 2)

[0970] The system according to claim 1, wherein the generating device creates digital information based on the subject and format input by the user, and collects and analyzes emotional data in real time to provide optimal digital information.

[0971] (Claim 3)

[0972] The system according to claim 1, wherein the generation device generates digital representations using at least a plurality of automated intelligent models and stores them in a data storage unit. [Explanation of symbols]

[0973] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of generating digital works using a generation device, A means of comparing generated digital works between content creators and content providers and recommending the most suitable creator, A means for registering the generated digital works on multiple sales platforms and managing their sales, A system that includes this.

2. The system according to claim 1, wherein the generation device creates content based on a theme and style input by the user.

3. The system according to claim 1, wherein the generation device generates digital works using at least a plurality of artificial intelligence models and stores them in a data storage unit.

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