System

Abstract

A system is provided.SOLUTION: A system comprising: means for parsing a create request to identify a predefined task; means for performing a plurality of create operations; means for consolidating created components; means for transmitting the consolidated components to a user terminal; and means for analyzing user evaluation and providing feedback for refinement of the create operations.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] Conventional virtual spaces are primarily created by humans, and have limitations in their quantity, quality, and variety. Furthermore, they are difficult to adapt to the diverse needs and preferences of users, affecting satisfaction and engagement. Furthermore, for those seeking creative expression, the lack of freedom and speed poses a problem. The present invention aims to solve these issues and provide a virtual experience with greater freedom and creativity. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, and a means for analyzing user evaluations and providing feedback for improving the generation operations. This system efficiently and quickly generates virtual spaces based on user requests and consistently provides high-quality content. As a result, customization to meet diverse user needs is realized, improving the user experience.

[0006] A "generation request" refers to a request that includes the information and instructions necessary to generate the virtual space desired by the user.

[0007] "Analysis" refers to the process of deciphering input data or information and understanding its structure and meaning.

[0008] "Identify" refers to the act of distinguishing and identifying a particular element or piece of information from others.

[0009] A "means" refers to a method or device used to achieve a particular purpose.

[0010] "Generation operation" refers to the process of generating components of a virtual space, such as text, images, and audio, using generative AI.

[0011] "Components" refer to the individual elements such as scenario, visuals, and sound that are necessary to create a virtual space.

[0012] "Synthesis" refers to the process of bringing together multiple individual elements into a coherent whole.

[0013] "Transmitting" refers to the act of moving generated data or information from one place to another.

[0014] "User terminal" refers to a device that a user operates to input information or view displayed data.

[0015] "Evaluation" refers to the user's impressions and feedback on the virtual space and generated elements they experienced.

[0016] "Analysis" refers to the process of examining collected data to find specific trends and patterns.

[0017] "Feedback" refers to information used to improve and adapt a system based on user evaluations and opinions.

[0018] Now we have definitions for the important words included in the claims. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

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

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The system of the present invention includes a process for analyzing a generation request, performing multiple generation operations, integrating the generated components, and sending the components to a user terminal. The following is a description of a specific embodiment.

[0041] overview

[0042] In this invention, we have constructed a system that receives a user's request (generation request) for the generation of a virtual space, analyzes it, and then executes multiple generation operations to generate components (scenario, visuals, audio, etc.), integrating them and providing them to the user. In addition, we collect user ratings and feedback, analyze them, and feed them back to the generation AI to improve the accuracy and quality of future generation operations.

[0043] Detailed embodiment

[0044] 1. Receiving a User Request

[0045] User: The user requests the creation of a virtual space. For example, the user inputs a request such as "Please create a medieval fantasy town" into the device.

[0046] Terminal: Receives requests typed by the user and sends them to the server.

[0047] 2. Parsing the Request

[0048] Server: Analyzes the generation request received from the device and identifies the required generation operations. For example, from the request for a "medieval fantasy town," it determines that the town's scenario, visuals, and audio must be generated.

[0049] 3. Performing the Generate Operation

[0050] Server: Instructs the text generation AI, image generation AI, and voice generation AI to generate each element.

[0051] Text generation AI: Generates scenarios such as the city's history, backstories of main characters, and events that occur in the city.

[0052] Image generation AI: Generates visual elements such as city buildings, landscapes, and character designs.

[0053] Voice generation AI: Generates city environmental sounds and character dialogue.

[0054] 4. Integration of Components

[0055] Server: Integrates the generated scenarios, visuals, and audio to create consistent virtual space data.

[0056] 5. Transmission and Display of Aggregated Data

[0057] Server: Sends the integrated virtual space data to the device.

[0058] Device: Displays a virtual space to the user based on the data received from the server. For example, the device allows the user to explore a city through VR goggles.

[0059] 6. User Experience and Feedback

[0060] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[0061] User: Enters their experience rating and feedback into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[0062] Device: Sends user feedback to the server.

[0063] 7. Feedback processing and AI training

[0064] Server: Analyzes the feedback received from the device and provides it as feedback data to the generation AI.

[0065] Generative AI: Learns from the feedback it receives to improve its generative process and generate better results in the future.

[0066] Specific examples

[0067] For example, if a user requests, "Generate a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[0068] 1. The user enters a request.

[0069] 2. The device sends a request to the server.

[0070] 3. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[0071] 4. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[0072] 5. Each AI generates its own elements.

[0073] 6. The server integrates all components and creates virtual space data.

[0074] 7. The server sends the integrated data to the device.

[0075] 8. The device displays the data to the user, who then explores the pyramid city through VR goggles.

[0076] 9. The user enters feedback into the device, which then sends it to the server.

[0077] 10. The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[0078] In this way, this system can efficiently generate and provide highly customizable virtual spaces that meet the diverse needs of users.

[0079] The processing flow will be explained below.

[0080] Step 1:

[0081] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[0082] Terminal: Sends the request entered by the user to the server.

[0083] Step 2:

[0084] Server: Analyzes the generation request received from the device, performs text analysis on the request content, and identifies the required generation operation (e.g., scenario generation, visual generation, audio generation).

[0085] Step 3:

[0086] Server: Issues instructions to the text generation AI to generate a scenario, including the town's setting and history, background information for the main characters, and events that will occur.

[0087] Text generation AI: Generates text data based on a specified scenario and sends it back to the server.

[0088] Step 4:

[0089] Server: Based on the scenario data received from the text generation AI, the server issues instructions to the image generation AI to generate visuals. These instructions include the design of city buildings, scenery, characters, etc.

[0090] Image generation AI: Generates appropriate visual elements based on scenario data and sends them back to the server.

[0091] Step 5:

[0092] Server: Based on the visual data received from the image generation AI, it issues instructions to the audio generation AI to generate sounds, including the city's ambient sounds and character dialogue.

[0093] Voice generation AI: Generates the necessary acoustic data based on a specified scenario and sends it back to the server.

[0094] Step 6:

[0095] Server: Integrates the generated scenario, visual, and audio data to create a consistent virtual space.

[0096] Step 7:

[0097] Server: Sends the integrated virtual space data to the device.

[0098] Step 8:

[0099] Device: Provides users with visual and auditory experiences based on the virtual space data received from the server. For example, it allows users to explore a city through VR goggles.

[0100] Step 9:

[0101] User: Enters their evaluation and feedback about the virtual space they experienced into the device. For example, they may say, "The building design is great, but the background noise is a little too loud."

[0102] Device: Sends user feedback to the server.

[0103] Step 10:

[0104] Server: Analyzes the feedback received from the device and provides the generated AI with data on areas that need improvement.

[0105] Generative AI: Based on the feedback received, it learns and improves the quality of its next generation operation.

[0106] By using the above steps, the system of the present invention can efficiently generate and provide a high-quality virtual space that meets the user's requirements.

[0107] Example 1

[0108] 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."

[0109] Conventional virtual space generation systems have difficulty generating and integrating individual elements (scenario, visuals, audio) consistently, making it difficult to provide a high-quality virtual experience that meets user demands. Furthermore, they lacked mechanisms for effectively incorporating user feedback and continuously improving the generation process. This resulted in inconsistent quality in the generated virtual spaces, leading to problems with reduced user satisfaction.

[0110] 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.

[0111] In this invention, the server includes means for analyzing a generation request and identifying a predetermined generation operation, means for executing multiple generation operations using a text generation AI, an image generation AI, and a voice generation AI, means for integrating the generated scenario, visual, and voice components, means for transmitting the integrated components to a user terminal, and means for collecting user experience evaluations and feedback and feeding them back to improve the generation AI model. This enables the generation of high-quality virtual spaces according to user requests and realizes continuous quality improvement.

