system

Abstract

To provide a system which enables a user to easily generate an ideal avatar and use it for many purposes.SOLUTION: The system includes means for collecting and classifying a plurality of image, voice and text data, means for preprocessing the collected data and storing the preprocessed data in a database, means for learning a figure, a voice and a character from the preprocessed data using a generative AI model, means for selecting a character or a person desired by a user through a user interface and transmitting the selected data to a server, means for generating a 3D avatar using the generated AI model based on the selected data, means for providing the generated 3D avatar to the user and allowing the user to edit the avatar, means for providing a media share option for sharing the edited avatar on an SNS or a video-sharing site, and means for supporting a promotion activity using the generated avatar.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Traditionally, it has been difficult to pursue an ideal persona in the real world, and methods for realizing it in virtual form have been limited. Furthermore, existing systems have made avatar creation and promotional activities cumbersome, often requiring a lot of effort from the user. In particular, there has been a demand for a comprehensive system that can generate high-quality 3D avatars compatible with different media and easily share and utilize them. The purpose of this invention is to solve these problems and provide a system that allows users to easily create their ideal avatar and use it for a variety of purposes. [Means for solving the problem]

[0005] The present invention provides a system including the following means: a means for collecting and classifying multiple image, audio, and text data; a means for preprocessing the collected data and storing it in a database; a means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data; a means for a user to select a desired character or person through a user interface and send the data to a server; a means for generating a 3D avatar using the generative AI model based on the selected data; a means for providing the generated 3D avatar to the user and allowing the user to edit it; a means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites; and a means for supporting promotional activities using the generated avatar. This allows users to easily generate high-quality avatars and use them in a wide variety of media. The generated avatars can also be used to support activities on virtual platforms such as the Metaverse.

[0006] "Multiple image, audio and text data" refers to a group of data including visual, audio and text information that is collected in order to generate the avatar desired by the user.

[0007] "Preprocessing" refers to processes such as resizing, noise removal, normalization, and tokenization that are performed on collected data to make it suitable for learning.

[0008] "Generative AI models" are artificial intelligence models used to learn from collected and preprocessed data and generate new avatars based on user specifications.

[0009] "User Interface" means the graphical operating environment through which a user interacts with the system and selects or customizes a desired character or persona.

[0010] A "server" is a central computer system that processes user requests and generates and manages multiple avatar elements (appearance, voice, personality).

[0011] A "3D avatar" is a three-dimensional virtual character generated using collected data and generative AI models.

[0012] The "Media Sharing Option" is a feature that allows users to easily share their generated avatars on social media, video sharing sites, and other online platforms.

[0013] "Promotional activities" include marketing, advertising, virtual events, and other activities that use the generated avatar. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention is a system that allows users to create their ideal avatar and use it for various purposes. Specific embodiments of this system are described below.

[0036] 1. Data Collection and Preprocessing

[0037] server

[0038] The server first collects image, audio, and text data about the characters or people desired by the user. This data is collected from a variety of sources, including the Internet, public databases, and user-uploaded data.

[0039] The collected data is resized, noise-removed, and normalized in the case of image data, and noise-removal, normalization, and extraction of important features in the case of audio data.Text data undergoes preprocessing such as tokenization, stop word removal, and stem extraction.The preprocessed data is stored in a database.

[0040] 2. Model training

[0041] server

[0042] The server trains a generative AI model based on the preprocessed data. For example, an image generation model (e.g., GAN) learns a person's appearance characteristics, a voice generation model learns voice characteristics, and a text generation model learns personality traits. These models are stored on the server and used later in the generation process.

[0043] 3. Providing a user interface

[0044] Terminal

[0045] The user interface provides a graphical operating environment for users to select desired characters or people and upload custom images and voices. Users select the desired character or person items and transmit the data from their terminal to the server.

[0046] 4. Avatar Generation

[0047] server

[0048] The server analyzes the data sent by the user and selects the appropriate generative AI model (image generation, voice generation, personality generation). Based on this, a 3D avatar is generated. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[0049] 5. Check and edit your avatar

[0050] Terminal

[0051] The device presents the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[0052] 6. Media Sharing and Promotional Activities

[0053] Terminal

[0054] The device provides media sharing options for sharing the generated avatar to social media icons, video sharing sites, etc. It also includes an export function, allowing users to use the avatar on different platforms.

[0055] server

[0056] The server will support promotional activities using the generated avatars, including event management and campaign planning and execution in the metaverse and other virtual platforms.

[0057] Specific examples

[0058] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model to generate a 3D avatar that combines Character A's appearance, Person B's voice, and personality C obtained from the trained model. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[0059] The above is a specific embodiment for carrying out the present invention.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] User:

[0063] Through the device's user interface, users select a character or person to base their ideal avatar on, and optionally upload custom images and audio files.

[0064] Step 2:

[0065] Device:

[0066] The device analyzes the user's selections and uploaded data, which includes images, audio, and text data, and transmits it to the server.

[0067] Step 3:

[0068] server:

[0069] The server preprocesses the received data: image data is resized and denoised, audio data is denoised and features are extracted, and text data is tokenised and stop words are removed.

[0070] Step 4:

[0071] server:

[0072] Based on the preprocessed data, a generative AI model is trained. Models for image generation (e.g., GAN), speech generation, and text generation are used to learn the characteristics of each.

[0073] Step 5:

[0074] server:

[0075] Save the trained generative AI model and prepare it for use based on user requests.

[0076] Step 6:

[0077] server:

[0078] The selection data sent by the user is analyzed and appropriate image generation, speech generation, and text generation models are selected.

[0079] Step 7:

[0080] server:

[0081] The selected generative AI model is used to generate each element of the 3D avatar: for example, an image generation model generates appearance, a speech generation model generates voice, and a text generation model generates personality.

[0082] Step 8:

[0083] server:

[0084] The generated avatar elements are integrated to create the final 3D avatar.

[0085] Step 9:

[0086] server:

[0087] The completed 3D avatar is sent to the device and provided to the user.

[0088] Step 10:

[0089] Device:

[0090] The user uses an interface to view the 3D avatar received on the device and edit it if necessary.

[0091] Step 11:

[0092] Device:

[0093] The edited avatar will provide a media sharing option to share to social media icons and video sharing sites according to the user's request.

[0094] Step 12:

[0095] server:

[0096] The server will support promotional activities using the generated avatars, including event management and planning and execution of promotional campaigns in the metaverse and other virtual platforms.

[0097] The above processing steps realize a system that allows users to easily create their ideal avatar and use it in a variety of media.

[0098] Example 1

[0099] 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."

[0100] In recent years, there has been a growing demand for systems that allow users to easily create their own original characters and use them for multiple purposes. In particular, creating anime-style characters or characters with the characteristics of celebrities and using them on social media and video sharing sites is extremely popular. However, existing technologies have difficulty efficiently collecting and classifying multiple data, and smoothly editing and sharing the generated characters.

[0101] 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.

[0102] In this invention, the server includes means for collecting and classifying a plurality of visual data, audio data, and text data, means for preprocessing the collected data and storing it in an information storage device, and means for learning appearance, voice, and personality traits from the preprocessed data using a generated machine learning model, thereby enabling the creation and multipurpose use of original characters desired by users.

[0103] "Visual data" refers to information that can be perceived visually, such as images and videos.

[0104] "Auditory data" refers to information that can be perceived auditorily, such as voice or music.

[0105] "Character data" refers to information expressed in text format.

[0106] An "information storage device" is a device for storing and managing data.

[0107] A "generated machine learning model" is a model that learns features from data and runs an algorithm to generate new data.

[0108] "Operation interface" refers to the screen and input devices that allow the user to interact with the system and perform operations.

[0109] A "central processing unit" is a computer that controls the entire system and processes data.

[0110] "3D virtual character" means a digitally generated character in three-dimensional form.

[0111] "Media sharing options" refers to functions and options for publishing the generated character and related information on social networks and video sharing sites.

[0112] "Promotional Activities" refers to promotional and marketing activities aimed at increasing awareness and sales of a particular product or service.

[0113] The present invention is a system that allows users to create their ideal original character and use it in a variety of ways. Specific embodiments of this system are described below.

[0114] System Configuration

[0115] server

[0116] The server plays a central role in the entire system and performs the following processes:

[0117] Data collection and preprocessing: The server collects visual, auditory, and text data from the internet, public databases, and uploaded by users. The collected data is resized and denoised using an image processing library (e.g., OpenCV), and denoised and feature extracted using an audio processing library (e.g., Librosa). Text data is tokenised and stopwords are removed using a natural language processing library (e.g., NLTK, spaCy).

[0118] Model training: The preprocessed data is used to train a generative AI model (e.g., GAN, speech synthesis model, text generation model) using a deep learning framework (e.g., TensorFlow, PyTorch) running on high-performance hardware (e.g., NVIDIA GPU).

[0119] Avatar generation: A trained generative AI model is used to generate a 3D virtual character based on user-submitted data. Visual elements are integrated using 3D modeling software like Blender.

[0120] Terminal

[0121] The terminal provides a user interface and editing functions. The specific process is as follows:

[0122] User Interface: Provides a web browser-based interface implemented using front-end frameworks such as React or Vue.js, where users can select their desired character or persona and upload custom visual and auditory data.

[0123] Avatar display and editing: The generated 3D virtual character is displayed using libraries such as Three.js. Users can edit details in real time, and the edits are sent to the server and saved.

[0124] Media Sharing and Export: Provides the option to share the completed avatar directly to social media and video sharing sites. Sharing is done using social media APIs (e.g. Twitter API, YouTube API). Export functionality is also provided, allowing you to save in standard 3D file formats (e.g. FBX, OBJ).

[0125] User

[0126] The user does the following:

[0127] Data Upload: Upload visual, auditory and textual data about the desired character or person through the interface.

[0128] Character Selection and Customization: Select your desired character or persona from the provided list and customize their detailed parameters.

[0129] Edit the generated avatar: Review the generated avatar and make any necessary adjustments, including adding facial expressions or accessories.

[0130] Media sharing: Share the completed avatar on social media and video sharing sites to promote it.

[0131] Specific examples

[0132] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses a trained generative AI model to generate a 3D virtual character that combines the appearance of Character A, the voice of Person B, and personality C obtained from the trained model. The generated character is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and for promotional activities.

[0133] Prompt Sentence Examples

[0134] For example, you might enter the following prompt for a generative AI model:

[0135] "Generate a 3D virtual character with the appearance of anime character A, the voice of celebrity B, and the traits of personality C."

[0136] This allows the user's ideal virtual character to be generated efficiently and with high quality.

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

[0138] Step 1: Data collection and preprocessing

[0139] The server receives requests from users and collects visual, auditory and textual data from the Internet, public databases and user uploaded data.

[0140] Input: Data collection request from user

[0141] What it does: The server uses API requests to retrieve the required data from the data source. For example, image data is collected by web scraping, and audio data is downloaded from a public audio database.

[0142] Data processing: The acquired visual data (images) are resized and denoised using OpenCV. The auditory data (audio) is denoised and features extracted using Librosa, and the text data is tokenised and stopwords removed using NLTK or spaCy.

[0143] Output: Preprocessed data (visual data, auditory data, text data)

[0144] Step 2: Model training

[0145] The server trains a generative AI model based on the preprocessed data.

[0146] Input: Preprocessed data (visual, auditory, textual)

[0147] Specific operation: The server uses TensorFlow or PyTorch to train generative AI models (e.g., GANs, speech synthesis models, text generation models). High-performance NVIDIA GPUs (e.g., Tesla V100) are used for hardware. Batch processing is used for learning, and the model is trained for the specified number of epochs.

[0148] Data calculation: Split the data into training and validation sets, and tune the hyperparameters to improve the model accuracy.

[0149] Output: Trained generative AI model

[0150] Step 3: Providing a User Interface

[0151] The terminal provides an operation interface for the user to select the desired character or person and upload custom data.

[0152] Input: User interaction and selection data (character / persona information, custom visual data, auditory data)

[0153] Specific operation: Display a web browser-based interface and build an operation screen using React and Vue.js. The user can upload data through the interface and send the data to the server using an Ajax request.

[0154] Output: User data sent to the server

[0155] Step 4: Avatar generation

[0156] The server analyzes the data sent by the user and selects an appropriate generative AI model to generate a 3D virtual character.

[0157] Input: User data (character / persona information, custom visual data, audio data)

[0158] How it works: The server analyzes the received data and inputs visual, auditory, and text data into each generative AI model. Each generative AI model generates its own elements and integrates them using 3D modeling software such as Blender.

[0159] Data calculation: The elements (appearance, voice, personality) generated by each generative AI model are combined to construct a 3D virtual character.

[0160] Output: Finished 3D virtual character

[0161] Step 5: Review and edit your avatar

[0162] The terminal provides the generated 3D virtual character to the user and provides an interface for editing.

[0163] Input: Finished 3D virtual character

[0164] How it works: It uses Three.js to display a 3D virtual character in the browser and allows users to edit it. The edits made by the user are sent to the server in real time and saved.

[0165] Output: The final edited 3D virtual character

[0166] Step 6: Media sharing and promotional activities

[0167] The terminal and server support media sharing and promotional activities.

[0168] Input: Edited 3D virtual character

[0169] Specific operation: The device uses social media APIs to provide sharing options to social media and video sharing sites. The server supports promotional activities using the generated virtual characters and manages events in the metaverse and virtual platforms.

[0170] Output: Analysis data on the effectiveness of virtual characters posted on social media and video sharing sites, and promotional activities

[0171] (Application example 1)

[0172] 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."

[0173] In today's virtual stores, it is difficult for users to obtain a shopping experience that reflects their personal preferences. In particular, there is a lack of a realistic sensory experience when trying on and purchasing products. Furthermore, non-personalized suggestions and product explanations hinder efficient shopping. There is a need to solve these problems and provide users with a high-quality shopping experience.

[0174] 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.

[0175] In this invention, the server includes means for collecting and classifying multiple image, audio, and text data, means for preprocessing the collected data and storing it in a database, means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data, means for a user to select a desired character or person through a user interface and send the data to the server, means for generating a 3D avatar using the generative AI model based on the selected data, means for providing the generated 3D avatar to the user and allowing the user to edit it, means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites, means for supporting the user's shopping experience in a virtual store using the generated avatar, means for providing a virtual try-on system that uses an avatar to try on and recommend products, and means for explaining products using an avatar's voice guide function. This provides a personalized shopping experience for the user, enabling a realistic try-on experience and efficient product recommendations.

[0176] "Image data" means a digital image containing visual information of a person or character designated by the user.

[0177] "Audio Data" means an audio file containing the voice characteristics of a person or character designated by the user.

[0178] "Text data" is written information about the personality and other attributes of a person or character designated by the user.

[0179] A "generative AI model" is an artificial intelligence algorithm that learns appearance, voice, and personality from preprocessed image, audio, and text data to generate an avatar.

[0180] A "user interface" is software that provides an operating environment for a user to interact with the system, select a desired character or person, and transmit that data to a server.

[0181] A "server" is a computer system that collects, preprocesses, and stores data, runs generative AI models, and manages generated avatars.

[0182] A "3D avatar" is a three-dimensional virtual character generated based on a generative AI model that expresses the user's desired appearance, voice, and personality.

[0183] The "Virtual Try-On System" is a system that allows users to try on and receive product recommendations in a virtual space using a generated 3D avatar.

[0184] The "audio guide function" is a feature in which a generated 3D avatar explains products and assists users with their shopping by voice.

[0185] "SNS" is a social networking service that allows users to share their generated 3D avatars and their activities.

[0186] A "video sharing site" is a web platform that allows users to upload content using generated avatars and share it with other users.

[0187] The system for implementing this invention is realized by the following procedure: The purpose of this system is to enable users to create their ideal avatar and use it to provide a personalized shopping experience.

[0188] First, the server collects multiple images, audio, and text data from the Internet, public databases, and data uploaded by users. The collected data is resized, denoised, and normalised for images, and denoised, normalised, and key features extracted for audio data. The text data is tokenised, stop words are removed, and stems are extracted. The preprocessed data is stored in a database. The hardware used includes a high-performance server, and the software uses data preprocessing libraries such as OpenCV, Librosa, and NLTK.

[0189] The server then uses generative AI models to learn appearance, voice, and personality from the preprocessed data. For example, these models use Generative Adversarial Networks (GANs) to generate images, voices, and text. These models are trained and stored on the server.

[0190] Users can operate a graphical user interface through their smartphone, tablet, or PC device to select the desired character or persona and upload custom images and voices. The selected and uploaded data is then sent to a server.

[0191] The server analyzes the received user data and generates a 3D avatar using a trained generative AI model. The generated 3D avatar is sent to the device, where the user can view and edit it. The editing interface allows the user to adjust details and save the completed avatar.

[0192] The completed avatar provides a media sharing option for sharing on social media and video sharing sites. Furthermore, the system also includes a function to support the user's shopping experience in a virtual store using the generated avatar. Specifically, the virtual try-on system allows the user to try on clothes and accessories using the avatar, and the avatar can suggest products and provide product explanations using an audio guide function.

[0193] For example, if a user wants to create an avatar with the characteristics of a favorite celebrity, they might enter the following prompt:

[0194] "Use the face and voice of your favorite celebrity to suggest outfits that would look good on me, just like a stylist. Then try them on on your avatar."

[0195] In this way, users can create avatars that reflect their preferences and use them to enjoy shopping in virtual stores.

[0196] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0197] Step 1:

[0198] The server collects multiple images, audio, and text data from the Internet, public databases, and data uploaded by users. This provides basic data about the characters and people desired by the user. The inputs are image files, audio files, and text data, which are stored in a database for centralized management.

[0199] Step 2:

[0200] The server preprocesses the collected data and stores it in a database. Image data is resized, denoised, and normalised, while audio data is denoised, normalised, and key features are extracted. Text data is tokenised, stop words are removed, and stems are extracted. This improves data accuracy and enables efficient training for the generative AI model.

[0201] Step 3:

[0202] The server trains a generative AI model based on the preprocessed data. Examples include image generation models, speech generation models, and text generation models using GANs (Generative Adversarial Networks). This builds a basic model that reflects the appearance, voice, and personality selected by the user. The preprocessed data is used as input, and a trained model is obtained as output.

[0203] Step 4:

[0204] The user uses a device to operate the user interface. The user can select a desired character or persona and upload custom images and voices. This data is sent to a server, which collects and stores the user's input. The input is the selected character information and additional images and voices, and the output is the user data sent to the server.

[0205] Step 5:

[0206] The server analyzes the received user data and generates a 3D avatar using a trained generative AI model. The input is the user data and the trained model, and the output is the generated 3D avatar. This avatar is stored on the server and provided to the user's device.

[0207] Step 6:

[0208] Users can view and edit the generated 3D avatar through their devices. They can adjust and modify details through the user interface. The input is the generated 3D avatar, and the output is the final avatar that reflects the user's edits.

[0209] Step 7:

[0210] The completed avatar provides a media sharing option for sharing to social networking sites and video sharing sites, allowing users to utilize their avatar across multiple platforms. The input is the final edited avatar, and the output is the avatar deployment on social networking sites and video sharing sites.

[0211] Step 8:

[0212] The generated avatar is used to support the user's shopping experience in a virtual store. For example, a virtual try-on system provides a function where the avatar tries on products, and an audio guide function provides product explanations. This allows the user to enjoy a realistic shopping experience. The input is the generated avatar and product data in the store, and the output is an avatar with try-on and guide functions.

[0213] As a specific example, a user can create an avatar with the features of their favorite celebrity and use the prompt, "Please suggest clothes that would suit me, like a stylist, using the face and voice of my favorite celebrity. Also, please let me try on the clothes on my avatar." to create a shopping experience that suits their tastes.

[0214] 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.

[0215] The present invention combines an emotion engine with a system that allows users to create their ideal avatar and use it for various purposes. By using the emotion engine, the user's emotions can be analyzed and the results can be reflected in the creation of the avatar and promotional activities. A specific embodiment of this system is described below.

[0216] 1. Data Collection and Preprocessing

[0217] server

[0218] The server first collects image, audio, and text data about the characters or people desired by the user. This data is collected from a variety of sources, including the Internet, public databases, and user-uploaded data.

[0219] The collected data is resized, noise-removed, and normalized in the case of image data, and noise-removal, normalization, and extraction of important features in the case of audio data.Text data undergoes preprocessing such as tokenization, stop word removal, and stem extraction.The preprocessed data is stored in a database.

