System

Abstract

A system is provided.SOLUTION: A system including input means for receiving an input by a user, transmission means for transmitting a prompt to a server, analysis means for analyzing the prompt in the server and transmitting the prompt to a generative model, generation means for generating a character image and lines by the generative model, preview means for providing the generated image and lines to the user as a preview, storage means for storing a finally generated stamp in an account of the user, provision means for providing the stored stamp as a download link or a use link, and management means for managing paid user authentication and fee deduction and compensation to a creator.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The stickers provided by existing messaging apps lack the flexibility to accurately express users' emotions and messages. They often struggle to provide the intuitive and quick expression desired by younger users. Existing sticker sets only include limited expressions and lines, making it difficult for users to find stickers that suit specific situations or emotions. Furthermore, the lack of a mechanism for providing customized stickers leads to low user satisfaction. Furthermore, there are challenges associated with the high cost and time burden on creators to meet these needs. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means: An input means for a user to input a prompt and a transmission means for transmitting the prompt to a server are provided. The server side is provided with an analysis means for analyzing the received prompt and passing it to a generative model. The generative model has a generation means for generating a character image and dialogue based on the prompt. The generated image and dialogue are provided to the user as a preview, and a preview means is included for the user to check. The system has a storage means for saving the final generated stamps in the user's account, and a provision means for providing the saved stamps as a download link or a usage link. The system also includes a management means for managing paid user authentication, fee deductions, and creator compensation. This makes it easy for users to create original stamps with the expressions they want, enabling fast and intuitive communication while also ensuring appropriate compensation is returned to creators.

[0006] "User" means an end user who utilizes the System to enter prompts and generate and use Stamps.

[0007] A "prompt" refers to a text instruction entered by the user to specify a character's facial expression, lines, etc.

[0008] "Server" refers to the computer system responsible for receiving prompts sent by users, parsing them, and passing them to the Generative Model.

[0009] "Generative model" refers to an algorithm or machine learning model that automatically generates character expressions and dialogue based on prompts.

[0010] "Input means" refers to a device or software that provides an interface for a user to enter a prompt.

[0011] "Transmission means" refers to a device or software with a communication function for transmitting the input prompt to the server.

[0012] "Analysis means" refers to software that has the function of analyzing received prompts and converting them into data to be passed to the generative model.

[0013] "Generation means" refers to software or algorithms capable of generating character images and dialogue based on analyzed prompts.

[0014] "Preview means" refers to a device or software that displays the generated character image and dialogue to the user and provides an interface for checking and correcting the image and dialogue.

[0015] "Storage Measure" means a device or software that stores the User's finalized Final Generated Stamp in the User's Account.

[0016] "Delivery Means" refers to a device or software for providing stored stamps as download links or usage links.

[0017] "Management means" refers to software or systems that have the function of managing the authentication of paying users, the debiting of fees, and the compensation of creators. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] This invention is a system that uses a generation AI to customize the character's facial expressions and lines based on prompts entered by the user, and generates original stamps. Below, we will explain the program processing of this system in natural language.

[0040] Overall system overview

[0041] The system works in collaboration between the user, the device, and the server. The user inputs a prompt from the device, the server analyzes the prompt, and creates a customized stamp using a generative AI.

[0042] Program processing

[0043] First, the user accesses the custom stamp creation screen within the LINE app, where they input a prompt such as "a character smiling and saying hello." The input prompt is then sent from the device to the server.

[0044] The device is responsible for sending the input prompt to the server as an API request, which transmits the prompt content to the server.

[0045] The server receives the prompt sent from the device and starts a process to analyze the content of the prompt. The analysis means converts the content of the prompt into a format that the generation AI can understand. In this analysis, elements of the character's facial expressions and dialogue are extracted, and appropriate generation instructions are passed to the generation AI.

[0046] The AI ​​then generates the character's facial expressions and lines based on the analyzed instructions. For example, if a prompt such as "Smile and say hello" is entered, the AI ​​adds a speech bubble with the words "Hello" to the smiling character image. The generated results are then sent back to the server.

[0047] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[0048] The device displays a preview link, allowing the user to check the generated character image and dialogue. If the user wishes to make corrections, they can enter a new prompt and submit it again. If no corrections are required, the user presses the "Confirm" button.

[0049] The server will save the final stamp generated by the user in the user's account. After this process is complete, a download link or usage link will be generated and sent to the device.

[0050] The device will provide the user with a download link, allowing them to download the stickers or use them within the LINE app, allowing users to easily create and use original stickers freely.

[0051] The server also authenticates paying users and deducts the associated fees from their accounts, a portion of which is kept as compensation for creators and later deposited into their accounts.

[0052] Specific examples

[0053] For example, consider the case where a prompt is entered as "I want a sleeping character to say goodnight." The user enters the prompt and the device sends it to the server. The server analyzes the prompt and extracts elements such as "sleeping character" and "goodnight." Based on the analysis results, the generation AI generates a sleeping character and a "goodnight" speech bubble, which are sent back to the server. The server temporarily saves this and provides the user with a preview link. After the user confirms, they press the confirm button, and the final generated stamp is saved in the user's account and a download link is provided. The user can click this link to download and use the stamp.

[0054] In this way, the system generates original stickers based on user prompts, supporting quick and intuitive communication, and also supports creators' activities by providing rewards to them.

[0055] The processing flow will be explained below.

[0056] Step 1:

[0057] Users access the custom stamp creation screen within the LINE app, enter a prompt such as "a character smiling and saying hello," and press the send button.

[0058] Step 2:

[0059] The device creates an API request from the input prompt and sends the request to the server.

[0060] Step 3:

[0061] The server receives the prompt sent from the terminal and starts a process for analyzing the content of the prompt, which is then converted by the analyzing means into a format that can be understood by the generative model.

[0062] Step 4:

[0063] The server passes the parsed prompts to the generative model, which triggers the generation process, generating the character's facial expressions and dialogue based on the parsed instructions.

[0064] Step 5:

[0065] The AI ​​generates a character image based on the prompt and adds the specified dialogue. For example, in response to the prompt "Smile and say hello," it adds a speech bubble saying "Hello" to a smiling character image.

[0066] Step 6:

[0067] The server temporarily stores the generated character image and dialogue, and generates a preview link that is sent to the user's device.

[0068] Step 7:

[0069] The device uses the preview link received from the server to display a preview screen of the generated stamp to the user, who then checks the preview.

[0070] Step 8:

[0071] The user can check the preview and, if necessary, enter a new prompt to request corrections. If no corrections are required, the user presses the "Confirm" button.

[0072] Step 9:

[0073] After the user presses the confirm button, the server saves the final stamp to the user's account. Once the saving process is complete, a download link or usage link will be generated.

[0074] Step 10:

[0075] The device will display the download link received from the server, allowing the user to download the stamp or use it within the LINE app.

[0076] Step 11:

[0077] The server authenticates the paying user and deducts the relevant fee from the user's account, and also manages a portion of the fee as a reward for the creator and processes it to be transferred to the creator's account.

[0078] Through these concrete steps, users can easily create and use original stamps, and creators are also rewarded appropriately.

[0079] Example 1

[0080] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0081] Until now, there have been limited systems that allow users to easily create and share their own digital content. In particular, the process for users to create characters with specific facial expressions and lines is complicated and often requires technical knowledge. Furthermore, for paid services, managing usage fees and paying creators is cumbersome. A system that solves these problems is needed.

[0082] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0083] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting a prompt to the information processing device, an analysis means for analyzing the prompt in the information processing device and passing it to the generation engine, a generation means for generating image data and text data using the generation engine, a preview means for providing the generated image data and text data as a preview to the user, a storage means for saving the final generated digital content in the user's account, a provision means for providing the saved digital content as a download link or a usage link, and a management means for managing paid user authentication, fee deductions, and creator compensation. This allows users to easily input prompt text to generate characters with specific facial expressions and lines, and easily obtain and use the final digital content. It also allows for efficient billing management for paid services and payment of compensation to creators.

[0084] An "input means" is a device or method by which a user inputs data or commands into a system.

[0085] "Transmission means" refers to a device or method for transmitting input data to another device or system.

[0086] An "analysis means" is a device or method for analyzing input data, extracting meaning, and converting it into a format suitable for further processing.

[0087] A "generator" is a device or method for generating new data or content based on the analyzed data.

[0088] The "preview means" is a device or method for temporarily displaying generated data or content so that the user can check it.

[0089] "Storage means" refers to a device or method for permanently storing generated data or content.

[0090] "Providing means" refers to a device or method for providing stored data or content to a user.

[0091] "Management means" refers to a device or method for authenticating paying users, debiting fees, and managing creator rewards.

[0092] A "generation engine" is software or hardware that generates new data or content from input data.

[0093] An "information processing device" is a computer or network facility for inputting, outputting, analyzing, storing, and providing data.

[0094] "Digital content" means information such as text, images, audio, and video that is stored and provided in electronic form.

[0095] A "prompt" is an instruction or question that a user enters into a system.

[0096] "User" means any person or entity that uses the System to generate, view, or store digital content.

[0097] This invention relates to a system that generates original digital content by customizing character expressions and dialogue using a generative AI model based on prompts entered by the user. The program processing of this system is explained below in natural language. In this system, the user, terminal, and server work together.

[0098] First, a user accesses a custom stamp creation screen and inputs a prompt to generate a character with a specific facial expression and dialogue. Specific examples include prompts such as "a character smiling and saying hello" or "a sleeping character saying goodnight." This input is performed via a terminal.

[0099] The device then sends the user-entered prompt as an API request to the server. This request data includes the user ID and the entered prompt text. The device is responsible for converting the request into the appropriate data format so that it can be processed correctly.

[0100] The server receives the prompt sent from the device and begins the analysis process. The server implements natural language processing (NLP) technology to analyze the content of the prompt and extract important elements (e.g., the character's facial expressions and lines). The information obtained from this analysis step is converted into a format that the generative AI model can understand.

[0101] The generative AI model generates the character's facial expressions and lines based on the analysis results passed from the server. Specific generative AI models used are models capable of understanding natural language and generating images (e.g., GPT-3 and DALL-E). If the prompt is "a character smiling and saying hello," the generative AI model generates an image of a smiling character and a speech bubble that says "hello."

[0102] The server receives the generated character image and lines and temporarily stores them. Next, the server generates a link to provide the user with a preview of the generated results. This link is a URL to a page that displays the generated character image.

[0103] The device presents a preview link to the user, allowing the user to check the generated character image. The user can check the generated result and input correction instructions as necessary, or press the OK button to save the generated result as final digital content.

[0104] If the user presses the "Confirm" button, the server saves the generated result to the user's account. After saving, the server generates a download link or usage link and sends it to the device.

[0105] Finally, the device provides the user with a download link, allowing them to download the digital content or use it within the LINE app. For paid users, the server also performs authentication and deducts the fee. A portion of this fee is managed as compensation to the creator and later transferred to the creator's account.

[0106] In this way, the system generates original digital content based on user prompts, providing it quickly and intuitively, and also supports creative activities by including compensation management for creators.

[0107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0108] Step 1:

[0109] The user accesses the custom stamp creation screen within the LINE app and enters a prompt text. This input is in the form of "a character smiling and saying hello." The user's input is sent to the device as text data. Input: Prompt text. Output: Prompt text sent to the device.

[0110] Step 2:

[0111] The terminal receives the prompt text entered by the user and sends it to the server as an API request. The terminal converts the prompt text into an appropriate data format (for example, JSON format) and sends it to the server using an HTTP request. Input: Prompt text received from the user. Output: Prompt text sent to the server.

[0112] Step 3:

[0113] The server receives the prompt sent from the device and begins the analysis process. The server uses natural language processing (NLP) technology to analyze the content of the prompt and extract important elements (facial expressions, lines). Input: Prompt received from the device. Output: Analyzed prompt information (facial expressions, lines, etc.).

[0114] Step 4:

[0115] The server creates generation instructions to be passed to the generative AI model based on the analysis results. The generation instructions are sent to the generative AI model as structured data (e.g., JSON). Input: Parsed prompt information. Output: Generation instructions to the generative AI model.

[0116] Step 5:

[0117] The generative AI model generates character expressions and lines based on the generation instructions received from the server. The generative AI model uses a generation engine such as GPT-3 or DALL-E. The generated result is a combination of image data and text data. Input: Generation instructions received from the server. Output: Generated character image and lines.

[0118] Step 6:

[0119] The generative AI model returns the generated character image and dialogue to the server. The server receives the data and temporarily stores it. Input: Character image and dialogue received from the generative AI model. Output: Temporarily stored generated data.

[0120] Step 7:

[0121] The server generates a preview link to allow the user to check the generated results. This link is provided to the user and contains the URL of a page that previews the generated character image. Input: Temporarily saved generated data. Output: Preview link provided to the user.

[0122] Step 8:

[0123] The terminal displays a preview link to the user and provides an interface for checking the generated results. The user checks the generated character image and lines, and if necessary, inputs correction instructions or presses the confirm button. Input: Preview link. Output: User confirmation and correction instructions or confirmation operation.

[0124] Step 9:

[0125] If the user presses the "Confirm" button, the server will save the final generated digital content to the user's account. At the same time, the server will generate a download link or usage link and send it to the device. Input: User's confirmation operation. Output: Saved digital content and generated download link.

[0126] Step 10:

[0127] The terminal provides the download link to the user, allowing the user to download or use the digital content. Input: Download link received from the server. Output: Download link provided to the user.

[0128] Step 11:

[0129] The server authenticates paid users and processes fee withdrawals. A portion of the fee is managed as compensation to the creator. Input: User information and fee information. Output: Fee withdrawal and compensation management for the creator.

[0130] This system allows users to easily generate characters with specific facial expressions and lines by simply entering a prompt, and then acquire and use them as digital content. It also efficiently manages billing for paid services and pays creators.

[0131] (Application example 1)

[0132] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0133] When users post product reviews on online shopping sites, there is a lack of effective ways to convey emotions and product appeal that are difficult to express through text-only reviews. This makes it difficult for other users to visually understand the review content, which can discourage them from purchasing the product. Another issue is that the system for rewarding creators is insufficient, making it difficult to distribute rewards fairly.

[0134] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0135] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting a prompt to the server, an analysis means in the server for analyzing the prompt and passing it to a generative model, a generation means for generating character images and dialogue using the generative model, a generation means for generating original stamps based on reviews on an online shopping site, a preview means for providing users with previews of the generated images and dialogue, a storage means for saving the final generated stamps in the user's account, a provision means for providing the saved stamps as download links or usage links, and a management means for managing paid user authentication, fee deductions, and creator compensation. This enables users to communicate product reviews in a visually appealing way, makes it easier for other users to intuitively understand the review content, and enables fair compensation distribution to creators.

[0136] An "input means" is a device or function that provides an interface for a user to input a prompt.

[0137] The "transmission means" is a device or function that transmits the prompt entered by the user to the server via the network.

[0138] The "analysis means" is a device or function that analyzes the prompts received at the server and converts them into a format that can be understood by the generative model.

[0139] "Generator" means a device or function that uses an AI model to generate character images and dialogue based on the instructions of the analyzed prompt.

[0140] The "preview means" is a device or function that provides an interface that allows the user to check the generated character image and lines.

[0141] "Storage means" refers to a device or function that stores the final generated stamp confirmed by the user in the user's account.

[0142] "Providing means" refers to a device or function that provides saved stamps as links that users can download or use.

[0143] "Management means" refers to a device or function that manages the authentication of paid users, the deduction of fees, and compensation to creators.

[0144] An "online shopping site" is an e-commerce platform that allows users to purchase products online.

[0145] "Review content" refers to information expressed in text or stamps about the user's impressions and evaluations of products purchased on an online shopping site.

[0146] "Custom Stamps" are visual graphic elements specially created by a generative AI model based on user prompts.

[0147] A "creator" is a person or entity that provides the source materials and instructions for content created by a generative AI model.

[0148] This invention relates to a system that uses AI to generate original stamps based on prompts entered by users. Specifically, it generates original stamps based on reviews on online shopping sites and provides a means for users to attach them to reviews and post them.

[0149] System configuration

[0150] This system works in cooperation with three parties: the user, the device (such as a smartphone or tablet), and the server. The main components of the system are as follows:

[0151] 1. Input Method

[0152] The user enters a prompt into the terminal. An example prompt is a smiling character saying, "This product is so useful, I'll never want to let it go!"

[0153] 2. Transmission Method

[0154] The device sends the entered prompt as an API request to the server, where the device communicates with the server over a network connection.

[0155] 3. Analysis method

[0156] The server receives the prompt sent from the device and analyzes it. The analysis method converts the content of the prompt into a format that the generation AI can understand. Specifically, elements such as "smile" and "This product is so convenient, I can't live without it!" are extracted from the prompt text.

[0157] 4. Generation means

[0158] Based on the analysis results, the server issues instructions to a generative AI model to generate a character image and dialogue. This generation is performed using a cloud-based generative AI model (such as OpenAI GPT-3). The generated results are obtained as a character image; for example, a character may be generated that smiles and says, "This product is so convenient, I can't live without it!"

[0159] 5. Preview Methods

[0160] To provide the user with a preview of the generated character image and lines, the server generates a preview link and sends it to the device. The user can open the preview link on the device and check the generated stamp.

[0161] 6. Preservation means

[0162] Once the user approves the generated stamp, the server stores it in the user's account, where it can be used to attach to reviews.

[0163] 7. Means of provision

[0164] The server generates a download link or usage link for the saved stamp and sends it to the device, allowing the user to actually use the stamp when posting a review.

[0165] 8. Control measures

[0166] The server also has the functionality to authenticate paying users, debit fees, and manage creator compensation. Specifically, it processes charges when users use the stamp generation service, and returns a portion of the charges to creators as compensation.

[0167] Specific examples

[0168] For example, when a user writes a product review on an online shopping site, they input a prompt such as, "A smiling character saying, 'This product is so convenient, I can't live without it!'" The device sends this prompt to the server, which analyzes it and gives instructions to the generation AI. The generation AI model generates an image of a smiling character and the words, "This product is so convenient, I can't live without it!", which are provided to the user as a preview link. Once the user confirms and confirms, the final generated stamp is saved to the user's account and a download link is provided. In this way, users can post visually appealing product reviews.

[0169] This invention utilizes a generative AI model based on prompt sentences to visually enrich product reviews on online shopping sites, not only increasing users' desire to purchase but also ensuring fair distribution of rewards to creators.

[0170] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0171] Step 1:

[0172] The user inputs a prompt sentence. For example, the user inputs a prompt such as "This product is so convenient, I can't live without it!" The input prompt is acquired through the input means of the terminal.

[0173] input:

[0174] The prompt text entered by the user.

[0175] output:

[0176] The prompt text captured on the terminal.

[0177] Specific operation:

[0178] The user types the prompt into the text input field on their smartphone or tablet and presses the submit button.

[0179] Step 2:

[0180] The terminal transmits the acquired prompt text to the server as an API request. The prompt text is transmitted to the server via the network using a transmission means.

[0181] input:

[0182] The prompt text captured on the terminal.

[0183] output:

[0184] The prompt text sent to the server.

[0185] Specific operation:

[0186] The terminal converts the prompt text into an API request format and sends it to the server via an HTTP request.

[0187] Step 3:

[0188] The server analyzes the received prompt text. Using the analysis method, the character's facial expression and lines are extracted from the prompt text. For example, elements such as "smile" and "This product is so convenient, I can't live without it!" are extracted.

[0189] input:

[0190] The prompt text sent to the server.

[0191] output:

[0192] Extracted facial expressions and dialogue elements.

[0193] Specific operation:

[0194] The server runs natural language processing algorithms to parse the prompt and extract key keywords and phrases.

[0195] Step 4:

[0196] The server passes the analysis results to a generative AI model, which generates a character image and dialogue. Using a generation method, the generative AI model creates a character image based on this information. For example, an image may be generated that includes a smiling character and the text, "This product is so useful, I can't live without it!"

[0197] input:

[0198] Extracted facial expressions and dialogue elements.

[0199] output:

[0200] Generated character images and lines.