[0112] A "generation request" is a request entered by a user wishing to create a specific virtual space.

[0113] "Analysis" refers to the process of decomposing an input production request and identifying the required production operations.

[0114] "Generation operations" refer to the procedures and means for generating the individual elements that make up a virtual space, such as text, images, and sounds.

[0115] "Text generation AI" is an artificial intelligence technology that generates text data such as scenarios and backstories based on requests entered by users.

[0116] "Image generation AI" is an artificial intelligence technology that generates visual elements such as buildings, landscapes, and characters in a virtual space in response to user requests.

[0117] "Voice generation AI" refers to artificial intelligence technology for generating background sounds and character dialogue used in virtual spaces.

[0118] "Components" refer to the individual data elements such as scenarios, visuals, and sounds that make up a virtual space.

[0119] "Synthesis" refers to the process of combining the individual generated components into a coherent virtual space.

[0120] "User device" means the device a user uses to request and experience a virtual space, such as a PC, smartphone, or VR goggles.

[0121] "Feedback" refers to evaluations and suggestions for improvement provided by users based on their experience in a virtual space.

[0122] A "generative AI model" is an overall artificial intelligence framework or methodology for performing text, image, and audio generation operations.

[0123] This invention is a system that generates a virtual space based on a user's generation request and provides the virtual space to the user. This system includes processes that analyze the generation request, perform multiple generation operations, integrate the generated components, and send them to the user's terminal. It also has a function that collects user feedback and reflects it in the generative AI model to continuously improve the generation process.

[0124] The system is mainly composed of the interaction between the server, terminals, and users. Below, we will explain each component of the system and its role.

[0125] Components and Roles

[0126] server

[0127] The server is the central control unit of this system. The server has the following roles:

[0128] Analysis of the generation request: The server has a special software module that receives and analyzes the generation request from the user. For example, if a user requests "Please generate a medieval fantasy town," the server analyzes it and identifies the required generation operations (scenario, visuals, audio).

[0129] Execution of generation operations: The server executes the necessary generation operations using text generation AI, image generation AI, and voice generation AI. Each AI module is responsible for generating a specific generation element (text, image, voice).

[0130] Text Generation AI: Generates text data. This AI creates city scenarios, character backstories, event details, etc.

[0131] Image generation AI: Generates image data. This AI creates visual elements such as city buildings, landscapes, and character designs.

[0132] Voice generation AI: Generates voice data. This AI creates the city's environmental sounds, character dialogue, and more.

[0133] Integration of components: The server integrates the scenario, visual, and audio data generated by each AI module to create a consistent virtual space.

[0134] Data transmission: The integrated virtual space data is transmitted to the user's terminal using a high-speed data transfer protocol.

[0135] Feedback processing: The server collects user feedback and feeds it back into the generative AI model. This feedback is used as data to improve the generation process in the future.

[0136] Terminal

[0137] A terminal is a device through which a user interacts with the system. It has the following functions:

[0138] Sending a request: The creation request entered by the user is sent to the server. For example, the user enters a request such as "Create an ancient Egyptian city centered around a pyramid."

[0139] Data display: The virtual space data sent from the server is displayed to the user. The terminal displays the virtual space using a device such as a VR goggle, smartphone, or PC.

[0140] Feedback collection: Users input ratings and suggestions for improvement based on their experience in the virtual space and send them to the server.

[0141] user

[0142] Users use the system to explore and experience virtual spaces.

[0143] Inputting a request: The user inputs a request for the creation of the desired virtual space into the terminal.

[0144] Explore the virtual space: Explore the generated virtual space and enjoy the experience.

[0145] Providing feedback: Provide feedback on the virtual space you have experienced.

[0146] Specific examples

[0147] For example, if a user enters the prompt "Create a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[0148] The user enters a prompt.

[0149] The terminal sends a prompt to the server.

[0150] The server parses the prompt statement and determines the required generation operation.

[0151] The server instructs the text generation AI to generate the scenario, the image generation AI to generate the visuals, and the voice generation AI to generate the voice.

[0152] Each generation AI generates elements.

[0153] The server integrates the generated elements to create virtual space data.

[0154] The server sends the integrated data to the terminal.

[0155] The device displays the data, and users explore the pyramid city with VR goggles.

[0156] The user enters feedback into the device, which then sends it to the server.

[0157] The server then applies the feedback to the generated AI model.

[0158] In this way, the system can generate and provide high-quality virtual spaces that meet the diverse needs of users. Furthermore, by continuously incorporating user feedback, the quality of the generation process can be improved.

[0159] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0160] Step 1: Receiving a user request

[0161] The user inputs a request to generate a virtual space into the device. For example, the user inputs the prompt "Please generate a medieval fantasy town."

[0162] The terminal receives a generation request from the user, converts it into JSON format, and sends it to the server. At this time, the input is the user's prompt, and the output is the JSON format data sent to the server.

[0163] Step 2: Parsing the request

[0164] The server parses the JSON data of the generation request received from the device. The input is the JSON formatted generation request data, and the server parses it to identify the necessary generation elements (scenario, visual, audio).

[0165] As a result of the analysis, the server determines that, for example, a request for a "medieval fantasy town" requires the generation of a town's scenario, visuals, and audio. The output is a list of elements to be generated as a result of the analysis.

[0166] Step 3: Specify the generation operation

[0167] The server instructs the text generation AI, image generation AI, and speech generation AI to generate each element. The input is a list of generated elements as the analysis result, and the output is the generation instruction sent to each generation AI.

[0168] The server instructs the text generation AI to generate the city's scenario (history, character backstories, events, etc.).

[0169] The server instructs the image generation AI to generate visual elements such as city buildings, scenery, and characters.

[0170] The server instructs the voice generation AI to generate the city's environmental sounds and character dialogue.

[0171] Step 4: Run the generate operation

[0172] Each generation AI generates each element based on the generation instructions received from the server. The input is the generation instructions from the server, and the output is the generated data (scenario, visuals, audio).

[0173] Text generation AI generates and outputs scenarios.

[0174] Image generation AI generates and outputs visual elements.

[0175] The voice generation AI generates and outputs voice data.

[0176] Step 5: Putting the Components Together

[0177] The server integrates the scenario, visual, and audio data received from each generation AI. The input is the generated data from each generation AI, and the server integrates them into a single virtual space data.

[0178] The server creates consistent virtual space data, and the output is integrated virtual space data.

[0179] Step 6: Send and view the integrated data

[0180] The server sends the integrated virtual space data to the terminal. The input is the integrated virtual space data, and the output is the data sent to the terminal.

[0181] The device analyzes the virtual space data received from the server and displays it to the user. Specifically, the device displays the virtual space to the user in real time using VR goggles. The input is the virtual space data from the server, and the output is the virtual space displayed to the user.

[0182] Step 7: User experience and feedback

[0183] Users explore generated virtual spaces and enjoy experiences, such as walking around a medieval fantasy town and interacting with its inhabitants.

[0184] The user inputs their experience evaluation and feedback into the device. The input is the user's feedback content, and the output is the feedback data input into the device.

[0185] The terminal sends the user's feedback to the server. The input is the feedback data entered into the terminal, and the output is the feedback data sent to the server.

[0186] Step 8: Processing feedback and training the AI

[0187] The server analyzes the feedback received from the device and reflects it in the generative AI model. The input is the user's feedback data, which the server analyzes and uses to improve the generative AI model.

[0188] The generative AI model learns from the feedback data and improves the generation process in the future, resulting in a higher quality virtual space the next time it is generated.

[0189] (Application example 1)

[0190] 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."