[0220] 2. Model training

[0221] server

[0222] The server trains a generative AI model based on the preprocessed data. For example, it uses an image generation model (e.g., GAN), a voice generation model, and a text generation model to learn the features of each. These models are stored on the server and used later in the generation process.

[0223] 3. Providing a user interface

[0224] Terminal

[0225] The user interface provides a graphical operating environment for users to select desired characters or people and upload custom images and voices. Users select the desired character or person items and transmit the data from their terminal to the server.

[0226] 4. Use of Emotion Engine

[0227] server

[0228] The server is equipped with an emotion engine that analyzes the user's emotions based on the user's operations and input data. This emotion data is used as feedback for each element of the avatar (appearance, voice, personality).

[0229] 5. Avatar Generation

[0230] server

[0231] The server selects the appropriate generative AI model (image generation, voice generation, text generation) based on the data submitted by the user and the results of emotion analysis. Based on this, a 3D avatar is generated. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[0232] 6. View and edit your avatar

[0233] Terminal

[0234] The device presents the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[0235] 7. Media Sharing and Promotional Activities

[0236] Terminal

[0237] The device provides media sharing options for sharing the generated avatar to social media icons, video sharing sites, etc. It also includes an export function, allowing users to use the avatar on different platforms.

[0238] server

[0239] The server will support promotional activities using the generated avatars, including event management and campaign planning and execution in the metaverse and other virtual platforms.

[0240] Specific examples

[0241] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model and emotion engine to generate a 3D avatar that combines the appearance of Character A, the voice of Person B, and personality C based on the user's emotions. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[0242] The above is a specific embodiment for carrying out the present invention.

[0243] The processing flow will be explained below.

[0244] Step 1:

[0245] User:

[0246] Through the device's user interface, users select a character or person to base their ideal avatar on, and optionally upload custom images and audio files.

[0247] Step 2:

[0248] Device:

[0249] The device analyzes the user's selections and uploaded data, which includes images, audio, and text data, and transmits it to the server.

[0250] Step 3:

[0251] server:

[0252] The server preprocesses the received data: image data is resized and denoised, audio data is denoised and features are extracted, and text data is tokenised and stop words are removed.

[0253] Step 4:

[0254] server:

[0255] Based on the preprocessed data, a generative AI model is trained. Models for image generation (e.g., GAN), speech generation, and text generation are used to learn the characteristics of each.

[0256] Step 5:

[0257] server:

[0258] Save the trained generative AI model and prepare it for use based on user requests.

[0259] Step 6:

[0260] server:

[0261] The server uses the emotion engine to analyze the user's emotions based on the user's operations and input data. The analyzed emotion data is used in subsequent processing.

[0262] Step 7:

[0263] server:

[0264] The selection data and emotion data sent by the user are analyzed, and appropriate image generation, speech generation, and text generation models are selected.

[0265] Step 8:

[0266] server:

[0267] The selected generative AI model is used to generate each element of the 3D avatar: for example, appearance is generated by an image generation model, voice by a voice generation model, and personality by a text generation model.

[0268] Step 9:

[0269] server:

[0270] Based on the analysis results of the emotion engine, necessary feedback is applied to each generated element to optimize the 3D avatar, allowing the avatar's appearance, voice, and personality to adapt to the user's emotional state.

[0271] Step 10:

[0272] server:

[0273] The completed 3D avatar is sent to the device and provided to the user.

[0274] Step 11:

[0275] Device:

[0276] The user uses an interface to view the 3D avatar received on the device and edit it if necessary.

[0277] Step 12:

[0278] Device:

[0279] The edited avatar will provide a media sharing option to share to social media icons and video sharing sites according to the user's request.

[0280] Step 13:

[0281] server:

[0282] The server will support promotional activities using the generated avatars, including event management and planning and execution of promotional campaigns in the metaverse and other virtual platforms.

[0283] As a specific example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model and emotion engine to generate a 3D avatar that combines Character A's appearance with Person B's voice and an optimal personality based on emotion analysis. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[0284] The above processing steps realize a system that allows users to easily create their ideal avatar and use it in a variety of media.

[0285] Example 2

[0286] 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."

[0287] Conventional avatar generation systems have had difficulty generating avatars that reflect the user's emotions. Furthermore, it is complicated to integrate different media formats (images, audio, text) to generate diverse avatars. This makes it difficult for users to easily create their ideal avatar and use it for multiple purposes.

[0288] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: [means for collecting and classifying multiple visual data, audio data, and natural language data]; [means for preprocessing the collected data and storing it in a database]; [means for using a generative artificial intelligence model to learn appearance, voice, and personality from the preprocessed data]; [means for an end user to select a desired character or person through a user interface and transmit the data to a host system]; [means for generating a three-dimensional avatar using a generative artificial intelligence model based on the selected data]; [means for analyzing the user's emotions using an emotion engine and reflecting the results in avatar generation]; [means for providing the generated three-dimensional avatar to the end user and allowing editing]; [means for providing a media sharing option for sharing the edited avatar on social networking services and video sharing platforms]; and [means for supporting marketing activities using the generated avatar]. This enables users to easily generate their ideal avatar and use it on various platforms.

[0289] "Visual data" is data expressed as images, and includes still images such as photographs, illustrations, and videos, as well as moving images.

[0290] "Audio data" refers to data expressed as sound, including music, speech, sound effects, and the like.

[0291] "Natural language data" refers to data in a language that is naturally spoken or written by humans, and includes text documents and records of conversations.

[0292] "Preprocessing" refers to a processing step for preparing data for use after collection, and includes processes such as data noise removal, normalization, and feature extraction.

[0293] "Database" means a system for efficiently and securely storing and managing collected and pre-processed data.

[0294] "Generative AI models" refers to algorithms or neural network models that learn specific tasks based on preprocessed data and generate new data or results.

[0295] "User Interface" means a graphical or text-based interface through which an end user interacts with and operates a system.

[0296] "Host System" refers to a central server or cloud computing environment that receives, analyzes, and processes user input data.

[0297] The "emotion engine" is a system that analyzes emotions from user operations and input data, and provides feedback to avatar generation based on that emotional data.

[0298] A "3D avatar" refers to a user-customizable 3D character or person model.

[0299] A "social networking service" is an online platform that allows users to exchange information with each other via the Internet.

[0300] A "video sharing platform" is an online platform for users to upload video content and share it with other users.

[0301] "Media sharing options" refers to a function for sharing the generated avatar and its related content with other users.

[0302] "Marketing activities" refers to the use of the generated avatar in commercial activities such as promotions and advertising campaigns.

[0303] The present invention provides a system that allows end users to create their ideal three-dimensional avatar and use it for a variety of purposes. This system also incorporates an emotion engine that can analyze the user's emotions and reflect the results in the avatar generation. The specific system configuration and operating procedures for implementing the present invention are described in detail below.

[0304] System Configuration

[0305] 1. Server

[0306] The server provides the following functions:

[0307] It has the ability to collect, classify, and preprocess multiple visual, audio, and natural language data.

[0308] It has the ability to train generative artificial intelligence models (e.g., generative adversarial networks (GANs), speech generation models, and text generation models) to generate the appearance, voice, and personality of avatars.

[0309] An emotion engine is used to analyze the user's emotions and reflect the results in avatar generation.

[0310] The database stores collected and preprocessed data, as well as trained generative AI models.

[0311] 2. Terminal

[0312] The device offers the user the following features:

[0313] Through a user interface, the end user can select the desired character or persona and upload custom visual and audio data.

[0314] The generated three-dimensional avatar is provided to the user, and an interface is displayed that allows the user to preview and edit the avatar.

[0315] It provides media sharing options to share your avatar to social networking services and video sharing platforms.

[0316] Specific examples

[0317] For example, if a user wants to create a virtual YouTuber with the characteristics of their favorite manga character "Character A" and a specific celebrity "Person B," they first select those characters and people using their device and send the data to the server. The server then uses the preprocessed data to generate a three-dimensional avatar using a trained generative AI model (e.g., GAN, voice generation model) and an emotion engine to combine the appearance of "Character A," the voice of "Person B," and "Personality C" based on the user's emotions.

[0318] The device provides the generated 3D avatar to the user, who can preview it and edit it as needed. The completed avatar can be shared via the device to social networking sites and video sharing sites. The server also supports marketing activities using the generated avatar, allowing users to run virtual events and campaigns.

[0319] Prompt Sentence Examples

[0320] "Generate a virtual YouTuber with the appearance of anime character 'Character A', the voice of celebrity 'Person B', and the personality 'Personality C' analyzed by the emotion engine."

[0321] The above is a specific embodiment for carrying out the present invention. This invention allows users to easily create their ideal three-dimensional avatar and use it on a wide range of platforms.

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

[0323] Step 1:

[0324] Data collection and classification:

[0325] Subject: Server

[0326] The server collects multiple visual, audio and natural language data from sources such as the Internet, public databases and user uploads.

[0327] Input: Image, audio, and text data related to characters and people.

[0328] Specific operations: Uses a web crawler to collect image data from the Internet, and stores audio files and text data uploaded by users in cloud storage.

[0329] Output: The collected dataset.

[0330] Step 2:

[0331] Data preprocessing:

[0332] Subject: Server

[0333] The server resizes, denoises, and normalizes the collected data for images, denoises, normalizes, and extracts features for audio data, and tokenizes, removes stop words, and extracts stems for text data.

[0334] Input: The collected dataset.

[0335] Specific operation: Resize to 128x128 pixels using an image processing library, remove noise using a speech processing library, and tokenize the text data using a natural language processing library.

[0336] Output: A preprocessed dataset.

[0337] Step 3:

[0338] Train the model:

[0339] Subject: Server

[0340] The server trains a generative artificial intelligence model (e.g., GAN, speech generation model, text generation model) based on the preprocessed data.

[0341] Input: Preprocessed image data, audio data, and natural language data.

[0342] How it works: We train GANs on a GPU cluster to generate trained models. Each generative AI model is fed with collected data and undergoes an optimization process over multiple epochs.

[0343] Output: A trained generative AI model.

[0344] Step 4:

[0345] Providing a user interface:

[0346] Subject: Terminal

[0347] Through a user interface, the device allows the end user to select the desired character or persona and upload custom visual and audio data.

[0348] Input: User selections and uploaded image and audio data.

[0349] Specific behavior: Build a UI using a web application framework and handle user interactions.

[0350] Output: User input data.

[0351] Step 5:

[0352] Sentiment analysis with emotion engine:

[0353] Subject: Server

[0354] The server uses an emotion engine to analyze emotions based on user operations and input data.

[0355] Input: The text the user types and the options selected.

[0356] Specific operation: Uses a sentiment analysis algorithm to extract sentiment from user input data. Calculates sentiment scores for each text using a sentiment dictionary.

[0357] Output: User emotion data.

[0358] Step 6:

[0359] Avatar Creation:

[0360] Subject: Server

[0361] The server selects an appropriate generative AI model based on the data sent by the user and the results of emotion analysis, and generates a three-dimensional avatar.

[0362] Input: A trained generative AI model and user emotion data.

[0363] How it works: A visual model is generated using GAN, and a voice model is used to generate a person's voice. These are then integrated to generate a 3D avatar.

[0364] Output: The generated 3D avatar.

[0365] Step 7:

[0366] Provide and edit your avatar:

[0367] Subject: Terminal

[0368] The terminal provides the generated three-dimensional avatar to the user and displays an interface for editing.

[0369] Input: A generated 3D avatar.

[0370] What it does: Allows users to preview their avatar and make any necessary changes. Reflects user editing requests in real time.

[0371] Output: An edited 3D avatar.

[0372] Step 8:

[0373] Media sharing options available:

[0374] Subject: Terminal

[0375] The device provides a media sharing option for sharing the edited avatar to social networking services and video sharing platforms.

[0376] Input: An edited 3D avatar.

[0377] What it does: It generates a share link and embed code so that users can easily share their edited avatar on social media or video sites. Simply click the share button and the data will be transferred automatically.

[0378] Output: Share link and embed code.

[0379] Step 9:

[0380] Supporting your marketing efforts:

[0381] Subject: Server

[0382] The server supports marketing activities using the generated avatars.

[0383] Input: A generated 3D avatar.

[0384] What it does: Provides data needed to design and execute marketing campaigns and virtual events. Customizes promotional avatars and distributes them to target audiences.

[0385] Output: Campaign data and virtual event configuration information.

[0386] (Application example 2)

[0387] 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."

[0388] Conventional avatar generation systems have difficulty adjusting avatars in real time to reflect user emotions, making it difficult to provide a personalized customer service experience, especially in virtual stores. Furthermore, they lack the functionality to generate and adjust avatars based on user emotions, making it impossible to improve the user experience. To solve these issues, a more advanced avatar generation system incorporating user emotion analysis is needed.

[0389] 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.

[0390] In this invention, the server includes: [means for collecting and classifying multiple image, audio, and text data;] [means for preprocessing the collected data and storing it in a database;] [means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data;] [means for the user to select a desired character or person through a user interface and send the data to the server;] [means for generating a 3D avatar using the generative AI model based on the selected data;] [means for providing the generated 3D avatar to the user and allowing the user to edit it;] [means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites;] [means for supporting promotional activities using the generated avatar;] [means for analyzing the user's emotions and adjusting the avatar based on the data;] [means for analyzing the emotion data on the server and reflecting it in each element of the avatar; and [means for the user to use the avatar in a virtual store and receive personalized guidance.] This allows the avatar to be adjusted in real time based on an analysis of the user's emotions, enabling a personalized customer service experience in the virtual store.

[0391] "Image, audio and text data" refers to visual, audio and textual information about a character or person desired by the user.

[0392] "Preprocessing" refers to the process of converting collected data into a format suitable for analysis and learning. Specifically, it includes resizing and noise removal for image data, noise removal and feature extraction for audio data, tokenization for text data, and stop word removal.

[0393] "Generative AI models" refer to machine learning models for generating and learning appearance, voice, and personality from collected and pre-processed data, including models for image generation, speech generation, and text generation.

[0394] "User interface" refers to the operating environment that allows a user to select a desired character or person and input and manage data.

[0395] A "3D avatar" refers to a three-dimensional character with the user's desired appearance, voice, and personality.

[0396] "Emotion analysis" refers to the process of analyzing a user's facial expressions and voice to identify their emotional state.

[0397] "Virtual store" refers to a shopping environment created in a virtual space via the Internet, where users can access the store through a virtual reality device and browse, select, and purchase products.

[0398] "Personalized guidance" refers to the provision of information and services that are individually optimized based on the user's emotions and past behavioral history.

[0399] "SNS" is an abbreviation for social networking service, and refers to an online service that allows users to interact with each other.

[0400] "Media sharing options" refers to the functionality that allows users to post and share their generated avatars on various online platforms.

[0401] "Promotional Activities" refers to marketing and advertising activities using the generated Avatars, including, specifically, events and campaigns in the Metaverse.

[0402] MODE FOR CARRYING OUT THE INVENTION

[0403] The system for implementing the present invention operates through the interaction of a server, a terminal, and a user.

[0404] 1. Data Collection and Preprocessing

[0405] First, the server collects multiple image, audio, and text data from the Internet, public databases, and users. Image data is resized and noise-removed, while audio data is denoised, key features are extracted, and normalisation is performed. Text data is tokenised, stop words are removed, and stemming is extracted. These preprocessed data are then stored in a database.

[0406] 2. Model training

[0407] The server trains a generative AI model based on the preprocessed data. Specifically, it uses an image generation model (e.g., GAN), a voice generation model, and a text generation model to learn the features of each. These models are stored on the server and used later in the generation process.

[0408] 3. Providing a user interface

[0409] A graphical operating environment is provided on the device to allow users to select the desired character or person and upload custom images and voices, through which the user selects the desired character or person data and transmits the data from the device to a server.

[0410] 4. Use of Emotion Engine

[0411] The server is equipped with an emotion engine that analyzes the user's emotions based on the user's operations and input data. This emotion data is used as feedback for each element of the avatar (appearance, voice, personality).

[0412] 5. Avatar Generation

[0413] The server selects an appropriate generative AI model based on the data submitted by the user and the results of emotion analysis, and generates a 3D avatar. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[0414] 6. View and edit your avatar

[0415] The device provides the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust the details of the avatar, and save the completed avatar.

[0416] 7. Media Sharing and Promotional Activities

[0417] Users can use the media sharing option to share the generated avatar on social media, video sharing sites, etc. The avatar can also be used to support promotional activities in the metaverse and virtual platforms provided by the server.

[0418] 8. Virtual store applications

[0419] The server adjusts the avatar in real time based on the results of the user's emotion analysis and provides personalized guidance in the virtual store. When a user wears a head-mounted display and visits a virtual store, emotion analysis data is sent to the server, which then generates an optimal avatar and displays it in the user's field of view, providing personalized guidance.

[0420] Specific examples

[0421] For example, if the device detects a user smiling while walking through a virtual store, the server receives emotional data indicating "happiness." Based on this, a lively and energetic avatar is generated and displayed on the smart glasses. The avatar then introduces the items in a cheerful voice, saying things like, "I'll show you our special sale items!"

[0422] Prompt Sentence Examples

[0423] For example, the following prompts can be sent to the generative AI model to generate each element of the avatar:

[0424] "Anime-style appearance"

[0425] "A bright tone of voice"

[0426] "Cheerful response phrases"

[0427] This creates a personalized avatar that matches the user's emotions and needs.

[0428] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0429] Step 1:

[0430] Data collection and preprocessing

[0431] The server collects multiple image, audio, and text data from the Internet, public databases, and users. The collected data undergoes resizing, noise removal, and normalization for image data, noise removal, normalization, and key feature extraction for audio data, and tokenization, stop word removal, and stem extraction for text data. These preprocessed data are then stored in a database.

[0432] Input: image, audio, and text data

[0433] Output: Preprocessed data (images, audio, text)

[0434] Step 2:

[0435] Model learning

[0436] The server trains a generative AI model based on the preprocessed data. This involves using a generative adversarial network (GAN) for image generation, a speech synthesis model for voice generation, and a natural language processing model for text generation. Each feature of the data is learned through these models.

[0437] Input: Preprocessed image, audio, and text data

[0438] Output: Trained generative AI model (image generation model, speech generation model, text generation model)

[0439] Step 3:

[0440] User Selection and Data Submission

[0441] The device provides the user with a graphical operating environment, allowing the user to select the desired character or persona and upload custom images and voices, and the user's selections are transmitted from the device to a server.

[0442] Input: User-selected characters, people, and uploaded custom data

[0443] Output: Data sent to the server

[0444] Step 4:

[0445] Emotion analysis

[0446] The server analyzes the user's emotions using an emotion engine based on the data received through the user interface and the user's operations. The analysis results are used as feedback for each element of the avatar (appearance, voice, personality).

[0447] Input: User input data and operation logs

[0448] Output: Emotion analysis results

[0449] Step 5:

[0450] Avatar generation

[0451] The server selects the appropriate generative AI model (image generation, voice generation, text generation) based on the data sent by the user and the results of emotion analysis, and generates a 3D avatar. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates them using the corresponding models for each and integrates them.

[0452] Input: User selection data, emotion analysis results, trained generative AI model

[0453] Output: 3D avatar

[0454] Step 6:

[0455] View and edit your avatar

[0456] The device provides the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[0457] Input: Generated 3D avatar

[0458] Output: Avatar adjusted and saved by the user

[0459] Step 7:

[0460] Media sharing and promotional activities

[0461] Users can use the media sharing option to share the generated avatars on social media, video sharing sites, etc. The server also uses the generated avatars to support promotional activities in the metaverse and other virtual platforms.

[0462] Input: User's sharing instructions

[0463] Output: Avatars shared on social media and video sharing sites

[0464] Step 8:

[0465] Personalized guidance in virtual stores

[0466] When a user wears a head-mounted display and visits a virtual store, emotion analysis data is sent to the server. The server generates an optimal avatar based on this data and displays it in the user's field of view. This avatar provides personalized guidance within the virtual store.

[0467] Input: User emotion data, trained generative AI model

[0468] Output: An avatar that guides you through a virtual store

[0469] 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.

[0470] 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.

[0471] 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.

[0472] [Second embodiment]

[0473] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0474] 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.

[0475] 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).

[0476] 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.