[0201] Specific operation:

[0202] The server converts the analyzed data into the input format for the generative AI model, sends a request to the generative AI model, and receives the generated image data.

[0203] Step 5:

[0204] The server provides the generated character image and lines to the terminal as a preview link, and generates a preview link using a preview means so that the user can check the image, and sends the preview link to the terminal.

[0205] input:

[0206] Generated character images and lines.

[0207] output:

[0208] The preview link sent to your device.

[0209] Specific operation:

[0210] The server temporarily stores the generated image in cloud storage, generates a link to it, and sends the link to the terminal as an HTTP response.

[0211] Step 6:

[0212] The user checks the preview link and approves the stamp. After opening the preview link on their device and checking the generated stamp, they press the confirm button to approve it.

[0213] input:

[0214] The preview link sent to your device.

[0215] output:

[0216] User approval operations.

[0217] Specific operation:

[0218] Users can click on the preview link on their device and use the interface to review and confirm the generated stamp in their browser or app.

[0219] Step 7:

[0220] The server stores the final generated stamp in the user's account. A storage means is used to store the generated stamp in the user's database.

[0221] input:

[0222] User approval operations.

[0223] output:

[0224] Stickers saved in the user's account.

[0225] Specific operation:

[0226] The server queries the database associated with the user's account to store the generated stamp.

[0227] Step 8:

[0228] The server provides a download link or a usage link for the stored stamp. The server generates a download link using the providing means and transmits it to the terminal.

[0229] input:

[0230] Stickers saved in the user's account.

[0231] output:

[0232] The download or usage link sent to your device.

[0233] Specific operation:

[0234] The server generates a downloadable URL for the stamp file for the client and sends the URL information to the device.

[0235] Step 9:

[0236] The server authenticates paid users, deducts fees, and manages rewards to creators. Using a management means, the server performs the authentication process for paid users, deducts usage fees, and transfers a portion of the fees to the creator's account as rewards.

[0237] input:

[0238] Paid users' account information and usage information of generated stamps.

[0239] output:

[0240] Completing billing transactions and transferring rewards to creators.

[0241] Specific operation:

[0242] The server sends the paying user's payment information to the payment provider, deducts the usage fee, then calculates the creator's remuneration and transfers the remuneration to the creator's account.

[0243] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0244] This invention combines a system that uses generation AI to customize the character's facial expressions and lines based on prompts entered by the user, generating original stamps, and an emotion engine that recognizes the user's emotions. Below, we will explain the program processing of this system in natural language.

[0245] Overall system overview

[0246] This system works in cooperation with four parties: the user, the device, the server, and the emotion engine. The user inputs a prompt from the device, and the emotion engine recognizes the user's emotion. The server analyzes the prompt and creates a customized stamp using a generation AI.

[0247] Program processing

[0248] First, the user accesses the custom stamp creation screen within the LINE app, enters a prompt such as "a character saying hello with a smile," and presses the send button. At this time, the text entered by the user, as well as the voice and facial expressions used, are analyzed by the emotion engine.

[0249] The device creates an API request based on the prompt and emotional information entered by the user and sends the request to the server.

[0250] The server receives the prompt and emotion information sent from the terminal and starts processing to analyze the content of the prompt. The analysis means converts the content of the prompt into a format that the generative model can understand. Furthermore, the emotion data analyzed by the emotion engine provides supplementary information to the prompt, generating a stamp that is more suited to the user's emotion.

[0251] The emotion engine recognizes the user's emotions from their facial expressions and voice, and complements or modifies prompts based on that emotional data. For example, if the user is smiling, a warmer tone might be added to a prompt like "Hello."

[0252] The generative AI generates character expressions and lines based on the analyzed instructions and emotional data. For example, if the prompt is "Smile and say hello," and the emotion engine determines that the user is very happy, the generated character's smile will be brighter and the "hello" line will have a more joyful nuance.

[0253] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[0254] The device will use the preview link to display a preview screen of the generated stamp to the user. The user can check this preview and, if necessary, enter new prompts or emotion data to request corrections. If no corrections are required, the user presses the "Confirm" button.

[0255] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated.

[0256] The device will display a download link, allowing users to download the stamp or use it within the LINE app.

[0257] The server also authenticates paying users and deducts the associated fees from their accounts, a portion of which is managed as a reward for the creators and later deposited into their accounts.

[0258] Specific examples

[0259] For example, consider the prompt "I want a sleeping character to say goodnight." The user enters the prompt, and the device sends it to the server. The server analyzes the prompt and emotion data, extracting elements such as "sleeping character" and "goodnight." The emotion engine recognizes the user's calm emotion, and generates a more relaxed facial expression and the phrase "goodnight" based on that.

[0260] The AI ​​generates a character and dialogue based on the specified content and sends it back to the server. The server temporarily saves it and provides the user with a preview link. After the user confirms it, they press the confirm button, and the final generated stamp is saved to their account and a download link is provided. Users can click this link to download and use the stamp.

[0261] In this way, the system generates original stamps based on user prompts and emotional data, supporting quick and intuitive communication, and also supports creators' activities by providing rewards to them.

[0262] The processing flow will be explained below.

[0263] Step 1:

[0264] Users access the custom stamp creation screen within the LINE app, input a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are also recorded by the emotion engine.

[0265] Step 2:

[0266] The device sends the input prompt and emotion data to the server as an API request.

[0267] Step 3:

[0268] The server receives the prompt and emotion data sent from the terminal and starts a process to analyze the prompt content and emotion data. The analysis means converts the prompt content into a format that can be understood by the generative model.

[0269] Step 4:

[0270] The emotion engine recognizes the user's emotions from their facial expressions and voice data, and provides the analysis results to the server. For example, when the user is smiling, emotion data of "joy" is generated.

[0271] Step 5:

[0272] The server complements or modifies the prompt using the emotion data provided by the emotion engine and passes it to the generative model, adding elements based on the user's emotions.

[0273] Step 6:

[0274] The AI ​​then generates the character's facial expressions and lines based on the analyzed prompt and emotion data. For example, if the emotion data for "hello with a smile" and "joy" are given, the generated character's smile will be brighter and the "hello" line will have a more joyful nuance.

[0275] Step 7:

[0276] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[0277] Step 8:

[0278] The device will use the preview link to display a preview screen of the generated stamp to the user. The user can check this preview and, if necessary, enter new prompts or emotion data to request corrections. If no corrections are required, the user presses the "Confirm" button.

[0279] Step 9:

[0280] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link is generated and sent to the device.

[0281] Step 10:

[0282] The device will display a download link, allowing users to download the stamp or use it within the LINE app.

[0283] Step 11:

[0284] The server authenticates the paying user and deducts the associated fees from the user's account, and a portion of the fees is managed as a reward for the creator and deposited into the creator's account.

[0285] In this way, a system is realized that generates original stamps that are optimal and intuitive for each user based on the user's prompts and emotional data, and also supports creators' activities by providing appropriate rewards to creators.

[0286] Example 2

[0287] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0288] Previous systems for generating customized stickers were able to generate character expressions and lines based on user prompts, but they were unable to customize characters based on the user's emotions. This made it difficult to generate stickers that fully reflected the user's intentions. Furthermore, the generation process was complex, potentially resulting in a poor user experience.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0290] In this invention, the server includes an analysis means for analyzing the prompt and emotion data and inputting them into a generative model, a preview means for providing the user with a preview of the generated image and dialogue, and a storage means for saving the final generated stickers in the user's account, thereby enabling quick and intuitive generation of customized stickers that take the user's emotions into account.

[0291] "User" refers to an individual or organization that uses the System to generate customized stamps.

[0292] An "input means" is an interface through which a user inputs prompts and other data into the system.

[0293] The "transmission means" is a function for transmitting a prompt input via the input means to the server.

[0294] The "analysis means" is a function for analyzing prompts and emotion data in the server and inputting them into the generative model.

[0295] A "generative model" is an AI algorithm that generates character images and dialogue based on input data.

[0296] "Generation means" is a function for generating character images and lines using a generative model.

[0297] The "preview means" is a function for providing the user with a preview of the generated character image and lines.

[0298] "Storage means" is a function for saving the final generated stamp in the user's account.

[0299] The "means of provision" is a function for providing saved stamps to users as download links or usage links.

[0300] The "management means" is a function for managing authentication of paying users, withdrawal of fees, and remuneration to content creators.

[0301] "Emotional data" refers to emotional information extracted from a user's facial expressions and voice.

[0302] This invention is a system that uses a generative AI model to customize character expressions and lines based on prompts entered by the user, generating original stamps. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it achieves even more precise customization.

[0303] Hardware and software used

[0304] 1. The user accesses the LINE application using a device such as a smartphone or tablet.

[0305] 2. The device makes an API request to communicate with the server via its internet connection.

[0306] 3. The server utilizes high-performance cloud servers to run generative AI models (e.g., OpenAI's GPT-3) and emotion engines (e.g., Affectiva Emotion AI).

[0307] 4. The emotion engine includes hardware and software that uses the device's camera and microphone to analyze the user's facial expressions and voice.

[0308] Data processing and calculation flow

[0309] Users access the "Customized Stamp Creation Screen" within the LINE app, enter a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are simultaneously analyzed by the emotion engine.

[0310] The device sends the prompt and emotion data entered by the user to the server as an API request, which processes data acquired from the camera and microphone and generates appropriate emotion data.

[0311] The server analyzes the data received from the device and converts the prompts into a format that the generative AI model can understand. It also analyzes the emotional data and adds additional information to the prompts. This analysis method provides more detailed instructions to the generative model.

[0312] The AI ​​then generates character expressions and lines based on the analyzed instructions and emotional data. For example, in response to the prompt "A character saying hello with a smile," the generated character's smile will become brighter and the lines will have a more joyful nuance.

[0313] The server receives the generated character data, temporarily stores it, and then provides the user with a preview link and sends an interface to the device for viewing and modifying the generated stamp.

[0314] The device will use the preview link to display a preview of the generated stamp to the user. The user can check the preview and, if necessary, enter new prompts and emotion data and submit it again. If no corrections are required, the user can press the "Confirm" button.

[0315] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated.

[0316] The device will display the generated download link to the user, allowing them to download the stamp or use it within the LINE app.

[0317] Specific examples

[0318] For example, consider the prompt "I want a sleeping character to say goodnight." The user enters the prompt, and the device sends it to the server. The server analyzes the prompt and emotion data, extracting elements such as "sleeping character" and "goodnight." The emotion engine recognizes the user's calm emotion, and generates a more relaxed facial expression and the phrase "goodnight" based on that.

[0319] Specific prompt examples:

[0320] I want my sleeping character to say goodnight

[0321] In this way, the system not only quickly and intuitively generates original stamps based on user prompts and emotional data, but also customizes them to reflect the user's emotions.

[0322] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0323] Step 1:

[0324] Users access the LINE application using a device such as a smartphone or tablet. They access the "Customized Stamp Creation Screen," enter a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are also analyzed by the emotion engine.

[0325] Input: User prompts, facial expressions, and voice data

[0326] Output: Prompt and emotion data sent to the device

[0327] Specific behavior:

[0328] A user enters text using the smartphone keyboard.

[0329] Data collection from cameras and microphones.

[0330] Step 2:

[0331] The device converts the user's input prompts and facial and voice data acquired from the camera and microphone into API requests and sends them to the server, where they are processed to generate appropriate emotion data.

[0332] Input: User prompts, facial expressions, and voice data

[0333] Output: API request sent to the server

[0334] Specific behavior:

[0335] Analyzes data from the camera and microphone to generate emotion labels.

[0336] Converts data into packets and sends them.

[0337] Step 3:

[0338] The server receives prompts and emotional data sent from the device, analyzes the content of the prompts, and converts them into a format that the generative AI model can understand. At the same time, it analyzes the emotional data and generates complementary information according to the prompts.

[0339] Input: Prompt and emotion data received from the device

[0340] Output: Parsed data to a generative AI model

[0341] Specific behavior:

[0342] Prompt text analysis (tokenization and context analysis)

[0343] Emotion data analysis (emotion labeling)

[0344] Step 4:

[0345] The server sends the analyzed data to the generation AI, which converts the data into a format that is easy for the generation AI to understand.

[0346] Input: Parsed prompt and sentiment data

[0347] Output: Formatted data sent to the generative AI

[0348] Specific behavior:

[0349] Data format conversion

[0350] Creating and sending an API request to the generation AI

[0351] Step 5:

[0352] The generative AI generates facial expressions and lines for the character based on the data it receives. For example, if the emotion engine determines that the user is happy in addition to the prompt "Smile and say hello," the character will have a brighter smile.

[0353] Input: Formatted data sent from the server

[0354] Output: Generated character and dialogue data

[0355] Specific behavior:

[0356] Running inference on a model

[0357] Formatting the generated results

[0358] Step 6:

[0359] The server temporarily stores the character data received from the generated AI, generates a preview link for the user to view, and sends it to the device.

[0360] Input: Character data received from the generation AI

[0361] Output: Preview link for user confirmation

[0362] Specific behavior:

[0363] Temporarily save to database

[0364] Generate and send a preview link

[0365] Step 7:

[0366] The device receives the preview link and displays a preview screen of the generated stamp to the user, which the user can confirm.

[0367] Input: Preview link received from the server

[0368] Output: The preview screen that the user sees

[0369] Specific behavior:

[0370] Preview screen drawing

[0371] Screen transition by clicking a link

[0372] Step 8:

[0373] The user checks the preview and, if satisfied with the stamp, presses the "Confirm" button. If corrections are needed, they enter new prompt and emotion data and submit again.

[0374] Input: User confirmation and correction instructions

[0375] Output: Confirm or correct instruction

[0376] Specific behavior:

[0377] Click the Confirm button

[0378] Re-enter correction prompt

[0379] Step 9:

[0380] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated and sent to the device.

[0381] Input: User confirmation instructions

[0382] Output: Download link or usage link

[0383] Specific behavior:

[0384] Final save to database

[0385] Link Generation and Notifications

[0386] Step 10:

[0387] The device will display the download link received from the server to the user, allowing the user to download the stamp or use it within the LINE app.

[0388] Input: Download link received from the server

[0389] output: the download link that is displayed to the user

[0390] Specific behavior:

[0391] View download links

[0392] Click on the link to download

[0393] (Application example 2)

[0394] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0395] There is a demand for improved customer support and user experience in virtual stores, but conventional systems have difficulty recognizing user emotions in real time and responding appropriately.In addition, the content generated is not optimized based on user emotions, which leads to a decrease in user satisfaction.

[0396] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0397] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting prompts to the server, an analysis means in the server for analyzing the prompts and passing them to a generative model, a generation means for generating character images and dialogue using the generative model, a preview means for providing the generated images and dialogue as previews to the user, an emotion recognition means for recognizing the user's emotion and using the emotion data to complement or modify the prompt, an optimization means for optimizing the generated character images and dialogue to match the user's emotion, a storage means for saving the final generated stamps in the user's account, a provision means for providing the saved stamps as a download link or a usage link, and a management means for managing paid user authentication, fee deductions, and creator compensation. This makes it possible to provide optimal customer support tailored to the user's emotions, which is expected to improve the user experience and increase satisfaction.

[0398] "User" refers to an individual or organization that uses this system.

[0399] "Input means" refers to a means that provides an interface for a user to input a prompt.

[0400] "Transmission means" refers to a means for transmitting the input prompt to the server.

[0401] "Analysis means" refers to means for analyzing prompts on the server and converting them into a format that conforms to the generative model.

[0402] The "generation means" refers to a means for generating a character image and lines based on the analyzed prompt.

[0403] "Preview means" refers to a means for temporarily displaying the generated character image and dialogue to the user.

[0404] "Emotion recognition means" refers to a means of analyzing the user's emotions and reflecting that data in prompts.

[0405] "Optimization means" refers to a means for adjusting the generated character images and lines based on emotional data.

[0406] "Storage Means" means the means by which the final generated stamps are stored in the User's account.

[0407] "Providing means" refers to the means of providing saved stamps as a download link or a usage link.

[0408] "Management means" refers to the means for authenticating paying users, deducting fees, and managing creator compensation.

[0409] The system of the present invention is for providing customer support within a virtual store based on user input. Specific embodiments will be described below.

[0410] Overall system configuration

[0411] The system consists of the following main components:

[0412] User devices (smart glasses, head-mounted displays, etc.)

[0413] server

[0414] Emotion Recognition Engine

[0415] Generative AI Models

[0416] Detailed Description of the Embodiments

[0417] 1. User device operation

[0418] The user enters the virtual store and puts on smart glasses or a head-mounted display. The device captures the user's facial expressions and voice tone in real time and sends the data to the server. At this point, the user enters a prompt, such as "Please tell me how to use the product."

[0419] 2. Server Processing

[0420] The server analyzes the prompt and emotion data received from the user's device. First, the prompt text is converted into a format that can be passed to the generative AI model using an analytical method. Next, the emotion recognition engine analyzes the user's emotion data and uses that information to complete or modify the prompt.

[0421] 3. Operation of the Emotion Recognition Engine

[0422] The emotion recognition engine analyzes the user's facial expressions and voice to determine their emotions, and provides the data to the server. This data plays an important role in the generation process of the generative AI model. For example, if the user is feeling anxious, a gentle-spoken character will be generated based on this emotional data.

[0423] 4. Processing generative AI models

[0424] The generative AI model generates a character image and dialogue based on the analyzed prompt and emotional data. For example, a character might say, "Don't worry. We'll explain in detail how to use this product." During this generation process, the character's facial expression is also adjusted based on the emotional data.

[0425] 5. Providing the generated results

[0426] The generated character image and dialogue are provided to the user as a preview by the server. The user can check this preview and make any necessary corrections. The corrections are also reflected again through the emotion recognition engine and generative AI model.

[0427] 6. Final storage and provision

[0428] The generated result confirmed by the user will be saved in the user's account by the server, and the saved stamp will be provided as a download link or a usage link.

[0429] Hardware and software used

[0430] Hardware:

[0431] Smart glasses / head-mounted displays (e.g. Microsoft HoloLens)

[0432] High-performance servers (cloud-based servers, etc.)

[0433] software:

[0434] Emotion recognition engines (e.g., Affectiva's Emotion AI)

[0435] Generative AI models (e.g., OpenAI GPT-4)

[0436] Virtual reality production tools (e.g. Unity)

[0437] Specific prompt examples

[0438] For example, if a user says, "I don't know how to use this product," the emotion engine recognizes the user's anxiety. The generative AI model creates a "character that explains things clearly" and displays a line such as, "Don't worry. I'll explain in detail how to use this product." This series of steps allows users to comfortably receive customer support in a virtual store.

[0439] As described above, the system of the present invention provides optimal customer support that is tailored to the user's emotions, thereby improving the user experience.

[0440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0441] Step 1:

[0442] A user accesses a virtual store and puts on smart glasses or a head-mounted display. The user inputs a prompt such as "Please tell me how to use the product." The input, along with the user's facial expressions and voice tone, is sent from the device to the server.

[0443] Step 2:

[0444] The server analyzes the prompt, facial expression data, and voice tone received from the terminal using an analysis means, and generates a prompt and emotion data in text format as the analysis results, since the analyzed data will be used in the next step.

[0445] Step 3:

[0446] The server sends the parsed prompt and emotion data to the emotion recognition engine, which analyzes the user's emotional state and sends the data back to the server. The output of emotion recognition can be, for example, the user's anxiety index and the reason for it.

[0447] Step 4:

[0448] The server receives emotional data from the emotion recognition engine and uses it to complement or modify the prompts. For example, if the anxiety index is high, it will modify the prompts to generate a "character that explains things clearly."

[0449] Step 5:

[0450] The server sends the modified prompt and emotion data to the generative AI model, which generates a character image and dialogue based on this data. During this generation process, the character's facial expressions and dialogue are adjusted based on the emotion data. The resulting character image and dialogue are obtained.

[0451] Step 6:

[0452] The generated character image and dialogue are provided to the user as a preview by the server. The preview screen is displayed on the user's device, and the user can check it and enter correction prompts as necessary.