[0191] In today's digital society, there is a demand for efficient generation of virtual spaces and improved user experiences. However, with conventional technologies, the virtual space generation process is complex and time-consuming, making it difficult to provide an integrated and consistent virtual experience. Furthermore, there was a lack of a mechanism for incorporating user feedback into the generation process, which hindered the improvement of the quality of the generation AI.

[0192] 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.

[0193] In this invention, the server includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for collecting feedback from the user and providing the feedback for improving the generation operations, and a means for generating and integrating visual, scenario, and audio elements to provide a virtual space. This enables the virtual space desired by the user to be generated quickly and consistently, improving the user experience. Furthermore, the collected feedback can be used to continuously improve the quality of the generation AI.

[0194] A "generation request" is a request in which the user specifies the details and elements of the virtual space they desire.

[0195] "Predetermined work" is a set of specific tasks that include the required creation operations, identified by analyzing the creation request.

[0196] "Generation operations" are processes for creating components of virtual space, such as text generation, image generation, and sound generation.

[0197] "Visuals" refers to visual elements in a virtual space, such as images and designs of buildings, characters, landscapes, etc.

[0198] "Scenario" refers to the content of the story or events that unfold within a virtual space, and includes text information and storylines to guide the user's experience.

[0199] "Audio" refers to auditory elements such as character dialogue, environmental sounds, and sound effects within the virtual space.

[0200] "User terminal" means a device used by a user to display and manipulate a virtual space, including a smartphone, smart glasses, or a head-mounted display.

[0201] "Feedback" refers to the evaluations and comments provided by users after experiencing a virtual space, and is information that is used to improve the quality of the generation operation.

[0202] An "integrated component" is a set of visuals, scenarios, and sounds created through generative operations that come together to form a coherent virtual space.

[0203] A "virtual space" is an imaginary space or world that users can experience interactively within a digital environment.

[0204] The present invention relates to a system for generating a virtual space based on a user request, which includes a means for analyzing the generation request and identifying a predetermined task, a means for performing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for collecting feedback from the user and providing the feedback for improving the generation operations, and a means for generating and integrating visual, scenario, and audio elements to provide the virtual space.

[0205] 1. Basic configuration

[0206] The system mainly consists of the following hardware and software:

[0207] Hardware: Smartphones, smart glasses, head-mounted displays

[0208] software:

[0209] OpenAI API library: for using generative AI (text, image, audio)

[0210] PIL (Python Imaging Library): Displaying images

[0211] pyttsx3: Audio playback

[0212] pydub: Audio data processing

[0213] 2. Overview of the processing flow

[0214] a. Receiving User Requests

[0215] The user requests the creation of a virtual space. For example, they input a request such as "Please create a virtual store specializing in high-end jewelry." This request is then sent from the device to the server.

[0216] b. Request Parsing

[0217] The server analyzes the request and determines the necessary operations. Specifically, it determines that the request for a "virtual store specializing in luxury jewelry" requires the creation of a store scenario, visuals, and audio.

[0218] c. Performing the generate operation

[0219] The server instructs the generation AI to generate each element.

[0220] Text generation AI: Generates store scenarios and stories.

[0221] Image generation AI: Generates store designs and product images.

[0222] Voice generation AI: Generates environmental sounds within the store and character dialogue.

[0223] d. Integration of Components

[0224] The server integrates the generated scenarios, visuals, and audio to create a consistent virtual space data, which is then sent to the user's device, where it is displayed.

[0225] Users can explore generated virtual spaces and enjoy experiences, such as walking around a virtual store specializing in high-end jewelry and interacting with elven characters.

[0226] Specific examples

[0227] If a user requests a medieval jewelry shop with elves selling ornaments, the system will:

[0228] The user enters a request.

[0229] The device sends a request to the server.

[0230] The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[0231] The server instructs the text generation AI to create the store scenario, the image generation AI to create the store design, and the voice generation AI to create environmental sounds.

[0232] Each AI generates its own elements.

[0233] The server integrates all the components and creates virtual space data.

[0234] The server sends the integrated data to the terminal.

[0235] The device displays the data to the user, who then explores the virtual store.

[0236] The user enters feedback into the device, which then sends it to the server.

[0237] The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[0238] Example prompt sentences to use

[0239] Create a medieval-style jewelry shop where elves sell decorative items. Provide the story, visuals, and audio for the shop.

[0240] In this way, it is possible to efficiently generate and provide highly customizable virtual spaces that can adapt to the diverse needs of users.

[0241] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0242] Step 1:

[0243] A user requests the creation of a virtual space. Specifically, the user inputs a request for creation, such as "Please create a virtual store specializing in luxury jewelry," using a smartphone or other device. The input request for creation is sent from the device to the server for processing in the next step.

[0244] Input: User's creation request (e.g., "Create a virtual store specializing in high-end jewelry")

[0245] Output: The generation request is sent to the server

[0246] Step 2:

[0247] The server analyzes the generation request received from the device. Specifically, it uses a text analysis algorithm to identify keywords and necessary components in the request. This analysis determines which generation operation (text generation, image generation, or audio generation) is required.

[0248] Input: Text data of the generation request

[0249] Output: Information about the required generation operations (scenario generation, visual generation, audio generation)

[0250] Step 3:

[0251] The server issues instructions to each generative AI model to execute the generation operations. Specifically, using OpenAI's API, it requests the text generation AI to generate the store scenario, the image generation AI to generate the store design, and the voice generation AI to generate the store's environmental sounds and character dialogue.

[0252] Input: Information about the generation operation, prompt

[0253] Output: Scenarios, visuals, and audio data generated by each generative AI model

[0254] Step 4:

[0255] The server integrates the generated scenarios, visuals, and audio. Specifically, it combines each generated data into a consistent virtual space data, which includes data format conversion and adjustment, and data association.

[0256] Input: Generated scenario, visual and audio data

[0257] Output: Integrated virtual space data

[0258] Step 5:

[0259] The server transmits the integrated virtual space data to the user's device. Specifically, it uses a data transfer protocol to deliver the virtual space data quickly and securely to the device. The device interprets the received data and provides the user with a visual and auditory virtual space experience.

[0260] Input: Integrated virtual space data

[0261] Output: The virtual space is displayed on the user's device.

[0262] Step 6:

[0263] Users can explore the generated virtual space and enjoy the experience, for example, walking around a virtual store specializing in high-end jewelry, checking out the products, and interacting with the characters.

[0264] Input: Virtual space experience (user operation and interaction)

[0265] Output: User experience and feedback

[0266] Step 7:

[0267] Users provide feedback about their experiences by entering ratings and comments on their devices, which are then sent to the server, which analyzes the feedback and uses it to improve the generation process.

[0268] Input: User feedback (text data)

[0269] Output: Feedback data for improvement

[0270] 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.

[0271] The system of the present invention includes a process for analyzing a generation request, performing multiple generation operations, integrating the generated components, and transmitting the integrated components to a user terminal. Furthermore, by combining an emotion engine that recognizes the user's emotions, the system can provide a customized virtual space according to the user's emotional state. The following is a description of a specific embodiment of the present invention.

[0272] overview

[0273] This invention receives a request (generation request) for the creation of a user's desired virtual space, analyzes it, and then executes multiple generation operations to generate components (scenario, visuals, audio, etc.), integrating them and providing them to the user. It also uses an emotion engine to recognize the user's emotions and adjust the created virtual space according to their emotional state. Furthermore, it collects user ratings and feedback, analyzes them, and feeds them back to the generation AI to improve the accuracy and quality of future generation operations.

[0274] Detailed embodiment

[0275] 1. Receiving a User Request

[0276] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[0277] Terminal: Sends the request entered by the user to the server.

[0278] 2. Parsing the Request

[0279] Server: Analyzes the generation request received from the device and identifies the required generation operations (e.g., scenario generation, visual generation, audio generation).