[0477] 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.

[0478] 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).

[0479] 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.

[0480] 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.

[0481] 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.

[0482] 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.

[0483] 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.

[0484] 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."

[0485] The present invention is a system that allows users to create their ideal avatar and use it for various purposes. Specific embodiments of this system are described below.

[0486] 1. Data Collection and Preprocessing

[0487] server

[0488] The server first collects image, audio, and text data about the characters or people desired by the user. This data is collected from a variety of sources, including the Internet, public databases, and user-uploaded data.

[0489] The collected data is resized, noise-removed, and normalized in the case of image data, and noise-removal, normalization, and extraction of important features in the case of audio data.Text data undergoes preprocessing such as tokenization, stop word removal, and stem extraction.The preprocessed data is stored in a database.

[0490] 2. Model training

[0491] server

[0492] The server trains a generative AI model based on the preprocessed data. For example, an image generation model (e.g., GAN) learns a person's appearance characteristics, a voice generation model learns voice characteristics, and a text generation model learns personality traits. These models are stored on the server and used later in the generation process.

[0493] 3. Providing a user interface

[0494] Terminal

[0495] The user interface provides a graphical operating environment for users to select desired characters or people and upload custom images and voices. Users select the desired character or person items and transmit the data from their terminal to the server.

[0496] 4. Avatar Generation

[0497] server

[0498] The server analyzes the data sent by the user and selects the appropriate generative AI model (image generation, voice generation, personality generation). Based on this, a 3D avatar is generated. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[0499] 5. Check and edit your avatar

[0500] Terminal

[0501] The device presents the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[0502] 6. Media Sharing and Promotional Activities

[0503] Terminal

[0504] The device provides media sharing options for sharing the generated avatar to social media icons, video sharing sites, etc. It also includes an export function, allowing users to use the avatar on different platforms.

[0505] server

[0506] The server will support promotional activities using the generated avatars, including event management and campaign planning and execution in the metaverse and other virtual platforms.

[0507] Specific examples

[0508] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model to generate a 3D avatar that combines Character A's appearance, Person B's voice, and personality C obtained from the trained model. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[0509] The above is a specific embodiment for carrying out the present invention.

[0510] The processing flow will be explained below.

[0511] Step 1:

[0512] User:

[0513] Through the device's user interface, users select a character or person to base their ideal avatar on, and optionally upload custom images and audio files.

[0514] Step 2:

[0515] Device:

[0516] The device analyzes the user's selections and uploaded data, which includes images, audio, and text data, and transmits it to the server.

[0517] Step 3:

[0518] server:

[0519] The server preprocesses the received data: image data is resized and denoised, audio data is denoised and features are extracted, and text data is tokenised and stop words are removed.

[0520] Step 4:

[0521] server:

[0522] Based on the preprocessed data, a generative AI model is trained. Models for image generation (e.g., GAN), speech generation, and text generation are used to learn the characteristics of each.

[0523] Step 5:

[0524] server:

[0525] Save the trained generative AI model and prepare it for use based on user requests.

[0526] Step 6:

[0527] server:

[0528] The selection data sent by the user is analyzed and appropriate image generation, speech generation, and text generation models are selected.

[0529] Step 7:

[0530] server:

[0531] The selected generative AI model is used to generate each element of the 3D avatar: for example, an image generation model generates appearance, a speech generation model generates voice, and a text generation model generates personality.

[0532] Step 8:

[0533] server:

[0534] The generated avatar elements are integrated to create the final 3D avatar.

[0535] Step 9:

[0536] server:

[0537] The completed 3D avatar is sent to the device and provided to the user.

[0538] Step 10:

[0539] Device:

[0540] The user uses an interface to view the 3D avatar received on the device and edit it if necessary.

[0541] Step 11:

[0542] Device:

[0543] The edited avatar will provide a media sharing option to share to social media icons and video sharing sites according to the user's request.

[0544] Step 12:

[0545] server:

[0546] The server will support promotional activities using the generated avatars, including event management and planning and execution of promotional campaigns in the metaverse and other virtual platforms.

[0547] The above processing steps realize a system that allows users to easily create their ideal avatar and use it in a variety of media.

[0548] Example 1

[0549] 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."

[0550] In recent years, there has been a growing demand for systems that allow users to easily create their own original characters and use them for multiple purposes. In particular, creating anime-style characters or characters with the characteristics of celebrities and using them on social media and video sharing sites is extremely popular. However, existing technologies have difficulty efficiently collecting and classifying multiple data, and smoothly editing and sharing the generated characters.

[0551] 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.

[0552] In this invention, the server includes means for collecting and classifying a plurality of visual data, audio data, and text data, means for preprocessing the collected data and storing it in an information storage device, and means for learning appearance, voice, and personality traits from the preprocessed data using a generated machine learning model, thereby enabling the creation and multipurpose use of original characters desired by users.

[0553] "Visual data" refers to information that can be perceived visually, such as images and videos.

[0554] "Auditory data" refers to information that can be perceived auditorily, such as voice or music.

[0555] "Character data" refers to information expressed in text format.

[0556] An "information storage device" is a device for storing and managing data.

[0557] A "generated machine learning model" is a model that learns features from data and runs an algorithm to generate new data.

[0558] "Operation interface" refers to the screen and input devices that allow the user to interact with the system and perform operations.

[0559] A "central processing unit" is a computer that controls the entire system and processes data.

[0560] "3D virtual character" means a digitally generated character in three-dimensional form.

[0561] "Media sharing options" refers to functions and options for publishing the generated character and related information on social networks and video sharing sites.

[0562] "Promotional Activities" refers to promotional and marketing activities aimed at increasing awareness and sales of a particular product or service.

[0563] The present invention is a system that allows users to create their ideal original character and use it in a variety of ways. Specific embodiments of this system are described below.

[0564] System Configuration

[0565] server

[0566] The server plays a central role in the entire system and performs the following processes:

[0567] Data collection and preprocessing: The server collects visual, auditory, and text data from the internet, public databases, and uploaded by users. The collected data is resized and denoised using an image processing library (e.g., OpenCV), and denoised and feature extracted using an audio processing library (e.g., Librosa). Text data is tokenised and stopwords are removed using a natural language processing library (e.g., NLTK, spaCy).

[0568] Model training: The preprocessed data is used to train a generative AI model (e.g., GAN, speech synthesis model, text generation model) using a deep learning framework (e.g., TensorFlow, PyTorch) running on high-performance hardware (e.g., NVIDIA GPU).

[0569] Avatar generation: A trained generative AI model is used to generate a 3D virtual character based on user-submitted data. Visual elements are integrated using 3D modeling software like Blender.

[0570] Terminal

[0571] The terminal provides a user interface and editing functions. The specific process is as follows:

[0572] User Interface: Provides a web browser-based interface implemented using front-end frameworks such as React or Vue.js, where users can select their desired character or persona and upload custom visual and auditory data.

[0573] Avatar display and editing: The generated 3D virtual character is displayed using libraries such as Three.js. Users can edit details in real time, and the edits are sent to the server and saved.

[0574] Media Sharing and Export: Provides the option to share the completed avatar directly to social media and video sharing sites. Sharing is done using social media APIs (e.g. Twitter API, YouTube API). Export functionality is also provided, allowing you to save in standard 3D file formats (e.g. FBX, OBJ).

[0575] User

[0576] The user does the following:

[0577] Data Upload: Upload visual, auditory and textual data about the desired character or person through the interface.

[0578] Character Selection and Customization: Select your desired character or persona from the provided list and customize their detailed parameters.

[0579] Edit the generated avatar: Review the generated avatar and make any necessary adjustments, including adding facial expressions or accessories.

[0580] Media sharing: Share the completed avatar on social media and video sharing sites to promote it.

[0581] Specific examples

[0582] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses a trained generative AI model to generate a 3D virtual character that combines the appearance of Character A, the voice of Person B, and personality C obtained from the trained model. The generated character is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and for promotional activities.

[0583] Prompt Sentence Examples

[0584] For example, you might enter the following prompt for a generative AI model:

[0585] "Generate a 3D virtual character with the appearance of anime character A, the voice of celebrity B, and the traits of personality C."

[0586] This allows the user's ideal virtual character to be generated efficiently and with high quality.

[0587] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0588] Step 1: Data collection and preprocessing

[0589] The server receives requests from users and collects visual, auditory and textual data from the Internet, public databases and user uploaded data.

[0590] Input: Data collection request from user

[0591] What it does: The server uses API requests to retrieve the required data from the data source. For example, image data is collected by web scraping, and audio data is downloaded from a public audio database.

[0592] Data processing: The acquired visual data (images) are resized and denoised using OpenCV. The auditory data (audio) is denoised and features extracted using Librosa, and the text data is tokenised and stopwords removed using NLTK or spaCy.

[0593] Output: Preprocessed data (visual data, auditory data, text data)

[0594] Step 2: Model training

[0595] The server trains a generative AI model based on the preprocessed data.

[0596] Input: Preprocessed data (visual, auditory, textual)

[0597] Specific operation: The server uses TensorFlow or PyTorch to train generative AI models (e.g., GANs, speech synthesis models, text generation models). High-performance NVIDIA GPUs (e.g., Tesla V100) are used for hardware. Batch processing is used for learning, and the model is trained for the specified number of epochs.

[0598] Data calculation: Split the data into training and validation sets, and tune the hyperparameters to improve the model accuracy.

[0599] Output: Trained generative AI model

[0600] Step 3: Providing a User Interface

[0601] The terminal provides an operation interface for the user to select the desired character or person and upload custom data.

[0602] Input: User interaction and selection data (character / persona information, custom visual data, auditory data)

[0603] Specific operation: Display a web browser-based interface and build an operation screen using React and Vue.js. The user can upload data through the interface and send the data to the server using an Ajax request.

[0604] Output: User data sent to the server

[0605] Step 4: Avatar generation

[0606] The server analyzes the data sent by the user and selects an appropriate generative AI model to generate a 3D virtual character.

[0607] Input: User data (character / persona information, custom visual data, audio data)

[0608] How it works: The server analyzes the received data and inputs visual, auditory, and text data into each generative AI model. Each generative AI model generates its own elements and integrates them using 3D modeling software such as Blender.

[0609] Data calculation: The elements (appearance, voice, personality) generated by each generative AI model are combined to construct a 3D virtual character.

[0610] Output: Finished 3D virtual character

[0611] Step 5: Review and edit your avatar

[0612] The terminal provides the generated 3D virtual character to the user and provides an interface for editing.

[0613] Input: Finished 3D virtual character

[0614] How it works: It uses Three.js to display a 3D virtual character in the browser and allows users to edit it. The edits made by the user are sent to the server in real time and saved.

[0615] Output: The final edited 3D virtual character

[0616] Step 6: Media sharing and promotional activities

[0617] The terminal and server support media sharing and promotional activities.

[0618] Input: Edited 3D virtual character

[0619] Specific operation: The device uses social media APIs to provide sharing options to social media and video sharing sites. The server supports promotional activities using the generated virtual characters and manages events in the metaverse and virtual platforms.

[0620] Output: Analysis data on the effectiveness of virtual characters posted on social media and video sharing sites, and promotional activities

[0621] (Application example 1)

[0622] 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."

[0623] In today's virtual stores, it is difficult for users to obtain a shopping experience that reflects their personal preferences. In particular, there is a lack of a realistic sensory experience when trying on and purchasing products. Furthermore, non-personalized suggestions and product explanations hinder efficient shopping. There is a need to solve these problems and provide users with a high-quality shopping experience.

[0624] 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.

[0625] In this invention, the server includes means for collecting and classifying multiple image, audio, and text data, means for preprocessing the collected data and storing it in a database, means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data, means for a user to select a desired character or person through a user interface and send the data to the server, means for generating a 3D avatar using the generative AI model based on the selected data, means for providing the generated 3D avatar to the user and allowing the user to edit it, means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites, means for supporting the user's shopping experience in a virtual store using the generated avatar, means for providing a virtual try-on system that uses an avatar to try on and recommend products, and means for explaining products using an avatar's voice guide function. This provides a personalized shopping experience for the user, enabling a realistic try-on experience and efficient product recommendations.

[0626] "Image data" means a digital image containing visual information of a person or character designated by the user.

[0627] "Audio Data" means an audio file containing the voice characteristics of a person or character designated by the user.

[0628] "Text data" is written information about the personality and other attributes of a person or character designated by the user.

[0629] A "generative AI model" is an artificial intelligence algorithm that learns appearance, voice, and personality from preprocessed image, audio, and text data to generate an avatar.

[0630] A "user interface" is software that provides an operating environment for a user to interact with the system, select a desired character or person, and transmit that data to a server.

[0631] A "server" is a computer system that collects, preprocesses, and stores data, runs generative AI models, and manages generated avatars.

[0632] A "3D avatar" is a three-dimensional virtual character generated based on a generative AI model that expresses the user's desired appearance, voice, and personality.

[0633] The "Virtual Try-On System" is a system that allows users to try on and receive product recommendations in a virtual space using a generated 3D avatar.

[0634] The "audio guide function" is a feature in which a generated 3D avatar explains products and assists users with their shopping by voice.

[0635] "SNS" is a social networking service that allows users to share their generated 3D avatars and their activities.

[0636] A "video sharing site" is a web platform that allows users to upload content using generated avatars and share it with other users.

[0637] The system for implementing this invention is realized by the following procedure: The purpose of this system is to enable users to create their ideal avatar and use it to provide a personalized shopping experience.

[0638] First, the server collects multiple images, audio, and text data from the Internet, public databases, and data uploaded by users. The collected data is resized, denoised, and normalised for images, and denoised, normalised, and key features extracted for audio data. The text data is tokenised, stop words are removed, and stems are extracted. The preprocessed data is stored in a database. The hardware used includes a high-performance server, and the software uses data preprocessing libraries such as OpenCV, Librosa, and NLTK.

[0639] The server then uses generative AI models to learn appearance, voice, and personality from the preprocessed data. For example, these models use Generative Adversarial Networks (GANs) to generate images, voices, and text. These models are trained and stored on the server.

[0640] Users can operate a graphical user interface through their smartphone, tablet, or PC device to select the desired character or persona and upload custom images and voices. The selected and uploaded data is then sent to a server.

[0641] The server analyzes the received user data and generates a 3D avatar using a trained generative AI model. The generated 3D avatar is sent to the device, where the user can view and edit it. The editing interface allows the user to adjust details and save the completed avatar.

[0642] The completed avatar provides a media sharing option for sharing on social media and video sharing sites. Furthermore, the system also includes a function to support the user's shopping experience in a virtual store using the generated avatar. Specifically, the virtual try-on system allows the user to try on clothes and accessories using the avatar, and the avatar can suggest products and provide product explanations using an audio guide function.

[0643] For example, if a user wants to create an avatar with the characteristics of a favorite celebrity, they might enter the following prompt:

[0644] "Use the face and voice of your favorite celebrity to suggest outfits that would look good on me, just like a stylist. Then try them on on your avatar."

[0645] In this way, users can create avatars that reflect their preferences and use them to enjoy shopping in virtual stores.

[0646] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0647] Step 1:

[0648] The server collects multiple images, audio, and text data from the Internet, public databases, and data uploaded by users. This provides basic data about the characters and people desired by the user. The inputs are image files, audio files, and text data, which are stored in a database for centralized management.

[0649] Step 2:

[0650] The server preprocesses the collected data and stores it in a database. Image data is resized, denoised, and normalised, while audio data is denoised, normalised, and key features are extracted. Text data is tokenised, stop words are removed, and stems are extracted. This improves data accuracy and enables efficient training for the generative AI model.

[0651] Step 3:

[0652] The server trains a generative AI model based on the preprocessed data. Examples include image generation models, speech generation models, and text generation models using GANs (Generative Adversarial Networks). This builds a basic model that reflects the appearance, voice, and personality selected by the user. The preprocessed data is used as input, and a trained model is obtained as output.

[0653] Step 4:

[0654] The user uses a device to operate the user interface. The user can select a desired character or persona and upload custom images and voices. This data is sent to a server, which collects and stores the user's input. The input is the selected character information and additional images and voices, and the output is the user data sent to the server.

[0655] Step 5:

[0656] The server analyzes the received user data and generates a 3D avatar using a trained generative AI model. The input is the user data and the trained model, and the output is the generated 3D avatar. This avatar is stored on the server and provided to the user's device.

[0657] Step 6:

[0658] Users can view and edit the generated 3D avatar through their devices. They can adjust and modify details through the user interface. The input is the generated 3D avatar, and the output is the final avatar that reflects the user's edits.

[0659] Step 7:

[0660] The completed avatar provides a media sharing option for sharing to social networking sites and video sharing sites, allowing users to utilize their avatar across multiple platforms. The input is the final edited avatar, and the output is the avatar deployment on social networking sites and video sharing sites.

[0661] Step 8:

[0662] The generated avatar is used to support the user's shopping experience in a virtual store. For example, a virtual try-on system provides a function where the avatar tries on products, and an audio guide function provides product explanations. This allows the user to enjoy a realistic shopping experience. The input is the generated avatar and product data in the store, and the output is an avatar with try-on and guide functions.

[0663] As a specific example, a user can create an avatar with the features of their favorite celebrity and use the prompt, "Please suggest clothes that would suit me, like a stylist, using the face and voice of my favorite celebrity. Also, please let me try on the clothes on my avatar." to create a shopping experience that suits their tastes.

[0664] 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.

[0665] The present invention combines an emotion engine with a system that allows users to create their ideal avatar and use it for various purposes. By using the emotion engine, the user's emotions can be analyzed and the results can be reflected in the creation of the avatar and promotional activities. A specific embodiment of this system is described below.

[0666] 1. Data Collection and Preprocessing

[0667] server

[0668] The server first collects image, audio, and text data about the characters or people desired by the user. This data is collected from a variety of sources, including the Internet, public databases, and user-uploaded data.

[0669] The collected data is resized, noise-removed, and normalized in the case of image data, and noise-removal, normalization, and extraction of important features in the case of audio data.Text data undergoes preprocessing such as tokenization, stop word removal, and stem extraction.The preprocessed data is stored in a database.

[0670] 2. Model training

[0671] server

[0672] The server trains a generative AI model based on the preprocessed data. For example, it uses an image generation model (e.g., GAN), a voice generation model, and a text generation model to learn the features of each. These models are stored on the server and used later in the generation process.

[0673] 3. Providing a user interface

[0674] Terminal

[0675] The user interface provides a graphical operating environment for users to select desired characters or people and upload custom images and voices. Users select the desired character or person items and transmit the data from their terminal to the server.

[0676] 4. Use of Emotion Engine

[0677] server

[0678] The server is equipped with an emotion engine that analyzes the user's emotions based on the user's operations and input data. This emotion data is used as feedback for each element of the avatar (appearance, voice, personality).

[0679] 5. Avatar Generation

[0680] server

[0681] The server selects the appropriate generative AI model (image generation, voice generation, text generation) based on the data submitted by the user and the results of emotion analysis. Based on this, a 3D avatar is generated. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[0682] 6. View and edit your avatar

[0683] Terminal

[0684] The device presents the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[0685] 7. Media Sharing and Promotional Activities

[0686] Terminal

[0687] The device provides media sharing options for sharing the generated avatar to social media icons, video sharing sites, etc. It also includes an export function, allowing users to use the avatar on different platforms.

[0688] server

[0689] The server will support promotional activities using the generated avatars, including event management and campaign planning and execution in the metaverse and other virtual platforms.

[0690] Specific examples

[0691] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model and emotion engine to generate a 3D avatar that combines the appearance of Character A, the voice of Person B, and personality C based on the user's emotions. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[0692] The above is a specific embodiment for carrying out the present invention.

[0693] The processing flow will be explained below.

[0694] Step 1:

[0695] User:

[0696] Through the device's user interface, users select a character or person to base their ideal avatar on, and optionally upload custom images and audio files.

[0697] Step 2:

[0698] Device:

[0699] The device analyzes the user's selections and uploaded data, which includes images, audio, and text data, and transmits it to the server.

[0700] Step 3:

[0701] server:

[0702] The server preprocesses the received data: image data is resized and denoised, audio data is denoised and features are extracted, and text data is tokenised and stop words are removed.

[0703] Step 4:

[0704] server:

[0705] Based on the preprocessed data, a generative AI model is trained. Models for image generation (e.g., GAN), speech generation, and text generation are used to learn the characteristics of each.