[0453] Step 7:

[0454] If the user is satisfied with the preview and confirms it, the device sends the information to the server, which saves the final stamp to the user's account. The saved stamp is then provided as a download link or a link to use.

[0455] Step 8:

[0456] If the user is a paid user, the server will authenticate them, deduct the fee, and manage the creator's compensation. This ensures that the user's provision and the creator's compensation are managed appropriately.

[0457] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0458] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0459] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0460] [Second embodiment]

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

[0462] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0463] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0464] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0465] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0466] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0467] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0468] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0469] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0470] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

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

[0472] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0473] This invention is a system that uses a generation AI to customize the character's facial expressions and lines based on prompts entered by the user, and generates original stamps. Below, we will explain the program processing of this system in natural language.

[0474] Overall system overview

[0475] The system works in collaboration between the user, the device, and the server. The user inputs a prompt from the device, the server analyzes the prompt, and creates a customized stamp using a generative AI.

[0476] Program processing

[0477] First, the user accesses the custom stamp creation screen within the LINE app, where they input a prompt such as "a character smiling and saying hello." The input prompt is then sent from the device to the server.

[0478] The device is responsible for sending the input prompt to the server as an API request, which transmits the prompt content to the server.

[0479] The server receives the prompt sent from the device and starts a process to analyze the content of the prompt. The analysis means converts the content of the prompt into a format that the generation AI can understand. In this analysis, elements of the character's facial expressions and dialogue are extracted, and appropriate generation instructions are passed to the generation AI.

[0480] The AI ​​then generates the character's facial expressions and lines based on the analyzed instructions. For example, if a prompt such as "Smile and say hello" is entered, the AI ​​adds a speech bubble with the words "Hello" to the smiling character image. The generated results are then sent back to the server.

[0481] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[0482] The device displays a preview link, allowing the user to check the generated character image and dialogue. If the user wishes to make corrections, they can enter a new prompt and submit it again. If no corrections are required, the user presses the "Confirm" button.

[0483] The server will save the final stamp generated by the user in the user's account. After this process is complete, a download link or usage link will be generated and sent to the device.

[0484] The device will provide the user with a download link, allowing them to download the stickers or use them within the LINE app, allowing users to easily create and use original stickers freely.

[0485] The server also authenticates paying users and deducts the associated fees from their accounts, a portion of which is kept as compensation for creators and later deposited into their accounts.

[0486] Specific examples

[0487] For example, consider the case where a prompt is entered as "I want a sleeping character to say goodnight." The user enters the prompt and the device sends it to the server. The server analyzes the prompt and extracts elements such as "sleeping character" and "goodnight." Based on the analysis results, the generation AI generates a sleeping character and a "goodnight" speech bubble, which are sent back to the server. The server temporarily saves this and provides the user with a preview link. After the user confirms, they press the confirm button, and the final generated stamp is saved in the user's account and a download link is provided. The user can click this link to download and use the stamp.

[0488] In this way, the system generates original stickers based on user prompts, supporting quick and intuitive communication, and also supports creators' activities by providing rewards to them.

[0489] The processing flow will be explained below.

[0490] Step 1:

[0491] Users access the custom stamp creation screen within the LINE app, enter a prompt such as "a character smiling and saying hello," and press the send button.

[0492] Step 2:

[0493] The device creates an API request from the input prompt and sends the request to the server.

[0494] Step 3:

[0495] The server receives the prompt sent from the terminal and starts a process for analyzing the content of the prompt, which is then converted by the analyzing means into a format that can be understood by the generative model.

[0496] Step 4:

[0497] The server passes the parsed prompts to the generative model, which triggers the generation process, generating the character's facial expressions and dialogue based on the parsed instructions.

[0498] Step 5:

[0499] The AI ​​generates a character image based on the prompt and adds the specified dialogue. For example, in response to the prompt "Smile and say hello," it adds a speech bubble saying "Hello" to a smiling character image.

[0500] Step 6:

[0501] The server temporarily stores the generated character image and dialogue, and generates a preview link that is sent to the user's device.

[0502] Step 7:

[0503] The device uses the preview link received from the server to display a preview screen of the generated stamp to the user, who then checks the preview.

[0504] Step 8:

[0505] The user can check the preview and, if necessary, enter a new prompt to request corrections. If no corrections are required, the user presses the "Confirm" button.

[0506] Step 9:

[0507] After the user presses the confirm button, the server saves the final stamp to the user's account. Once the saving process is complete, a download link or usage link will be generated.

[0508] Step 10:

[0509] The device will display the download link received from the server, allowing the user to download the stamp or use it within the LINE app.

[0510] Step 11:

[0511] The server authenticates the paying user and deducts the relevant fee from the user's account, and also manages a portion of the fee as a reward for the creator and processes it to be transferred to the creator's account.

[0512] Through these concrete steps, users can easily create and use original stamps, and creators are also rewarded appropriately.

[0513] Example 1

[0514] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0515] Until now, there have been limited systems that allow users to easily create and share their own digital content. In particular, the process for users to create characters with specific facial expressions and lines is complicated and often requires technical knowledge. Furthermore, for paid services, managing usage fees and paying creators is cumbersome. A system that solves these problems is needed.

[0516] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0517] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting a prompt to the information processing device, an analysis means for analyzing the prompt in the information processing device and passing it to the generation engine, a generation means for generating image data and text data using the generation engine, a preview means for providing the generated image data and text data as a preview to the user, a storage means for saving the final generated digital content in the user's account, a provision means for providing the saved digital content as a download link or a usage link, and a management means for managing paid user authentication, fee deductions, and creator compensation. This allows users to easily input prompt text to generate characters with specific facial expressions and lines, and easily obtain and use the final digital content. It also allows for efficient billing management for paid services and payment of compensation to creators.

[0518] An "input means" is a device or method by which a user inputs data or commands into a system.

[0519] "Transmission means" refers to a device or method for transmitting input data to another device or system.

[0520] An "analysis means" is a device or method for analyzing input data, extracting meaning, and converting it into a format suitable for further processing.

[0521] A "generator" is a device or method for generating new data or content based on the analyzed data.

[0522] The "preview means" is a device or method for temporarily displaying generated data or content so that the user can check it.

[0523] "Storage means" refers to a device or method for permanently storing generated data or content.

[0524] "Providing means" refers to a device or method for providing stored data or content to a user.

[0525] "Management means" refers to a device or method for authenticating paying users, debiting fees, and managing creator rewards.

[0526] A "generation engine" is software or hardware that generates new data or content from input data.

[0527] An "information processing device" is a computer or network facility for inputting, outputting, analyzing, storing, and providing data.

[0528] "Digital content" means information such as text, images, audio, and video that is stored and provided in electronic form.

[0529] A "prompt" is an instruction or question that a user enters into a system.

[0530] "User" means any person or entity that uses the System to generate, view, or store digital content.

[0531] This invention relates to a system that generates original digital content by customizing character expressions and dialogue using a generative AI model based on prompts entered by the user. The program processing of this system is explained below in natural language. In this system, the user, terminal, and server work together.

[0532] First, a user accesses a custom stamp creation screen and inputs a prompt to generate a character with a specific facial expression and dialogue. Specific examples include prompts such as "a character smiling and saying hello" or "a sleeping character saying goodnight." This input is performed via a terminal.

[0533] The device then sends the user-entered prompt as an API request to the server. This request data includes the user ID and the entered prompt text. The device is responsible for converting the request into the appropriate data format so that it can be processed correctly.

[0534] The server receives the prompt sent from the device and begins the analysis process. The server implements natural language processing (NLP) technology to analyze the content of the prompt and extract important elements (e.g., the character's facial expressions and lines). The information obtained from this analysis step is converted into a format that the generative AI model can understand.

[0535] The generative AI model generates the character's facial expressions and lines based on the analysis results passed from the server. Specific generative AI models used are models capable of understanding natural language and generating images (e.g., GPT-3 and DALL-E). If the prompt is "a character smiling and saying hello," the generative AI model generates an image of a smiling character and a speech bubble that says "hello."

[0536] The server receives the generated character image and lines and temporarily stores them. Next, the server generates a link to provide the user with a preview of the generated results. This link is a URL to a page that displays the generated character image.

[0537] The device presents a preview link to the user, allowing the user to check the generated character image. The user can check the generated result and input correction instructions as necessary, or press the OK button to save the generated result as final digital content.

[0538] If the user presses the "Confirm" button, the server saves the generated result to the user's account. After saving, the server generates a download link or usage link and sends it to the device.

[0539] Finally, the device provides the user with a download link, allowing them to download the digital content or use it within the LINE app. For paid users, the server also performs authentication and deducts the fee. A portion of this fee is managed as compensation to the creator and later transferred to the creator's account.

[0540] In this way, the system generates original digital content based on user prompts, providing it quickly and intuitively, and also supports creative activities by including compensation management for creators.

[0541] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0542] Step 1:

[0543] The user accesses the custom stamp creation screen within the LINE app and enters a prompt text. This input is in the form of "a character smiling and saying hello." The user's input is sent to the device as text data. Input: Prompt text. Output: Prompt text sent to the device.

[0544] Step 2:

[0545] The terminal receives the prompt text entered by the user and sends it to the server as an API request. The terminal converts the prompt text into an appropriate data format (for example, JSON format) and sends it to the server using an HTTP request. Input: Prompt text received from the user. Output: Prompt text sent to the server.

[0546] Step 3:

[0547] The server receives the prompt sent from the device and begins the analysis process. The server uses natural language processing (NLP) technology to analyze the content of the prompt and extract important elements (facial expressions, lines). Input: Prompt received from the device. Output: Analyzed prompt information (facial expressions, lines, etc.).

[0548] Step 4:

[0549] The server creates generation instructions to be passed to the generative AI model based on the analysis results. The generation instructions are sent to the generative AI model as structured data (e.g., JSON). Input: Parsed prompt information. Output: Generation instructions to the generative AI model.

[0550] Step 5:

[0551] The generative AI model generates character expressions and lines based on the generation instructions received from the server. The generative AI model uses a generation engine such as GPT-3 or DALL-E. The generated result is a combination of image data and text data. Input: Generation instructions received from the server. Output: Generated character image and lines.

[0552] Step 6:

[0553] The generative AI model returns the generated character image and dialogue to the server. The server receives the data and temporarily stores it. Input: Character image and dialogue received from the generative AI model. Output: Temporarily stored generated data.

[0554] Step 7:

[0555] The server generates a preview link to allow the user to check the generated results. This link is provided to the user and contains the URL of a page that previews the generated character image. Input: Temporarily saved generated data. Output: Preview link provided to the user.

[0556] Step 8:

[0557] The terminal displays a preview link to the user and provides an interface for checking the generated results. The user checks the generated character image and lines, and if necessary, inputs correction instructions or presses the confirm button. Input: Preview link. Output: User confirmation and correction instructions or confirmation operation.

[0558] Step 9:

[0559] If the user presses the "Confirm" button, the server will save the final generated digital content to the user's account. At the same time, the server will generate a download link or usage link and send it to the device. Input: User's confirmation operation. Output: Saved digital content and generated download link.

[0560] Step 10:

[0561] The terminal provides the download link to the user, allowing the user to download or use the digital content. Input: Download link received from the server. Output: Download link provided to the user.

[0562] Step 11:

[0563] The server authenticates paid users and processes fee withdrawals. A portion of the fee is managed as compensation to the creator. Input: User information and fee information. Output: Fee withdrawal and compensation management for the creator.

[0564] This system allows users to easily generate characters with specific facial expressions and lines by simply entering a prompt, and then acquire and use them as digital content. It also efficiently manages billing for paid services and pays creators.

[0565] (Application example 1)

[0566] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0567] When users post product reviews on online shopping sites, there is a lack of effective ways to convey emotions and product appeal that are difficult to express through text-only reviews. This makes it difficult for other users to visually understand the review content, which can discourage them from purchasing the product. Another issue is that the system for rewarding creators is insufficient, making it difficult to distribute rewards fairly.

[0568] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0569] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting a prompt to the server, an analysis means in the server for analyzing the prompt and passing it to a generative model, a generation means for generating character images and dialogue using the generative model, a generation means for generating original stamps based on reviews on an online shopping site, a preview means for providing users with previews of the generated images and dialogue, a storage means for saving the final generated stamps in the user's account, a provision means for providing the saved stamps as download links or usage links, and a management means for managing paid user authentication, fee deductions, and creator compensation. This enables users to communicate product reviews in a visually appealing way, makes it easier for other users to intuitively understand the review content, and enables fair compensation distribution to creators.

[0570] An "input means" is a device or function that provides an interface for a user to input a prompt.

[0571] The "transmission means" is a device or function that transmits the prompt entered by the user to the server via the network.

[0572] The "analysis means" is a device or function that analyzes the prompts received at the server and converts them into a format that can be understood by the generative model.

[0573] "Generator" means a device or function that uses an AI model to generate character images and dialogue based on the instructions of the analyzed prompt.

[0574] The "preview means" is a device or function that provides an interface that allows the user to check the generated character image and lines.

[0575] "Storage means" refers to a device or function that stores the final generated stamp confirmed by the user in the user's account.

[0576] "Providing means" refers to a device or function that provides saved stamps as links that users can download or use.

[0577] "Management means" refers to a device or function that manages the authentication of paid users, the deduction of fees, and compensation to creators.

[0578] An "online shopping site" is an e-commerce platform that allows users to purchase products online.

[0579] "Review content" refers to information expressed in text or stamps about the user's impressions and evaluations of products purchased on an online shopping site.

[0580] "Custom Stamps" are visual graphic elements specially created by a generative AI model based on user prompts.

[0581] A "creator" is a person or entity that provides the source materials and instructions for content created by a generative AI model.

[0582] This invention relates to a system that uses AI to generate original stamps based on prompts entered by users. Specifically, it generates original stamps based on reviews on online shopping sites and provides a means for users to attach them to reviews and post them.

[0583] System configuration

[0584] This system works in cooperation with three parties: the user, the device (such as a smartphone or tablet), and the server. The main components of the system are as follows:

[0585] 1. Input Method

[0586] The user enters a prompt into the terminal. An example prompt is a smiling character saying, "This product is so useful, I'll never want to let it go!"

[0587] 2. Transmission Method

[0588] The device sends the entered prompt as an API request to the server, where the device communicates with the server over a network connection.

[0589] 3. Analysis method

[0590] The server receives the prompt sent from the device and analyzes it. The analysis method converts the content of the prompt into a format that the generation AI can understand. Specifically, elements such as "smile" and "This product is so convenient, I can't live without it!" are extracted from the prompt text.

[0591] 4. Generation means

[0592] Based on the analysis results, the server issues instructions to a generative AI model to generate a character image and dialogue. This generation is performed using a cloud-based generative AI model (such as OpenAI GPT-3). The generated results are obtained as a character image; for example, a character may be generated that smiles and says, "This product is so convenient, I can't live without it!"

[0593] 5. Preview Methods

[0594] To provide the user with a preview of the generated character image and lines, the server generates a preview link and sends it to the device. The user can open the preview link on the device and check the generated stamp.

[0595] 6. Preservation means

[0596] Once the user approves the generated stamp, the server stores it in the user's account, where it can be used to attach to reviews.

[0597] 7. Means of provision

[0598] The server generates a download link or usage link for the saved stamp and sends it to the device, allowing the user to actually use the stamp when posting a review.

[0599] 8. Control measures

[0600] The server also has the functionality to authenticate paying users, debit fees, and manage creator compensation. Specifically, it processes charges when users use the stamp generation service, and returns a portion of the charges to creators as compensation.

[0601] Specific examples

[0602] For example, when a user writes a product review on an online shopping site, they input a prompt such as, "A smiling character saying, 'This product is so convenient, I can't live without it!'" The device sends this prompt to the server, which analyzes it and gives instructions to the generation AI. The generation AI model generates an image of a smiling character and the words, "This product is so convenient, I can't live without it!", which are provided to the user as a preview link. Once the user confirms and confirms, the final generated stamp is saved to the user's account and a download link is provided. In this way, users can post visually appealing product reviews.

[0603] This invention utilizes a generative AI model based on prompt sentences to visually enrich product reviews on online shopping sites, not only increasing users' desire to purchase but also ensuring fair distribution of rewards to creators.

[0604] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0605] Step 1:

[0606] The user inputs a prompt sentence. For example, the user inputs a prompt such as "This product is so convenient, I can't live without it!" The input prompt is acquired through the input means of the terminal.

[0607] input:

[0608] The prompt text entered by the user.

[0609] output:

[0610] The prompt text captured on the terminal.

[0611] Specific operation:

[0612] The user types the prompt into the text input field on their smartphone or tablet and presses the submit button.

[0613] Step 2:

[0614] The terminal transmits the acquired prompt text to the server as an API request. The prompt text is transmitted to the server via the network using a transmission means.

[0615] input:

[0616] The prompt text captured on the terminal.

[0617] output:

[0618] The prompt text sent to the server.

[0619] Specific operation:

[0620] The terminal converts the prompt text into an API request format and sends it to the server via an HTTP request.

[0621] Step 3:

[0622] The server analyzes the received prompt text. Using the analysis method, the character's facial expression and lines are extracted from the prompt text. For example, elements such as "smile" and "This product is so convenient, I can't live without it!" are extracted.

[0623] input:

[0624] The prompt text sent to the server.

[0625] output:

[0626] Extracted facial expressions and dialogue elements.

[0627] Specific operation:

[0628] The server runs natural language processing algorithms to parse the prompt and extract key keywords and phrases.

[0629] Step 4:

[0630] The server passes the analysis results to a generative AI model, which generates a character image and dialogue. Using a generation method, the generative AI model creates a character image based on this information. For example, an image may be generated that includes a smiling character and the text, "This product is so useful, I can't live without it!"

[0631] input:

[0632] Extracted facial expressions and dialogue elements.

[0633] output:

[0634] Generated character images and lines.

[0635] Specific operation:

[0636] The server converts the analyzed data into the input format for the generative AI model, sends a request to the generative AI model, and receives the generated image data.

[0637] Step 5:

[0638] The server provides the generated character image and lines to the terminal as a preview link, and generates a preview link using a preview means so that the user can check the image, and sends the preview link to the terminal.

[0639] input:

[0640] Generated character images and lines.

[0641] output:

[0642] The preview link sent to your device.

[0643] Specific operation:

[0644] The server temporarily stores the generated image in cloud storage, generates a link to it, and sends the link to the terminal as an HTTP response.

[0645] Step 6:

[0646] The user checks the preview link and approves the stamp. After opening the preview link on their device and checking the generated stamp, they press the confirm button to approve it.

[0647] input:

[0648] The preview link sent to your device.

[0649] output:

[0650] User approval operations.

[0651] Specific operation:

[0652] Users can click on the preview link on their device and use the interface to review and confirm the generated stamp in their browser or app.

[0653] Step 7:

[0654] The server stores the final generated stamp in the user's account. A storage means is used to store the generated stamp in the user's database.

[0655] input:

[0656] User approval operations.

[0657] output:

[0658] Stickers saved in the user's account.

[0659] Specific operation:

[0660] The server queries the database associated with the user's account to store the generated stamp.

[0661] Step 8:

[0662] The server provides a download link or a usage link for the stored stamp. The server generates a download link using the providing means and transmits it to the terminal.

[0663] input:

[0664] Stickers saved in the user's account.

[0665] output:

[0666] The download or usage link sent to your device.

[0667] Specific operation:

[0668] The server generates a downloadable URL for the stamp file for the client and sends the URL information to the device.

[0669] Step 9:

[0670] The server authenticates paid users, deducts fees, and manages rewards to creators. Using a management means, the server performs the authentication process for paid users, deducts usage fees, and transfers a portion of the fees to the creator's account as rewards.

[0671] input:

[0672] Paid users' account information and usage information of generated stamps.

[0673] output:

[0674] Completing billing transactions and transferring rewards to creators.

[0675] Specific operation:

[0676] The server sends the paying user's payment information to the payment provider, deducts the usage fee, then calculates the creator's remuneration and transfers the remuneration to the creator's account.