[0280] 3. Emotion Recognition by Emotion Engine

[0281] On the device: Uses an emotion engine to analyze the user's facial expressions, voice tone, and behavior to recognize the user's emotional state.

[0282] Emotion engine: Determines the user's emotional state (e.g., happy, excited, calm) based on the data obtained.

[0283] 4. Performing the Generate Operation

[0284] Server: Instructs the text generation AI, image generation AI, and voice generation AI to generate each element.

[0285] Text generation AI: Generates scenarios such as the city's history, backstories of main characters, and events that occur in the city.

[0286] Image generation AI: Generates visual elements such as city buildings, landscapes, and character designs.

[0287] Voice generation AI: Generates city environmental sounds and character dialogue.

[0288] 5. Integration of Components

[0289] Server: Integrates the generated scenario, visual, and audio data to create consistent virtual space data.

[0290] 6. Adjusting to your emotional state

[0291] Server: Adjusts elements of the virtual space (e.g., colors, music, and environment) based on the user's emotional state obtained from the emotion engine. For example, if the user is determined to be relaxed, the colors and music will be changed to calmer ones.

[0292] 7. Transmission and Display of Aggregated Data

[0293] Server: The server transmits the integrated virtual space data, adjusted according to the user's emotional state, to the device.

[0294] Device: Provides users with visual, auditory, and other experiences based on the virtual space data received from the server. For example, the device allows users to explore a city through VR goggles.

[0295] 8. User Experience and Feedback

[0296] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[0297] User: Enters their experience rating and feedback into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[0298] Device: Sends user feedback to the server.

[0299] 9. Feedback processing and AI training

[0300] Server: Analyzes the feedback received from the device and provides the generated AI with data on areas that need improvement.

[0301] Generative AI: Based on the feedback received, it learns and improves the quality of the next generation operation.

[0302] Specific examples

[0303] For example, if a user requests, "Generate a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[0304] 1. The user enters a request.

[0305] 2. The device sends a request to the server.

[0306] 3. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[0307] 4. The device uses an emotion engine to recognize the user's emotions.

[0308] 5. The emotion engine determines the user's emotional state and sends it to the server.

[0309] 6. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[0310] 7. Each AI generates its own elements.

[0311] 8. The server integrates all components and creates virtual space data.

[0312] 9. The server adjusts the virtual space based on data from the emotion engine.

[0313] 10. The server sends the integrated data to the device.

[0314] 11. The device displays the data to the user, who then explores the pyramid city through VR goggles.

[0315] 12. The user enters feedback into the device, which then sends it to the server.

[0316] 13. The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[0317] In this way, by combining the emotion engine, this system can efficiently generate and provide a highly customized virtual space that corresponds to the user's emotional state.

[0318] The processing flow will be explained below.

[0319] Step 1:

[0320] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[0321] Terminal: Sends the request entered by the user to the server.

[0322] Step 2:

[0323] Server: Analyzes the generation request received from the device, performs text analysis on the request content, and identifies the required generation operation (e.g., scenario generation, visual generation, audio generation).

[0324] Step 3:

[0325] On the device: Uses an emotion engine to recognize the user's emotional state by analyzing their facial expressions, voice tone, and behavior in real time.

[0326] Emotion engine: Determines the user's emotions (e.g., happy, relaxed, excited) based on facial expressions, vocal tone, and behavioral data such as excitement and calm.

[0327] Step 4:

[0328] Emotion engine: Sends data indicating the user's emotional state to the server.

[0329] Step 5:

[0330] Server: Issues instructions to the text generation AI to generate a scenario, including the town's setting and history, background information for the main characters, and events that will occur.

[0331] Text generation AI: Generates text data based on a specified scenario and sends it back to the server.

[0332] Step 6:

[0333] Server: Based on the scenario data received from the text generation AI, the server issues instructions to the image generation AI to generate visuals. These instructions include the design of city buildings, scenery, characters, etc.

[0334] Image generation AI: Generates appropriate visual elements based on scenario data and sends them back to the server.

[0335] Step 7:

[0336] Server: Based on the visual data received from the image generation AI, it issues instructions to the sound generation AI to generate sounds, including the city's ambient sounds and character dialogue.

[0337] Voice generation AI: Generates the necessary acoustic data based on a specified scenario and sends it back to the server.

[0338] Step 8:

[0339] Server: Integrates the generated scenario, visual, and audio data to create a consistent virtual space.

[0340] Step 9:

[0341] Server: Adjusts elements of the virtual space (e.g., colors, music, and environmental settings) based on the user's emotional state data obtained from the emotion engine. For example, if the user is in a relaxed state, soften the colors and change the background music to a calmer one.

[0342] Step 10:

[0343] Server: The server transmits the integrated virtual space data, adjusted according to the user's emotional state, to the device.

[0344] Step 11:

[0345] Device: Provides users with visual, auditory, and other experiences based on the virtual space data received from the server. For example, the device allows users to explore a city through VR goggles.

[0346] Step 12:

[0347] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[0348] Step 13:

[0349] User: Enters their experience rating and feedback into the device, for example, "The building design is great, but the background noise is a bit too loud."

[0350] Terminal: Sends user-entered feedback to the server.

[0351] Step 14:

[0352] Server: Analyzes the feedback received from the device and provides it as data on areas for improvement to the generative AI and emotion engine.

[0353] Generative AI: Based on the received feedback data, it learns to help with the next generation operation and aims to improve quality.

[0354] Emotion Engine: Improves the user emotion recognition algorithm based on feedback data, improving recognition accuracy.

[0355] Through the above steps, the system of the present invention can efficiently generate and provide a high-quality, customized virtual space that meets the user's requirements and emotional state.

[0356] Example 2

[0357] 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."

[0358] Conventional virtual space generation systems provide virtual spaces by generating and integrating components based on user requests, but they have the problem of making it difficult to increase user satisfaction because they do not adjust according to the user's emotional state.Furthermore, there is also the problem of not providing appropriate feedback based on evaluations of the generated virtual space, which makes continuous quality improvement insufficient.

[0359] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0360] In this invention, the server includes means for analyzing the generation request and identifying a predetermined task, means for executing a plurality of generation operations, means for integrating the generated components, means for transmitting the integrated components to the user terminal, means for analyzing the user's evaluation and providing feedback for improving the generation operations, means for recognizing the user's emotional state, and means for adjusting the components according to the emotional state, thereby enabling the provision of a virtual space according to the user's emotional state and continuous quality improvement based on the user's evaluation.

[0361] A "generation request" is a specific request that a user inputs to request the generation of a virtual space.

[0362] The "predetermined work" refers to the various operations and processes required to generate a virtual space, which are identified as a result of analyzing the generation request.

[0363] A "creation operation" is an operation or procedure for generating content such as text, images, or audio.

[0364] "Components" refer to the individual elements such as scenarios, visuals, and sounds that make up a virtual space.

[0365] "Synthesis" refers to the process of combining the components generated by individual generation operations into a coherent virtual space data set.

[0366] "User terminal" refers to the device that a user uses to experience a virtual space, and specifically includes a PC, smartphone, VR goggles, etc.

[0367] An "emotion engine" is a technology or algorithm that analyzes a user's facial expressions, tone of voice, behavior, etc. to determine their emotional state.

[0368] "Feedback" refers to the evaluations and opinions that users give about their virtual space experiences, and is information that is used to improve and optimize the system.

[0369] A "text generation operation" is an operation that generates a sentence or scenario based on a specific prompt.

[0370] An "image generation operation" is an operation that generates visual content based on a particular prompt.

[0371] An "audio generation operation" is an operation that generates audio content based on a particular prompt.