[0706] Step 5:

[0707] server:

[0708] Save the trained generative AI model and prepare it for use based on user requests.

[0709] Step 6:

[0710] server:

[0711] The server uses the emotion engine to analyze the user's emotions based on the user's operations and input data. The analyzed emotion data is used in subsequent processing.

[0712] Step 7:

[0713] server:

[0714] The selection data and emotion data sent by the user are analyzed, and appropriate image generation, speech generation, and text generation models are selected.

[0715] Step 8:

[0716] server:

[0717] The selected generative AI model is used to generate each element of the 3D avatar: for example, appearance is generated by an image generation model, voice by a voice generation model, and personality by a text generation model.

[0718] Step 9:

[0719] server:

[0720] Based on the analysis results of the emotion engine, necessary feedback is applied to each generated element to optimize the 3D avatar, allowing the avatar's appearance, voice, and personality to adapt to the user's emotional state.

[0721] Step 10:

[0722] server:

[0723] The completed 3D avatar is sent to the device and provided to the user.

[0724] Step 11:

[0725] Device:

[0726] The user uses an interface to view the 3D avatar received on the device and edit it if necessary.

[0727] Step 12:

[0728] Device:

[0729] The edited avatar will provide a media sharing option to share to social media icons and video sharing sites according to the user's request.

[0730] Step 13:

[0731] server:

[0732] The server will support promotional activities using the generated avatars, including event management and planning and execution of promotional campaigns in the metaverse and other virtual platforms.

[0733] As a specific example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model and emotion engine to generate a 3D avatar that combines Character A's appearance with Person B's voice and an optimal personality based on emotion analysis. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[0734] The above processing steps realize a system that allows users to easily create their ideal avatar and use it in a variety of media.

[0735] Example 2

[0736] 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."

[0737] Conventional avatar generation systems have had difficulty generating avatars that reflect the user's emotions. Furthermore, it is complicated to integrate different media formats (images, audio, text) to generate diverse avatars. This makes it difficult for users to easily create their ideal avatar and use it for multiple purposes.

[0738] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: [means for collecting and classifying multiple visual data, audio data, and natural language data]; [means for preprocessing the collected data and storing it in a database]; [means for using a generative artificial intelligence model to learn appearance, voice, and personality from the preprocessed data]; [means for an end user to select a desired character or person through a user interface and transmit the data to a host system]; [means for generating a three-dimensional avatar using a generative artificial intelligence model based on the selected data]; [means for analyzing the user's emotions using an emotion engine and reflecting the results in avatar generation]; [means for providing the generated three-dimensional avatar to the end user and allowing editing]; [means for providing a media sharing option for sharing the edited avatar on social networking services and video sharing platforms]; and [means for supporting marketing activities using the generated avatar]. This enables users to easily generate their ideal avatar and use it on various platforms.

[0739] "Visual data" is data expressed as images, and includes still images such as photographs, illustrations, and videos, as well as moving images.

[0740] "Audio data" refers to data expressed as sound, including music, speech, sound effects, and the like.

[0741] "Natural language data" refers to data in a language that is naturally spoken or written by humans, and includes text documents and records of conversations.

[0742] "Preprocessing" refers to a processing step for preparing data for use after collection, and includes processes such as data noise removal, normalization, and feature extraction.

[0743] "Database" means a system for efficiently and securely storing and managing collected and pre-processed data.

[0744] "Generative AI models" refers to algorithms or neural network models that learn specific tasks based on preprocessed data and generate new data or results.

[0745] "User Interface" means a graphical or text-based interface through which an end user interacts with and operates a system.

[0746] "Host System" refers to a central server or cloud computing environment that receives, analyzes, and processes user input data.

[0747] The "emotion engine" is a system that analyzes emotions from user operations and input data, and provides feedback to avatar generation based on that emotional data.

[0748] A "3D avatar" refers to a user-customizable 3D character or person model.

[0749] A "social networking service" is an online platform that allows users to exchange information with each other via the Internet.

[0750] A "video sharing platform" is an online platform for users to upload video content and share it with other users.

[0751] "Media sharing options" refers to a function for sharing the generated avatar and its related content with other users.

[0752] "Marketing activities" refers to the use of the generated avatar in commercial activities such as promotions and advertising campaigns.

[0753] The present invention provides a system that allows end users to create their ideal three-dimensional avatar and use it for a variety of purposes. This system also incorporates an emotion engine that can analyze the user's emotions and reflect the results in the avatar generation. The specific system configuration and operating procedures for implementing the present invention are described in detail below.

[0754] System Configuration

[0755] 1. Server

[0756] The server provides the following functions:

[0757] It has the ability to collect, classify, and preprocess multiple visual, audio, and natural language data.

[0758] It has the ability to train generative artificial intelligence models (e.g., generative adversarial networks (GANs), speech generation models, and text generation models) to generate the appearance, voice, and personality of avatars.

[0759] An emotion engine is used to analyze the user's emotions and reflect the results in avatar generation.

[0760] The database stores collected and preprocessed data, as well as trained generative AI models.

[0761] 2. Terminal

[0762] The device offers the user the following features:

[0763] Through a user interface, the end user can select the desired character or persona and upload custom visual and audio data.

[0764] The generated three-dimensional avatar is provided to the user, and an interface is displayed that allows the user to preview and edit the avatar.

[0765] It provides media sharing options to share your avatar to social networking services and video sharing platforms.

[0766] Specific examples

[0767] For example, if a user wants to create a virtual YouTuber with the characteristics of their favorite manga character "Character A" and a specific celebrity "Person B," they first select those characters and people using their device and send the data to the server. The server then uses the preprocessed data to generate a three-dimensional avatar using a trained generative AI model (e.g., GAN, voice generation model) and an emotion engine to combine the appearance of "Character A," the voice of "Person B," and "Personality C" based on the user's emotions.

[0768] The device provides the generated 3D avatar to the user, who can preview it and edit it as needed. The completed avatar can be shared via the device to social networking sites and video sharing sites. The server also supports marketing activities using the generated avatar, allowing users to run virtual events and campaigns.

[0769] Prompt Sentence Examples

[0770] "Generate a virtual YouTuber with the appearance of anime character 'Character A', the voice of celebrity 'Person B', and the personality 'Personality C' analyzed by the emotion engine."

[0771] The above is a specific embodiment for carrying out the present invention. This invention allows users to easily create their ideal three-dimensional avatar and use it on a wide range of platforms.

[0772] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0773] Step 1:

[0774] Data collection and classification:

[0775] Subject: Server

[0776] The server collects multiple visual, audio and natural language data from sources such as the Internet, public databases and user uploads.

[0777] Input: Image, audio, and text data related to characters and people.

[0778] Specific operations: Uses a web crawler to collect image data from the Internet, and stores audio files and text data uploaded by users in cloud storage.

[0779] Output: The collected dataset.

[0780] Step 2:

[0781] Data preprocessing:

[0782] Subject: Server

[0783] The server resizes, denoises, and normalizes the collected data for images, denoises, normalizes, and extracts features for audio data, and tokenizes, removes stop words, and extracts stems for text data.

[0784] Input: The collected dataset.

[0785] Specific operation: Resize to 128x128 pixels using an image processing library, remove noise using a speech processing library, and tokenize the text data using a natural language processing library.

[0786] Output: A preprocessed dataset.

[0787] Step 3:

[0788] Train the model:

[0789] Subject: Server

[0790] The server trains a generative artificial intelligence model (e.g., GAN, speech generation model, text generation model) based on the preprocessed data.

[0791] Input: Preprocessed image data, audio data, and natural language data.

[0792] How it works: We train GANs on a GPU cluster to generate trained models. Each generative AI model is fed with collected data and undergoes an optimization process over multiple epochs.

[0793] Output: A trained generative AI model.

[0794] Step 4:

[0795] Providing a user interface:

[0796] Subject: Terminal

[0797] Through a user interface, the device allows the end user to select the desired character or persona and upload custom visual and audio data.

[0798] Input: User selections and uploaded image and audio data.

[0799] Specific behavior: Build a UI using a web application framework and handle user interactions.

[0800] Output: User input data.

[0801] Step 5:

[0802] Sentiment analysis with emotion engine:

[0803] Subject: Server

[0804] The server uses an emotion engine to analyze emotions based on user operations and input data.

[0805] Input: The text the user types and the options selected.

[0806] Specific operation: Uses a sentiment analysis algorithm to extract sentiment from user input data. Calculates sentiment scores for each text using a sentiment dictionary.

[0807] Output: User emotion data.

[0808] Step 6:

[0809] Avatar Creation:

[0810] Subject: Server

[0811] The server selects an appropriate generative AI model based on the data sent by the user and the results of emotion analysis, and generates a three-dimensional avatar.

[0812] Input: A trained generative AI model and user emotion data.

[0813] How it works: A visual model is generated using GAN, and a voice model is used to generate a person's voice. These are then integrated to generate a 3D avatar.

[0814] Output: The generated 3D avatar.

[0815] Step 7:

[0816] Provide and edit your avatar:

[0817] Subject: Terminal

[0818] The terminal provides the generated three-dimensional avatar to the user and displays an interface for editing.

[0819] Input: A generated 3D avatar.

[0820] What it does: Allows users to preview their avatar and make any necessary changes. Reflects user editing requests in real time.

[0821] Output: An edited 3D avatar.

[0822] Step 8:

[0823] Media sharing options available:

[0824] Subject: Terminal

[0825] The device provides a media sharing option for sharing the edited avatar to social networking services and video sharing platforms.

[0826] Input: An edited 3D avatar.

[0827] What it does: It generates a share link and embed code so that users can easily share their edited avatar on social media or video sites. Simply click the share button and the data will be transferred automatically.

[0828] Output: Share link and embed code.

[0829] Step 9:

[0830] Supporting your marketing efforts:

[0831] Subject: Server

[0832] The server supports marketing activities using the generated avatars.

[0833] Input: A generated 3D avatar.

[0834] What it does: Provides data needed to design and execute marketing campaigns and virtual events. Customizes promotional avatars and distributes them to target audiences.

[0835] Output: Campaign data and virtual event configuration information.

[0836] (Application example 2)

[0837] 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."

[0838] Conventional avatar generation systems have difficulty adjusting avatars in real time to reflect user emotions, making it difficult to provide a personalized customer service experience, especially in virtual stores. Furthermore, they lack the functionality to generate and adjust avatars based on user emotions, making it impossible to improve the user experience. To solve these issues, a more advanced avatar generation system incorporating user emotion analysis is needed.

[0839] 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.

[0840] In this invention, the server includes: [means for collecting and classifying multiple image, audio, and text data;] [means for preprocessing the collected data and storing it in a database;] [means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data;] [means for the user to select a desired character or person through a user interface and send the data to the server;] [means for generating a 3D avatar using the generative AI model based on the selected data;] [means for providing the generated 3D avatar to the user and allowing the user to edit it;] [means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites;] [means for supporting promotional activities using the generated avatar;] [means for analyzing the user's emotions and adjusting the avatar based on the data;] [means for analyzing the emotion data on the server and reflecting it in each element of the avatar; and [means for the user to use the avatar in a virtual store and receive personalized guidance.] This allows the avatar to be adjusted in real time based on an analysis of the user's emotions, enabling a personalized customer service experience in the virtual store.

[0841] "Image, audio and text data" refers to visual, audio and textual information about a character or person desired by the user.

[0842] "Preprocessing" refers to the process of converting collected data into a format suitable for analysis and learning. Specifically, it includes resizing and noise removal for image data, noise removal and feature extraction for audio data, tokenization for text data, and stop word removal.

[0843] "Generative AI models" refer to machine learning models for generating and learning appearance, voice, and personality from collected and pre-processed data, including models for image generation, speech generation, and text generation.

[0844] "User interface" refers to the operating environment that allows a user to select a desired character or person and input and manage data.

[0845] A "3D avatar" refers to a three-dimensional character with the user's desired appearance, voice, and personality.

[0846] "Emotion analysis" refers to the process of analyzing a user's facial expressions and voice to identify their emotional state.

[0847] "Virtual store" refers to a shopping environment created in a virtual space via the Internet, where users can access the store through a virtual reality device and browse, select, and purchase products.

[0848] "Personalized guidance" refers to the provision of information and services that are individually optimized based on the user's emotions and past behavioral history.

[0849] "SNS" is an abbreviation for social networking service, and refers to an online service that allows users to interact with each other.

[0850] "Media sharing options" refers to the functionality that allows users to post and share their generated avatars on various online platforms.

[0851] "Promotional Activities" refers to marketing and advertising activities using the generated Avatars, including, specifically, events and campaigns in the Metaverse.

[0852] MODE FOR CARRYING OUT THE INVENTION

[0853] The system for implementing the present invention operates through the interaction of a server, a terminal, and a user.

[0854] 1. Data Collection and Preprocessing

[0855] First, the server collects multiple image, audio, and text data from the Internet, public databases, and users. Image data is resized and noise-removed, while audio data is denoised, key features are extracted, and normalisation is performed. Text data is tokenised, stop words are removed, and stemming is extracted. These preprocessed data are then stored in a database.

[0856] 2. Model training

[0857] The server trains a generative AI model based on the preprocessed data. Specifically, it uses an image generation model (e.g., GAN), a voice generation model, and a text generation model to learn the features of each. These models are stored on the server and used later in the generation process.

[0858] 3. Providing a user interface

[0859] A graphical operating environment is provided on the device to allow users to select the desired character or person and upload custom images and voices, through which the user selects the desired character or person data and transmits the data from the device to a server.

[0860] 4. Use of Emotion Engine

[0861] The server is equipped with an emotion engine that analyzes the user's emotions based on the user's operations and input data. This emotion data is used as feedback for each element of the avatar (appearance, voice, personality).

[0862] 5. Avatar Generation

[0863] The server selects an appropriate generative AI model based on the data submitted by the user and the results of emotion analysis, and generates a 3D avatar. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[0864] 6. View and edit your avatar

[0865] The device provides the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust the details of the avatar, and save the completed avatar.

[0866] 7. Media Sharing and Promotional Activities

[0867] Users can use the media sharing option to share the generated avatar on social media, video sharing sites, etc. The avatar can also be used to support promotional activities in the metaverse and virtual platforms provided by the server.

[0868] 8. Virtual store applications

[0869] The server adjusts the avatar in real time based on the results of the user's emotion analysis and provides personalized guidance in the virtual store. When a user wears a head-mounted display and visits a virtual store, emotion analysis data is sent to the server, which then generates an optimal avatar and displays it in the user's field of view, providing personalized guidance.

[0870] Specific examples

[0871] For example, if the device detects a user smiling while walking through a virtual store, the server receives emotional data indicating "happiness." Based on this, a lively and energetic avatar is generated and displayed on the smart glasses. The avatar then introduces the items in a cheerful voice, saying things like, "I'll show you our special sale items!"

[0872] Prompt Sentence Examples

[0873] For example, the following prompts can be sent to the generative AI model to generate each element of the avatar:

[0874] "Anime-style appearance"

[0875] "A bright tone of voice"

[0876] "Cheerful response phrases"

[0877] This creates a personalized avatar that matches the user's emotions and needs.

[0878] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0879] Step 1:

[0880] Data collection and preprocessing

[0881] The server collects multiple image, audio, and text data from the Internet, public databases, and users. The collected data undergoes resizing, noise removal, and normalization for image data, noise removal, normalization, and key feature extraction for audio data, and tokenization, stop word removal, and stem extraction for text data. These preprocessed data are then stored in a database.

[0882] Input: image, audio, and text data

[0883] Output: Preprocessed data (images, audio, text)

[0884] Step 2:

[0885] Model learning

[0886] The server trains a generative AI model based on the preprocessed data. This involves using a generative adversarial network (GAN) for image generation, a speech synthesis model for voice generation, and a natural language processing model for text generation. Each feature of the data is learned through these models.

[0887] Input: Preprocessed image, audio, and text data

[0888] Output: Trained generative AI model (image generation model, speech generation model, text generation model)

[0889] Step 3:

[0890] User Selection and Data Submission

[0891] The device provides the user with a graphical operating environment, allowing the user to select the desired character or persona and upload custom images and voices, and the user's selections are transmitted from the device to a server.

[0892] Input: User-selected characters, people, and uploaded custom data

[0893] Output: Data sent to the server

[0894] Step 4:

[0895] Emotion analysis

[0896] The server analyzes the user's emotions using an emotion engine based on the data received through the user interface and the user's operations. The analysis results are used as feedback for each element of the avatar (appearance, voice, personality).

[0897] Input: User input data and operation logs

[0898] Output: Emotion analysis results

[0899] Step 5:

[0900] Avatar generation

[0901] The server selects the appropriate generative AI model (image generation, voice generation, text generation) based on the data sent by the user and the results of emotion analysis, and generates a 3D avatar. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates them using the corresponding models for each and integrates them.

[0902] Input: User selection data, emotion analysis results, trained generative AI model

[0903] Output: 3D avatar

[0904] Step 6:

[0905] View and edit your avatar

[0906] The device provides the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[0907] Input: Generated 3D avatar

[0908] Output: Avatar adjusted and saved by the user

[0909] Step 7:

[0910] Media sharing and promotional activities

[0911] Users can use the media sharing option to share the generated avatars on social media, video sharing sites, etc. The server also uses the generated avatars to support promotional activities in the metaverse and other virtual platforms.

[0912] Input: User's sharing instructions

[0913] Output: Avatars shared on social media and video sharing sites

[0914] Step 8:

[0915] Personalized guidance in virtual stores

[0916] When a user wears a head-mounted display and visits a virtual store, emotion analysis data is sent to the server. The server generates an optimal avatar based on this data and displays it in the user's field of view. This avatar provides personalized guidance within the virtual store.

[0917] Input: User emotion data, trained generative AI model

[0918] Output: An avatar that guides you through a virtual store

[0919] 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.

[0920] 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.

[0921] 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.

[0922] [Third embodiment]

[0923] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0924] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0925] 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).

[0926] 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.

[0927] 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.

[0928] 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).

[0929] 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.

[0930] 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.

[0931] 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.

[0932] 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.

[0933] 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.

[0934] 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."

[0935] The present invention is a system that allows users to create their ideal avatar and use it for various purposes. Specific embodiments of this system are described below.

[0936] 1. Data Collection and Preprocessing

[0937] server

[0938] The server first collects image, audio, and text data about the characters or people desired by the user. This data is collected from a variety of sources, including the Internet, public databases, and user-uploaded data.

[0939] The collected data is resized, noise-removed, and normalized in the case of image data, and noise-removal, normalization, and extraction of important features in the case of audio data.Text data undergoes preprocessing such as tokenization, stop word removal, and stem extraction.The preprocessed data is stored in a database.

[0940] 2. Model training

[0941] server

[0942] The server trains a generative AI model based on the preprocessed data. For example, an image generation model (e.g., GAN) learns a person's appearance characteristics, a voice generation model learns voice characteristics, and a text generation model learns personality traits. These models are stored on the server and used later in the generation process.

[0943] 3. Providing a user interface

[0944] Terminal

[0945] The user interface provides a graphical operating environment for users to select desired characters or people and upload custom images and voices. Users select the desired character or person items and transmit the data from their terminal to the server.

[0946] 4. Avatar Generation

[0947] server

[0948] The server analyzes the data sent by the user and selects the appropriate generative AI model (image generation, voice generation, personality generation). Based on this, a 3D avatar is generated. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[0949] 5. Check and edit your avatar

[0950] Terminal

[0951] The device presents the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[0952] 6. Media Sharing and Promotional Activities

[0953] Terminal

[0954] The device provides media sharing options for sharing the generated avatar to social media icons, video sharing sites, etc. It also includes an export function, allowing users to use the avatar on different platforms.

[0955] server

[0956] The server will support promotional activities using the generated avatars, including event management and campaign planning and execution in the metaverse and other virtual platforms.

[0957] Specific examples

[0958] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model to generate a 3D avatar that combines Character A's appearance, Person B's voice, and personality C obtained from the trained model. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[0959] The above is a specific embodiment for carrying out the present invention.

[0960] The processing flow will be explained below.

[0961] Step 1:

[0962] User:

[0963] Through the device's user interface, users select a character or person to base their ideal avatar on, and optionally upload custom images and audio files.

[0964] Step 2:

[0965] Device:

[0966] The device analyzes the user's selections and uploaded data, which includes images, audio, and text data, and transmits it to the server.