[0677] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0678] This invention combines a system that uses generation AI to customize the character's facial expressions and lines based on prompts entered by the user, generating original stamps, and an emotion engine that recognizes the user's emotions. Below, we will explain the program processing of this system in natural language.

[0679] Overall system overview

[0680] This system works in cooperation with four parties: the user, the device, the server, and the emotion engine. The user inputs a prompt from the device, and the emotion engine recognizes the user's emotion. The server analyzes the prompt and creates a customized stamp using a generation AI.

[0681] Program processing

[0682] First, the user accesses the custom stamp creation screen within the LINE app, enters a prompt such as "a character saying hello with a smile," and presses the send button. At this time, the text entered by the user, as well as the voice and facial expressions used, are analyzed by the emotion engine.

[0683] The device creates an API request based on the prompt and emotional information entered by the user and sends the request to the server.

[0684] The server receives the prompt and emotion information sent from the terminal and starts processing to analyze the content of the prompt. The analysis means converts the content of the prompt into a format that the generative model can understand. Furthermore, the emotion data analyzed by the emotion engine provides supplementary information to the prompt, generating a stamp that is more suited to the user's emotion.

[0685] The emotion engine recognizes the user's emotions from their facial expressions and voice, and complements or modifies prompts based on that emotional data. For example, if the user is smiling, a warmer tone might be added to a prompt like "Hello."

[0686] The generative AI generates character expressions and lines based on the analyzed instructions and emotional data. For example, if the prompt is "Smile and say hello," and the emotion engine determines that the user is very happy, the generated character's smile will be brighter and the "hello" line will have a more joyful nuance.

[0687] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[0688] The device will use the preview link to display a preview screen of the generated stamp to the user. The user can check this preview and, if necessary, enter new prompts or emotion data to request corrections. If no corrections are required, the user presses the "Confirm" button.

[0689] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated.

[0690] The device will display a download link, allowing users to download the stamp or use it within the LINE app.

[0691] The server also authenticates paying users and deducts the associated fees from their accounts, a portion of which is managed as a reward for the creators and later deposited into their accounts.

[0692] Specific examples

[0693] For example, consider the prompt "I want a sleeping character to say goodnight." The user enters the prompt, and the device sends it to the server. The server analyzes the prompt and emotion data, extracting elements such as "sleeping character" and "goodnight." The emotion engine recognizes the user's calm emotion, and generates a more relaxed facial expression and the phrase "goodnight" based on that.

[0694] The AI ​​generates a character and dialogue based on the specified content and sends it back to the server. The server temporarily saves it and provides the user with a preview link. After the user confirms it, they press the confirm button, and the final generated stamp is saved to their account and a download link is provided. Users can click this link to download and use the stamp.

[0695] In this way, the system generates original stamps based on user prompts and emotional data, supporting quick and intuitive communication, and also supports creators' activities by providing rewards to them.

[0696] The processing flow will be explained below.

[0697] Step 1:

[0698] Users access the custom stamp creation screen within the LINE app, input a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are also recorded by the emotion engine.

[0699] Step 2:

[0700] The device sends the input prompt and emotion data to the server as an API request.

[0701] Step 3:

[0702] The server receives the prompt and emotion data sent from the terminal and starts a process to analyze the prompt content and emotion data. The analysis means converts the prompt content into a format that can be understood by the generative model.

[0703] Step 4:

[0704] The emotion engine recognizes the user's emotions from their facial expressions and voice data, and provides the analysis results to the server. For example, when the user is smiling, emotion data of "joy" is generated.

[0705] Step 5:

[0706] The server complements or modifies the prompt using the emotion data provided by the emotion engine and passes it to the generative model, adding elements based on the user's emotions.

[0707] Step 6:

[0708] The AI ​​then generates the character's facial expressions and lines based on the analyzed prompt and emotion data. For example, if the emotion data for "hello with a smile" and "joy" are given, the generated character's smile will be brighter and the "hello" line will have a more joyful nuance.

[0709] Step 7:

[0710] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[0711] Step 8:

[0712] The device will use the preview link to display a preview screen of the generated stamp to the user. The user can check this preview and, if necessary, enter new prompts or emotion data to request corrections. If no corrections are required, the user presses the "Confirm" button.

[0713] Step 9:

[0714] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link is generated and sent to the device.

[0715] Step 10:

[0716] The device will display a download link, allowing users to download the stamp or use it within the LINE app.

[0717] Step 11:

[0718] The server authenticates the paying user and deducts the associated fees from the user's account, and a portion of the fees is managed as a reward for the creator and deposited into the creator's account.

[0719] In this way, a system is realized that generates original stamps that are optimal and intuitive for each user based on the user's prompts and emotional data, and also supports creators' activities by providing appropriate rewards to creators.

[0720] Example 2

[0721] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0722] Previous systems for generating customized stickers were able to generate character expressions and lines based on user prompts, but they were unable to customize characters based on the user's emotions. This made it difficult to generate stickers that fully reflected the user's intentions. Furthermore, the generation process was complex, potentially resulting in a poor user experience.

[0723] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0724] In this invention, the server includes an analysis means for analyzing the prompt and emotion data and inputting them into a generative model, a preview means for providing the user with a preview of the generated image and dialogue, and a storage means for saving the final generated stickers in the user's account, thereby enabling quick and intuitive generation of customized stickers that take the user's emotions into account.

[0725] "User" refers to an individual or organization that uses the System to generate customized stamps.

[0726] An "input means" is an interface through which a user inputs prompts and other data into the system.

[0727] The "transmission means" is a function for transmitting a prompt input via the input means to the server.

[0728] The "analysis means" is a function for analyzing prompts and emotion data in the server and inputting them into the generative model.

[0729] A "generative model" is an AI algorithm that generates character images and dialogue based on input data.

[0730] "Generation means" is a function for generating character images and lines using a generative model.

[0731] The "preview means" is a function for providing the user with a preview of the generated character image and lines.

[0732] "Storage means" is a function for saving the final generated stamp in the user's account.

[0733] The "means of provision" is a function for providing saved stamps to users as download links or usage links.

[0734] The "management means" is a function for managing authentication of paying users, withdrawal of fees, and remuneration to content creators.

[0735] "Emotional data" refers to emotional information extracted from a user's facial expressions and voice.

[0736] This invention is a system that uses a generative AI model to customize character expressions and lines based on prompts entered by the user, generating original stamps. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it achieves even more precise customization.

[0737] Hardware and software used

[0738] 1. The user accesses the LINE application using a device such as a smartphone or tablet.

[0739] 2. The device makes an API request to communicate with the server via its internet connection.

[0740] 3. The server utilizes high-performance cloud servers to run generative AI models (e.g., OpenAI's GPT-3) and emotion engines (e.g., Affectiva Emotion AI).

[0741] 4. The emotion engine includes hardware and software that uses the device's camera and microphone to analyze the user's facial expressions and voice.

[0742] Data processing and calculation flow

[0743] Users access the "Customized Stamp Creation Screen" within the LINE app, enter a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are simultaneously analyzed by the emotion engine.

[0744] The device sends the prompt and emotion data entered by the user to the server as an API request, which processes data acquired from the camera and microphone and generates appropriate emotion data.

[0745] The server analyzes the data received from the device and converts the prompts into a format that the generative AI model can understand. It also analyzes the emotional data and adds additional information to the prompts. This analysis method provides more detailed instructions to the generative model.

[0746] The AI ​​then generates character expressions and lines based on the analyzed instructions and emotional data. For example, in response to the prompt "A character saying hello with a smile," the generated character's smile will become brighter and the lines will have a more joyful nuance.

[0747] The server receives the generated character data, temporarily stores it, and then provides the user with a preview link and sends an interface to the device for viewing and modifying the generated stamp.

[0748] The device will use the preview link to display a preview of the generated stamp to the user. The user can check the preview and, if necessary, enter new prompts and emotion data and submit it again. If no corrections are required, the user can press the "Confirm" button.

[0749] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated.

[0750] The device will display the generated download link to the user, allowing them to download the stamp or use it within the LINE app.

[0751] Specific examples

[0752] For example, consider the prompt "I want a sleeping character to say goodnight." The user enters the prompt, and the device sends it to the server. The server analyzes the prompt and emotion data, extracting elements such as "sleeping character" and "goodnight." The emotion engine recognizes the user's calm emotion, and generates a more relaxed facial expression and the phrase "goodnight" based on that.

[0753] Specific prompt examples:

[0754] I want my sleeping character to say goodnight

[0755] In this way, the system not only quickly and intuitively generates original stamps based on user prompts and emotional data, but also customizes them to reflect the user's emotions.

[0756] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0757] Step 1:

[0758] Users access the LINE application using a device such as a smartphone or tablet. They access the "Customized Stamp Creation Screen," enter a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are also analyzed by the emotion engine.

[0759] Input: User prompts, facial expressions, and voice data

[0760] Output: Prompt and emotion data sent to the device

[0761] Specific behavior:

[0762] A user enters text using the smartphone keyboard.

[0763] Data collection from cameras and microphones.

[0764] Step 2:

[0765] The device converts the user's input prompts and facial and voice data acquired from the camera and microphone into API requests and sends them to the server, where they are processed to generate appropriate emotion data.

[0766] Input: User prompts, facial expressions, and voice data

[0767] Output: API request sent to the server

[0768] Specific behavior:

[0769] Analyzes data from the camera and microphone to generate emotion labels.

[0770] Converts data into packets and sends them.

[0771] Step 3:

[0772] The server receives prompts and emotional data sent from the device, analyzes the content of the prompts, and converts them into a format that the generative AI model can understand. At the same time, it analyzes the emotional data and generates complementary information according to the prompts.

[0773] Input: Prompt and emotion data received from the device

[0774] Output: Parsed data to a generative AI model

[0775] Specific behavior:

[0776] Prompt text analysis (tokenization and context analysis)

[0777] Emotion data analysis (emotion labeling)

[0778] Step 4:

[0779] The server sends the analyzed data to the generation AI, which converts the data into a format that is easy for the generation AI to understand.

[0780] Input: Parsed prompt and sentiment data

[0781] Output: Formatted data sent to the generative AI

[0782] Specific behavior:

[0783] Data format conversion

[0784] Creating and sending an API request to the generation AI

[0785] Step 5:

[0786] The generative AI generates facial expressions and lines for the character based on the data it receives. For example, if the emotion engine determines that the user is happy in addition to the prompt "Smile and say hello," the character will have a brighter smile.

[0787] Input: Formatted data sent from the server

[0788] Output: Generated character and dialogue data

[0789] Specific behavior:

[0790] Running inference on a model

[0791] Formatting the generated results

[0792] Step 6:

[0793] The server temporarily stores the character data received from the generated AI, generates a preview link for the user to view, and sends it to the device.

[0794] Input: Character data received from the generation AI

[0795] Output: Preview link for user confirmation

[0796] Specific behavior:

[0797] Temporarily save to database

[0798] Generate and send a preview link

[0799] Step 7:

[0800] The device receives the preview link and displays a preview screen of the generated stamp to the user, which the user can confirm.

[0801] Input: Preview link received from the server

[0802] Output: The preview screen that the user sees

[0803] Specific behavior:

[0804] Preview screen drawing

[0805] Screen transition by clicking a link

[0806] Step 8:

[0807] The user checks the preview and, if satisfied with the stamp, presses the "Confirm" button. If corrections are needed, they enter new prompt and emotion data and submit again.

[0808] Input: User confirmation and correction instructions

[0809] Output: Confirm or correct instruction

[0810] Specific behavior:

[0811] Click the Confirm button

[0812] Re-enter correction prompt

[0813] Step 9:

[0814] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated and sent to the device.

[0815] Input: User confirmation instructions

[0816] Output: Download link or usage link

[0817] Specific behavior:

[0818] Final save to database

[0819] Link Generation and Notifications

[0820] Step 10:

[0821] The device will display the download link received from the server to the user, allowing the user to download the stamp or use it within the LINE app.

[0822] Input: Download link received from the server

[0823] output: the download link that is displayed to the user

[0824] Specific behavior:

[0825] View download links

[0826] Click on the link to download

[0827] (Application example 2)

[0828] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0829] There is a demand for improved customer support and user experience in virtual stores, but conventional systems have difficulty recognizing user emotions in real time and responding appropriately.In addition, the content generated is not optimized based on user emotions, which leads to a decrease in user satisfaction.

[0830] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0831] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting prompts to the server, an analysis means in the server for analyzing the prompts and passing them to a generative model, a generation means for generating character images and dialogue using the generative model, a preview means for providing the generated images and dialogue as previews to the user, an emotion recognition means for recognizing the user's emotion and using the emotion data to complement or modify the prompt, an optimization means for optimizing the generated character images and dialogue to match the user's emotion, a storage means for saving the final generated stamps in the user's account, a provision means for providing the saved stamps as a download link or a usage link, and a management means for managing paid user authentication, fee deductions, and creator compensation. This makes it possible to provide optimal customer support tailored to the user's emotions, which is expected to improve the user experience and increase satisfaction.

[0832] "User" refers to an individual or organization that uses this system.

[0833] "Input means" refers to a means that provides an interface for a user to input a prompt.

[0834] "Transmission means" refers to a means for transmitting the input prompt to the server.

[0835] "Analysis means" refers to means for analyzing prompts on the server and converting them into a format that conforms to the generative model.

[0836] The "generation means" refers to a means for generating a character image and lines based on the analyzed prompt.

[0837] "Preview means" refers to a means for temporarily displaying the generated character image and dialogue to the user.

[0838] "Emotion recognition means" refers to a means of analyzing the user's emotions and reflecting that data in prompts.

[0839] "Optimization means" refers to a means for adjusting the generated character images and lines based on emotional data.

[0840] "Storage Means" means the means by which the final generated stamps are stored in the User's account.

[0841] "Providing means" refers to the means of providing saved stamps as a download link or a usage link.

[0842] "Management means" refers to the means for authenticating paying users, deducting fees, and managing creator compensation.

[0843] The system of the present invention is for providing customer support within a virtual store based on user input. Specific embodiments will be described below.

[0844] Overall system configuration

[0845] The system consists of the following main components:

[0846] User devices (smart glasses, head-mounted displays, etc.)

[0847] server

[0848] Emotion Recognition Engine

[0849] Generative AI Models

[0850] Detailed Description of the Embodiments

[0851] 1. User device operation

[0852] The user enters the virtual store and puts on smart glasses or a head-mounted display. The device captures the user's facial expressions and voice tone in real time and sends the data to the server. At this point, the user enters a prompt, such as "Please tell me how to use the product."

[0853] 2. Server Processing

[0854] The server analyzes the prompt and emotion data received from the user's device. First, the prompt text is converted into a format that can be passed to the generative AI model using an analytical method. Next, the emotion recognition engine analyzes the user's emotion data and uses that information to complete or modify the prompt.

[0855] 3. Operation of the Emotion Recognition Engine

[0856] The emotion recognition engine analyzes the user's facial expressions and voice to determine their emotions, and provides the data to the server. This data plays an important role in the generation process of the generative AI model. For example, if the user is feeling anxious, a gentle-spoken character will be generated based on this emotional data.

[0857] 4. Processing generative AI models

[0858] The generative AI model generates a character image and dialogue based on the analyzed prompt and emotional data. For example, a character might say, "Don't worry. We'll explain in detail how to use this product." During this generation process, the character's facial expression is also adjusted based on the emotional data.

[0859] 5. Providing the generated results

[0860] The generated character image and dialogue are provided to the user as a preview by the server. The user can check this preview and make any necessary corrections. The corrections are also reflected again through the emotion recognition engine and generative AI model.

[0861] 6. Final storage and provision

[0862] The generated result confirmed by the user will be saved in the user's account by the server, and the saved stamp will be provided as a download link or a usage link.

[0863] Hardware and software used

[0864] Hardware:

[0865] Smart glasses / head-mounted displays (e.g. Microsoft HoloLens)

[0866] High-performance servers (cloud-based servers, etc.)

[0867] software:

[0868] Emotion recognition engines (e.g., Affectiva's Emotion AI)

[0869] Generative AI models (e.g., OpenAI GPT-4)

[0870] Virtual reality production tools (e.g. Unity)

[0871] Specific prompt examples

[0872] For example, if a user says, "I don't know how to use this product," the emotion engine recognizes the user's anxiety. The generative AI model creates a "character that explains things clearly" and displays a line such as, "Don't worry. I'll explain in detail how to use this product." This series of steps allows users to comfortably receive customer support in a virtual store.

[0873] As described above, the system of the present invention provides optimal customer support that is tailored to the user's emotions, thereby improving the user experience.

[0874] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0875] Step 1:

[0876] A user accesses a virtual store and puts on smart glasses or a head-mounted display. The user inputs a prompt such as "Please tell me how to use the product." The input, along with the user's facial expressions and voice tone, is sent from the device to the server.

[0877] Step 2:

[0878] The server analyzes the prompt, facial expression data, and voice tone received from the terminal using an analysis means, and generates a prompt and emotion data in text format as the analysis results, since the analyzed data will be used in the next step.

[0879] Step 3:

[0880] The server sends the parsed prompt and emotion data to the emotion recognition engine, which analyzes the user's emotional state and sends the data back to the server. The output of emotion recognition can be, for example, the user's anxiety index and the reason for it.

[0881] Step 4:

[0882] The server receives emotional data from the emotion recognition engine and uses it to complement or modify the prompts. For example, if the anxiety index is high, it will modify the prompts to generate a "character that explains things clearly."

[0883] Step 5:

[0884] The server sends the modified prompt and emotion data to the generative AI model, which generates a character image and dialogue based on this data. During this generation process, the character's facial expressions and dialogue are adjusted based on the emotion data. The resulting character image and dialogue are obtained.

[0885] Step 6:

[0886] The generated character image and dialogue are provided to the user as a preview by the server. The preview screen is displayed on the user's device, and the user can check it and enter correction prompts as necessary.

[0887] Step 7:

[0888] If the user is satisfied with the preview and confirms it, the device sends the information to the server, which saves the final stamp to the user's account. The saved stamp is then provided as a download link or a link to use.

[0889] Step 8:

[0890] If the user is a paid user, the server will authenticate them, deduct the fee, and manage the creator's compensation. This ensures that the user's provision and the creator's compensation are managed appropriately.

[0891] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0892] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0893] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0894] [Third embodiment]

[0895] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0896] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0897] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0898] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0899] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0900] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0901] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0902] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0903] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0904] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0905] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0906] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0907] This invention is a system that uses a generation AI to customize the character's facial expressions and lines based on prompts entered by the user, and generates original stamps. Below, we will explain the program processing of this system in natural language.

[0908] Overall system overview

[0909] The system works in collaboration between the user, the device, and the server. The user inputs a prompt from the device, the server analyzes the prompt, and creates a customized stamp using a generative AI.

[0910] Program processing

[0911] First, the user accesses the custom stamp creation screen within the LINE app, where they input a prompt such as "a character smiling and saying hello." The input prompt is then sent from the device to the server.

[0912] The device is responsible for sending the input prompt to the server as an API request, which transmits the prompt content to the server.

[0913] The server receives the prompt sent from the device and starts a process to analyze the content of the prompt. The analysis means converts the content of the prompt into a format that the generation AI can understand. In this analysis, elements of the character's facial expressions and dialogue are extracted, and appropriate generation instructions are passed to the generation AI.

[0914] The AI ​​then generates the character's facial expressions and lines based on the analyzed instructions. For example, if a prompt such as "Smile and say hello" is entered, the AI ​​adds a speech bubble with the words "Hello" to the smiling character image. The generated results are then sent back to the server.

[0915] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[0916] The device displays a preview link, allowing the user to check the generated character image and dialogue. If the user wishes to make corrections, they can enter a new prompt and submit it again. If no corrections are required, the user presses the "Confirm" button.

[0917] The server will save the final stamp generated by the user in the user's account. After this process is complete, a download link or usage link will be generated and sent to the device.

[0918] The device will provide the user with a download link, allowing them to download the stickers or use them within the LINE app, allowing users to easily create and use original stickers freely.

[0919] The server also authenticates paying users and deducts the associated fees from their accounts, a portion of which is kept as compensation for creators and later deposited into their accounts.