[0372] "Tuning" refers to the process of optimizing each element of the generated virtual space based on the user's emotional state as determined by the emotion engine.

[0373] "Analysis" is the process of extracting and understanding specific information from input data.

[0374] The present invention is a system that generates a virtual space based on a user's request, integrates its components, and provides the virtual space to the user. This system also has the ability to recognize the user's emotional state and adjust the generated virtual space accordingly. Specific embodiments of this system are described below.

[0375] Hardware and software used

[0376] Hardware

[0377] Server: Parses requests, directs production operations, integrates the generated data, and coordinates with the emotion engine.

[0378] Terminal: The device used by the user, including PCs, smartphones, VR goggles, etc.

[0379] software

[0380] Generative AI models: Includes text generation AI, image generation AI, and speech generation AI, and performs each generation operation.

[0381] Emotion engine: Software that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state.

[0382] Database Management System (DBMS): A system for storing and integrating generated data in a consistent format.

[0383] Process Overview

[0384] Receiving and sending user requests

[0385] The user inputs a specific request for generating a virtual space. For example, the user inputs a prompt statement such as "Please generate a medieval fantasy town."

[0386] The device sends a request to the server, sending data using an HTTP POST request.

[0387] Parsing the request

[0388] The server analyzes the received request and extracts the information needed for the generation operation. It uses a natural language processing (NLP) engine to identify key keywords.

[0389] Emotion recognition by emotion engine

[0390] The device uses an emotion engine to analyze the user's facial expressions and tone of voice.

[0391] The emotion engine determines the user's emotional state based on the analysis results and generates emotion labels such as "fun" or "excited."

[0392] Running the generate operation

[0393] The server issues generation instructions to the text generation AI, image generation AI, and voice generation AI.

[0394] The text generation AI generates the city's history and backstories for the main characters.

[0395] Image generation AI generates visuals of city buildings, landscapes, and characters.

[0396] The voice generation AI generates the city's environmental sounds and character dialogue.

[0397] Integration of each element

[0398] The server integrates the generated scenario, visual and audio data, and uses a DBMS to organize the data into a consistent format.

[0399] Adjusting according to emotional state

[0400] The server adjusts the elements of the generated virtual space based on the emotional data obtained from the emotion engine. For example, if the user is feeling relaxed, it will change the colors and music to calmer ones.

[0401] Sending and displaying consolidated data

[0402] The server sends the adjusted virtual space data to the terminal.

[0403] The device displays a virtual space to the user, allowing them to explore a city using VR goggles, for example.

[0404] User Experience and Feedback

[0405] The user explores the generated virtual space and provides feedback on their experience.

[0406] The device sends feedback to the server, which is analyzed and used to improve future generation operations.

[0407] Specific examples

[0408] If the user enters the prompt "Generate a city centered around an ancient Egyptian pyramid," the system will:

[0409] 1. The user enters a prompt and the terminal sends a request to the server.

[0410] 2. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[0411] 3. The device uses an emotion engine to analyze the user's emotional state.

[0412] 4. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[0413] 5. Each AI generates its own element.

[0414] 6. The server integrates all components to create virtual space data and adjusts it based on data from the emotion engine.

[0415] 7. The server sends the integrated data to the device, which displays it to the user, who then explores the pyramid city through the VR goggles.

[0416] 8. The user enters feedback and the device sends it to the server.

[0417] 9. The server analyzes the feedback and provides it to the generation AI to help improve the quality of future generation.

[0418] In this way, the system of the present invention can generate highly customized virtual spaces and continuously improve their quality based on the user's emotional state and feedback.

[0419] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0420] Step 1: Receiving a user request

[0421] The user inputs a specific request for generating a virtual space into the terminal, for example, a prompt sentence such as "Please generate a medieval fantasy town."

[0422] The terminal sends the input request to the server using an HTTP POST request, and sends the prompt received from the user to the server.

[0423] Input: The prompt text entered by the user.

[0424] Output: Sends a request to the server.

[0425] Step 2: Parsing the request

[0426] The server analyzes the request received from the terminal. First, it parses the received data and checks its contents.

[0427] The server analyzes the request and identifies the required generation operations (scenario generation, visual generation, audio generation). A natural language processing (NLP) engine is used for the analysis to extract key keywords. For example, keywords such as "medieval fantasy," "town," and "generation" are extracted.

[0428] Input: The prompt text sent to the server.

[0429] Output: A list of the required generation operations.

[0430] Step 3: Emotion recognition by the emotion engine

[0431] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, and captures the user's facial expressions and voice through the built-in camera and microphone.

[0432] The emotion engine analyzes the captured data and determines the user's emotion using a machine learning model (e.g., a CNN model for emotion recognition).

[0433] Input: User facial and voice capture data.

[0434] Output: The user's emotional state (happy, excited, relaxed, etc.).

[0435] Step 4: Run the generate operation

[0436] The server issues instructions to the text generation AI, image generation AI, and voice generation AI to generate each element.

[0437] The text generation AI generates a scenario based on the request, such as the history of the town, the backstories of the main characters, and events that occur in the town.

[0438] Image generation AI generates visual elements based on requests, such as city buildings, landscapes, and character designs.

[0439] The voice generation AI generates audio elements based on requests, such as city ambient sounds and character dialogue.

[0440] Input: Request parsing results.

[0441] Output: Generated scenarios, visuals, and audio data.

[0442] Step 5: Putting the Components Together

[0443] The server integrates the generated scenario, visual, and audio data, and uses a DBMS to organize the data into a consistent format, for example, to create a unified design and background story, linking the entire virtual space.

[0444] Input: Generated scenario, visual and audio data.

[0445] Output: Integrated virtual space data.

[0446] Step 6: Adjust according to your emotional state

[0447] The server adjusts the virtual space based on the emotional data it obtains from the emotion engine. For example, if the user is feeling relaxed, it will change the background music to a calmer one and use a more subdued color scheme.

[0448] Input: Integrated virtual space data, user emotional state.

[0449] Output: Calibrated virtual space data.

[0450] Step 7: Send and view integrated data

[0451] The server sends the adjusted virtual space data to the device, using the WebSocket communication protocol for real-time data transfer.

[0452] The device displays a virtual space to the user based on the data received, allowing the user to explore a city using VR goggles, for example.

[0453] Input: Calibrated virtual space data.

[0454] Output: A display of the virtual space.

[0455] Step 8: User experience and feedback

[0456] Users explore generated virtual spaces and enjoy experiences, such as walking around a medieval fantasy town and interacting with its inhabitants.

[0457] The user enters feedback about their experience into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[0458] The device sends feedback data to the server in JSON format.

[0459] Input: User feedback.

[0460] Output: Send feedback to the server.

[0461] Step 9: Processing feedback and training the AI

[0462] The server receives the feedback and analyzes it. For example, it uses a text analysis engine to extract content such as "background noise is too loud."

[0463] The generation AI uses the feedback to learn and improve its next generation operation, for example by improving the background sound volume adjustment algorithm.

[0464] Input: User feedback.

[0465] Output: Improved generation algorithm.

[0466] (Application example 2)

[0467] 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."

[0468] Current virtual space generation technology faces challenges, such as inconsistent quality of content and user experience generated automatically based on user requests, particularly difficulty in flexibly adjusting content in response to user emotions and feedback. Furthermore, the generated virtual space may not be optimized for the user's emotional state, potentially resulting in reduced user satisfaction. Furthermore, insufficient analysis of feedback can make future improvements difficult.

[0469] 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.

[0470] In this invention, the server includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for analyzing a user's evaluation and providing feedback for improving the generation operation, a means for performing emotion recognition, and a means for adjusting the integrated components according to the user's emotional state. This not only enables the generation of a high-quality virtual space based on the user's generation request, but also improves user satisfaction by customizing the virtual space according to the user's emotional state. Furthermore, by analyzing user feedback, the accuracy and quality of the generation operation are continuously improved.