[0967] Step 3:

[0968] server:

[0969] The server preprocesses the received data: image data is resized and denoised, audio data is denoised and features are extracted, and text data is tokenised and stop words are removed.

[0970] Step 4:

[0971] server:

[0972] Based on the preprocessed data, a generative AI model is trained. Models for image generation (e.g., GAN), speech generation, and text generation are used to learn the characteristics of each.

[0973] Step 5:

[0974] server:

[0975] Save the trained generative AI model and prepare it for use based on user requests.

[0976] Step 6:

[0977] server:

[0978] The selection data sent by the user is analyzed and appropriate image generation, speech generation, and text generation models are selected.

[0979] Step 7:

[0980] server:

[0981] The selected generative AI model is used to generate each element of the 3D avatar: for example, an image generation model generates appearance, a speech generation model generates voice, and a text generation model generates personality.

[0982] Step 8:

[0983] server:

[0984] The generated avatar elements are integrated to create the final 3D avatar.

[0985] Step 9:

[0986] server:

[0987] The completed 3D avatar is sent to the device and provided to the user.

[0988] Step 10:

[0989] Device:

[0990] The user uses an interface to view the 3D avatar received on the device and edit it if necessary.

[0991] Step 11:

[0992] Device:

[0993] The edited avatar will provide a media sharing option to share to social media icons and video sharing sites according to the user's request.

[0994] Step 12:

[0995] server:

[0996] The server will support promotional activities using the generated avatars, including event management and planning and execution of promotional campaigns in the metaverse and other virtual platforms.

[0997] The above processing steps realize a system that allows users to easily create their ideal avatar and use it in a variety of media.

[0998] Example 1

[0999] 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."

[1000] In recent years, there has been a growing demand for systems that allow users to easily create their own original characters and use them for multiple purposes. In particular, creating anime-style characters or characters with the characteristics of celebrities and using them on social media and video sharing sites is extremely popular. However, existing technologies have difficulty efficiently collecting and classifying multiple data, and smoothly editing and sharing the generated characters.

[1001] 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.

[1002] In this invention, the server includes means for collecting and classifying a plurality of visual data, audio data, and text data, means for preprocessing the collected data and storing it in an information storage device, and means for learning appearance, voice, and personality traits from the preprocessed data using a generated machine learning model, thereby enabling the creation and multipurpose use of original characters desired by users.

[1003] "Visual data" refers to information that can be perceived visually, such as images and videos.

[1004] "Auditory data" refers to information that can be perceived auditorily, such as voice or music.

[1005] "Character data" refers to information expressed in text format.

[1006] An "information storage device" is a device for storing and managing data.

[1007] A "generated machine learning model" is a model that learns features from data and runs an algorithm to generate new data.

[1008] "Operation interface" refers to the screen and input devices that allow the user to interact with the system and perform operations.

[1009] A "central processing unit" is a computer that controls the entire system and processes data.

[1010] "3D virtual character" means a digitally generated character in three-dimensional form.

[1011] "Media sharing options" refers to functions and options for publishing the generated character and related information on social networks and video sharing sites.

[1012] "Promotional Activities" refers to promotional and marketing activities aimed at increasing awareness and sales of a particular product or service.

[1013] The present invention is a system that allows users to create their ideal original character and use it in a variety of ways. Specific embodiments of this system are described below.

[1014] System Configuration

[1015] server

[1016] The server plays a central role in the entire system and performs the following processes:

[1017] Data collection and preprocessing: The server collects visual, auditory, and text data from the internet, public databases, and uploaded by users. The collected data is resized and denoised using an image processing library (e.g., OpenCV), and denoised and feature extracted using an audio processing library (e.g., Librosa). Text data is tokenised and stopwords are removed using a natural language processing library (e.g., NLTK, spaCy).

[1018] Model training: The preprocessed data is used to train a generative AI model (e.g., GAN, speech synthesis model, text generation model) using a deep learning framework (e.g., TensorFlow, PyTorch) running on high-performance hardware (e.g., NVIDIA GPU).

[1019] Avatar generation: A trained generative AI model is used to generate a 3D virtual character based on user-submitted data. Visual elements are integrated using 3D modeling software like Blender.

[1020] Terminal

[1021] The terminal provides a user interface and editing functions. The specific process is as follows:

[1022] User Interface: Provides a web browser-based interface implemented using front-end frameworks such as React or Vue.js, where users can select their desired character or persona and upload custom visual and auditory data.

[1023] Avatar display and editing: The generated 3D virtual character is displayed using libraries such as Three.js. Users can edit details in real time, and the edits are sent to the server and saved.

[1024] Media Sharing and Export: Provides the option to share the completed avatar directly to social media and video sharing sites. Sharing is done using social media APIs (e.g. Twitter API, YouTube API). Export functionality is also provided, allowing you to save in standard 3D file formats (e.g. FBX, OBJ).

[1025] User

[1026] The user does the following:

[1027] Data Upload: Upload visual, auditory and textual data about the desired character or person through the interface.

[1028] Character Selection and Customization: Select your desired character or persona from the provided list and customize their detailed parameters.

[1029] Edit the generated avatar: Review the generated avatar and make any necessary adjustments, including adding facial expressions or accessories.

[1030] Media sharing: Share the completed avatar on social media and video sharing sites to promote it.

[1031] Specific examples

[1032] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses a trained generative AI model to generate a 3D virtual character that combines the appearance of Character A, the voice of Person B, and personality C obtained from the trained model. The generated character is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and for promotional activities.

[1033] Prompt Sentence Examples

[1034] For example, you might enter the following prompt for a generative AI model:

[1035] "Generate a 3D virtual character with the appearance of anime character A, the voice of celebrity B, and the traits of personality C."

[1036] This allows the user's ideal virtual character to be generated efficiently and with high quality.

[1037] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1038] Step 1: Data collection and preprocessing

[1039] The server receives requests from users and collects visual, auditory and textual data from the Internet, public databases and user uploaded data.

[1040] Input: Data collection request from user

[1041] What it does: The server uses API requests to retrieve the required data from the data source. For example, image data is collected by web scraping, and audio data is downloaded from a public audio database.

[1042] Data processing: The acquired visual data (images) are resized and denoised using OpenCV. The auditory data (audio) is denoised and features extracted using Librosa, and the text data is tokenised and stopwords removed using NLTK or spaCy.

[1043] Output: Preprocessed data (visual data, auditory data, text data)

[1044] Step 2: Model training

[1045] The server trains a generative AI model based on the preprocessed data.

[1046] Input: Preprocessed data (visual, auditory, textual)

[1047] Specific operation: The server uses TensorFlow or PyTorch to train generative AI models (e.g., GANs, speech synthesis models, text generation models). High-performance NVIDIA GPUs (e.g., Tesla V100) are used for hardware. Batch processing is used for learning, and the model is trained for the specified number of epochs.

[1048] Data calculation: Split the data into training and validation sets, and tune the hyperparameters to improve the model accuracy.

[1049] Output: Trained generative AI model

[1050] Step 3: Providing a User Interface

[1051] The terminal provides an operation interface for the user to select the desired character or person and upload custom data.

[1052] Input: User interaction and selection data (character / persona information, custom visual data, auditory data)

[1053] Specific operation: Display a web browser-based interface and build an operation screen using React and Vue.js. The user can upload data through the interface and send the data to the server using an Ajax request.

[1054] Output: User data sent to the server

[1055] Step 4: Avatar generation

[1056] The server analyzes the data sent by the user and selects an appropriate generative AI model to generate a 3D virtual character.

[1057] Input: User data (character / persona information, custom visual data, audio data)

[1058] How it works: The server analyzes the received data and inputs visual, auditory, and text data into each generative AI model. Each generative AI model generates its own elements and integrates them using 3D modeling software such as Blender.

[1059] Data calculation: The elements (appearance, voice, personality) generated by each generative AI model are combined to construct a 3D virtual character.

[1060] Output: Finished 3D virtual character

[1061] Step 5: Review and edit your avatar

[1062] The terminal provides the generated 3D virtual character to the user and provides an interface for editing.

[1063] Input: Finished 3D virtual character

[1064] How it works: It uses Three.js to display a 3D virtual character in the browser and allows users to edit it. The edits made by the user are sent to the server in real time and saved.

[1065] Output: The final edited 3D virtual character

[1066] Step 6: Media sharing and promotional activities

[1067] The terminal and server support media sharing and promotional activities.

[1068] Input: Edited 3D virtual character

[1069] Specific operation: The device uses social media APIs to provide sharing options to social media and video sharing sites. The server supports promotional activities using the generated virtual characters and manages events in the metaverse and virtual platforms.

[1070] Output: Analysis data on the effectiveness of virtual characters posted on social media and video sharing sites, and promotional activities

[1071] (Application example 1)

[1072] 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."

[1073] In today's virtual stores, it is difficult for users to obtain a shopping experience that reflects their personal preferences. In particular, there is a lack of a realistic sensory experience when trying on and purchasing products. Furthermore, non-personalized suggestions and product explanations hinder efficient shopping. There is a need to solve these problems and provide users with a high-quality shopping experience.

[1074] 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.

[1075] In this invention, the server includes means for collecting and classifying multiple image, audio, and text data, means for preprocessing the collected data and storing it in a database, means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data, means for a user to select a desired character or person through a user interface and send the data to the server, means for generating a 3D avatar using the generative AI model based on the selected data, means for providing the generated 3D avatar to the user and allowing the user to edit it, means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites, means for supporting the user's shopping experience in a virtual store using the generated avatar, means for providing a virtual try-on system that uses an avatar to try on and recommend products, and means for explaining products using an avatar's voice guide function. This provides a personalized shopping experience for the user, enabling a realistic try-on experience and efficient product recommendations.

[1076] "Image data" means a digital image containing visual information of a person or character designated by the user.

[1077] "Audio Data" means an audio file containing the voice characteristics of a person or character designated by the user.

[1078] "Text data" is written information about the personality and other attributes of a person or character designated by the user.

[1079] A "generative AI model" is an artificial intelligence algorithm that learns appearance, voice, and personality from preprocessed image, audio, and text data to generate an avatar.

[1080] A "user interface" is software that provides an operating environment for a user to interact with the system, select a desired character or person, and transmit that data to a server.

[1081] A "server" is a computer system that collects, preprocesses, and stores data, runs generative AI models, and manages generated avatars.

[1082] A "3D avatar" is a three-dimensional virtual character generated based on a generative AI model that expresses the user's desired appearance, voice, and personality.

[1083] The "Virtual Try-On System" is a system that allows users to try on and receive product recommendations in a virtual space using a generated 3D avatar.

[1084] The "audio guide function" is a feature in which a generated 3D avatar explains products and assists users with their shopping by voice.

[1085] "SNS" is a social networking service that allows users to share their generated 3D avatars and their activities.

[1086] A "video sharing site" is a web platform that allows users to upload content using generated avatars and share it with other users.

[1087] The system for implementing this invention is realized by the following procedure: The purpose of this system is to enable users to create their ideal avatar and use it to provide a personalized shopping experience.

[1088] First, the server collects multiple images, audio, and text data from the Internet, public databases, and data uploaded by users. The collected data is resized, denoised, and normalised for images, and denoised, normalised, and key features extracted for audio data. The text data is tokenised, stop words are removed, and stems are extracted. The preprocessed data is stored in a database. The hardware used includes a high-performance server, and the software uses data preprocessing libraries such as OpenCV, Librosa, and NLTK.

[1089] The server then uses generative AI models to learn appearance, voice, and personality from the preprocessed data. For example, these models use Generative Adversarial Networks (GANs) to generate images, voices, and text. These models are trained and stored on the server.

[1090] Users can operate a graphical user interface through their smartphone, tablet, or PC device to select the desired character or persona and upload custom images and voices. The selected and uploaded data is then sent to a server.

[1091] The server analyzes the received user data and generates a 3D avatar using a trained generative AI model. The generated 3D avatar is sent to the device, where the user can view and edit it. The editing interface allows the user to adjust details and save the completed avatar.

[1092] The completed avatar provides a media sharing option for sharing on social media and video sharing sites. Furthermore, the system also includes a function to support the user's shopping experience in a virtual store using the generated avatar. Specifically, the virtual try-on system allows the user to try on clothes and accessories using the avatar, and the avatar can suggest products and provide product explanations using an audio guide function.

[1093] For example, if a user wants to create an avatar with the characteristics of a favorite celebrity, they might enter the following prompt:

[1094] "Use the face and voice of your favorite celebrity to suggest outfits that would look good on me, just like a stylist. Then try them on on your avatar."

[1095] In this way, users can create avatars that reflect their preferences and use them to enjoy shopping in virtual stores.

[1096] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1097] Step 1:

[1098] The server collects multiple images, audio, and text data from the Internet, public databases, and data uploaded by users. This provides basic data about the characters and people desired by the user. The inputs are image files, audio files, and text data, which are stored in a database for centralized management.

[1099] Step 2:

[1100] The server preprocesses the collected data and stores it in a database. Image data is resized, denoised, and normalised, while audio data is denoised, normalised, and key features are extracted. Text data is tokenised, stop words are removed, and stems are extracted. This improves data accuracy and enables efficient training for the generative AI model.

[1101] Step 3:

[1102] The server trains a generative AI model based on the preprocessed data. Examples include image generation models, speech generation models, and text generation models using GANs (Generative Adversarial Networks). This builds a basic model that reflects the appearance, voice, and personality selected by the user. The preprocessed data is used as input, and a trained model is obtained as output.

[1103] Step 4:

[1104] The user uses a device to operate the user interface. The user can select a desired character or persona and upload custom images and voices. This data is sent to a server, which collects and stores the user's input. The input is the selected character information and additional images and voices, and the output is the user data sent to the server.

[1105] Step 5:

[1106] The server analyzes the received user data and generates a 3D avatar using a trained generative AI model. The input is the user data and the trained model, and the output is the generated 3D avatar. This avatar is stored on the server and provided to the user's device.

[1107] Step 6:

[1108] Users can view and edit the generated 3D avatar through their devices. They can adjust and modify details through the user interface. The input is the generated 3D avatar, and the output is the final avatar that reflects the user's edits.

[1109] Step 7:

[1110] The completed avatar provides a media sharing option for sharing to social networking sites and video sharing sites, allowing users to utilize their avatar across multiple platforms. The input is the final edited avatar, and the output is the avatar deployment on social networking sites and video sharing sites.

[1111] Step 8:

[1112] The generated avatar is used to support the user's shopping experience in a virtual store. For example, a virtual try-on system provides a function where the avatar tries on products, and an audio guide function provides product explanations. This allows the user to enjoy a realistic shopping experience. The input is the generated avatar and product data in the store, and the output is an avatar with try-on and guide functions.

[1113] As a specific example, a user can create an avatar with the features of their favorite celebrity and use the prompt, "Please suggest clothes that would suit me, like a stylist, using the face and voice of my favorite celebrity. Also, please let me try on the clothes on my avatar." to create a shopping experience that suits their tastes.

[1114] 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.

[1115] The present invention combines an emotion engine with a system that allows users to create their ideal avatar and use it for various purposes. By using the emotion engine, the user's emotions can be analyzed and the results can be reflected in the creation of the avatar and promotional activities. A specific embodiment of this system is described below.

[1116] 1. Data Collection and Preprocessing

[1117] server

[1118] The server first collects image, audio, and text data about the characters or people desired by the user. This data is collected from a variety of sources, including the Internet, public databases, and user-uploaded data.

[1119] The collected data is resized, noise-removed, and normalized in the case of image data, and noise-removal, normalization, and extraction of important features in the case of audio data.Text data undergoes preprocessing such as tokenization, stop word removal, and stem extraction.The preprocessed data is stored in a database.

[1120] 2. Model training

[1121] server

[1122] The server trains a generative AI model based on the preprocessed data. For example, it uses an image generation model (e.g., GAN), a voice generation model, and a text generation model to learn the features of each. These models are stored on the server and used later in the generation process.

[1123] 3. Providing a user interface

[1124] Terminal

[1125] The user interface provides a graphical operating environment for users to select desired characters or people and upload custom images and voices. Users select the desired character or person items and transmit the data from their terminal to the server.

[1126] 4. Use of Emotion Engine

[1127] server

[1128] The server is equipped with an emotion engine that analyzes the user's emotions based on the user's operations and input data. This emotion data is used as feedback for each element of the avatar (appearance, voice, personality).

[1129] 5. Avatar Generation

[1130] server

[1131] The server selects the appropriate generative AI model (image generation, voice generation, text generation) based on the data submitted by the user and the results of emotion analysis. Based on this, a 3D avatar is generated. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[1132] 6. View and edit your avatar

[1133] Terminal

[1134] The device presents the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[1135] 7. Media Sharing and Promotional Activities

[1136] Terminal

[1137] The device provides media sharing options for sharing the generated avatar to social media icons, video sharing sites, etc. It also includes an export function, allowing users to use the avatar on different platforms.

[1138] server

[1139] The server will support promotional activities using the generated avatars, including event management and campaign planning and execution in the metaverse and other virtual platforms.

[1140] Specific examples

[1141] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model and emotion engine to generate a 3D avatar that combines the appearance of Character A, the voice of Person B, and personality C based on the user's emotions. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[1142] The above is a specific embodiment for carrying out the present invention.

[1143] The processing flow will be explained below.

[1144] Step 1:

[1145] User:

[1146] Through the device's user interface, users select a character or person to base their ideal avatar on, and optionally upload custom images and audio files.

[1147] Step 2:

[1148] Device:

[1149] The device analyzes the user's selections and uploaded data, which includes images, audio, and text data, and transmits it to the server.

[1150] Step 3:

[1151] server:

[1152] The server preprocesses the received data: image data is resized and denoised, audio data is denoised and features are extracted, and text data is tokenised and stop words are removed.

[1153] Step 4:

[1154] server:

[1155] Based on the preprocessed data, a generative AI model is trained. Models for image generation (e.g., GAN), speech generation, and text generation are used to learn the characteristics of each.

[1156] Step 5:

[1157] server:

[1158] Save the trained generative AI model and prepare it for use based on user requests.

[1159] Step 6:

[1160] server:

[1161] The server uses the emotion engine to analyze the user's emotions based on the user's operations and input data. The analyzed emotion data is used in subsequent processing.

[1162] Step 7:

[1163] server:

[1164] The selection data and emotion data sent by the user are analyzed, and appropriate image generation, speech generation, and text generation models are selected.

[1165] Step 8:

[1166] server:

[1167] The selected generative AI model is used to generate each element of the 3D avatar: for example, appearance is generated by an image generation model, voice by a voice generation model, and personality by a text generation model.

[1168] Step 9:

[1169] server:

[1170] Based on the analysis results of the emotion engine, necessary feedback is applied to each generated element to optimize the 3D avatar, allowing the avatar's appearance, voice, and personality to adapt to the user's emotional state.

[1171] Step 10:

[1172] server:

[1173] The completed 3D avatar is sent to the device and provided to the user.

[1174] Step 11:

[1175] Device:

[1176] The user uses an interface to view the 3D avatar received on the device and edit it if necessary.

[1177] Step 12:

[1178] Device:

[1179] The edited avatar will provide a media sharing option to share to social media icons and video sharing sites according to the user's request.

[1180] Step 13:

[1181] server:

[1182] The server will support promotional activities using the generated avatars, including event management and planning and execution of promotional campaigns in the metaverse and other virtual platforms.

[1183] As a specific example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model and emotion engine to generate a 3D avatar that combines Character A's appearance with Person B's voice and an optimal personality based on emotion analysis. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[1184] The above processing steps realize a system that allows users to easily create their ideal avatar and use it in a variety of media.

[1185] Example 2

[1186] 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."

[1187] Conventional avatar generation systems have had difficulty generating avatars that reflect the user's emotions. Furthermore, it is complicated to integrate different media formats (images, audio, text) to generate diverse avatars. This makes it difficult for users to easily create their ideal avatar and use it for multiple purposes.

[1188] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: [means for collecting and classifying multiple visual data, audio data, and natural language data]; [means for preprocessing the collected data and storing it in a database]; [means for using a generative artificial intelligence model to learn appearance, voice, and personality from the preprocessed data]; [means for an end user to select a desired character or person through a user interface and transmit the data to a host system]; [means for generating a three-dimensional avatar using a generative artificial intelligence model based on the selected data]; [means for analyzing the user's emotions using an emotion engine and reflecting the results in avatar generation]; [means for providing the generated three-dimensional avatar to the end user and allowing editing]; [means for providing a media sharing option for sharing the edited avatar on social networking services and video sharing platforms]; and [means for supporting marketing activities using the generated avatar]. This enables users to easily generate their ideal avatar and use it on various platforms.