[0920] Specific examples

[0921] For example, consider the case where a prompt is entered as "I want a sleeping character to say goodnight." The user enters the prompt and the device sends it to the server. The server analyzes the prompt and extracts elements such as "sleeping character" and "goodnight." Based on the analysis results, the generation AI generates a sleeping character and a "goodnight" speech bubble, which are sent back to the server. The server temporarily saves this and provides the user with a preview link. After the user confirms, they press the confirm button, and the final generated stamp is saved in the user's account and a download link is provided. The user can click this link to download and use the stamp.

[0922] In this way, the system generates original stickers based on user prompts, supporting quick and intuitive communication, and also supports creators' activities by providing rewards to them.

[0923] The processing flow will be explained below.

[0924] Step 1:

[0925] Users access the custom stamp creation screen within the LINE app, enter a prompt such as "a character smiling and saying hello," and press the send button.

[0926] Step 2:

[0927] The device creates an API request from the input prompt and sends the request to the server.

[0928] Step 3:

[0929] The server receives the prompt sent from the terminal and starts a process for analyzing the content of the prompt, which is then converted by the analyzing means into a format that can be understood by the generative model.

[0930] Step 4:

[0931] The server passes the parsed prompts to the generative model, which triggers the generation process, generating the character's facial expressions and dialogue based on the parsed instructions.

[0932] Step 5:

[0933] The AI ​​generates a character image based on the prompt and adds the specified dialogue. For example, in response to the prompt "Smile and say hello," it adds a speech bubble saying "Hello" to a smiling character image.

[0934] Step 6:

[0935] The server temporarily stores the generated character image and dialogue, and generates a preview link that is sent to the user's device.

[0936] Step 7:

[0937] The device uses the preview link received from the server to display a preview screen of the generated stamp to the user, who then checks the preview.

[0938] Step 8:

[0939] The user can check the preview and, if necessary, enter a new prompt to request corrections. If no corrections are required, the user presses the "Confirm" button.

[0940] Step 9:

[0941] After the user presses the confirm button, the server saves the final stamp to the user's account. Once the saving process is complete, a download link or usage link will be generated.

[0942] Step 10:

[0943] The device will display the download link received from the server, allowing the user to download the stamp or use it within the LINE app.

[0944] Step 11:

[0945] The server authenticates the paying user and deducts the relevant fee from the user's account, and also manages a portion of the fee as a reward for the creator and processes it to be transferred to the creator's account.

[0946] Through these concrete steps, users can easily create and use original stamps, and creators are also rewarded appropriately.

[0947] Example 1

[0948] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0949] Until now, there have been limited systems that allow users to easily create and share their own digital content. In particular, the process for users to create characters with specific facial expressions and lines is complicated and often requires technical knowledge. Furthermore, for paid services, managing usage fees and paying creators is cumbersome. A system that solves these problems is needed.

[0950] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0951] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting a prompt to the information processing device, an analysis means for analyzing the prompt in the information processing device and passing it to the generation engine, a generation means for generating image data and text data using the generation engine, a preview means for providing the generated image data and text data as a preview to the user, a storage means for saving the final generated digital content in the user's account, a provision means for providing the saved digital content as a download link or a usage link, and a management means for managing paid user authentication, fee deductions, and creator compensation. This allows users to easily input prompt text to generate characters with specific facial expressions and lines, and easily obtain and use the final digital content. It also allows for efficient billing management for paid services and payment of compensation to creators.

[0952] An "input means" is a device or method by which a user inputs data or commands into a system.

[0953] "Transmission means" refers to a device or method for transmitting input data to another device or system.

[0954] An "analysis means" is a device or method for analyzing input data, extracting meaning, and converting it into a format suitable for further processing.

[0955] A "generator" is a device or method for generating new data or content based on the analyzed data.

[0956] The "preview means" is a device or method for temporarily displaying generated data or content so that the user can check it.

[0957] "Storage means" refers to a device or method for permanently storing generated data or content.

[0958] "Providing means" refers to a device or method for providing stored data or content to a user.

[0959] "Management means" refers to a device or method for authenticating paying users, debiting fees, and managing creator rewards.

[0960] A "generation engine" is software or hardware that generates new data or content from input data.

[0961] An "information processing device" is a computer or network facility for inputting, outputting, analyzing, storing, and providing data.

[0962] "Digital content" means information such as text, images, audio, and video that is stored and provided in electronic form.

[0963] A "prompt" is an instruction or question that a user enters into a system.

[0964] "User" means any person or entity that uses the System to generate, view, or store digital content.

[0965] This invention relates to a system that generates original digital content by customizing character expressions and dialogue using a generative AI model based on prompts entered by the user. The program processing of this system is explained below in natural language. In this system, the user, terminal, and server work together.

[0966] First, a user accesses a custom stamp creation screen and inputs a prompt to generate a character with a specific facial expression and dialogue. Specific examples include prompts such as "a character smiling and saying hello" or "a sleeping character saying goodnight." This input is performed via a terminal.

[0967] The device then sends the user-entered prompt as an API request to the server. This request data includes the user ID and the entered prompt text. The device is responsible for converting the request into the appropriate data format so that it can be processed correctly.

[0968] The server receives the prompt sent from the device and begins the analysis process. The server implements natural language processing (NLP) technology to analyze the content of the prompt and extract important elements (e.g., the character's facial expressions and lines). The information obtained from this analysis step is converted into a format that the generative AI model can understand.

[0969] The generative AI model generates the character's facial expressions and lines based on the analysis results passed from the server. Specific generative AI models used are models capable of understanding natural language and generating images (e.g., GPT-3 and DALL-E). If the prompt is "a character smiling and saying hello," the generative AI model generates an image of a smiling character and a speech bubble that says "hello."

[0970] The server receives the generated character image and lines and temporarily stores them. Next, the server generates a link to provide the user with a preview of the generated results. This link is a URL to a page that displays the generated character image.

[0971] The device presents a preview link to the user, allowing the user to check the generated character image. The user can check the generated result and input correction instructions as necessary, or press the OK button to save the generated result as final digital content.

[0972] If the user presses the "Confirm" button, the server saves the generated result to the user's account. After saving, the server generates a download link or usage link and sends it to the device.

[0973] Finally, the device provides the user with a download link, allowing them to download the digital content or use it within the LINE app. For paid users, the server also performs authentication and deducts the fee. A portion of this fee is managed as compensation to the creator and later transferred to the creator's account.

[0974] In this way, the system generates original digital content based on user prompts, providing it quickly and intuitively, and also supports creative activities by including compensation management for creators.

[0975] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0976] Step 1:

[0977] The user accesses the custom stamp creation screen within the LINE app and enters a prompt text. This input is in the form of "a character smiling and saying hello." The user's input is sent to the device as text data. Input: Prompt text. Output: Prompt text sent to the device.

[0978] Step 2:

[0979] The terminal receives the prompt text entered by the user and sends it to the server as an API request. The terminal converts the prompt text into an appropriate data format (for example, JSON format) and sends it to the server using an HTTP request. Input: Prompt text received from the user. Output: Prompt text sent to the server.

[0980] Step 3:

[0981] The server receives the prompt sent from the device and begins the analysis process. The server uses natural language processing (NLP) technology to analyze the content of the prompt and extract important elements (facial expressions, lines). Input: Prompt received from the device. Output: Analyzed prompt information (facial expressions, lines, etc.).

[0982] Step 4:

[0983] The server creates generation instructions to be passed to the generative AI model based on the analysis results. The generation instructions are sent to the generative AI model as structured data (e.g., JSON). Input: Parsed prompt information. Output: Generation instructions to the generative AI model.

[0984] Step 5:

[0985] The generative AI model generates character expressions and lines based on the generation instructions received from the server. The generative AI model uses a generation engine such as GPT-3 or DALL-E. The generated result is a combination of image data and text data. Input: Generation instructions received from the server. Output: Generated character image and lines.

[0986] Step 6:

[0987] The generative AI model returns the generated character image and dialogue to the server. The server receives the data and temporarily stores it. Input: Character image and dialogue received from the generative AI model. Output: Temporarily stored generated data.

[0988] Step 7:

[0989] The server generates a preview link to allow the user to check the generated results. This link is provided to the user and contains the URL of a page that previews the generated character image. Input: Temporarily saved generated data. Output: Preview link provided to the user.

[0990] Step 8:

[0991] The terminal displays a preview link to the user and provides an interface for checking the generated results. The user checks the generated character image and lines, and if necessary, inputs correction instructions or presses the confirm button. Input: Preview link. Output: User confirmation and correction instructions or confirmation operation.

[0992] Step 9:

[0993] If the user presses the "Confirm" button, the server will save the final generated digital content to the user's account. At the same time, the server will generate a download link or usage link and send it to the device. Input: User's confirmation operation. Output: Saved digital content and generated download link.

[0994] Step 10:

[0995] The terminal provides the download link to the user, allowing the user to download or use the digital content. Input: Download link received from the server. Output: Download link provided to the user.

[0996] Step 11:

[0997] The server authenticates paid users and processes fee withdrawals. A portion of the fee is managed as compensation to the creator. Input: User information and fee information. Output: Fee withdrawal and compensation management for the creator.

[0998] This system allows users to easily generate characters with specific facial expressions and lines by simply entering a prompt, and then acquire and use them as digital content. It also efficiently manages billing for paid services and pays creators.

[0999] (Application example 1)

[1000] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1001] When users post product reviews on online shopping sites, there is a lack of effective ways to convey emotions and product appeal that are difficult to express through text-only reviews. This makes it difficult for other users to visually understand the review content, which can discourage them from purchasing the product. Another issue is that the system for rewarding creators is insufficient, making it difficult to distribute rewards fairly.

[1002] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1003] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting a prompt to the server, an analysis means in the server for analyzing the prompt and passing it to a generative model, a generation means for generating character images and dialogue using the generative model, a generation means for generating original stamps based on reviews on an online shopping site, a preview means for providing users with previews of the generated images and dialogue, a storage means for saving the final generated stamps in the user's account, a provision means for providing the saved stamps as download links or usage links, and a management means for managing paid user authentication, fee deductions, and creator compensation. This enables users to communicate product reviews in a visually appealing way, makes it easier for other users to intuitively understand the review content, and enables fair compensation distribution to creators.

[1004] An "input means" is a device or function that provides an interface for a user to input a prompt.

[1005] The "transmission means" is a device or function that transmits the prompt entered by the user to the server via the network.

[1006] The "analysis means" is a device or function that analyzes the prompts received at the server and converts them into a format that can be understood by the generative model.

[1007] "Generator" means a device or function that uses an AI model to generate character images and dialogue based on the instructions of the analyzed prompt.

[1008] The "preview means" is a device or function that provides an interface that allows the user to check the generated character image and lines.

[1009] "Storage means" refers to a device or function that stores the final generated stamp confirmed by the user in the user's account.

[1010] "Providing means" refers to a device or function that provides saved stamps as links that users can download or use.

[1011] "Management means" refers to a device or function that manages the authentication of paid users, the deduction of fees, and compensation to creators.

[1012] An "online shopping site" is an e-commerce platform that allows users to purchase products online.

[1013] "Review content" refers to information expressed in text or stamps about the user's impressions and evaluations of products purchased on an online shopping site.

[1014] "Custom Stamps" are visual graphic elements specially created by a generative AI model based on user prompts.

[1015] A "creator" is a person or entity that provides the source materials and instructions for content created by a generative AI model.

[1016] This invention relates to a system that uses AI to generate original stamps based on prompts entered by users. Specifically, it generates original stamps based on reviews on online shopping sites and provides a means for users to attach them to reviews and post them.

[1017] System configuration

[1018] This system works in cooperation with three parties: the user, the device (such as a smartphone or tablet), and the server. The main components of the system are as follows:

[1019] 1. Input Method

[1020] The user enters a prompt into the terminal. An example prompt is a smiling character saying, "This product is so useful, I'll never want to let it go!"

[1021] 2. Transmission Method

[1022] The device sends the entered prompt as an API request to the server, where the device communicates with the server over a network connection.

[1023] 3. Analysis method

[1024] The server receives the prompt sent from the device and analyzes it. The analysis method converts the content of the prompt into a format that the generation AI can understand. Specifically, elements such as "smile" and "This product is so convenient, I can't live without it!" are extracted from the prompt text.

[1025] 4. Generation means

[1026] Based on the analysis results, the server issues instructions to a generative AI model to generate a character image and dialogue. This generation is performed using a cloud-based generative AI model (such as OpenAI GPT-3). The generated results are obtained as a character image; for example, a character may be generated that smiles and says, "This product is so convenient, I can't live without it!"

[1027] 5. Preview Methods

[1028] To provide the user with a preview of the generated character image and lines, the server generates a preview link and sends it to the device. The user can open the preview link on the device and check the generated stamp.

[1029] 6. Preservation means

[1030] Once the user approves the generated stamp, the server stores it in the user's account, where it can be used to attach to reviews.

[1031] 7. Means of provision

[1032] The server generates a download link or usage link for the saved stamp and sends it to the device, allowing the user to actually use the stamp when posting a review.

[1033] 8. Control measures

[1034] The server also has the functionality to authenticate paying users, debit fees, and manage creator compensation. Specifically, it processes charges when users use the stamp generation service, and returns a portion of the charges to creators as compensation.

[1035] Specific examples

[1036] For example, when a user writes a product review on an online shopping site, they input a prompt such as, "A smiling character saying, 'This product is so convenient, I can't live without it!'" The device sends this prompt to the server, which analyzes it and gives instructions to the generation AI. The generation AI model generates an image of a smiling character and the words, "This product is so convenient, I can't live without it!", which are provided to the user as a preview link. Once the user confirms and confirms, the final generated stamp is saved to the user's account and a download link is provided. In this way, users can post visually appealing product reviews.

[1037] This invention utilizes a generative AI model based on prompt sentences to visually enrich product reviews on online shopping sites, not only increasing users' desire to purchase but also ensuring fair distribution of rewards to creators.

[1038] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1039] Step 1:

[1040] The user inputs a prompt sentence. For example, the user inputs a prompt such as "This product is so convenient, I can't live without it!" The input prompt is acquired through the input means of the terminal.

[1041] input:

[1042] The prompt text entered by the user.

[1043] output:

[1044] The prompt text captured on the terminal.

[1045] Specific operation:

[1046] The user types the prompt into the text input field on their smartphone or tablet and presses the submit button.

[1047] Step 2:

[1048] The terminal transmits the acquired prompt text to the server as an API request. The prompt text is transmitted to the server via the network using a transmission means.

[1049] input:

[1050] The prompt text captured on the terminal.

[1051] output:

[1052] The prompt text sent to the server.

[1053] Specific operation:

[1054] The terminal converts the prompt text into an API request format and sends it to the server via an HTTP request.

[1055] Step 3:

[1056] The server analyzes the received prompt text. Using the analysis method, the character's facial expression and lines are extracted from the prompt text. For example, elements such as "smile" and "This product is so convenient, I can't live without it!" are extracted.

[1057] input:

[1058] The prompt text sent to the server.

[1059] output:

[1060] Extracted facial expressions and dialogue elements.

[1061] Specific operation:

[1062] The server runs natural language processing algorithms to parse the prompt and extract key keywords and phrases.

[1063] Step 4:

[1064] The server passes the analysis results to a generative AI model, which generates a character image and dialogue. Using a generation method, the generative AI model creates a character image based on this information. For example, an image may be generated that includes a smiling character and the text, "This product is so useful, I can't live without it!"

[1065] input:

[1066] Extracted facial expressions and dialogue elements.

[1067] output:

[1068] Generated character images and lines.

[1069] Specific operation:

[1070] The server converts the analyzed data into the input format for the generative AI model, sends a request to the generative AI model, and receives the generated image data.

[1071] Step 5:

[1072] The server provides the generated character image and lines to the terminal as a preview link, and generates a preview link using a preview means so that the user can check the image, and sends the preview link to the terminal.

[1073] input:

[1074] Generated character images and lines.

[1075] output:

[1076] The preview link sent to your device.

[1077] Specific operation:

[1078] The server temporarily stores the generated image in cloud storage, generates a link to it, and sends the link to the terminal as an HTTP response.

[1079] Step 6:

[1080] The user checks the preview link and approves the stamp. After opening the preview link on their device and checking the generated stamp, they press the confirm button to approve it.

[1081] input:

[1082] The preview link sent to your device.

[1083] output:

[1084] User approval operations.

[1085] Specific operation:

[1086] Users can click on the preview link on their device and use the interface to review and confirm the generated stamp in their browser or app.

[1087] Step 7:

[1088] The server stores the final generated stamp in the user's account. A storage means is used to store the generated stamp in the user's database.

[1089] input:

[1090] User approval operations.

[1091] output:

[1092] Stickers saved in the user's account.

[1093] Specific operation:

[1094] The server queries the database associated with the user's account to store the generated stamp.

[1095] Step 8:

[1096] The server provides a download link or a usage link for the stored stamp. The server generates a download link using the providing means and transmits it to the terminal.

[1097] input:

[1098] Stickers saved in the user's account.

[1099] output:

[1100] The download or usage link sent to your device.

[1101] Specific operation:

[1102] The server generates a downloadable URL for the stamp file for the client and sends the URL information to the device.

[1103] Step 9:

[1104] The server authenticates paid users, deducts fees, and manages rewards to creators. Using a management means, the server performs the authentication process for paid users, deducts usage fees, and transfers a portion of the fees to the creator's account as rewards.

[1105] input:

[1106] Paid users' account information and usage information of generated stamps.

[1107] output:

[1108] Completing billing transactions and transferring rewards to creators.

[1109] Specific operation:

[1110] The server sends the paying user's payment information to the payment provider, deducts the usage fee, then calculates the creator's remuneration and transfers the remuneration to the creator's account.

[1111] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1112] This invention combines a system that uses generation AI to customize the character's facial expressions and lines based on prompts entered by the user, generating original stamps, and an emotion engine that recognizes the user's emotions. Below, we will explain the program processing of this system in natural language.

[1113] Overall system overview

[1114] This system works in cooperation with four parties: the user, the device, the server, and the emotion engine. The user inputs a prompt from the device, and the emotion engine recognizes the user's emotion. The server analyzes the prompt and creates a customized stamp using a generation AI.

[1115] Program processing

[1116] First, the user accesses the custom stamp creation screen within the LINE app, enters a prompt such as "a character saying hello with a smile," and presses the send button. At this time, the text entered by the user, as well as the voice and facial expressions used, are analyzed by the emotion engine.

[1117] The device creates an API request based on the prompt and emotional information entered by the user and sends the request to the server.

[1118] The server receives the prompt and emotion information sent from the terminal and starts processing to analyze the content of the prompt. The analysis means converts the content of the prompt into a format that the generative model can understand. Furthermore, the emotion data analyzed by the emotion engine provides supplementary information to the prompt, generating a stamp that is more suited to the user's emotion.

[1119] The emotion engine recognizes the user's emotions from their facial expressions and voice, and complements or modifies prompts based on that emotional data. For example, if the user is smiling, a warmer tone might be added to a prompt like "Hello."

[1120] The generative AI generates character expressions and lines based on the analyzed instructions and emotional data. For example, if the prompt is "Smile and say hello," and the emotion engine determines that the user is very happy, the generated character's smile will be brighter and the "hello" line will have a more joyful nuance.

[1121] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[1122] The device will use the preview link to display a preview screen of the generated stamp to the user. The user can check this preview and, if necessary, enter new prompts or emotion data to request corrections. If no corrections are required, the user presses the "Confirm" button.

[1123] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated.

[1124] The device will display a download link, allowing users to download the stamp or use it within the LINE app.

[1125] The server also authenticates paying users and deducts the associated fees from their accounts, a portion of which is managed as a reward for the creators and later deposited into their accounts.

[1126] Specific examples

[1127] For example, consider the prompt "I want a sleeping character to say goodnight." The user enters the prompt, and the device sends it to the server. The server analyzes the prompt and emotion data, extracting elements such as "sleeping character" and "goodnight." The emotion engine recognizes the user's calm emotion, and generates a more relaxed facial expression and the phrase "goodnight" based on that.