[0471] A "generation request" is a request from a user to generate a virtual space.

[0472] A "predetermined task" is a series of production operations that are specified based on a production request.

[0473] "Generation operations" refers to the various generation processes that are carried out to construct a virtual space.

[0474] "Components" refer to elements such as scenarios, visuals, and sounds that are generated to form a virtual space.

[0475] "User terminal" means the device used by a user to receive and experience a virtual space.

[0476] "Evaluation" refers to the feedback and reviews that users give about the virtual space they have experienced.

[0477] "Emotion recognition" is the process of identifying a user's emotional state from their facial expressions, vocal tone, behavior, etc.

[0478] "Emotional state" refers to the user's current emotional state, such as happy, excited, calm, etc.

[0479] The "means for analyzing user evaluations and providing feedback to improve the generation operation" refers to a means for collecting and analyzing evaluations from users to help improve the quality of the generation operation from the next time onwards.

[0480] System Program

[0481] The system of the present invention includes a series of processes, including analyzing a generation request, performing multiple generation operations, integrating the generated components, and transmitting the components to a user terminal. It also has the function of performing emotion recognition and adjusting the components according to the user's emotional state. The following describes specific means for realizing this application example.

[0482] System configuration

[0483] Hardware and software used

[0484] 1. Hardware

[0485] User device: A device used by a user, such as smart glasses or a head-mounted display.

[0486] Server: A back-end server for generating operations and data processing.

[0487] 2. Software

[0488] Emotion Recognition Engine (EmotionEngine): An engine that analyzes a user's facial expressions, tone of voice, and behavior to identify their emotional state.

[0489] Virtual Space Generator: An engine that integrates generated scenarios, visuals, and sounds to generate virtual spaces.

[0490] Text generation AI (e.g., OpenAI GPT-3): An AI model for generating scenarios and stories.

[0491] Image generation AI (e.g., DeepDream): An AI model for generating visual elements of virtual spaces.

[0492] Audio generation AI: An AI model for generating acoustic elements in virtual spaces.

[0493] Program processing

[0494] Natural language explanation

[0495] After receiving a generation request from the user, the server analyzes it and performs multiple generation operations using text generation AI, image generation AI, and voice generation AI. The generated scenario, visuals, and audio are integrated by the virtual space generation engine to create consistent virtual space data.

[0496] The system then uses an emotion recognition engine to identify the user's emotional state and adjusts the colors, music, and other aspects of the virtual space based on that data, creating a personalized virtual space that reflects the user's emotional state.

[0497] Finally, the generated virtual space data is sent to the user's device, where the user experiences the virtual space through smart glasses or a head-mounted display. The user provides evaluations and feedback on the virtual space they experienced, which is then sent back to the server to help improve the quality of future generation operations.

[0498] Examples of concrete examples and prompts

[0499] Examples:

[0500] The user inputs a request such as "Show me clothes from the summer collection." Based on this request, the system generates products from the summer collection in a virtual store and uses an emotion recognition engine to identify the user's emotional state. The atmosphere and presentation of the virtual store are then adjusted to match the user's emotions, and the store is presented to the user through smart glasses.

[0501] Example prompt sentence:

[0502] "User request: Show me clothes from the summer collection"

[0503] "User's emotional state: excited"

[0504] In this way, the system of the present invention can provide a high-quality virtual space that responds to the user's emotions, achieving a highly satisfying experience.

[0505] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0506] Step 1:

[0507] The user enters a generation request.

[0508] The user inputs a generation request, for example, "Show me the clothes from the summer collection," through smart glasses or a head-mounted display, and the terminal sends this generation request to the server.

[0509] Step 2:

[0510] The server parses the create request.

[0511] The server analyzes the input generation request and extracts the data necessary for the generation operation (text generation, image generation, voice generation). Specifically, it generates prompts for the text generation AI, image generation AI, and voice generation AI.

[0512] Step 3:

[0513] The server performs the text generation operation.

[0514] The server instructs the text generation AI to create a scenario based on the generation request. The input is a prompt sentence, which the text generation AI processes and calculates to output a scenario such as a description of the clothing or a product story.

[0515] Step 4:

[0516] The server performs the image generation operation.

[0517] The server instructs the image generation AI to create visuals based on the generation request. The input is the output of the text generation AI and the generation request itself, and the image generation AI processes and calculates it to output images of clothing designs and the exterior of a virtual store.

[0518] Step 5:

[0519] The server performs the audio generation operations.

[0520] The server instructs the voice generation AI to create audio based on the generation request. The input is the output of the text generation AI and the generation request itself, and the voice generation AI processes and calculates it to output audio elements such as background sounds and narration.

[0521] Step 6:

[0522] The server performs emotion recognition.

[0523] The device collects the user's facial expressions, voice tone, and behavior, and sends them to an emotion recognition engine, which analyzes this data as input and outputs the user's emotional state (e.g., excited, relaxed, etc.).

[0524] Step 7:

[0525] The server integrates the generated components.

[0526] The server uses the outputs from the text generation AI, image generation AI, and voice generation AI to integrate each component in a virtual space generation engine and generate a unified virtual space.

[0527] Step 8:

[0528] The server adjusts based on the emotional state.

[0529] Based on the emotional state data obtained from the emotion recognition engine, the server adjusts each element of the virtual space (color, music, visual effects, etc.) to match the user's emotional state.

[0530] Step 9:

[0531] The server sends the integrated and adjusted virtual space data to the terminal.

[0532] The server transmits the completed virtual space data to the user's terminal, which displays it, providing the user with a virtual shopping experience.

[0533] Step 10:

[0534] The user enters feedback.

[0535] The user inputs their evaluation and feedback on the virtual space they experienced into the terminal, which then transmits this information to the server.

[0536] Step 11:

[0537] The server analyzes the feedback and improves the AI ​​model.

[0538] The server analyzes the feedback received from users and feeds that data back into the generative AI model to improve the quality of future generations.

[0539] In this way, users can enjoy a high-quality virtual shopping experience that is emotionally customized.

[0540] 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.

[0541] 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.

[0542] 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.

[0543] [Second embodiment]

[0544] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0545] 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.

[0546] 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).

[0547] 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.

[0548] 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.

[0549] 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).

[0550] 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.

[0551] 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.

[0552] 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.

[0553] 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.

[0554] 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.

[0555] 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."

[0556] The system of the present invention includes a process for analyzing a generation request, performing multiple generation operations, integrating the generated components, and sending the components to a user terminal. The following is a description of a specific embodiment.

[0557] overview

[0558] In this invention, we have constructed a system that receives a user's request (generation request) for the generation of a virtual space, analyzes it, and then executes multiple generation operations to generate components (scenario, visuals, audio, etc.), integrating them and providing them to the user. In addition, we collect user ratings and feedback, analyze them, and feed them back to the generation AI to improve the accuracy and quality of future generation operations.

[0559] Detailed embodiment

[0560] 1. Receiving a User Request

[0561] User: The user requests the creation of a virtual space. For example, the user inputs a request such as "Please create a medieval fantasy town" into the device.

[0562] Terminal: Receives requests typed by the user and sends them to the server.

[0563] 2. Parsing the Request

[0564] Server: Analyzes the generation request received from the device and identifies the required generation operations. For example, from the request for a "medieval fantasy town," it determines that the town's scenario, visuals, and audio must be generated.

[0565] 3. Performing the Generate Operation

[0566] Server: Instructs the text generation AI, image generation AI, and voice generation AI to generate each element.

[0567] Text generation AI: Generates scenarios such as the city's history, backstories of main characters, and events that occur in the city.