[1189] "Visual data" is data expressed as images, and includes still images such as photographs, illustrations, and videos, as well as moving images.

[1190] "Audio data" refers to data expressed as sound, including music, speech, sound effects, and the like.

[1191] "Natural language data" refers to data in a language that is naturally spoken or written by humans, and includes text documents and records of conversations.

[1192] "Preprocessing" refers to a processing step for preparing data for use after collection, and includes processes such as data noise removal, normalization, and feature extraction.

[1193] "Database" means a system for efficiently and securely storing and managing collected and pre-processed data.

[1194] "Generative AI models" refers to algorithms or neural network models that learn specific tasks based on preprocessed data and generate new data or results.

[1195] "User Interface" means a graphical or text-based interface through which an end user interacts with and operates a system.

[1196] "Host System" refers to a central server or cloud computing environment that receives, analyzes, and processes user input data.

[1197] The "emotion engine" is a system that analyzes emotions from user operations and input data, and provides feedback to avatar generation based on that emotional data.

[1198] A "3D avatar" refers to a user-customizable 3D character or person model.

[1199] A "social networking service" is an online platform that allows users to exchange information with each other via the Internet.

[1200] A "video sharing platform" is an online platform for users to upload video content and share it with other users.

[1201] "Media sharing options" refers to a function for sharing the generated avatar and its related content with other users.

[1202] "Marketing activities" refers to the use of the generated avatar in commercial activities such as promotions and advertising campaigns.

[1203] The present invention provides a system that allows end users to create their ideal three-dimensional avatar and use it for a variety of purposes. This system also incorporates an emotion engine that can analyze the user's emotions and reflect the results in the avatar generation. The specific system configuration and operating procedures for implementing the present invention are described in detail below.

[1204] System Configuration

[1205] 1. Server

[1206] The server provides the following functions:

[1207] It has the ability to collect, classify, and preprocess multiple visual, audio, and natural language data.

[1208] It has the ability to train generative artificial intelligence models (e.g., generative adversarial networks (GANs), speech generation models, and text generation models) to generate the appearance, voice, and personality of avatars.

[1209] An emotion engine is used to analyze the user's emotions and reflect the results in avatar generation.

[1210] The database stores collected and preprocessed data, as well as trained generative AI models.

[1211] 2. Terminal

[1212] The device offers the user the following features:

[1213] Through a user interface, the end user can select the desired character or persona and upload custom visual and audio data.

[1214] The generated three-dimensional avatar is provided to the user, and an interface is displayed that allows the user to preview and edit the avatar.

[1215] It provides media sharing options to share your avatar to social networking services and video sharing platforms.

[1216] Specific examples

[1217] For example, if a user wants to create a virtual YouTuber with the characteristics of their favorite manga character "Character A" and a specific celebrity "Person B," they first select those characters and people using their device and send the data to the server. The server then uses the preprocessed data to generate a three-dimensional avatar using a trained generative AI model (e.g., GAN, voice generation model) and an emotion engine to combine the appearance of "Character A," the voice of "Person B," and "Personality C" based on the user's emotions.

[1218] The device provides the generated 3D avatar to the user, who can preview it and edit it as needed. The completed avatar can be shared via the device to social networking sites and video sharing sites. The server also supports marketing activities using the generated avatar, allowing users to run virtual events and campaigns.

[1219] Prompt Sentence Examples

[1220] "Generate a virtual YouTuber with the appearance of anime character 'Character A', the voice of celebrity 'Person B', and the personality 'Personality C' analyzed by the emotion engine."

[1221] The above is a specific embodiment for carrying out the present invention. This invention allows users to easily create their ideal three-dimensional avatar and use it on a wide range of platforms.

[1222] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1223] Step 1:

[1224] Data collection and classification:

[1225] Subject: Server

[1226] The server collects multiple visual, audio and natural language data from sources such as the Internet, public databases and user uploads.

[1227] Input: Image, audio, and text data related to characters and people.

[1228] Specific operations: Uses a web crawler to collect image data from the Internet, and stores audio files and text data uploaded by users in cloud storage.

[1229] Output: The collected dataset.

[1230] Step 2:

[1231] Data preprocessing:

[1232] Subject: Server

[1233] The server resizes, denoises, and normalizes the collected data for images, denoises, normalizes, and extracts features for audio data, and tokenizes, removes stop words, and extracts stems for text data.

[1234] Input: The collected dataset.

[1235] Specific operation: Resize to 128x128 pixels using an image processing library, remove noise using a speech processing library, and tokenize the text data using a natural language processing library.

[1236] Output: A preprocessed dataset.

[1237] Step 3:

[1238] Train the model:

[1239] Subject: Server

[1240] The server trains a generative artificial intelligence model (e.g., GAN, speech generation model, text generation model) based on the preprocessed data.

[1241] Input: Preprocessed image data, audio data, and natural language data.

[1242] How it works: We train GANs on a GPU cluster to generate trained models. Each generative AI model is fed with collected data and undergoes an optimization process over multiple epochs.

[1243] Output: A trained generative AI model.

[1244] Step 4:

[1245] Providing a user interface:

[1246] Subject: Terminal

[1247] Through a user interface, the device allows the end user to select the desired character or persona and upload custom visual and audio data.

[1248] Input: User selections and uploaded image and audio data.

[1249] Specific behavior: Build a UI using a web application framework and handle user interactions.

[1250] Output: User input data.

[1251] Step 5:

[1252] Sentiment analysis with emotion engine:

[1253] Subject: Server

[1254] The server uses an emotion engine to analyze emotions based on user operations and input data.

[1255] Input: The text the user types and the options selected.

[1256] Specific operation: Uses a sentiment analysis algorithm to extract sentiment from user input data. Calculates sentiment scores for each text using a sentiment dictionary.

[1257] Output: User emotion data.

[1258] Step 6:

[1259] Avatar Creation:

[1260] Subject: Server

[1261] The server selects an appropriate generative AI model based on the data sent by the user and the results of emotion analysis, and generates a three-dimensional avatar.

[1262] Input: A trained generative AI model and user emotion data.

[1263] How it works: A visual model is generated using GAN, and a voice model is used to generate a person's voice. These are then integrated to generate a 3D avatar.

[1264] Output: The generated 3D avatar.

[1265] Step 7:

[1266] Provide and edit your avatar:

[1267] Subject: Terminal

[1268] The terminal provides the generated three-dimensional avatar to the user and displays an interface for editing.

[1269] Input: A generated 3D avatar.

[1270] What it does: Allows users to preview their avatar and make any necessary changes. Reflects user editing requests in real time.

[1271] Output: An edited 3D avatar.

[1272] Step 8:

[1273] Media sharing options available:

[1274] Subject: Terminal

[1275] The device provides a media sharing option for sharing the edited avatar to social networking services and video sharing platforms.

[1276] Input: An edited 3D avatar.

[1277] What it does: It generates a share link and embed code so that users can easily share their edited avatar on social media or video sites. Simply click the share button and the data will be transferred automatically.

[1278] Output: Share link and embed code.

[1279] Step 9:

[1280] Supporting your marketing efforts:

[1281] Subject: Server

[1282] The server supports marketing activities using the generated avatars.

[1283] Input: A generated 3D avatar.

[1284] What it does: Provides data needed to design and execute marketing campaigns and virtual events. Customizes promotional avatars and distributes them to target audiences.

[1285] Output: Campaign data and virtual event configuration information.

[1286] (Application example 2)

[1287] 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."

[1288] Conventional avatar generation systems have difficulty adjusting avatars in real time to reflect user emotions, making it difficult to provide a personalized customer service experience, especially in virtual stores. Furthermore, they lack the functionality to generate and adjust avatars based on user emotions, making it impossible to improve the user experience. To solve these issues, a more advanced avatar generation system incorporating user emotion analysis is needed.

[1289] 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.

[1290] In this invention, the server includes: [means for collecting and classifying multiple image, audio, and text data;] [means for preprocessing the collected data and storing it in a database;] [means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data;] [means for the user to select a desired character or person through a user interface and send the data to the server;] [means for generating a 3D avatar using the generative AI model based on the selected data;] [means for providing the generated 3D avatar to the user and allowing the user to edit it;] [means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites;] [means for supporting promotional activities using the generated avatar;] [means for analyzing the user's emotions and adjusting the avatar based on the data;] [means for analyzing the emotion data on the server and reflecting it in each element of the avatar; and [means for the user to use the avatar in a virtual store and receive personalized guidance.] This allows the avatar to be adjusted in real time based on an analysis of the user's emotions, enabling a personalized customer service experience in the virtual store.

[1291] "Image, audio and text data" refers to visual, audio and textual information about a character or person desired by the user.

[1292] "Preprocessing" refers to the process of converting collected data into a format suitable for analysis and learning. Specifically, it includes resizing and noise removal for image data, noise removal and feature extraction for audio data, tokenization for text data, and stop word removal.

[1293] "Generative AI models" refer to machine learning models for generating and learning appearance, voice, and personality from collected and pre-processed data, including models for image generation, speech generation, and text generation.

[1294] "User interface" refers to the operating environment that allows a user to select a desired character or person and input and manage data.

[1295] A "3D avatar" refers to a three-dimensional character with the user's desired appearance, voice, and personality.

[1296] "Emotion analysis" refers to the process of analyzing a user's facial expressions and voice to identify their emotional state.

[1297] "Virtual store" refers to a shopping environment created in a virtual space via the Internet, where users can access the store through a virtual reality device and browse, select, and purchase products.

[1298] "Personalized guidance" refers to the provision of information and services that are individually optimized based on the user's emotions and past behavioral history.

[1299] "SNS" is an abbreviation for social networking service, and refers to an online service that allows users to interact with each other.

[1300] "Media sharing options" refers to the functionality that allows users to post and share their generated avatars on various online platforms.

[1301] "Promotional Activities" refers to marketing and advertising activities using the generated Avatars, including, specifically, events and campaigns in the Metaverse.

[1302] MODE FOR CARRYING OUT THE INVENTION

[1303] The system for implementing the present invention operates through the interaction of a server, a terminal, and a user.

[1304] 1. Data Collection and Preprocessing

[1305] First, the server collects multiple image, audio, and text data from the Internet, public databases, and users. Image data is resized and noise-removed, while audio data is denoised, key features are extracted, and normalisation is performed. Text data is tokenised, stop words are removed, and stemming is extracted. These preprocessed data are then stored in a database.

[1306] 2. Model training

[1307] The server trains a generative AI model based on the preprocessed data. Specifically, it uses an image generation model (e.g., GAN), a voice generation model, and a text generation model to learn the features of each. These models are stored on the server and used later in the generation process.

[1308] 3. Providing a user interface

[1309] A graphical operating environment is provided on the device to allow users to select the desired character or person and upload custom images and voices, through which the user selects the desired character or person data and transmits the data from the device to a server.

[1310] 4. Use of Emotion Engine

[1311] The server is equipped with an emotion engine that analyzes the user's emotions based on the user's operations and input data. This emotion data is used as feedback for each element of the avatar (appearance, voice, personality).

[1312] 5. Avatar Generation

[1313] The server selects an appropriate generative AI model based on the data submitted by the user and the results of emotion analysis, and generates a 3D avatar. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[1314] 6. View and edit your avatar

[1315] The device provides the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust the details of the avatar, and save the completed avatar.

[1316] 7. Media Sharing and Promotional Activities

[1317] Users can use the media sharing option to share the generated avatar on social media, video sharing sites, etc. The avatar can also be used to support promotional activities in the metaverse and virtual platforms provided by the server.

[1318] 8. Virtual store applications

[1319] The server adjusts the avatar in real time based on the results of the user's emotion analysis and provides personalized guidance in the virtual store. When a user wears a head-mounted display and visits a virtual store, emotion analysis data is sent to the server, which then generates an optimal avatar and displays it in the user's field of view, providing personalized guidance.

[1320] Specific examples

[1321] For example, if the device detects a user smiling while walking through a virtual store, the server receives emotional data indicating "happiness." Based on this, a lively and energetic avatar is generated and displayed on the smart glasses. The avatar then introduces the items in a cheerful voice, saying things like, "I'll show you our special sale items!"

[1322] Prompt Sentence Examples

[1323] For example, the following prompts can be sent to the generative AI model to generate each element of the avatar:

[1324] "Anime-style appearance"

[1325] "A bright tone of voice"

[1326] "Cheerful response phrases"

[1327] This creates a personalized avatar that matches the user's emotions and needs.

[1328] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1329] Step 1:

[1330] Data collection and preprocessing

[1331] The server collects multiple image, audio, and text data from the Internet, public databases, and users. The collected data undergoes resizing, noise removal, and normalization for image data, noise removal, normalization, and key feature extraction for audio data, and tokenization, stop word removal, and stem extraction for text data. These preprocessed data are then stored in a database.

[1332] Input: image, audio, and text data

[1333] Output: Preprocessed data (images, audio, text)

[1334] Step 2:

[1335] Model learning

[1336] The server trains a generative AI model based on the preprocessed data. This involves using a generative adversarial network (GAN) for image generation, a speech synthesis model for voice generation, and a natural language processing model for text generation. Each feature of the data is learned through these models.

[1337] Input: Preprocessed image, audio, and text data

[1338] Output: Trained generative AI model (image generation model, speech generation model, text generation model)

[1339] Step 3:

[1340] User Selection and Data Submission

[1341] The device provides the user with a graphical operating environment, allowing the user to select the desired character or persona and upload custom images and sounds. The user's selections are transmitted from the device to a server.

[1342] Input: User-selected characters, people, and uploaded custom data

[1343] Output: Data sent to the server

[1344] Step 4:

[1345] Emotion analysis

[1346] The server analyzes the user's emotions using an emotion engine based on the data received through the user interface and the user's operations. The analysis results are used as feedback for each element of the avatar (appearance, voice, personality).

[1347] Input: User input data and operation logs

[1348] Output: Emotion analysis results

[1349] Step 5:

[1350] Avatar generation

[1351] The server selects the appropriate generative AI model (image generation, voice generation, text generation) based on the data sent by the user and the results of emotion analysis, and generates a 3D avatar. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates them using the corresponding models for each and integrates them.

[1352] Input: User selection data, emotion analysis results, trained generative AI model

[1353] Output: 3D avatar

[1354] Step 6:

[1355] View and edit your avatar

[1356] The device provides the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[1357] Input: Generated 3D avatar

[1358] Output: Avatar adjusted and saved by the user

[1359] Step 7:

[1360] Media sharing and promotional activities

[1361] Users can use the media sharing option to share the generated avatars on social media, video sharing sites, etc. The server also uses the generated avatars to support promotional activities in the metaverse and other virtual platforms.

[1362] Input: User's sharing instructions

[1363] Output: Avatars shared on social media and video sharing sites

[1364] Step 8:

[1365] Personalized guidance in virtual stores

[1366] When a user wears a head-mounted display and visits a virtual store, emotion analysis data is sent to the server. The server generates an optimal avatar based on this data and displays it in the user's field of view. This avatar provides personalized guidance within the virtual store.

[1367] Input: User emotion data, trained generative AI model

[1368] Output: An avatar that guides you through a virtual store

[1369] 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.

[1370] 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.

[1371] 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.

[1372] [Fourth embodiment]

[1373] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1374] 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.

[1375] 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).

[1376] 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.

[1377] 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.

[1378] 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).

[1379] 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.

[1380] 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.

[1381] 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.

[1382] 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.

[1383] 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.

[1384] 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.

[1385] 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."

[1386] The present invention is a system that allows users to create their ideal avatar and use it for various purposes. Specific embodiments of this system are described below.

[1387] 1. Data Collection and Preprocessing

[1388] server

[1389] The server first collects image, audio, and text data about the characters or people desired by the user. This data is collected from a variety of sources, including the Internet, public databases, and user-uploaded data.

[1390] The collected data is resized, noise-removed, and normalized in the case of image data, and noise-removal, normalization, and extraction of important features in the case of audio data.Text data undergoes preprocessing such as tokenization, stop word removal, and stem extraction.The preprocessed data is stored in a database.

[1391] 2. Model training

[1392] server

[1393] The server trains a generative AI model based on the preprocessed data. For example, an image generation model (e.g., GAN) learns a person's appearance characteristics, a voice generation model learns voice characteristics, and a text generation model learns personality traits. These models are stored on the server and used later in the generation process.

[1394] 3. Providing a user interface

[1395] Terminal

[1396] The user interface provides a graphical operating environment for users to select desired characters or people and upload custom images and voices. Users select the desired character or person items and transmit the data from their terminal to the server.

[1397] 4. Avatar Generation

[1398] server

[1399] The server analyzes the data sent by the user and selects the appropriate generative AI model (image generation, voice generation, personality generation). Based on this, a 3D avatar is generated. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[1400] 5. Check and edit your avatar

[1401] Terminal

[1402] The device presents the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[1403] 6. Media Sharing and Promotional Activities

[1404] Terminal

[1405] The device provides media sharing options for sharing the generated avatar to social media icons, video sharing sites, etc. It also includes an export function, allowing users to use the avatar on different platforms.

[1406] server

[1407] The server will support promotional activities using the generated avatars, including event management and campaign planning and execution in the metaverse and other virtual platforms.

[1408] Specific examples

[1409] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model to generate a 3D avatar that combines Character A's appearance, Person B's voice, and personality C obtained from the trained model. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[1410] The above is a specific embodiment for carrying out the present invention.

[1411] The processing flow will be explained below.

[1412] Step 1:

[1413] User:

[1414] Through the device's user interface, users select a character or person to base their ideal avatar on, and optionally upload custom images and audio files.

[1415] Step 2:

[1416] Device:

[1417] The device analyzes the user's selections and uploaded data, which includes images, audio, and text data, and transmits it to the server.

[1418] Step 3:

[1419] server:

[1420] The server preprocesses the received data: image data is resized and denoised, audio data is denoised and features are extracted, and text data is tokenised and stop words are removed.

[1421] Step 4:

[1422] server:

[1423] Based on the preprocessed data, a generative AI model is trained. Models for image generation (e.g., GAN), speech generation, and text generation are used to learn the characteristics of each.

[1424] Step 5:

[1425] server:

[1426] Save the trained generative AI model and prepare it for use based on user requests.

[1427] Step 6:

[1428] server:

[1429] The selection data sent by the user is analyzed and appropriate image generation, speech generation, and text generation models are selected.

[1430] Step 7:

[1431] server:

[1432] The selected generative AI model is used to generate each element of the 3D avatar: for example, an image generation model generates appearance, a speech generation model generates voice, and a text generation model generates personality.

[1433] Step 8:

[1434] server:

[1435] The generated avatar elements are integrated to create the final 3D avatar.

[1436] Step 9:

[1437] server:

[1438] The completed 3D avatar is sent to the device and provided to the user.

[1439] Step 10:

[1440] Device:

[1441] The user uses an interface to view the 3D avatar received on the device and edit it if necessary.

[1442] Step 11:

[1443] Device:

[1444] The edited avatar will provide a media sharing option to share to social media icons and video sharing sites according to the user's request.

[1445] Step 12:

[1446] server:

[1447] The server will support promotional activities using the generated avatars, including event management and planning and execution of promotional campaigns in the metaverse and other virtual platforms.

[1448] The above processing steps realize a system that allows users to easily create their ideal avatar and use it in a variety of media.

[1449] Example 1

[1450] 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."

[1451] In recent years, there has been a growing demand for systems that allow users to easily create their own original characters and use them for multiple purposes. In particular, creating anime-style characters or characters with the characteristics of celebrities and using them on social media and video sharing sites is extremely popular. However, existing technologies have difficulty efficiently collecting and classifying multiple data, and smoothly editing and sharing the generated characters.

[1452] 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.

[1453] In this invention, the server includes means for collecting and classifying a plurality of visual data, audio data, and text data, means for preprocessing the collected data and storing it in an information storage device, and means for learning appearance, voice, and personality traits from the preprocessed data using a generated machine learning model, thereby enabling the creation and multipurpose use of original characters desired by users.