[1128] The AI ​​generates a character and dialogue based on the specified content and sends it back to the server. The server temporarily saves it and provides the user with a preview link. After the user confirms it, they press the confirm button, and the final generated stamp is saved to their account and a download link is provided. Users can click this link to download and use the stamp.

[1129] In this way, the system generates original stamps based on user prompts and emotional data, supporting quick and intuitive communication, and also supports creators' activities by providing rewards to them.

[1130] The processing flow will be explained below.

[1131] Step 1:

[1132] Users access the custom stamp creation screen within the LINE app, input a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are also recorded by the emotion engine.

[1133] Step 2:

[1134] The device sends the input prompt and emotion data to the server as an API request.

[1135] Step 3:

[1136] The server receives the prompt and emotion data sent from the terminal and starts a process to analyze the prompt content and emotion data. The analysis means converts the prompt content into a format that can be understood by the generative model.

[1137] Step 4:

[1138] The emotion engine recognizes the user's emotions from their facial expressions and voice data, and provides the analysis results to the server. For example, when the user is smiling, emotion data of "joy" is generated.

[1139] Step 5:

[1140] The server complements or modifies the prompt using the emotion data provided by the emotion engine and passes it to the generative model, adding elements based on the user's emotions.

[1141] Step 6:

[1142] The AI ​​then generates the character's facial expressions and lines based on the analyzed prompt and emotion data. For example, if the emotion data for "hello with a smile" and "joy" are given, the generated character's smile will be brighter and the "hello" line will have a more joyful nuance.

[1143] Step 7:

[1144] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[1145] Step 8:

[1146] The device will use the preview link to display a preview screen of the generated stamp to the user. The user can check this preview and, if necessary, enter new prompts or emotion data to request corrections. If no corrections are required, the user presses the "Confirm" button.

[1147] Step 9:

[1148] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link is generated and sent to the device.

[1149] Step 10:

[1150] The device will display a download link, allowing users to download the stamp or use it within the LINE app.

[1151] Step 11:

[1152] The server authenticates the paying user and deducts the associated fees from the user's account, and a portion of the fees is managed as a reward for the creator and deposited into the creator's account.

[1153] In this way, a system is realized that generates original stamps that are optimal and intuitive for each user based on the user's prompts and emotional data, and also supports creators' activities by providing appropriate rewards to creators.

[1154] Example 2

[1155] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1156] Previous systems for generating customized stickers were able to generate character expressions and lines based on user prompts, but they were unable to customize characters based on the user's emotions. This made it difficult to generate stickers that fully reflected the user's intentions. Furthermore, the generation process was complex, potentially resulting in a poor user experience.

[1157] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1158] In this invention, the server includes an analysis means for analyzing the prompt and emotion data and inputting them into a generative model, a preview means for providing the user with a preview of the generated image and dialogue, and a storage means for saving the final generated stickers in the user's account, thereby enabling quick and intuitive generation of customized stickers that take the user's emotions into account.

[1159] "User" refers to an individual or organization that uses the System to generate customized stamps.

[1160] An "input means" is an interface through which a user inputs prompts and other data into the system.

[1161] The "transmission means" is a function for transmitting a prompt input via the input means to the server.

[1162] The "analysis means" is a function for analyzing prompts and emotion data in the server and inputting them into the generative model.

[1163] A "generative model" is an AI algorithm that generates character images and dialogue based on input data.

[1164] "Generation means" is a function for generating character images and lines using a generative model.

[1165] The "preview means" is a function for providing the user with a preview of the generated character image and lines.

[1166] "Storage means" is a function for saving the final generated stamp in the user's account.

[1167] The "means of provision" is a function for providing saved stamps to users as download links or usage links.

[1168] The "management means" is a function for managing authentication of paying users, withdrawal of fees, and remuneration to content creators.

[1169] "Emotional data" refers to emotional information extracted from a user's facial expressions and voice.

[1170] This invention is a system that uses a generative AI model to customize character expressions and lines based on prompts entered by the user, generating original stamps. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it achieves even more precise customization.

[1171] Hardware and software used

[1172] 1. The user accesses the LINE application using a device such as a smartphone or tablet.

[1173] 2. The device makes an API request to communicate with the server via its internet connection.

[1174] 3. The server utilizes high-performance cloud servers to run generative AI models (e.g., OpenAI's GPT-3) and emotion engines (e.g., Affectiva Emotion AI).

[1175] 4. The emotion engine includes hardware and software that uses the device's camera and microphone to analyze the user's facial expressions and voice.

[1176] Data processing and calculation flow

[1177] Users access the "Customized Stamp Creation Screen" within the LINE app, enter a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are simultaneously analyzed by the emotion engine.

[1178] The device sends the prompt and emotion data entered by the user to the server as an API request, which processes data acquired from the camera and microphone and generates appropriate emotion data.

[1179] The server analyzes the data received from the device and converts the prompts into a format that the generative AI model can understand. It also analyzes the emotional data and adds additional information to the prompts. This analysis method provides more detailed instructions to the generative model.

[1180] The AI ​​then generates character expressions and lines based on the analyzed instructions and emotional data. For example, in response to the prompt "A character saying hello with a smile," the generated character's smile will become brighter and the lines will have a more joyful nuance.

[1181] The server receives the generated character data, temporarily stores it, and then provides the user with a preview link and sends an interface to the device for viewing and modifying the generated stamp.

[1182] The device will use the preview link to display a preview of the generated stamp to the user. The user can check the preview and, if necessary, enter new prompts and emotion data and submit it again. If no corrections are required, the user can press the "Confirm" button.

[1183] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated.

[1184] The device will display the generated download link to the user, allowing them to download the stamp or use it within the LINE app.

[1185] Specific examples

[1186] For example, consider the prompt "I want a sleeping character to say goodnight." The user enters the prompt, and the device sends it to the server. The server analyzes the prompt and emotion data, extracting elements such as "sleeping character" and "goodnight." The emotion engine recognizes the user's calm emotion, and generates a more relaxed facial expression and the phrase "goodnight" based on that.

[1187] Specific prompt examples:

[1188] I want my sleeping character to say goodnight

[1189] In this way, the system not only quickly and intuitively generates original stamps based on user prompts and emotional data, but also customizes them to reflect the user's emotions.

[1190] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1191] Step 1:

[1192] Users access the LINE application using a device such as a smartphone or tablet. They access the "Customized Stamp Creation Screen," enter a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are also analyzed by the emotion engine.

[1193] Input: User prompts, facial expressions, and voice data

[1194] Output: Prompt and emotion data sent to the device

[1195] Specific behavior:

[1196] A user enters text using the smartphone keyboard.

[1197] Data collection from cameras and microphones.

[1198] Step 2:

[1199] The device converts the user's input prompts and facial and voice data acquired from the camera and microphone into API requests and sends them to the server, where they are processed to generate appropriate emotion data.

[1200] Input: User prompts, facial expressions, and voice data

[1201] Output: API request sent to the server

[1202] Specific behavior:

[1203] Analyzes data from the camera and microphone to generate emotion labels.

[1204] Converts data into packets and sends them.

[1205] Step 3:

[1206] The server receives prompts and emotional data sent from the device, analyzes the content of the prompts, and converts them into a format that the generative AI model can understand. At the same time, it analyzes the emotional data and generates complementary information according to the prompts.

[1207] Input: Prompt and emotion data received from the device

[1208] Output: Parsed data to a generative AI model

[1209] Specific behavior:

[1210] Prompt text analysis (tokenization and context analysis)

[1211] Emotion data analysis (emotion labeling)

[1212] Step 4:

[1213] The server sends the analyzed data to the generation AI, which converts the data into a format that is easy for the generation AI to understand.

[1214] Input: Parsed prompt and sentiment data

[1215] Output: Formatted data sent to the generative AI

[1216] Specific behavior:

[1217] Data format conversion

[1218] Creating and sending an API request to the generation AI

[1219] Step 5:

[1220] The generative AI generates facial expressions and lines for the character based on the data it receives. For example, if the emotion engine determines that the user is happy in addition to the prompt "Smile and say hello," the character will have a brighter smile.

[1221] Input: Formatted data sent from the server

[1222] Output: Generated character and dialogue data

[1223] Specific behavior:

[1224] Running inference on a model

[1225] Formatting the generated results

[1226] Step 6:

[1227] The server temporarily stores the character data received from the generated AI, generates a preview link for the user to view, and sends it to the device.

[1228] Input: Character data received from the generation AI

[1229] Output: Preview link for user confirmation

[1230] Specific behavior:

[1231] Temporarily save to database

[1232] Generate and send a preview link

[1233] Step 7:

[1234] The device receives the preview link and displays a preview screen of the generated stamp to the user, which the user can confirm.

[1235] Input: Preview link received from the server

[1236] Output: The preview screen that the user sees

[1237] Specific behavior:

[1238] Preview screen drawing

[1239] Screen transition by clicking a link

[1240] Step 8:

[1241] The user checks the preview and, if satisfied with the stamp, presses the "Confirm" button. If corrections are needed, they enter new prompt and emotion data and submit again.

[1242] Input: User confirmation and correction instructions

[1243] Output: Confirm or correct instruction

[1244] Specific behavior:

[1245] Click the Confirm button

[1246] Re-enter correction prompt

[1247] Step 9:

[1248] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated and sent to the device.

[1249] Input: User confirmation instructions

[1250] Output: Download link or usage link

[1251] Specific behavior:

[1252] Final save to database

[1253] Link Generation and Notifications

[1254] Step 10:

[1255] The device will display the download link received from the server to the user, allowing the user to download the stamp or use it within the LINE app.

[1256] Input: Download link received from the server

[1257] output: the download link that is displayed to the user

[1258] Specific behavior:

[1259] View download links

[1260] Click on the link to download

[1261] (Application example 2)

[1262] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1263] There is a demand for improved customer support and user experience in virtual stores, but conventional systems have difficulty recognizing user emotions in real time and responding appropriately.In addition, the content generated is not optimized based on user emotions, which leads to a decrease in user satisfaction.

[1264] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1265] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting prompts to the server, an analysis means in the server for analyzing the prompts and passing them to a generative model, a generation means for generating character images and dialogue using the generative model, a preview means for providing the generated images and dialogue as previews to the user, an emotion recognition means for recognizing the user's emotion and using the emotion data to complement or modify the prompt, an optimization means for optimizing the generated character images and dialogue to match the user's emotion, a storage means for saving the final generated stamps in the user's account, a provision means for providing the saved stamps as a download link or a usage link, and a management means for managing paid user authentication, fee deductions, and creator compensation. This makes it possible to provide optimal customer support tailored to the user's emotions, which is expected to improve the user experience and increase satisfaction.

[1266] "User" refers to an individual or organization that uses this system.

[1267] "Input means" refers to a means that provides an interface for a user to input a prompt.

[1268] "Transmission means" refers to a means for transmitting the input prompt to the server.

[1269] "Analysis means" refers to means for analyzing prompts on the server and converting them into a format that conforms to the generative model.

[1270] The "generation means" refers to a means for generating a character image and lines based on the analyzed prompt.

[1271] "Preview means" refers to a means for temporarily displaying the generated character image and dialogue to the user.

[1272] "Emotion recognition means" refers to a means of analyzing the user's emotions and reflecting that data in prompts.

[1273] "Optimization means" refers to a means for adjusting the generated character images and lines based on emotional data.

[1274] "Storage Means" means the means by which the final generated stamps are stored in the User's account.

[1275] "Providing means" refers to the means of providing saved stamps as a download link or a usage link.

[1276] "Management means" refers to the means for authenticating paying users, deducting fees, and managing creator compensation.

[1277] The system of the present invention is for providing customer support within a virtual store based on user input. Specific embodiments will be described below.

[1278] Overall system configuration

[1279] The system consists of the following main components:

[1280] User devices (smart glasses, head-mounted displays, etc.)

[1281] server

[1282] Emotion Recognition Engine

[1283] Generative AI Models

[1284] Detailed Description of the Embodiments

[1285] 1. User device operation

[1286] The user enters the virtual store and puts on smart glasses or a head-mounted display. The device captures the user's facial expressions and voice tone in real time and sends the data to the server. At this point, the user enters a prompt, such as "Please tell me how to use the product."

[1287] 2. Server Processing

[1288] The server analyzes the prompt and emotion data received from the user's device. First, the prompt text is converted into a format that can be passed to the generative AI model using an analytical method. Next, the emotion recognition engine analyzes the user's emotion data and uses that information to complete or modify the prompt.

[1289] 3. Operation of the Emotion Recognition Engine

[1290] The emotion recognition engine analyzes the user's facial expressions and voice to determine their emotions, and provides the data to the server. This data plays an important role in the generation process of the generative AI model. For example, if the user is feeling anxious, a gentle-spoken character will be generated based on this emotional data.

[1291] 4. Processing generative AI models

[1292] The generative AI model generates a character image and dialogue based on the analyzed prompt and emotional data. For example, a character might say, "Don't worry. We'll explain in detail how to use this product." During this generation process, the character's facial expression is also adjusted based on the emotional data.

[1293] 5. Providing the generated results

[1294] The generated character image and dialogue are provided to the user as a preview by the server. The user can check this preview and make any necessary corrections. The corrections are also reflected again through the emotion recognition engine and generative AI model.

[1295] 6. Final storage and provision

[1296] The generated result confirmed by the user will be saved in the user's account by the server, and the saved stamp will be provided as a download link or a usage link.

[1297] Hardware and software used

[1298] Hardware:

[1299] Smart glasses / head-mounted displays (e.g. Microsoft HoloLens)

[1300] High-performance servers (cloud-based servers, etc.)

[1301] software:

[1302] Emotion recognition engines (e.g., Affectiva's Emotion AI)

[1303] Generative AI models (e.g., OpenAI GPT-4)

[1304] Virtual reality production tools (e.g. Unity)

[1305] Specific prompt examples

[1306] For example, if a user says, "I don't know how to use this product," the emotion engine recognizes the user's anxiety. The generative AI model creates a "character that explains things clearly" and displays a line such as, "Don't worry. I'll explain in detail how to use this product." This series of steps allows users to comfortably receive customer support in a virtual store.

[1307] As described above, the system of the present invention provides optimal customer support that is tailored to the user's emotions, thereby improving the user experience.

[1308] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1309] Step 1:

[1310] A user accesses a virtual store and puts on smart glasses or a head-mounted display. The user inputs a prompt such as "Please tell me how to use the product." The input, along with the user's facial expressions and voice tone, is sent from the device to the server.

[1311] Step 2:

[1312] The server analyzes the prompt, facial expression data, and voice tone received from the terminal using an analysis means, and generates a prompt and emotion data in text format as the analysis results, since the analyzed data will be used in the next step.

[1313] Step 3:

[1314] The server sends the parsed prompt and emotion data to the emotion recognition engine, which analyzes the user's emotional state and sends the data back to the server. The output of emotion recognition can be, for example, the user's anxiety index and the reason for it.

[1315] Step 4:

[1316] The server receives emotional data from the emotion recognition engine and uses it to complement or modify the prompts. For example, if the anxiety index is high, it will modify the prompts to generate a "character that explains things clearly."

[1317] Step 5:

[1318] The server sends the modified prompt and emotion data to the generative AI model, which generates a character image and dialogue based on this data. During this generation process, the character's facial expressions and dialogue are adjusted based on the emotion data. The resulting character image and dialogue are obtained.

[1319] Step 6:

[1320] The generated character image and dialogue are provided to the user as a preview by the server. The preview screen is displayed on the user's device, and the user can check it and enter correction prompts as necessary.

[1321] Step 7:

[1322] If the user is satisfied with the preview and confirms it, the device sends the information to the server, which saves the final stamp to the user's account. The saved stamp is then provided as a download link or a link to use.

[1323] Step 8:

[1324] If the user is a paid user, the server will authenticate them, deduct the fee, and manage the creator's compensation. This ensures that the user's provision and the creator's compensation are managed appropriately.

[1325] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1326] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1327] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1328] [Fourth embodiment]

[1329] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1330] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1331] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1332] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1333] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1334] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1335] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1336] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1337] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1338] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1339] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1340] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1341] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1342] This invention is a system that uses a generation AI to customize the character's facial expressions and lines based on prompts entered by the user, and generates original stamps. Below, we will explain the program processing of this system in natural language.

[1343] Overall system overview

[1344] The system works in collaboration between the user, the device, and the server. The user inputs a prompt from the device, the server analyzes the prompt, and creates a customized stamp using a generative AI.

[1345] Program processing

[1346] First, the user accesses the custom stamp creation screen within the LINE app, where they input a prompt such as "a character smiling and saying hello." The input prompt is then sent from the device to the server.

[1347] The device is responsible for sending the input prompt to the server as an API request, which transmits the prompt content to the server.

[1348] The server receives the prompt sent from the device and starts a process to analyze the content of the prompt. The analysis means converts the content of the prompt into a format that the generation AI can understand. In this analysis, elements of the character's facial expressions and dialogue are extracted, and appropriate generation instructions are passed to the generation AI.

[1349] The AI ​​then generates the character's facial expressions and lines based on the analyzed instructions. For example, if a prompt such as "Smile and say hello" is entered, the AI ​​adds a speech bubble with the words "Hello" to the smiling character image. The generated results are then sent back to the server.

[1350] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[1351] The device displays a preview link, allowing the user to check the generated character image and dialogue. If the user wishes to make corrections, they can enter a new prompt and submit it again. If no corrections are required, the user presses the "Confirm" button.

[1352] The server will save the final stamp generated by the user in the user's account. After this process is complete, a download link or usage link will be generated and sent to the device.

[1353] The device will provide the user with a download link, allowing them to download the stickers or use them within the LINE app, allowing users to easily create and use original stickers freely.

[1354] The server also authenticates paying users and deducts the associated fees from their accounts, a portion of which is kept as compensation for creators and later deposited into their accounts.

[1355] Specific examples

[1356] For example, consider the case where a prompt is entered as "I want a sleeping character to say goodnight." The user enters the prompt and the device sends it to the server. The server analyzes the prompt and extracts elements such as "sleeping character" and "goodnight." Based on the analysis results, the generation AI generates a sleeping character and a "goodnight" speech bubble, which are sent back to the server. The server temporarily saves this and provides the user with a preview link. After the user confirms, they press the confirm button, and the final generated stamp is saved in the user's account and a download link is provided. The user can click this link to download and use the stamp.

[1357] In this way, the system generates original stickers based on user prompts, supporting quick and intuitive communication, and also supports creators' activities by providing rewards to them.

[1358] The processing flow will be explained below.

[1359] Step 1:

[1360] Users access the custom stamp creation screen within the LINE app, enter a prompt such as "a character smiling and saying hello," and press the send button.

[1361] Step 2:

[1362] The device creates an API request from the input prompt and sends the request to the server.

[1363] Step 3:

[1364] The server receives the prompt sent from the terminal and starts a process for analyzing the content of the prompt, which is then converted by the analyzing means into a format that can be understood by the generative model.

[1365] Step 4:

[1366] The server passes the parsed prompts to the generative model, which triggers the generation process, generating the character's facial expressions and dialogue based on the parsed instructions.

[1367] Step 5:

[1368] The AI ​​generates a character image based on the prompt and adds the specified dialogue. For example, in response to the prompt "Smile and say hello," it adds a speech bubble saying "Hello" to a smiling character image.

[1369] Step 6:

[1370] The server temporarily stores the generated character image and dialogue, and generates a preview link that is sent to the user's device.

[1371] Step 7:

[1372] The device uses the preview link received from the server to display a preview screen of the generated stamp to the user, who then checks the preview.

[1373] Step 8:

[1374] The user can check the preview and, if necessary, enter a new prompt to request corrections. If no corrections are required, the user presses the "Confirm" button.

[1375] Step 9:

[1376] After the user presses the confirm button, the server saves the final stamp to the user's account. Once the saving process is complete, a download link or usage link will be generated.

[1377] Step 10:

[1378] The device will display the download link received from the server, allowing the user to download the stamp or use it within the LINE app.