[0568] Image generation AI: Generates visual elements such as city buildings, landscapes, and character designs.

[0569] Voice generation AI: Generates city environmental sounds and character dialogue.

[0570] 4. Integration of Components

[0571] Server: Integrates the generated scenarios, visuals, and audio to create consistent virtual space data.

[0572] 5. Transmission and Display of Aggregated Data

[0573] Server: Sends the integrated virtual space data to the device.

[0574] Device: Displays a virtual space to the user based on the data received from the server. For example, the device allows the user to explore a city through VR goggles.

[0575] 6. User Experience and Feedback

[0576] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[0577] User: Enters their experience rating and feedback into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[0578] Device: Sends user feedback to the server.

[0579] 7. Feedback processing and AI training

[0580] Server: Analyzes the feedback received from the device and provides it as feedback data to the generation AI.

[0581] Generative AI: Learns from the feedback it receives to improve its generative process and generate better results in the future.

[0582] Specific examples

[0583] For example, if a user requests, "Generate a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[0584] 1. The user enters a request.

[0585] 2. The device sends a request to the server.

[0586] 3. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[0587] 4. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[0588] 5. Each AI generates its own elements.

[0589] 6. The server integrates all components and creates virtual space data.

[0590] 7. The server sends the integrated data to the device.

[0591] 8. The device displays the data to the user, who then explores the pyramid city through VR goggles.

[0592] 9. The user enters feedback into the device, which then sends it to the server.

[0593] 10. The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[0594] In this way, this system can efficiently generate and provide highly customizable virtual spaces that meet the diverse needs of users.

[0595] The processing flow will be explained below.

[0596] Step 1:

[0597] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[0598] Terminal: Sends the request entered by the user to the server.

[0599] Step 2:

[0600] Server: Analyzes the generation request received from the device, performs text analysis on the request content, and identifies the required generation operation (e.g., scenario generation, visual generation, audio generation).

[0601] Step 3:

[0602] Server: Issues instructions to the text generation AI to generate a scenario, including the town's setting and history, background information for the main characters, and events that will occur.

[0603] Text generation AI: Generates text data based on a specified scenario and sends it back to the server.

[0604] Step 4:

[0605] Server: Based on the scenario data received from the text generation AI, the server issues instructions to the image generation AI to generate visuals. These instructions include the design of city buildings, scenery, characters, etc.

[0606] Image generation AI: Generates appropriate visual elements based on scenario data and sends them back to the server.

[0607] Step 5:

[0608] Server: Based on the visual data received from the image generation AI, it issues instructions to the audio generation AI to generate sounds, including the city's ambient sounds and character dialogue.

[0609] Voice generation AI: Generates the necessary acoustic data based on a specified scenario and sends it back to the server.

[0610] Step 6:

[0611] Server: Integrates the generated scenario, visual, and audio data to create a consistent virtual space.

[0612] Step 7:

[0613] Server: Sends the integrated virtual space data to the device.

[0614] Step 8:

[0615] Device: Provides users with visual and auditory experiences based on the virtual space data received from the server. For example, it allows users to explore a city through VR goggles.

[0616] Step 9:

[0617] User: Enters their evaluation and feedback about the virtual space they experienced into the device. For example, they may say, "The building design is great, but the background noise is a little too loud."

[0618] Device: Sends user feedback to the server.

[0619] Step 10:

[0620] Server: Analyzes the feedback received from the device and provides the generated AI with data on areas that need improvement.

[0621] Generative AI: Based on the feedback received, it learns and improves the quality of its next generation operation.

[0622] By using the above steps, the system of the present invention can efficiently generate and provide a high-quality virtual space that meets the user's requirements.

[0623] Example 1

[0624] 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."

[0625] Conventional virtual space generation systems have difficulty generating and integrating individual elements (scenario, visuals, audio) consistently, making it difficult to provide a high-quality virtual experience that meets user demands. Furthermore, they lacked mechanisms for effectively incorporating user feedback and continuously improving the generation process. This resulted in inconsistent quality in the generated virtual spaces, leading to problems with reduced user satisfaction.

[0626] 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.

[0627] In this invention, the server includes means for analyzing a generation request and identifying a predetermined generation operation, means for executing multiple generation operations using a text generation AI, an image generation AI, and a voice generation AI, means for integrating the generated scenario, visual, and voice components, means for transmitting the integrated components to a user terminal, and means for collecting user experience evaluations and feedback and feeding them back to improve the generation AI model. This enables the generation of high-quality virtual spaces according to user requests and realizes continuous quality improvement.

[0628] A "generation request" is a request entered by a user wishing to create a specific virtual space.

[0629] "Analysis" refers to the process of decomposing an input production request and identifying the required production operations.

[0630] "Generation operations" refer to the procedures and means for generating the individual elements that make up a virtual space, such as text, images, and sounds.

[0631] "Text generation AI" is an artificial intelligence technology that generates text data such as scenarios and backstories based on requests entered by users.

[0632] "Image generation AI" is an artificial intelligence technology that generates visual elements such as buildings, landscapes, and characters in a virtual space in response to user requests.

[0633] "Voice generation AI" refers to artificial intelligence technology for generating background sounds and character dialogue used in virtual spaces.

[0634] "Components" refer to the individual data elements such as scenarios, visuals, and sounds that make up a virtual space.

[0635] "Synthesis" refers to the process of combining the individual generated components into a coherent virtual space.

[0636] "User device" means the device a user uses to request and experience a virtual space, such as a PC, smartphone, or VR goggles.

[0637] "Feedback" refers to evaluations and suggestions for improvement provided by users based on their experience in a virtual space.

[0638] A "generative AI model" is an overall artificial intelligence framework or methodology for performing text, image, and audio generation operations.

[0639] This invention is a system that generates a virtual space based on a user's generation request and provides the virtual space to the user. This system includes processes that analyze the generation request, perform multiple generation operations, integrate the generated components, and send them to the user's terminal. It also has a function that collects user feedback and reflects it in the generative AI model to continuously improve the generation process.

[0640] The system is mainly composed of the interaction between the server, terminals, and users. Below, we will explain each component of the system and its role.

[0641] Components and Roles

[0642] server

[0643] The server is the central control unit of this system. The server has the following roles:

[0644] Analysis of the generation request: The server has a special software module that receives and analyzes the generation request from the user. For example, if a user requests "Please generate a medieval fantasy town," the server analyzes it and identifies the required generation operations (scenario, visuals, audio).

[0645] Execution of generation operations: The server executes the necessary generation operations using text generation AI, image generation AI, and voice generation AI. Each AI module is responsible for generating a specific generation element (text, image, voice).

[0646] Text Generation AI: Generates text data. This AI creates city scenarios, character backstories, event details, etc.

[0647] Image generation AI: Generates image data. This AI creates visual elements such as city buildings, landscapes, and character designs.

[0648] Voice generation AI: Generates voice data. This AI creates the city's environmental sounds, character dialogue, and more.

[0649] Integration of components: The server integrates the scenario, visual, and audio data generated by each AI module to create a consistent virtual space.

[0650] Data transmission: The integrated virtual space data is transmitted to the user's terminal using a high-speed data transfer protocol.

[0651] Feedback processing: The server collects user feedback and feeds it back into the generative AI model. This feedback is used as data to improve the generation process in the future.

[0652] Terminal

[0653] A terminal is a device through which a user interacts with the system. It has the following functions:

[0654] Sending a request: The creation request entered by the user is sent to the server. For example, the user enters a request such as "Create an ancient Egyptian city centered around a pyramid."

[0655] Data display: The virtual space data sent from the server is displayed to the user. The terminal displays the virtual space using a device such as a VR goggle, smartphone, or PC.