[1454] "Visual data" refers to information that can be perceived visually, such as images and videos.

[1455] "Auditory data" refers to information that can be perceived auditorily, such as voice or music.

[1456] "Character data" refers to information expressed in text format.

[1457] An "information storage device" is a device for storing and managing data.

[1458] A "generated machine learning model" is a model that learns features from data and runs an algorithm to generate new data.

[1459] "Operation interface" refers to the screen and input devices that allow the user to interact with the system and perform operations.

[1460] A "central processing unit" is a computer that controls the entire system and processes data.

[1461] "3D virtual character" means a digitally generated character in three-dimensional form.

[1462] "Media sharing options" refers to functions and options for publishing the generated character and related information on social networks and video sharing sites.

[1463] "Promotional Activities" refers to promotional and marketing activities aimed at increasing awareness and sales of a particular product or service.

[1464] The present invention is a system that allows users to create their ideal original character and use it in a variety of ways. Specific embodiments of this system are described below.

[1465] System Configuration

[1466] server

[1467] The server plays a central role in the entire system and performs the following processes:

[1468] Data collection and preprocessing: The server collects visual, auditory, and text data from the internet, public databases, and uploaded by users. The collected data is resized and denoised using an image processing library (e.g., OpenCV), and denoised and feature extracted using an audio processing library (e.g., Librosa). Text data is tokenised and stopwords are removed using a natural language processing library (e.g., NLTK, spaCy).

[1469] Model training: The preprocessed data is used to train a generative AI model (e.g., GAN, speech synthesis model, text generation model) using a deep learning framework (e.g., TensorFlow, PyTorch) running on high-performance hardware (e.g., NVIDIA GPU).

[1470] Avatar generation: A trained generative AI model is used to generate a 3D virtual character based on user-submitted data. Visual elements are integrated using 3D modeling software like Blender.

[1471] Terminal

[1472] The terminal provides a user interface and editing functions. The specific process is as follows:

[1473] User Interface: Provides a web browser-based interface implemented using front-end frameworks such as React or Vue.js, where users can select their desired character or persona and upload custom visual and auditory data.

[1474] Avatar display and editing: The generated 3D virtual character is displayed using libraries such as Three.js. Users can edit details in real time, and the edits are sent to the server and saved.

[1475] Media Sharing and Export: Provides the option to share the completed avatar directly to social media and video sharing sites. Sharing is done using social media APIs (e.g. Twitter API, YouTube API). Export functionality is also provided, allowing you to save in standard 3D file formats (e.g. FBX, OBJ).

[1476] User

[1477] The user does the following:

[1478] Data Upload: Upload visual, auditory and textual data about the desired character or person through the interface.

[1479] Character Selection and Customization: Select your desired character or persona from the provided list and customize their detailed parameters.

[1480] Edit the generated avatar: Review the generated avatar and make any necessary adjustments, including adding facial expressions or accessories.

[1481] Media sharing: Share the completed avatar on social media and video sharing sites to promote it.

[1482] Specific examples

[1483] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses a trained generative AI model to generate a 3D virtual character that combines the appearance of Character A, the voice of Person B, and personality C obtained from the trained model. The generated character is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and for promotional activities.

[1484] Prompt Sentence Examples

[1485] For example, you might enter the following prompt for a generative AI model:

[1486] "Generate a 3D virtual character with the appearance of anime character A, the voice of celebrity B, and the traits of personality C."

[1487] This allows the user's ideal virtual character to be generated efficiently and with high quality.

[1488] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1489] Step 1: Data collection and preprocessing

[1490] The server receives requests from users and collects visual, auditory and textual data from the Internet, public databases and user uploaded data.

[1491] Input: Data collection request from user

[1492] What it does: The server uses API requests to retrieve the required data from the data source. For example, image data is collected by web scraping, and audio data is downloaded from a public audio database.

[1493] Data processing: The acquired visual data (images) are resized and denoised using OpenCV. The auditory data (audio) is denoised and features extracted using Librosa, and the text data is tokenised and stopwords removed using NLTK or spaCy.

[1494] Output: Preprocessed data (visual data, auditory data, text data)

[1495] Step 2: Model training

[1496] The server trains a generative AI model based on the preprocessed data.

[1497] Input: Preprocessed data (visual, auditory, textual)

[1498] Specific operation: The server uses TensorFlow or PyTorch to train generative AI models (e.g., GANs, speech synthesis models, text generation models). High-performance NVIDIA GPUs (e.g., Tesla V100) are used for hardware. Batch processing is used for learning, and the model is trained for the specified number of epochs.

[1499] Data calculation: Split the data into training and validation sets, and tune the hyperparameters to improve the model accuracy.

[1500] Output: Trained generative AI model

[1501] Step 3: Providing a User Interface

[1502] The terminal provides an operation interface for the user to select the desired character or person and upload custom data.

[1503] Input: User interaction and selection data (character / persona information, custom visual data, auditory data)

[1504] Specific operation: Display a web browser-based interface and build an operation screen using React and Vue.js. The user can upload data through the interface and send the data to the server using an Ajax request.

[1505] Output: User data sent to the server

[1506] Step 4: Avatar generation

[1507] The server analyzes the data sent by the user and selects an appropriate generative AI model to generate a 3D virtual character.

[1508] Input: User data (character / persona information, custom visual data, audio data)

[1509] How it works: The server analyzes the received data and inputs visual, auditory, and text data into each generative AI model. Each generative AI model generates its own elements and integrates them using 3D modeling software such as Blender.

[1510] Data calculation: The elements (appearance, voice, personality) generated by each generative AI model are combined to construct a 3D virtual character.

[1511] Output: Finished 3D virtual character

[1512] Step 5: Review and edit your avatar

[1513] The terminal provides the generated 3D virtual character to the user and provides an interface for editing.

[1514] Input: Finished 3D virtual character

[1515] How it works: It uses Three.js to display a 3D virtual character in the browser and allows users to edit it. The edits made by the user are sent to the server in real time and saved.

[1516] Output: The final edited 3D virtual character

[1517] Step 6: Media sharing and promotional activities

[1518] The terminal and server support media sharing and promotional activities.

[1519] Input: Edited 3D virtual character

[1520] Specific operation: The device uses social media APIs to provide sharing options to social media and video sharing sites. The server supports promotional activities using the generated virtual characters and manages events in the metaverse and virtual platforms.

[1521] Output: Analysis data on the effectiveness of virtual characters posted on social media and video sharing sites, and promotional activities

[1522] (Application example 1)

[1523] 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."

[1524] In today's virtual stores, it is difficult for users to obtain a shopping experience that reflects their personal preferences. In particular, there is a lack of a realistic sensory experience when trying on and purchasing products. Furthermore, non-personalized suggestions and product explanations hinder efficient shopping. There is a need to solve these problems and provide users with a high-quality shopping experience.

[1525] 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.

[1526] In this invention, the server includes means for collecting and classifying multiple image, audio, and text data, means for preprocessing the collected data and storing it in a database, means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data, means for a user to select a desired character or person through a user interface and send the data to the server, means for generating a 3D avatar using the generative AI model based on the selected data, means for providing the generated 3D avatar to the user and allowing the user to edit it, means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites, means for supporting the user's shopping experience in a virtual store using the generated avatar, means for providing a virtual try-on system that uses an avatar to try on and recommend products, and means for explaining products using an avatar's voice guide function. This provides a personalized shopping experience for the user, enabling a realistic try-on experience and efficient product recommendations.

[1527] "Image data" means a digital image containing visual information of a person or character designated by the user.

[1528] "Audio Data" means an audio file containing the voice characteristics of a person or character designated by the user.

[1529] "Text data" is written information about the personality and other attributes of a person or character designated by the user.

[1530] A "generative AI model" is an artificial intelligence algorithm that learns appearance, voice, and personality from preprocessed image, audio, and text data to generate an avatar.

[1531] A "user interface" is software that provides an operating environment for a user to interact with the system, select a desired character or person, and transmit that data to a server.

[1532] A "server" is a computer system that collects, preprocesses, and stores data, runs generative AI models, and manages generated avatars.

[1533] A "3D avatar" is a three-dimensional virtual character generated based on a generative AI model that expresses the user's desired appearance, voice, and personality.

[1534] The "Virtual Try-On System" is a system that allows users to try on and receive product recommendations in a virtual space using a generated 3D avatar.

[1535] The "audio guide function" is a feature in which a generated 3D avatar explains products and assists users with their shopping by voice.

[1536] "SNS" is a social networking service that allows users to share their generated 3D avatars and their activities.

[1537] A "video sharing site" is a web platform that allows users to upload content using generated avatars and share it with other users.

[1538] The system for implementing this invention is realized by the following procedure: The purpose of this system is to enable users to create their ideal avatar and use it to provide a personalized shopping experience.

[1539] First, the server collects multiple images, audio, and text data from the Internet, public databases, and data uploaded by users. The collected data is resized, denoised, and normalised for images, and denoised, normalised, and key features extracted for audio data. The text data is tokenised, stop words are removed, and stems are extracted. The preprocessed data is stored in a database. The hardware used includes a high-performance server, and the software uses data preprocessing libraries such as OpenCV, Librosa, and NLTK.

[1540] The server then uses generative AI models to learn appearance, voice, and personality from the preprocessed data. For example, these models use Generative Adversarial Networks (GANs) to generate images, voices, and text. These models are trained and stored on the server.

[1541] Users can operate a graphical user interface through their smartphone, tablet, or PC device to select the desired character or persona and upload custom images and voices. The selected and uploaded data is then sent to a server.

[1542] The server analyzes the received user data and generates a 3D avatar using a trained generative AI model. The generated 3D avatar is sent to the device, where the user can view and edit it. The editing interface allows the user to adjust details and save the completed avatar.

[1543] The completed avatar provides a media sharing option for sharing on social media and video sharing sites. Furthermore, the system also includes a function to support the user's shopping experience in a virtual store using the generated avatar. Specifically, the virtual try-on system allows the user to try on clothes and accessories using the avatar, and the avatar can suggest products and provide product explanations using an audio guide function.

[1544] For example, if a user wants to create an avatar with the characteristics of a favorite celebrity, they might enter the following prompt:

[1545] "Use the face and voice of your favorite celebrity to suggest outfits that would look good on me, just like a stylist. Then try them on on your avatar."

[1546] In this way, users can create avatars that reflect their preferences and use them to enjoy shopping in virtual stores.

[1547] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1548] Step 1:

[1549] The server collects multiple images, audio, and text data from the Internet, public databases, and data uploaded by users. This provides basic data about the characters and people desired by the user. The inputs are image files, audio files, and text data, which are stored in a database for centralized management.

[1550] Step 2:

[1551] The server preprocesses the collected data and stores it in a database. Image data is resized, denoised, and normalised, while audio data is denoised, normalised, and key features are extracted. Text data is tokenised, stop words are removed, and stems are extracted. This improves data accuracy and enables efficient training for the generative AI model.

[1552] Step 3:

[1553] The server trains a generative AI model based on the preprocessed data. Examples include image generation models, speech generation models, and text generation models using GANs (Generative Adversarial Networks). This builds a basic model that reflects the appearance, voice, and personality selected by the user. The preprocessed data is used as input, and a trained model is obtained as output.

[1554] Step 4:

[1555] The user uses a device to operate the user interface. The user can select a desired character or persona and upload custom images and voices. This data is sent to a server, which collects and stores the user's input. The input is the selected character information and additional images and voices, and the output is the user data sent to the server.

[1556] Step 5:

[1557] The server analyzes the received user data and generates a 3D avatar using a trained generative AI model. The input is the user data and the trained model, and the output is the generated 3D avatar. This avatar is stored on the server and provided to the user's device.

[1558] Step 6:

[1559] Users can view and edit the generated 3D avatar through their devices. They can adjust and modify details through the user interface. The input is the generated 3D avatar, and the output is the final avatar that reflects the user's edits.

[1560] Step 7:

[1561] The completed avatar provides a media sharing option for sharing to social networking sites and video sharing sites, allowing users to utilize their avatar across multiple platforms. The input is the final edited avatar, and the output is the avatar deployment on social networking sites and video sharing sites.

[1562] Step 8:

[1563] The generated avatar is used to support the user's shopping experience in a virtual store. For example, a virtual try-on system provides a function where the avatar tries on products, and an audio guide function provides product explanations. This allows the user to enjoy a realistic shopping experience. The input is the generated avatar and product data in the store, and the output is an avatar with try-on and guide functions.

[1564] As a specific example, a user can create an avatar with the features of their favorite celebrity and use the prompt, "Please suggest clothes that would suit me, like a stylist, using the face and voice of my favorite celebrity. Also, please let me try on the clothes on my avatar." to create a shopping experience that suits their tastes.

[1565] 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.

[1566] The present invention combines an emotion engine with a system that allows users to create their ideal avatar and use it for various purposes. By using the emotion engine, the user's emotions can be analyzed and the results can be reflected in the creation of the avatar and promotional activities. A specific embodiment of this system is described below.

[1567] 1. Data Collection and Preprocessing

[1568] server

[1569] The server first collects image, audio, and text data about the characters or people desired by the user. This data is collected from a variety of sources, including the Internet, public databases, and user-uploaded data.

[1570] The collected data is resized, noise-removed, and normalized in the case of image data, and noise-removal, normalization, and extraction of important features in the case of audio data.Text data undergoes preprocessing such as tokenization, stop word removal, and stem extraction.The preprocessed data is stored in a database.

[1571] 2. Model training

[1572] server

[1573] The server trains a generative AI model based on the preprocessed data. For example, it uses an image generation model (e.g., GAN), a voice generation model, and a text generation model to learn the features of each. These models are stored on the server and used later in the generation process.

[1574] 3. Providing a user interface

[1575] Terminal

[1576] The user interface provides a graphical operating environment for users to select desired characters or people and upload custom images and voices. Users select the desired character or person items and transmit the data from their terminal to the server.

[1577] 4. Use of Emotion Engine

[1578] server

[1579] The server is equipped with an emotion engine that analyzes the user's emotions based on the user's operations and input data. This emotion data is used as feedback for each element of the avatar (appearance, voice, personality).

[1580] 5. Avatar Generation

[1581] server

[1582] The server selects the appropriate generative AI model (image generation, voice generation, text generation) based on the data submitted by the user and the results of emotion analysis. Based on this, a 3D avatar is generated. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[1583] 6. View and edit your avatar

[1584] Terminal

[1585] The device presents the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[1586] 7. Media Sharing and Promotional Activities

[1587] Terminal

[1588] The device provides media sharing options for sharing the generated avatar to social media icons, video sharing sites, etc. It also includes an export function, allowing users to use the avatar on different platforms.

[1589] server

[1590] The server will support promotional activities using the generated avatars, including event management and campaign planning and execution in the metaverse and other virtual platforms.

[1591] Specific examples

[1592] For example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model and emotion engine to generate a 3D avatar that combines the appearance of Character A, the voice of Person B, and personality C based on the user's emotions. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[1593] The above is a specific embodiment for carrying out the present invention.

[1594] The processing flow will be explained below.

[1595] Step 1:

[1596] User:

[1597] Through the device's user interface, users select a character or person to base their ideal avatar on, and optionally upload custom images and audio files.

[1598] Step 2:

[1599] Device:

[1600] The device analyzes the user's selections and uploaded data, which includes images, audio, and text data, and transmits it to the server.

[1601] Step 3:

[1602] server:

[1603] The server preprocesses the received data: image data is resized and denoised, audio data is denoised and features are extracted, and text data is tokenised and stop words are removed.

[1604] Step 4:

[1605] server:

[1606] Based on the preprocessed data, a generative AI model is trained. Models for image generation (e.g., GAN), speech generation, and text generation are used to learn the characteristics of each.

[1607] Step 5:

[1608] server:

[1609] Save the trained generative AI model and prepare it for use based on user requests.

[1610] Step 6:

[1611] server:

[1612] The server uses the emotion engine to analyze the user's emotions based on the user's operations and input data. The analyzed emotion data is used in subsequent processing.

[1613] Step 7:

[1614] server:

[1615] The selection data and emotion data sent by the user are analyzed, and appropriate image generation, speech generation, and text generation models are selected.

[1616] Step 8:

[1617] server:

[1618] The selected generative AI model is used to generate each element of the 3D avatar: for example, appearance is generated by an image generation model, voice by a voice generation model, and personality by a text generation model.

[1619] Step 9:

[1620] server:

[1621] Based on the analysis results of the emotion engine, necessary feedback is applied to each generated element to optimize the 3D avatar, allowing the avatar's appearance, voice, and personality to adapt to the user's emotional state.

[1622] Step 10:

[1623] server:

[1624] The completed 3D avatar is sent to the device and provided to the user.

[1625] Step 11:

[1626] Device:

[1627] The user uses an interface to view the 3D avatar received on the device and edit it if necessary.

[1628] Step 12:

[1629] Device:

[1630] The edited avatar will provide a media sharing option to share to social media icons and video sharing sites according to the user's request.

[1631] Step 13:

[1632] server:

[1633] The server will support promotional activities using the generated avatars, including event management and planning and execution of promotional campaigns in the metaverse and other virtual platforms.

[1634] As a specific example, if a user wants to create a VTuber with the characteristics of their favorite anime character "Character A" and a specific celebrity "Person B," they first select them on their device and send the data to the server. The server then uses the trained model and emotion engine to generate a 3D avatar that combines Character A's appearance with Person B's voice and an optimal personality based on emotion analysis. The generated avatar is then sent to the device, where the user can view and edit it. Finally, the completed avatar can be used on social media and video sharing sites, and can also be used for promotional activities.

[1635] The above processing steps realize a system that allows users to easily create their ideal avatar and use it in a variety of media.

[1636] Example 2

[1637] 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."

[1638] Conventional avatar generation systems have had difficulty generating avatars that reflect the user's emotions. Furthermore, it is complicated to integrate different media formats (images, audio, text) to generate diverse avatars. This makes it difficult for users to easily create their ideal avatar and use it for multiple purposes.

[1639] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: [means for collecting and classifying multiple visual data, audio data, and natural language data]; [means for preprocessing the collected data and storing it in a database]; [means for using a generative artificial intelligence model to learn appearance, voice, and personality from the preprocessed data]; [means for an end user to select a desired character or person through a user interface and transmit the data to a host system]; [means for generating a three-dimensional avatar using a generative artificial intelligence model based on the selected data]; [means for analyzing the user's emotions using an emotion engine and reflecting the results in avatar generation]; [means for providing the generated three-dimensional avatar to the end user and allowing editing]; [means for providing a media sharing option for sharing the edited avatar on social networking services and video sharing platforms]; and [means for supporting marketing activities using the generated avatar]. This enables users to easily generate their ideal avatar and use it on various platforms.

[1640] "Visual data" is data expressed as images, and includes still images such as photographs, illustrations, and videos, as well as moving images.

[1641] "Audio data" refers to data expressed as sound, including music, speech, sound effects, and the like.

[1642] "Natural language data" refers to data in a language that is naturally spoken or written by humans, and includes text documents and records of conversations.

[1643] "Preprocessing" refers to a processing step for preparing data for use after collection, and includes processes such as data noise removal, normalization, and feature extraction.

[1644] "Database" means a system for efficiently and securely storing and managing collected and pre-processed data.

[1645] "Generative AI models" refers to algorithms or neural network models that learn specific tasks based on preprocessed data and generate new data or results.

[1646] "User Interface" means a graphical or text-based interface through which an end user interacts with and operates a system.

[1647] "Host System" refers to a central server or cloud computing environment that receives, analyzes, and processes user input data.

[1648] The "emotion engine" is a system that analyzes emotions from user operations and input data, and provides feedback to avatar generation based on that emotional data.

[1649] A "3D avatar" refers to a user-customizable 3D character or person model.

[1650] A "social networking service" is an online platform that allows users to exchange information with each other via the Internet.

[1651] A "video sharing platform" is an online platform for users to upload video content and share it with other users.

[1652] "Media sharing options" refers to a function for sharing the generated avatar and its related content with other users.

[1653] "Marketing activities" refers to the use of the generated avatar in commercial activities such as promotions and advertising campaigns.

[1654] The present invention provides a system that allows end users to create their ideal three-dimensional avatar and use it for a variety of purposes. This system also incorporates an emotion engine that can analyze the user's emotions and reflect the results in the avatar generation. The specific system configuration and operating procedures for implementing the present invention are described in detail below.