[1379] Step 11:

[1380] The server authenticates the paying user and deducts the relevant fee from the user's account, and also manages a portion of the fee as a reward for the creator and processes it to be transferred to the creator's account.

[1381] Through these concrete steps, users can easily create and use original stamps, and creators are also rewarded appropriately.

[1382] Example 1

[1383] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1384] Until now, there have been limited systems that allow users to easily create and share their own digital content. In particular, the process for users to create characters with specific facial expressions and lines is complicated and often requires technical knowledge. Furthermore, for paid services, managing usage fees and paying creators is cumbersome. A system that solves these problems is needed.

[1385] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1386] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting a prompt to the information processing device, an analysis means for analyzing the prompt in the information processing device and passing it to the generation engine, a generation means for generating image data and text data using the generation engine, a preview means for providing the generated image data and text data as a preview to the user, a storage means for saving the final generated digital content in the user's account, a provision means for providing the saved digital content as a download link or a usage link, and a management means for managing paid user authentication, fee deductions, and creator compensation. This allows users to easily input prompt text to generate characters with specific facial expressions and lines, and easily obtain and use the final digital content. It also allows for efficient billing management for paid services and payment of compensation to creators.

[1387] An "input means" is a device or method by which a user inputs data or commands into a system.

[1388] "Transmission means" refers to a device or method for transmitting input data to another device or system.

[1389] An "analysis means" is a device or method for analyzing input data, extracting meaning, and converting it into a format suitable for further processing.

[1390] A "generator" is a device or method for generating new data or content based on the analyzed data.

[1391] The "preview means" is a device or method for temporarily displaying generated data or content so that the user can check it.

[1392] "Storage means" refers to a device or method for permanently storing generated data or content.

[1393] "Providing means" refers to a device or method for providing stored data or content to a user.

[1394] "Management means" refers to a device or method for authenticating paying users, debiting fees, and managing creator rewards.

[1395] A "generation engine" is software or hardware that generates new data or content from input data.

[1396] An "information processing device" is a computer or network facility for inputting, outputting, analyzing, storing, and providing data.

[1397] "Digital content" means information such as text, images, audio, and video that is stored and provided in electronic form.

[1398] A "prompt" is an instruction or question that a user enters into a system.

[1399] "User" means any person or entity that uses the System to generate, view, or store digital content.

[1400] This invention relates to a system that generates original digital content by customizing character expressions and dialogue using a generative AI model based on prompts entered by the user. The program processing of this system is explained below in natural language. In this system, the user, terminal, and server work together.

[1401] First, a user accesses a custom stamp creation screen and inputs a prompt to generate a character with a specific facial expression and dialogue. Specific examples include prompts such as "a character smiling and saying hello" or "a sleeping character saying goodnight." This input is performed via a terminal.

[1402] The device then sends the user-entered prompt as an API request to the server. This request data includes the user ID and the entered prompt text. The device is responsible for converting the request into the appropriate data format so that it can be processed correctly.

[1403] The server receives the prompt sent from the device and begins the analysis process. The server implements natural language processing (NLP) technology to analyze the content of the prompt and extract important elements (e.g., the character's facial expressions and lines). The information obtained from this analysis step is converted into a format that the generative AI model can understand.

[1404] The generative AI model generates the character's facial expressions and lines based on the analysis results passed from the server. Specific generative AI models used are models capable of understanding natural language and generating images (e.g., GPT-3 and DALL-E). If the prompt is "a character smiling and saying hello," the generative AI model generates an image of a smiling character and a speech bubble that says "hello."

[1405] The server receives the generated character image and lines and temporarily stores them. Next, the server generates a link to provide the user with a preview of the generated results. This link is a URL to a page that displays the generated character image.

[1406] The device presents a preview link to the user, allowing the user to check the generated character image. The user can check the generated result and input correction instructions as necessary, or press the OK button to save the generated result as final digital content.

[1407] If the user presses the "Confirm" button, the server saves the generated result to the user's account. After saving, the server generates a download link or usage link and sends it to the device.

[1408] Finally, the device provides the user with a download link, allowing them to download the digital content or use it within the LINE app. For paid users, the server also performs authentication and deducts the fee. A portion of this fee is managed as compensation to the creator and later transferred to the creator's account.

[1409] In this way, the system generates original digital content based on user prompts, providing it quickly and intuitively, and also supports creative activities by including compensation management for creators.

[1410] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1411] Step 1:

[1412] The user accesses the custom stamp creation screen within the LINE app and enters a prompt text. This input is in the form of "a character smiling and saying hello." The user's input is sent to the device as text data. Input: Prompt text. Output: Prompt text sent to the device.

[1413] Step 2:

[1414] The terminal receives the prompt text entered by the user and sends it to the server as an API request. The terminal converts the prompt text into an appropriate data format (for example, JSON format) and sends it to the server using an HTTP request. Input: Prompt text received from the user. Output: Prompt text sent to the server.

[1415] Step 3:

[1416] The server receives the prompt sent from the device and begins the analysis process. The server uses natural language processing (NLP) technology to analyze the content of the prompt and extract important elements (facial expressions, lines). Input: Prompt received from the device. Output: Analyzed prompt information (facial expressions, lines, etc.).

[1417] Step 4:

[1418] The server creates generation instructions to be passed to the generative AI model based on the analysis results. The generation instructions are sent to the generative AI model as structured data (e.g., JSON). Input: Parsed prompt information. Output: Generation instructions to the generative AI model.

[1419] Step 5:

[1420] The generative AI model generates character expressions and lines based on the generation instructions received from the server. The generative AI model uses a generation engine such as GPT-3 or DALL-E. The generated result is a combination of image data and text data. Input: Generation instructions received from the server. Output: Generated character image and lines.

[1421] Step 6:

[1422] The generative AI model returns the generated character image and dialogue to the server. The server receives the data and temporarily stores it. Input: Character image and dialogue received from the generative AI model. Output: Temporarily stored generated data.

[1423] Step 7:

[1424] The server generates a preview link to allow the user to check the generated results. This link is provided to the user and contains the URL of a page that previews the generated character image. Input: Temporarily saved generated data. Output: Preview link provided to the user.

[1425] Step 8:

[1426] The terminal displays a preview link to the user and provides an interface for checking the generated results. The user checks the generated character image and lines, and if necessary, inputs correction instructions or presses the confirm button. Input: Preview link. Output: User confirmation and correction instructions or confirmation operation.

[1427] Step 9:

[1428] If the user presses the "Confirm" button, the server will save the final generated digital content to the user's account. At the same time, the server will generate a download link or usage link and send it to the device. Input: User's confirmation operation. Output: Saved digital content and generated download link.

[1429] Step 10:

[1430] The terminal provides the download link to the user, allowing the user to download or use the digital content. Input: Download link received from the server. Output: Download link provided to the user.

[1431] Step 11:

[1432] The server authenticates paid users and processes fee withdrawals. A portion of the fee is managed as compensation to the creator. Input: User information and fee information. Output: Fee withdrawal and compensation management for the creator.

[1433] This system allows users to easily generate characters with specific facial expressions and lines by simply entering a prompt, and then acquire and use them as digital content. It also efficiently manages billing for paid services and pays creators.

[1434] (Application example 1)

[1435] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1436] When users post product reviews on online shopping sites, there is a lack of effective ways to convey emotions and product appeal that are difficult to express through text-only reviews. This makes it difficult for other users to visually understand the review content, which can discourage them from purchasing the product. Another issue is that the system for rewarding creators is insufficient, making it difficult to distribute rewards fairly.

[1437] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1438] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting a prompt to the server, an analysis means in the server for analyzing the prompt and passing it to a generative model, a generation means for generating character images and dialogue using the generative model, a generation means for generating original stamps based on reviews on an online shopping site, a preview means for providing users with previews of the generated images and dialogue, a storage means for saving the final generated stamps in the user's account, a provision means for providing the saved stamps as download links or usage links, and a management means for managing paid user authentication, fee deductions, and creator compensation. This enables users to communicate product reviews in a visually appealing way, makes it easier for other users to intuitively understand the review content, and enables fair compensation distribution to creators.

[1439] An "input means" is a device or function that provides an interface for a user to input a prompt.

[1440] The "transmission means" is a device or function that transmits the prompt entered by the user to the server via the network.

[1441] The "analysis means" is a device or function that analyzes the prompts received at the server and converts them into a format that can be understood by the generative model.

[1442] "Generator" means a device or function that uses an AI model to generate character images and dialogue based on the instructions of the analyzed prompt.

[1443] The "preview means" is a device or function that provides an interface that allows the user to check the generated character image and lines.

[1444] "Storage means" refers to a device or function that stores the final generated stamp confirmed by the user in the user's account.

[1445] "Providing means" refers to a device or function that provides saved stamps as links that users can download or use.

[1446] "Management means" refers to a device or function that manages the authentication of paid users, the deduction of fees, and compensation to creators.

[1447] An "online shopping site" is an e-commerce platform that allows users to purchase products online.

[1448] "Review content" refers to information expressed in text or stamps about the user's impressions and evaluations of products purchased on an online shopping site.

[1449] "Custom Stamps" are visual graphic elements specially created by a generative AI model based on user prompts.

[1450] A "creator" is a person or entity that provides the source materials and instructions for content created by a generative AI model.

[1451] This invention relates to a system that uses AI to generate original stamps based on prompts entered by users. Specifically, it generates original stamps based on reviews on online shopping sites and provides a means for users to attach them to reviews and post them.

[1452] System configuration

[1453] This system works in cooperation with three parties: the user, the device (such as a smartphone or tablet), and the server. The main components of the system are as follows:

[1454] 1. Input Method

[1455] The user enters a prompt into the terminal. An example prompt is a smiling character saying, "This product is so useful, I'll never want to let it go!"

[1456] 2. Transmission Method

[1457] The device sends the entered prompt as an API request to the server, where the device communicates with the server over a network connection.

[1458] 3. Analysis method

[1459] The server receives the prompt sent from the device and analyzes it. The analysis method converts the content of the prompt into a format that the generation AI can understand. Specifically, elements such as "smile" and "This product is so convenient, I can't live without it!" are extracted from the prompt text.

[1460] 4. Generation means

[1461] Based on the analysis results, the server issues instructions to a generative AI model to generate a character image and dialogue. This generation is performed using a cloud-based generative AI model (such as OpenAI GPT-3). The generated results are obtained as a character image; for example, a character may be generated that smiles and says, "This product is so convenient, I can't live without it!"

[1462] 5. Preview Methods

[1463] To provide the user with a preview of the generated character image and lines, the server generates a preview link and sends it to the device. The user can open the preview link on the device and check the generated stamp.

[1464] 6. Preservation means

[1465] Once the user approves the generated stamp, the server stores it in the user's account, where it can be used to attach to reviews.

[1466] 7. Means of provision

[1467] The server generates a download link or usage link for the saved stamp and sends it to the device, allowing the user to actually use the stamp when posting a review.

[1468] 8. Control measures

[1469] The server also has the functionality to authenticate paying users, debit fees, and manage creator compensation. Specifically, it processes charges when users use the stamp generation service, and returns a portion of the charges to creators as compensation.

[1470] Specific examples

[1471] For example, when a user writes a product review on an online shopping site, they input a prompt such as, "A smiling character saying, 'This product is so convenient, I can't live without it!'" The device sends this prompt to the server, which analyzes it and gives instructions to the generation AI. The generation AI model generates an image of a smiling character and the words, "This product is so convenient, I can't live without it!", which are provided to the user as a preview link. Once the user confirms and confirms, the final generated stamp is saved to the user's account and a download link is provided. In this way, users can post visually appealing product reviews.

[1472] This invention utilizes a generative AI model based on prompt sentences to visually enrich product reviews on online shopping sites, not only increasing users' desire to purchase but also ensuring fair distribution of rewards to creators.

[1473] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1474] Step 1:

[1475] The user inputs a prompt sentence. For example, the user inputs a prompt such as "This product is so convenient, I can't live without it!" The input prompt is acquired through the input means of the terminal.

[1476] input:

[1477] The prompt text entered by the user.

[1478] output:

[1479] The prompt text captured on the terminal.

[1480] Specific operation:

[1481] The user types the prompt into the text input field on their smartphone or tablet and presses the submit button.

[1482] Step 2:

[1483] The terminal transmits the acquired prompt text to the server as an API request. The prompt text is transmitted to the server via the network using a transmission means.

[1484] input:

[1485] The prompt text captured on the terminal.

[1486] output:

[1487] The prompt text sent to the server.

[1488] Specific operation:

[1489] The terminal converts the prompt text into an API request format and sends it to the server via an HTTP request.

[1490] Step 3:

[1491] The server analyzes the received prompt text. Using the analysis method, the character's facial expression and lines are extracted from the prompt text. For example, elements such as "smile" and "This product is so convenient, I can't live without it!" are extracted.

[1492] input:

[1493] The prompt text sent to the server.

[1494] output:

[1495] Extracted facial expressions and dialogue elements.

[1496] Specific operation:

[1497] The server runs natural language processing algorithms to parse the prompt and extract key keywords and phrases.

[1498] Step 4:

[1499] The server passes the analysis results to a generative AI model, which generates a character image and dialogue. Using a generation method, the generative AI model creates a character image based on this information. For example, an image may be generated that includes a smiling character and the text, "This product is so useful, I can't live without it!"

[1500] input:

[1501] Extracted facial expressions and dialogue elements.

[1502] output:

[1503] Generated character images and lines.

[1504] Specific operation:

[1505] The server converts the analyzed data into the input format for the generative AI model, sends a request to the generative AI model, and receives the generated image data.

[1506] Step 5:

[1507] The server provides the generated character image and lines to the terminal as a preview link, and generates a preview link using a preview means so that the user can check the image, and sends the preview link to the terminal.

[1508] input:

[1509] Generated character images and lines.

[1510] output:

[1511] The preview link sent to your device.

[1512] Specific operation:

[1513] The server temporarily stores the generated image in cloud storage, generates a link to it, and sends the link to the terminal as an HTTP response.

[1514] Step 6:

[1515] The user checks the preview link and approves the stamp. After opening the preview link on their device and checking the generated stamp, they press the confirm button to approve it.

[1516] input:

[1517] The preview link sent to your device.

[1518] output:

[1519] User approval operations.

[1520] Specific operation:

[1521] Users can click on the preview link on their device and use the interface to review and confirm the generated stamp in their browser or app.

[1522] Step 7:

[1523] The server stores the final generated stamp in the user's account. A storage means is used to store the generated stamp in the user's database.

[1524] input:

[1525] User approval operations.

[1526] output:

[1527] Stickers saved in the user's account.

[1528] Specific operation:

[1529] The server queries the database associated with the user's account to store the generated stamp.

[1530] Step 8:

[1531] The server provides a download link or a usage link for the stored stamp. The server generates a download link using the providing means and transmits it to the terminal.

[1532] input:

[1533] Stickers saved in the user's account.

[1534] output:

[1535] The download or usage link sent to your device.

[1536] Specific operation:

[1537] The server generates a downloadable URL for the stamp file for the client and sends the URL information to the device.

[1538] Step 9:

[1539] The server authenticates paid users, deducts fees, and manages rewards to creators. Using a management means, the server performs the authentication process for paid users, deducts usage fees, and transfers a portion of the fees to the creator's account as rewards.

[1540] input:

[1541] Paid users' account information and usage information of generated stamps.

[1542] output:

[1543] Completing billing transactions and transferring rewards to creators.

[1544] Specific operation:

[1545] The server sends the paying user's payment information to the payment provider, deducts the usage fee, then calculates the creator's remuneration and transfers the remuneration to the creator's account.

[1546] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1547] This invention combines a system that uses generation AI to customize the character's facial expressions and lines based on prompts entered by the user, generating original stamps, and an emotion engine that recognizes the user's emotions. Below, we will explain the program processing of this system in natural language.

[1548] Overall system overview

[1549] This system works in cooperation with four parties: the user, the device, the server, and the emotion engine. The user inputs a prompt from the device, and the emotion engine recognizes the user's emotion. The server analyzes the prompt and creates a customized stamp using a generation AI.

[1550] Program processing

[1551] First, the user accesses the custom stamp creation screen within the LINE app, enters a prompt such as "a character saying hello with a smile," and presses the send button. At this time, the text entered by the user, as well as the voice and facial expressions used, are analyzed by the emotion engine.

[1552] The device creates an API request based on the prompt and emotional information entered by the user and sends the request to the server.

[1553] The server receives the prompt and emotion information sent from the terminal and starts processing to analyze the content of the prompt. The analysis means converts the content of the prompt into a format that the generative model can understand. Furthermore, the emotion data analyzed by the emotion engine provides supplementary information to the prompt, generating a stamp that is more suited to the user's emotion.

[1554] The emotion engine recognizes the user's emotions from their facial expressions and voice, and complements or modifies prompts based on that emotional data. For example, if the user is smiling, a warmer tone might be added to a prompt like "Hello."

[1555] The generative AI generates character expressions and lines based on the analyzed instructions and emotional data. For example, if the prompt is "Smile and say hello," and the emotion engine determines that the user is very happy, the generated character's smile will be brighter and the "hello" line will have a more joyful nuance.

[1556] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[1557] The device will use the preview link to display a preview screen of the generated stamp to the user. The user can check this preview and, if necessary, enter new prompts or emotion data to request corrections. If no corrections are required, the user presses the "Confirm" button.

[1558] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated.

[1559] The device will display a download link, allowing users to download the stamp or use it within the LINE app.

[1560] The server also authenticates paying users and deducts the associated fees from their accounts, a portion of which is managed as a reward for the creators and later deposited into their accounts.

[1561] Specific examples

[1562] For example, consider the prompt "I want a sleeping character to say goodnight." The user enters the prompt, and the device sends it to the server. The server analyzes the prompt and emotion data, extracting elements such as "sleeping character" and "goodnight." The emotion engine recognizes the user's calm emotion, and generates a more relaxed facial expression and the phrase "goodnight" based on that.

[1563] The AI ​​generates a character and dialogue based on the specified content and sends it back to the server. The server temporarily saves it and provides the user with a preview link. After the user confirms it, they press the confirm button, and the final generated stamp is saved to their account and a download link is provided. Users can click this link to download and use the stamp.

[1564] In this way, the system generates original stamps based on user prompts and emotional data, supporting quick and intuitive communication, and also supports creators' activities by providing rewards to them.

[1565] The processing flow will be explained below.

[1566] Step 1:

[1567] Users access the custom stamp creation screen within the LINE app, input a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are also recorded by the emotion engine.

[1568] Step 2:

[1569] The device sends the input prompt and emotion data to the server as an API request.

[1570] Step 3:

[1571] The server receives the prompt and emotion data sent from the terminal and starts a process to analyze the prompt content and emotion data. The analysis means converts the prompt content into a format that can be understood by the generative model.

[1572] Step 4:

[1573] The emotion engine recognizes the user's emotions from their facial expressions and voice data, and provides the analysis results to the server. For example, when the user is smiling, emotion data of "joy" is generated.

[1574] Step 5:

[1575] The server complements or modifies the prompt using the emotion data provided by the emotion engine and passes it to the generative model, adding elements based on the user's emotions.

[1576] Step 6:

[1577] The AI ​​then generates the character's facial expressions and lines based on the analyzed prompt and emotion data. For example, if the emotion data for "hello with a smile" and "joy" are given, the generated character's smile will be brighter and the "hello" line will have a more joyful nuance.

[1578] Step 7:

[1579] The server receives the generated stamp, temporarily stores it, and then provides a preview link to the user and sends an interface to the terminal for viewing and modifying the generated stamp.

[1580] Step 8:

[1581] The device will use the preview link to display a preview screen of the generated stamp to the user. The user can check this preview and, if necessary, enter new prompts or emotion data to request corrections. If no corrections are required, the user presses the "Confirm" button.

[1582] Step 9:

[1583] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link is generated and sent to the device.

[1584] Step 10:

[1585] The device will display a download link, allowing users to download the stamp or use it within the LINE app.

[1586] Step 11:

[1587] The server authenticates the paying user and deducts the associated fees from the user's account, and a portion of the fees is managed as a reward for the creator and deposited into the creator's account.

[1588] In this way, a system is realized that generates original stamps that are optimal and intuitive for each user based on the user's prompts and emotional data, and also supports creators' activities by providing appropriate rewards to creators.

[1589] Example 2

[1590] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1591] Previous systems for generating customized stickers were able to generate character expressions and lines based on user prompts, but they were unable to customize characters based on the user's emotions. This made it difficult to generate stickers that fully reflected the user's intentions. Furthermore, the generation process was complex, potentially resulting in a poor user experience.

[1592] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1593] In this invention, the server includes an analysis means for analyzing the prompt and emotion data and inputting them into a generative model, a preview means for providing the user with a preview of the generated image and dialogue, and a storage means for saving the final generated stickers in the user's account, thereby enabling quick and intuitive generation of customized stickers that take the user's emotions into account.

[1594] "User" refers to an individual or organization that uses the System to generate customized stamps.

[1595] An "input means" is an interface through which a user inputs prompts and other data into the system.

[1596] The "transmission means" is a function for transmitting a prompt input via the input means to the server.

[1597] The "analysis means" is a function for analyzing prompts and emotion data in the server and inputting them into the generative model.

[1598] A "generative model" is an AI algorithm that generates character images and dialogue based on input data.

[1599] "Generation means" is a function for generating character images and lines using a generative model.

[1600] The "preview means" is a function for providing the user with a preview of the generated character image and lines.

[1601] "Storage means" is a function for saving the final generated stamp in the user's account.

[1602] The "means of provision" is a function for providing saved stamps to users as download links or usage links.

[1603] The "management means" is a function for managing authentication of paying users, withdrawal of fees, and remuneration to content creators.

[1604] "Emotional data" refers to emotional information extracted from a user's facial expressions and voice.

[1605] This invention is a system that uses a generative AI model to customize character expressions and lines based on prompts entered by the user, generating original stamps. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it achieves even more precise customization.

[1606] Hardware and software used

[1607] 1. The user accesses the LINE application using a device such as a smartphone or tablet.

[1608] 2. The device makes an API request to communicate with the server via its internet connection.

[1609] 3. The server utilizes high-performance cloud servers to run generative AI models (e.g., OpenAI's GPT-3) and emotion engines (e.g., Affectiva Emotion AI).

[1610] 4. The emotion engine includes hardware and software that uses the device's camera and microphone to analyze the user's facial expressions and voice.

[1611] Data processing and calculation flow

[1612] Users access the "Customized Stamp Creation Screen" within the LINE app, enter a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are simultaneously analyzed by the emotion engine.

[1613] The device sends the prompt and emotion data entered by the user to the server as an API request, which processes data acquired from the camera and microphone and generates appropriate emotion data.

[1614] The server analyzes the data received from the device and converts the prompts into a format that the generative AI model can understand. It also analyzes the emotional data and adds additional information to the prompts. This analysis method provides more detailed instructions to the generative model.

[1615] The AI ​​then generates character expressions and lines based on the analyzed instructions and emotional data. For example, in response to the prompt "A character saying hello with a smile," the generated character's smile will become brighter and the lines will have a more joyful nuance.

[1616] The server receives the generated character data, temporarily stores it, and then provides the user with a preview link and sends an interface to the device for viewing and modifying the generated stamp.

[1617] The device will use the preview link to display a preview of the generated stamp to the user. The user can check the preview and, if necessary, enter new prompts and emotion data and submit it again. If no corrections are required, the user can press the "Confirm" button.

[1618] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated.

[1619] The device will display the generated download link to the user, allowing them to download the stamp or use it within the LINE app.

[1620] Specific examples

[1621] For example, consider the prompt "I want a sleeping character to say goodnight." The user enters the prompt, and the device sends it to the server. The server analyzes the prompt and emotion data, extracting elements such as "sleeping character" and "goodnight." The emotion engine recognizes the user's calm emotion, and generates a more relaxed facial expression and the phrase "goodnight" based on that.

[1622] Specific prompt examples:

[1623] I want my sleeping character to say goodnight

[1624] In this way, the system not only quickly and intuitively generates original stamps based on user prompts and emotional data, but also customizes them to reflect the user's emotions.

[1625] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1626] Step 1:

[1627] Users access the LINE application using a device such as a smartphone or tablet. They access the "Customized Stamp Creation Screen," enter a prompt such as "a character smiling and saying hello," and press the send button. At this time, the user's facial expressions and voice are also analyzed by the emotion engine.

[1628] Input: User prompts, facial expressions, and voice data

[1629] Output: Prompt and emotion data sent to the device

[1630] Specific behavior:

[1631] A user enters text using the smartphone keyboard.

[1632] Data collection from cameras and microphones.

[1633] Step 2:

[1634] The device converts the user's input prompts and facial and voice data acquired from the camera and microphone into API requests and sends them to the server, where they are processed to generate appropriate emotion data.

[1635] Input: User prompts, facial expressions, and voice data

[1636] Output: API request sent to the server

[1637] Specific behavior:

[1638] Analyzes data from the camera and microphone to generate emotion labels.

[1639] Converts data into packets and sends them.

[1640] Step 3:

[1641] The server receives prompts and emotional data sent from the device, analyzes the content of the prompts, and converts them into a format that the generative AI model can understand. At the same time, it analyzes the emotional data and generates complementary information according to the prompts.

[1642] Input: Prompt and emotion data received from the device

[1643] Output: Parsed data to a generative AI model

[1644] Specific behavior:

[1645] Prompt text analysis (tokenization and context analysis)

[1646] Emotion data analysis (emotion labeling)

[1647] Step 4:

[1648] The server sends the analyzed data to the generation AI, which converts the data into a format that is easy for the generation AI to understand.

[1649] Input: Parsed prompt and sentiment data

[1650] Output: Formatted data sent to the generative AI

[1651] Specific behavior:

[1652] Data format conversion

[1653] Creating and sending an API request to the generation AI

[1654] Step 5:

[1655] The generative AI generates facial expressions and lines for the character based on the data it receives. For example, if the emotion engine determines that the user is happy in addition to the prompt "Smile and say hello," the character will have a brighter smile.

[1656] Input: Formatted data sent from the server

[1657] Output: Generated character and dialogue data

[1658] Specific behavior:

[1659] Running inference on a model

[1660] Formatting the generated results

[1661] Step 6:

[1662] The server temporarily stores the character data received from the generated AI, generates a preview link for the user to view, and sends it to the device.

[1663] Input: Character data received from the generation AI

[1664] Output: Preview link for user confirmation

[1665] Specific behavior:

[1666] Temporarily save to database

[1667] Generate and send a preview link

[1668] Step 7:

[1669] The device receives the preview link and displays a preview screen of the generated stamp to the user, which the user can confirm.

[1670] Input: Preview link received from the server

[1671] Output: The preview screen that the user sees

[1672] Specific behavior:

[1673] Preview screen drawing

[1674] Screen transition by clicking a link

[1675] Step 8:

[1676] The user checks the preview and, if satisfied with the stamp, presses the "Confirm" button. If corrections are needed, they enter new prompt and emotion data and submit again.

[1677] Input: User confirmation and correction instructions

[1678] Output: Confirm or correct instruction

[1679] Specific behavior:

[1680] Click the Confirm button

[1681] Re-enter correction prompt

[1682] Step 9:

[1683] After the user presses the confirm button, the server saves the final stamp to the user's account. Once this saving process is complete, a download link or usage link will be generated and sent to the device.

[1684] Input: User confirmation instructions

[1685] Output: Download link or usage link

[1686] Specific behavior:

[1687] Final save to database

[1688] Link Generation and Notifications

[1689] Step 10:

[1690] The device will display the download link received from the server to the user, allowing the user to download the stamp or use it within the LINE app.

[1691] Input: Download link received from the server

[1692] output: the download link that is displayed to the user

[1693] Specific behavior:

[1694] View download links

[1695] Click on the link to download

[1696] (Application example 2)

[1697] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1698] There is a demand for improved customer support and user experience in virtual stores, but conventional systems have difficulty recognizing user emotions in real time and responding appropriately.In addition, the content generated is not optimized based on user emotions, which leads to a decrease in user satisfaction.

[1699] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1700] In this invention, the server includes an input means for accepting user input, a transmission means for transmitting prompts to the server, an analysis means in the server for analyzing the prompts and passing them to a generative model, a generation means for generating character images and dialogue using the generative model, a preview means for providing the generated images and dialogue as previews to the user, an emotion recognition means for recognizing the user's emotion and using the emotion data to complement or modify the prompt, an optimization means for optimizing the generated character images and dialogue to match the user's emotion, a storage means for saving the final generated stamps in the user's account, a provision means for providing the saved stamps as a download link or a usage link, and a management means for managing paid user authentication, fee deductions, and creator compensation. This makes it possible to provide optimal customer support tailored to the user's emotions, which is expected to improve the user experience and increase satisfaction.

[1701] "User" refers to an individual or organization that uses this system.

[1702] "Input means" refers to a means that provides an interface for a user to input a prompt.

[1703] "Transmission means" refers to a means for transmitting the input prompt to the server.

[1704] "Analysis means" refers to means for analyzing prompts on the server and converting them into a format that conforms to the generative model.

[1705] The "generation means" refers to a means for generating a character image and lines based on the analyzed prompt.

[1706] "Preview means" refers to a means for temporarily displaying the generated character image and dialogue to the user.

[1707] "Emotion recognition means" refers to a means of analyzing the user's emotions and reflecting that data in prompts.

[1708] "Optimization means" refers to a means for adjusting the generated character images and lines based on emotional data.

[1709] "Storage Means" means the means by which the final generated stamps are stored in the User's account.

[1710] "Providing means" refers to the means of providing saved stamps as a download link or a usage link.

[1711] "Management means" refers to the means for authenticating paying users, deducting fees, and managing creator compensation.

[1712] The system of the present invention is for providing customer support within a virtual store based on user input. Specific embodiments will be described below.

[1713] Overall system configuration

[1714] The system consists of the following main components:

[1715] User devices (smart glasses, head-mounted displays, etc.)

[1716] server

[1717] Emotion Recognition Engine

[1718] Generative AI Models

[1719] Detailed Description of the Embodiments

[1720] 1. User device operation

[1721] The user enters the virtual store and puts on smart glasses or a head-mounted display. The device captures the user's facial expressions and voice tone in real time and sends the data to the server. At this point, the user enters a prompt, such as "Please tell me how to use the product."

[1722] 2. Server Processing

[1723] The server analyzes the prompt and emotion data received from the user's device. First, the prompt text is converted into a format that can be passed to the generative AI model using an analytical method. Next, the emotion recognition engine analyzes the user's emotion data and uses that information to complete or modify the prompt.

[1724] 3. Operation of the Emotion Recognition Engine

[1725] The emotion recognition engine analyzes the user's facial expressions and voice to determine their emotions, and provides the data to the server. This data plays an important role in the generation process of the generative AI model. For example, if the user is feeling anxious, a gentle-spoken character will be generated based on this emotional data.

[1726] 4. Processing generative AI models

[1727] The generative AI model generates a character image and dialogue based on the analyzed prompt and emotional data. For example, a character might say, "Don't worry. We'll explain in detail how to use this product." During this generation process, the character's facial expression is also adjusted based on the emotional data.

[1728] 5. Providing the generated results

[1729] The generated character image and dialogue are provided to the user as a preview by the server. The user can check this preview and make any necessary corrections. The corrections are also reflected again through the emotion recognition engine and generative AI model.

[1730] 6. Final storage and provision

[1731] The generated result confirmed by the user will be saved in the user's account by the server, and the saved stamp will be provided as a download link or a usage link.

[1732] Hardware and software used

[1733] Hardware:

[1734] Smart glasses / head-mounted displays (e.g. Microsoft HoloLens)

[1735] High-performance servers (cloud-based servers, etc.)

[1736] software:

[1737] Emotion recognition engines (e.g., Affectiva's Emotion AI)

[1738] Generative AI models (e.g., OpenAI GPT-4)

[1739] Virtual reality production tools (e.g. Unity)

[1740] Specific prompt examples

[1741] For example, if a user says, "I don't know how to use this product," the emotion engine recognizes the user's anxiety. The generative AI model creates a "character that explains things clearly" and displays a line such as, "Don't worry. I'll explain in detail how to use this product." This series of steps allows users to comfortably receive customer support in a virtual store.

[1742] As described above, the system of the present invention provides optimal customer support that is tailored to the user's emotions, thereby improving the user experience.

[1743] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1744] Step 1:

[1745] A user accesses a virtual store and puts on smart glasses or a head-mounted display. The user inputs a prompt such as "Please tell me how to use the product." The input, along with the user's facial expressions and voice tone, is sent from the device to the server.

[1746] Step 2:

[1747] The server analyzes the prompt, facial expression data, and voice tone received from the terminal using an analysis means, and generates a prompt and emotion data in text format as the analysis results, since the analyzed data will be used in the next step.

[1748] Step 3:

[1749] The server sends the parsed prompt and emotion data to the emotion recognition engine, which analyzes the user's emotional state and sends the data back to the server. The output of emotion recognition can be, for example, the user's anxiety index and the reason for it.

[1750] Step 4:

[1751] The server receives emotional data from the emotion recognition engine and uses it to complement or modify the prompts. For example, if the anxiety index is high, it will modify the prompts to generate a "character that explains things clearly."

[1752] Step 5:

[1753] The server sends the modified prompt and emotion data to the generative AI model, which generates a character image and dialogue based on this data. During this generation process, the character's facial expressions and dialogue are adjusted based on the emotion data. The resulting character image and dialogue are obtained.

[1754] Step 6:

[1755] The generated character image and dialogue are provided to the user as a preview by the server. The preview screen is displayed on the user's device, and the user can check it and enter correction prompts as necessary.

[1756] Step 7:

[1757] If the user is satisfied with the preview and confirms it, the device sends the information to the server, which saves the final stamp to the user's account. The saved stamp is then provided as a download link or a link to use.

[1758] Step 8:

[1759] If the user is a paid user, the server will authenticate them, deduct the fee, and manage the creator's compensation. This ensures that the user's provision and the creator's compensation are managed appropriately.

[1760] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1761] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1762] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1763] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1764] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1765] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1766] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1767] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1768] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1769] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1770] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1771] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1772] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1773] 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.

[1774] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1775] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1776] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1777] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1778] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1779] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1780] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1781] The following is further disclosed regarding the above embodiment.

[1782] (Claim 1)

[1783] an input means for accepting input from a user;

[1784] sending means for sending the prompt to a server;

[1785] parsing means at the server for parsing prompts and passing them to a generative model;

[1786] A generating means for generating a character image and lines using a generative model;

[1787] a preview means for providing a user with a preview of the generated image and dialogue;

[1788] a storage means for storing the final generated stamps in the user's account;

[1789] A means for providing the stored stamp as a download link or a usage link;

[1790] A management method for managing paid user authentication, fee withdrawals, and creator compensation;

[1791] A system including:

[1792] (Claim 2)

[1793] The system of claim 1 receives user prompts, manages input from analysis to the generative model, provision and correction of generated character images and dialogue, and acceptance and confirmation, and final storage and provision.

[1794] (Claim 3)

[1795] The system of claim 1, including authentication of paid users, withdrawal of fees, and management of rewards to creators.

[1796] "Example 1"

[1797] (Claim 1)

[1798] an input means for accepting input from a user;

[1799] a transmitting means for transmitting a prompt to the information processing device;

[1800] analysis means for analyzing the prompt in the information processing device and passing the prompt to the generation engine;

[1801] a generation means for generating image data and text data using a generation engine;

[1802] a preview means for providing a user with a preview of the generated image data and text data;

[1803] a storage means for storing the final generated digital content in the user's account;

[1804] providing means for providing the stored digital content as a download link or a usage link;

[1805] a management means for managing paid user authentication, fee deductions, and creator rewards;

[1806] A system including:

[1807] (Claim 2)

[1808] The system of claim 1 receives user prompts, manages input from the analysis to the generation engine, the provision and correction of generated image data and text data, its confirmation, and final storage and provision.

[1809] (Claim 3)

[1810] 10. The system of claim 1, including paid user authentication, fee debiting, and creator reward management.

[1811] "Application Example 1"

[1812] Rewriting of original claims

[1813] (Claim 1)

[1814] an input means for accepting input from a user;

[1815] sending means for sending the prompt to a server;

[1816] parsing means at the server for parsing prompts and passing them to a generative model;

[1817] A generating means for generating a character image and lines using a generative model;

[1818] A generating means for generating original stamps based on the review content of an online shopping site;

[1819] a preview means for providing a user with a preview of the generated image and dialogue;

[1820] a storage means for storing the final generated stamps in the user's account;

[1821] A means for providing the stored stamp as a download link or a usage link;

[1822] A management method for managing paid user authentication, fee withdrawals, and creator compensation;

[1823] A system including:

[1824] (Claim 2)

[1825] The system of claim 1 receives user prompts, manages input from analysis to the generative model, provision and correction of generated character images and dialogue, and acceptance and confirmation, and final storage and provision.

[1826] (Claim 3)

[1827] The system of claim 1, including authentication of paid users, withdrawal of fees, and management of rewards to creators.

[1828] "Example 2: Combining Emotion Engines"

[1829] (Claim 1)

[1830] an input means for accepting input from a user;

[1831] sending means for sending the prompt to a server;

[1832] an analysis means for analyzing the prompt and emotion data in the server and inputting the prompt and emotion data into the generative model;

[1833] A generating means for generating a character image and lines using a generative model;

[1834] a preview means for providing a user with a preview of the generated image and dialogue;

[1835] a storage means for storing the final generated stamps in the user's account;

[1836] A means for providing the stored stamp as a download link or a usage link;

[1837] a management means for managing paid user authentication, payment withdrawals, and compensation to content creators;

[1838] A system including:

[1839] (Claim 2)

[1840] The system of claim 1 receives user prompts, manages input from analysis to the generative model, acceptance and confirmation of provision and correction of generated character images and dialogue, customization with emotional data, and final saving and provision.

[1841] (Claim 3)

[1842] 10. The system of claim 1, including paid user authentication, fee debiting, and content creator compensation management.

[1843] "Application example 2 when combining emotion engines"

[1844] New Claims

[1845] (Claim 1)

[1846] an input means for accepting input from a user;

[1847] sending means for sending the prompt to a server;

[1848] parsing means at the server for parsing prompts and passing them to a generative model;

[1849] A generating means for generating a character image and lines using a generative model;

[1850] a preview means for providing a user with a preview of the generated image and dialogue;

[1851] emotion recognition means for recognizing an emotion of the user and using the emotion data to complement or modify the prompt;

[1852] An optimization method to optimize the generated character images and lines to match the user's emotions,

[1853] a storage means for storing the final generated stamps in the user's account;

[1854] A means for providing the stored stamp as a download link or a usage link;

[1855] A management method for managing paid user authentication, fee withdrawals, and creator compensation;

[1856] A system including:

[1857] (Claim 2)

[1858] The system of claim 1 receives user prompts, manages input from analysis to the generative model, the provision and correction of generated character images and dialogue, their confirmation, final storage and provision, and recognizes and responds to user emotions.

[1859] (Claim 3)

[1860] The system according to claim 1, which provides customized generated content based on user emotions, including paid user authentication, fee deduction, and creator reward management. [Explanation of symbols]

[1861] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an input means for accepting input from a user; sending means for sending the prompt to a server; parsing means at the server for parsing prompts and passing them to a generative model; A generating means for generating a character image and lines using a generative model; a preview means for providing a user with a preview of the generated image and dialogue; a storage means for storing the final generated stamps in the user's account; A means for providing the stored stamp as a download link or a usage link; A management method for managing paid user authentication, fee withdrawals, and creator compensation; A system including:

2. The system of claim 1 receives user prompts, manages input from analysis to the generative model, provision and correction of generated character images and dialogue, and acceptance and confirmation, and final storage and provision.

3. The system according to claim 1, further comprising a system for authentication of paid users, debiting fees, and managing rewards to creators.

Images