[1655] System Configuration

[1656] 1. Server

[1657] The server provides the following functions:

[1658] It has the ability to collect, classify, and preprocess multiple visual, audio, and natural language data.

[1659] It has the ability to train generative artificial intelligence models (e.g., generative adversarial networks (GANs), speech generation models, and text generation models) to generate the appearance, voice, and personality of avatars.

[1660] An emotion engine is used to analyze the user's emotions and reflect the results in avatar generation.

[1661] The database stores collected and preprocessed data, as well as trained generative AI models.

[1662] 2. Terminal

[1663] The device offers the user the following features:

[1664] Through a user interface, the end user can select the desired character or persona and upload custom visual and audio data.

[1665] The generated three-dimensional avatar is provided to the user, and an interface is displayed that allows the user to preview and edit the avatar.

[1666] It provides media sharing options to share your avatar to social networking services and video sharing platforms.

[1667] Specific examples

[1668] For example, if a user wants to create a virtual YouTuber with the characteristics of their favorite manga character "Character A" and a specific celebrity "Person B," they first select those characters and people using their device and send the data to the server. The server then uses the preprocessed data to generate a three-dimensional avatar using a trained generative AI model (e.g., GAN, voice generation model) and an emotion engine to combine the appearance of "Character A," the voice of "Person B," and "Personality C" based on the user's emotions.

[1669] The device provides the generated 3D avatar to the user, who can preview it and edit it as needed. The completed avatar can be shared via the device to social networking sites and video sharing sites. The server also supports marketing activities using the generated avatar, allowing users to run virtual events and campaigns.

[1670] Prompt Sentence Examples

[1671] "Generate a virtual YouTuber with the appearance of anime character 'Character A', the voice of celebrity 'Person B', and the personality 'Personality C' analyzed by the emotion engine."

[1672] The above is a specific embodiment for carrying out the present invention. This invention allows users to easily create their ideal three-dimensional avatar and use it on a wide range of platforms.

[1673] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1674] Step 1:

[1675] Data collection and classification:

[1676] Subject: Server

[1677] The server collects multiple visual, audio and natural language data from sources such as the Internet, public databases and user uploads.

[1678] Input: Image, audio, and text data related to characters and people.

[1679] Specific operations: Uses a web crawler to collect image data from the Internet, and stores audio files and text data uploaded by users in cloud storage.

[1680] Output: The collected dataset.

[1681] Step 2:

[1682] Data preprocessing:

[1683] Subject: Server

[1684] The server resizes, denoises, and normalizes the collected data for images, denoises, normalizes, and extracts features for audio data, and tokenizes, removes stop words, and extracts stems for text data.

[1685] Input: The collected dataset.

[1686] Specific operation: Resize to 128x128 pixels using an image processing library, remove noise using a speech processing library, and tokenize the text data using a natural language processing library.

[1687] Output: A preprocessed dataset.

[1688] Step 3:

[1689] Train the model:

[1690] Subject: Server

[1691] The server trains a generative artificial intelligence model (e.g., GAN, speech generation model, text generation model) based on the preprocessed data.

[1692] Input: Preprocessed image data, audio data, and natural language data.

[1693] How it works: We train GANs on a GPU cluster to generate trained models. Each generative AI model is fed with collected data and undergoes an optimization process over multiple epochs.

[1694] Output: A trained generative AI model.

[1695] Step 4:

[1696] Providing a user interface:

[1697] Subject: Terminal

[1698] Through a user interface, the device allows the end user to select the desired character or persona and upload custom visual and audio data.

[1699] Input: User selections and uploaded image and audio data.

[1700] Specific behavior: Build a UI using a web application framework and handle user interactions.

[1701] Output: User input data.

[1702] Step 5:

[1703] Sentiment analysis with emotion engine:

[1704] Subject: Server

[1705] The server uses an emotion engine to analyze emotions based on user operations and input data.

[1706] Input: The text the user types and the options selected.

[1707] Specific operation: Uses a sentiment analysis algorithm to extract sentiment from user input data. Calculates sentiment scores for each text using a sentiment dictionary.

[1708] Output: User emotion data.

[1709] Step 6:

[1710] Avatar Creation:

[1711] Subject: Server

[1712] The server selects an appropriate generative AI model based on the data sent by the user and the results of emotion analysis, and generates a three-dimensional avatar.

[1713] Input: A trained generative AI model and user emotion data.

[1714] How it works: A visual model is generated using GAN, and a voice model is used to generate a person's voice. These are then integrated to generate a 3D avatar.

[1715] Output: The generated 3D avatar.

[1716] Step 7:

[1717] Provide and edit your avatar:

[1718] Subject: Terminal

[1719] The terminal provides the generated three-dimensional avatar to the user and displays an interface for editing.

[1720] Input: A generated 3D avatar.

[1721] What it does: Allows users to preview their avatar and make any necessary changes. Reflects user editing requests in real time.

[1722] Output: An edited 3D avatar.

[1723] Step 8:

[1724] Media sharing options available:

[1725] Subject: Terminal

[1726] The device provides a media sharing option for sharing the edited avatar to social networking services and video sharing platforms.

[1727] Input: An edited 3D avatar.

[1728] What it does: It generates a share link and embed code so that users can easily share their edited avatar on social media or video sites. Simply click the share button and the data will be transferred automatically.

[1729] Output: Share link and embed code.

[1730] Step 9:

[1731] Supporting your marketing efforts:

[1732] Subject: Server

[1733] The server supports marketing activities using the generated avatars.

[1734] Input: A generated 3D avatar.

[1735] What it does: Provides data needed to design and execute marketing campaigns and virtual events. Customizes promotional avatars and distributes them to target audiences.

[1736] Output: Campaign data and virtual event configuration information.

[1737] (Application example 2)

[1738] 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."

[1739] Conventional avatar generation systems have difficulty adjusting avatars in real time to reflect user emotions, making it difficult to provide a personalized customer service experience, especially in virtual stores. Furthermore, they lack the functionality to generate and adjust avatars based on user emotions, making it impossible to improve the user experience. To solve these issues, a more advanced avatar generation system incorporating user emotion analysis is needed.

[1740] 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.

[1741] In this invention, the server includes: [means for collecting and classifying multiple image, audio, and text data;] [means for preprocessing the collected data and storing it in a database;] [means for using a generative AI model to learn appearance, voice, and personality from the preprocessed data;] [means for the user to select a desired character or person through a user interface and send the data to the server;] [means for generating a 3D avatar using the generative AI model based on the selected data;] [means for providing the generated 3D avatar to the user and allowing the user to edit it;] [means for providing a media sharing option for sharing the edited avatar on social networking sites and video sharing sites;] [means for supporting promotional activities using the generated avatar;] [means for analyzing the user's emotions and adjusting the avatar based on the data;] [means for analyzing the emotion data on the server and reflecting it in each element of the avatar; and [means for the user to use the avatar in a virtual store and receive personalized guidance.] This allows the avatar to be adjusted in real time based on an analysis of the user's emotions, enabling a personalized customer service experience in the virtual store.

[1742] "Image, audio and text data" refers to visual, audio and textual information about a character or person desired by the user.

[1743] "Preprocessing" refers to the process of converting collected data into a format suitable for analysis and learning. Specifically, it includes resizing and noise removal for image data, noise removal and feature extraction for audio data, tokenization for text data, and stop word removal.

[1744] "Generative AI models" refer to machine learning models for generating and learning appearance, voice, and personality from collected and pre-processed data, including models for image generation, speech generation, and text generation.

[1745] "User interface" refers to the operating environment that allows a user to select a desired character or person and input and manage data.

[1746] A "3D avatar" refers to a three-dimensional character with the user's desired appearance, voice, and personality.

[1747] "Emotion analysis" refers to the process of analyzing a user's facial expressions and voice to identify their emotional state.

[1748] "Virtual store" refers to a shopping environment created in a virtual space via the Internet, where users can access the store through a virtual reality device and browse, select, and purchase products.

[1749] "Personalized guidance" refers to the provision of information and services that are individually optimized based on the user's emotions and past behavioral history.

[1750] "SNS" is an abbreviation for social networking service, and refers to an online service that allows users to interact with each other.

[1751] "Media sharing options" refers to the functionality that allows users to post and share their generated avatars on various online platforms.

[1752] "Promotional Activities" refers to marketing and advertising activities using the generated Avatars, including, specifically, events and campaigns in the Metaverse.

[1753] MODE FOR CARRYING OUT THE INVENTION

[1754] The system for implementing the present invention operates through the interaction of a server, a terminal, and a user.

[1755] 1. Data Collection and Preprocessing

[1756] First, the server collects multiple image, audio, and text data from the Internet, public databases, and users. Image data is resized and noise-removed, while audio data is denoised, key features are extracted, and normalisation is performed. Text data is tokenised, stop words are removed, and stemming is extracted. These preprocessed data are then stored in a database.

[1757] 2. Model training

[1758] The server trains a generative AI model based on the preprocessed data. Specifically, it uses an image generation model (e.g., GAN), a voice generation model, and a text generation model to learn the features of each. These models are stored on the server and used later in the generation process.

[1759] 3. Providing a user interface

[1760] A graphical operating environment is provided on the device to allow users to select the desired character or person and upload custom images and voices, through which the user selects the desired character or person data and transmits the data from the device to a server.

[1761] 4. Use of Emotion Engine

[1762] The server is equipped with an emotion engine that analyzes the user's emotions based on the user's operations and input data. This emotion data is used as feedback for each element of the avatar (appearance, voice, personality).

[1763] 5. Avatar Generation

[1764] The server selects an appropriate generative AI model based on the data submitted by the user and the results of emotion analysis, and generates a 3D avatar. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates avatar elements using each corresponding model and integrates them to complete the 3D avatar.

[1765] 6. View and edit your avatar

[1766] The device provides the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust the details of the avatar, and save the completed avatar.

[1767] 7. Media Sharing and Promotional Activities

[1768] Users can use the media sharing option to share the generated avatar on social media, video sharing sites, etc. The avatar can also be used to support promotional activities in the metaverse and virtual platforms provided by the server.

[1769] 8. Virtual store applications

[1770] The server adjusts the avatar in real time based on the results of the user's emotion analysis and provides personalized guidance in the virtual store. When a user wears a head-mounted display and visits a virtual store, emotion analysis data is sent to the server, which then generates an optimal avatar and displays it in the user's field of view, providing personalized guidance.

[1771] Specific examples

[1772] For example, if the device detects a user smiling while walking through a virtual store, the server receives emotional data indicating "happiness." Based on this, a lively and energetic avatar is generated and displayed on the smart glasses. The avatar then introduces the items in a cheerful voice, saying things like, "I'll show you our special sale items!"

[1773] Prompt Sentence Examples

[1774] For example, the following prompts can be sent to the generative AI model to generate each element of the avatar:

[1775] "Anime-style appearance"

[1776] "A bright tone of voice"

[1777] "Cheerful response phrases"

[1778] This creates a personalized avatar that matches the user's emotions and needs.

[1779] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1780] Step 1:

[1781] Data collection and preprocessing

[1782] The server collects multiple image, audio, and text data from the Internet, public databases, and users. The collected data undergoes resizing, noise removal, and normalization for image data, noise removal, normalization, and key feature extraction for audio data, and tokenization, stop word removal, and stem extraction for text data. These preprocessed data are then stored in a database.

[1783] Input: image, audio, and text data

[1784] Output: Preprocessed data (images, audio, text)

[1785] Step 2:

[1786] Model learning

[1787] The server trains a generative AI model based on the preprocessed data. This involves using a generative adversarial network (GAN) for image generation, a speech synthesis model for voice generation, and a natural language processing model for text generation. Each feature of the data is learned through these models.

[1788] Input: Preprocessed image, audio, and text data

[1789] Output: Trained generative AI model (image generation model, speech generation model, text generation model)

[1790] Step 3:

[1791] User Selection and Data Submission

[1792] The device provides the user with a graphical operating environment, allowing the user to select the desired character or persona and upload custom images and sounds. The user's selections are transmitted from the device to a server.

[1793] Input: User-selected characters, people, and uploaded custom data

[1794] Output: Data sent to the server

[1795] Step 4:

[1796] Emotion analysis

[1797] The server analyzes the user's emotions using an emotion engine based on the data received through the user interface and the user's operations. The analysis results are used as feedback for each element of the avatar (appearance, voice, personality).

[1798] Input: User input data and operation logs

[1799] Output: Emotion analysis results

[1800] Step 5:

[1801] Avatar generation

[1802] The server selects the appropriate generative AI model (image generation, voice generation, text generation) based on the data sent by the user and the results of emotion analysis, and generates a 3D avatar. For example, if a user selects the appearance of "Character A," the voice of "Character B," and "Personality C," the server generates them using the corresponding models for each and integrates them.

[1803] Input: User selection data, emotion analysis results, trained generative AI model

[1804] Output: 3D avatar

[1805] Step 6:

[1806] View and edit your avatar

[1807] The device provides the generated 3D avatar to the user and provides an interface that allows the user to view and edit the avatar, adjust details, and save the completed avatar.

[1808] Input: Generated 3D avatar

[1809] Output: Avatar adjusted and saved by the user

[1810] Step 7:

[1811] Media sharing and promotional activities

[1812] Users can use the media sharing option to share the generated avatars on social media, video sharing sites, etc. The server also uses the generated avatars to support promotional activities in the metaverse and other virtual platforms.

[1813] Input: User's sharing instructions

[1814] Output: Avatars shared on social media and video sharing sites

[1815] Step 8:

[1816] Personalized guidance in virtual stores

[1817] When a user wears a head-mounted display and visits a virtual store, emotion analysis data is sent to the server. The server generates an optimal avatar based on this data and displays it in the user's field of view. This avatar provides personalized guidance within the virtual store.

[1818] Input: User emotion data, trained generative AI model

[1819] Output: An avatar that guides you through a virtual store

[1820] 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.

[1821] 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.

[1822] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1823] 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.

[1824] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1825] 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.

[1826] 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).

[1827] 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.

[1828] 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."

[1829] 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.

[1830] 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).

[1831] 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.

[1832] 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.

[1833] 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.

[1834] 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.

[1835] 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.

[1836] 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.

[1837] 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.

[1838] 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.

[1839] 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.

[1840] 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.

[1841] The following is further disclosed regarding the above embodiment.

[1842] (Claim 1)

[1843] [Means for collecting and classifying a plurality of image, audio and text data;

[1844] [Means for preprocessing the collected data and storing it in a database;

[1845] [Means of using generative AI models to learn appearance, voice, and personality from pre-processed data; and

[1846] [Means for the user to select the desired character or person through a user interface and transmit that data to the server;

[1847] [Means for generating a 3D avatar using a generative AI model based on the selected data;

[1848] [Means for providing the generated 3D avatar to the user and allowing them to edit it;

[1849] [Means to provide media sharing options for sharing edited avatars to social media and video sharing sites, and

[1850] [Means for supporting promotional activities using the generated avatar;

[1851] A system including:

[1852] (Claim 2)

[1853] [The system of claim 1, wherein the preprocessed data is used to train different generative AI models.

[1854] (Claim 3)

[1855] [The system of claim 1, wherein the user interface allows a user to upload custom images and sounds.

[1856] "Example 1"

[1857] (Claim 1)

[1858] [Means for collecting and classifying a plurality of visual data, auditory data, and text data;

[1859] [means for preprocessing the collected data and storing it in an information storage device;

[1860] [Means for using the generated machine learning model to learn appearance, voice, and personality traits from the preprocessed data; and

[1861] [Means for a user to select a desired character or person through an operation interface and transmit the data to a central processing unit;

[1862] [Means for generating a 3D virtual character using the generated machine learning model based on the selected data; and

[1863] [Means for providing the generated 3D virtual character to a user and allowing the user to edit it;

[1864] [Means for providing media sharing options for sharing edited virtual characters to social networking sites and video sharing sites; and

[1865] [Means for supporting promotional activities using the generated virtual character;

[1866] A system including:

[1867] (Claim 2)

[1868] The system of claim 1, wherein the preprocessed data is used to train different generated machine learning models.

[1869] (Claim 3)

[1870] [The system of claim 1, wherein the system allows a user to upload custom visual and / or auditory data through an operating interface.

[1871] "Application Example 1"

[1872] (Claim 1)

[1873] [Means for collecting and classifying a plurality of image, audio and text data;

[1874] [Means for preprocessing the collected data and storing it in a database;

[1875] [Means of using generative AI models to learn appearance, voice, and personality from pre-processed data; and

[1876] [Means for the user to select the desired character or person through a user interface and transmit that data to the server;

[1877] [Means for generating a 3D avatar using a generative AI model based on the selected data;

[1878] [Means for providing the generated 3D avatar to the user and allowing them to edit it;

[1879] [Means to provide media sharing options for sharing edited avatars to social media and video sharing sites, and

[1880] [Means for supporting a user's shopping experience in a virtual store using the generated avatar;

[1881] [Means for providing a virtual try-on system that uses an avatar to try on and recommend products;

[1882] [Means for explaining products using an avatar voice guide function;

[1883] A system including:

[1884] (Claim 2)

[1885] [The system of claim 1, wherein the preprocessed data is used to train different generative AI models.

[1886] (Claim 3)

[1887] [The system of claim 1, wherein the user interface allows a user to upload custom images and sounds.

[1888] "Example 2: Combining Emotion Engines"

[1889] (Claim 1)

[1890] [Means for collecting and classifying a plurality of visual data, audio data, and natural language data;

[1891] [Means for preprocessing the collected data and storing it in a database;

[1892] [Means for using generative artificial intelligence models to learn appearance, voice, and personality from preprocessed data; and

[1893] [Means for the end user to select a desired character or persona through a user interface and transmit that data to the host system;

[1894] [Means for generating a three-dimensional avatar using a generative artificial intelligence model based on the selected data;

[1895] [Means of analyzing user emotions using an emotion engine and reflecting the results in avatar generation;

[1896] [Means for providing the generated three-dimensional avatar to the end user and allowing them to edit it;

[1897] [Means for providing media sharing options for sharing the edited avatar to social networking services and video sharing platforms; and

[1898] [Means for supporting marketing activities using the generated avatars,

[1899] A system including:

[1900] (Claim 2)

[1901] [The system of claim 1, wherein the preprocessed data is used to train different generative artificial intelligence models.

[1902] (Claim 3)

[1903] [The system of claim 1, wherein the system allows an end user to upload custom visual and audio data through a user interface.

[1904] "Application example 2 when combining emotion engines"

[1905] (Claim 1)

[1906] [Means for collecting and classifying a plurality of image, audio and text data;

[1907] [Means for preprocessing the collected data and storing it in a database;

[1908] [Means of using generative AI models to learn appearance, voice, and personality from pre-processed data; and

[1909] [Means for the user to select the desired character or person through a user interface and transmit that data to the server;

[1910] [Means for generating a 3D avatar using a generative AI model based on the selected data;

[1911] [Means for providing the generated 3D avatar to the user and allowing them to edit it;

[1912] [Means to provide media sharing options for sharing edited avatars to social media and video sharing sites, and

[1913] [Means for supporting promotional activities using the generated avatar;

[1914] [Means for analyzing user emotions and adjusting the avatar based on that data; and

[1915] [Method of analyzing emotional data on the server and reflecting it in each element of the avatar,

[1916] [Means for users to use avatars in virtual stores to provide personalized guidance;

[1917] A system including:

[1918] (Claim 2)

[1919] [The system of claim 1, wherein the preprocessed data is used to train different generative AI models.

[1920] (Claim 3)

[1921] [The system of claim 1, wherein the user interface allows a user to upload custom images and sounds. [Explanation of symbols]

[1922] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for collecting and classifying a plurality of image, audio and text data; a means for preprocessing the collected data and storing it in a database; A means for using a generative AI model to learn appearance, voice, and personality from pre-processed data; and A means for a user to select a desired character or person through a user interface and transmit the data to a server; a means for generating a 3D avatar using a generative AI model based on the selected data; A means for providing the generated 3D avatar to a user and allowing the user to edit the avatar; A means to provide media sharing options for sharing the edited avatar to social media and video sharing sites; A means for supporting promotional activities using the generated avatar; A system including:

2. The system of claim 1 , wherein the preprocessed data is used to train different generative AI models.

3. 10. The system of claim 1, wherein the user interface allows a user to upload custom images and sounds.

Images