[0656] Feedback collection: Users input ratings and suggestions for improvement based on their experience in the virtual space and send them to the server.

[0657] user

[0658] Users use the system to explore and experience virtual spaces.

[0659] Inputting a request: The user inputs a request for the creation of the desired virtual space into the terminal.

[0660] Explore the virtual space: Explore the generated virtual space and enjoy the experience.

[0661] Providing feedback: Provide feedback on the virtual space you have experienced.

[0662] Specific examples

[0663] For example, if a user enters the prompt "Create a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[0664] The user enters a prompt.

[0665] The terminal sends a prompt to the server.

[0666] The server parses the prompt statement and determines the required generation operation.

[0667] The server instructs the text generation AI to generate the scenario, the image generation AI to generate the visuals, and the voice generation AI to generate the voice.

[0668] Each generation AI generates elements.

[0669] The server integrates the generated elements to create virtual space data.

[0670] The server sends the integrated data to the terminal.

[0671] The device displays the data, and users explore the pyramid city with VR goggles.

[0672] The user enters feedback into the device, which then sends it to the server.

[0673] The server then applies the feedback to the generated AI model.

[0674] In this way, the system can generate and provide high-quality virtual spaces that meet the diverse needs of users. Furthermore, by continuously incorporating user feedback, the quality of the generation process can be improved.

[0675] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0676] Step 1: Receiving a user request

[0677] The user inputs a request to generate a virtual space into the device. For example, the user inputs the prompt "Please generate a medieval fantasy town."

[0678] The terminal receives a generation request from the user, converts it into JSON format, and sends it to the server. At this time, the input is the user's prompt, and the output is the JSON format data sent to the server.

[0679] Step 2: Parsing the request

[0680] The server parses the JSON data of the generation request received from the device. The input is the JSON formatted generation request data, and the server parses it to identify the necessary generation elements (scenario, visual, audio).

[0681] As a result of the analysis, the server determines that, for example, a request for a "medieval fantasy town" requires the generation of a town's scenario, visuals, and audio. The output is a list of elements to be generated as a result of the analysis.

[0682] Step 3: Specify the generation operation

[0683] The server instructs the text generation AI, image generation AI, and speech generation AI to generate each element. The input is a list of generated elements as the analysis result, and the output is the generation instruction sent to each generation AI.

[0684] The server instructs the text generation AI to generate the city's scenario (history, character backstories, events, etc.).

[0685] The server instructs the image generation AI to generate visual elements such as city buildings, scenery, and characters.

[0686] The server instructs the voice generation AI to generate the city's environmental sounds and character dialogue.

[0687] Step 4: Run the generate operation

[0688] Each generation AI generates each element based on the generation instructions received from the server. The input is the generation instructions from the server, and the output is the generated data (scenario, visuals, audio).

[0689] Text generation AI generates and outputs scenarios.

[0690] Image generation AI generates and outputs visual elements.

[0691] The voice generation AI generates and outputs voice data.

[0692] Step 5: Putting the Components Together

[0693] The server integrates the scenario, visual, and audio data received from each generation AI. The input is the generated data from each generation AI, and the server integrates them into a single virtual space data.

[0694] The server creates consistent virtual space data, and the output is integrated virtual space data.

[0695] Step 6: Send and view the integrated data

[0696] The server sends the integrated virtual space data to the terminal. The input is the integrated virtual space data, and the output is the data sent to the terminal.

[0697] The device analyzes the virtual space data received from the server and displays it to the user. Specifically, the device displays the virtual space to the user in real time using VR goggles. The input is the virtual space data from the server, and the output is the virtual space displayed to the user.

[0698] Step 7: User experience and feedback

[0699] Users explore generated virtual spaces and enjoy experiences, such as walking around a medieval fantasy town and interacting with its inhabitants.

[0700] The user inputs their experience evaluation and feedback into the device. The input is the user's feedback content, and the output is the feedback data input into the device.

[0701] The terminal sends the user's feedback to the server. The input is the feedback data entered into the terminal, and the output is the feedback data sent to the server.

[0702] Step 8: Processing feedback and training the AI

[0703] The server analyzes the feedback received from the device and reflects it in the generative AI model. The input is the user's feedback data, which the server analyzes and uses to improve the generative AI model.

[0704] The generative AI model learns from the feedback data and improves the generation process in the future, resulting in a higher quality virtual space the next time it is generated.

[0705] (Application example 1)

[0706] 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."

[0707] In today's digital society, there is a demand for efficient generation of virtual spaces and improved user experiences. However, with conventional technologies, the virtual space generation process is complex and time-consuming, making it difficult to provide an integrated and consistent virtual experience. Furthermore, there was a lack of a mechanism for incorporating user feedback into the generation process, which hindered the improvement of the quality of the generation AI.

[0708] 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.

[0709] In this invention, the server includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for collecting feedback from the user and providing the feedback for improving the generation operations, and a means for generating and integrating visual, scenario, and audio elements to provide a virtual space. This enables the virtual space desired by the user to be generated quickly and consistently, improving the user experience. Furthermore, the collected feedback can be used to continuously improve the quality of the generation AI.

[0710] A "generation request" is a request in which the user specifies the details and elements of the virtual space they desire.

[0711] "Predetermined work" is a set of specific tasks that include the required creation operations, identified by analyzing the creation request.

[0712] "Generation operations" are processes for creating components of virtual space, such as text generation, image generation, and sound generation.

[0713] "Visuals" refers to visual elements in a virtual space, such as images and designs of buildings, characters, landscapes, etc.

[0714] "Scenario" refers to the content of the story or events that unfold within a virtual space, and includes text information and storylines to guide the user's experience.

[0715] "Audio" refers to auditory elements such as character dialogue, environmental sounds, and sound effects within the virtual space.

[0716] "User terminal" means a device used by a user to display and manipulate a virtual space, including a smartphone, smart glasses, or a head-mounted display.

[0717] "Feedback" refers to the evaluations and comments provided by users after experiencing a virtual space, and is information that is used to improve the quality of the generation operation.

[0718] An "integrated component" is a set of visuals, scenarios, and sounds created through generative operations that come together to form a coherent virtual space.

[0719] A "virtual space" is an imaginary space or world that users can experience interactively within a digital environment.

[0720] The present invention relates to a system for generating a virtual space based on a user request, which includes a means for analyzing the generation request and identifying a predetermined task, a means for performing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for collecting feedback from the user and providing the feedback for improving the generation operations, and a means for generating and integrating visual, scenario, and audio elements to provide the virtual space.

[0721] 1. Basic configuration

[0722] The system mainly consists of the following hardware and software:

[0723] Hardware: Smartphones, smart glasses, head-mounted displays

[0724] software:

[0725] OpenAI API library: for using generative AI (text, image, audio)

[0726] PIL (Python Imaging Library): Displaying images

[0727] pyttsx3: Audio playback

[0728] pydub: Audio data processing

[0729] 2. Overview of the processing flow

[0730] a. Receiving User Requests

[0731] The user requests the creation of a virtual space. For example, they input a request such as "Please create a virtual store specializing in high-end jewelry." This request is then sent from the device to the server.

[0732] b. Request Parsing

[0733] The server analyzes the request and determines the necessary operations. Specifically, it determines that the request for a "virtual store specializing in luxury jewelry" requires the creation of a store scenario, visuals, and audio.

[0734] c. Performing the generate operation

[0735] The server instructs the generation AI to generate each element.

[0736] Text generation AI: Generates store scenarios and stories.

[0737] Image generation AI: Generates store designs and product images.

[0738] Voice generation AI: Generates environmental sounds within the store and character dialogue.

[0739] d. Integration of Components

[0740] The server integrates the generated scenarios, visuals, and audio to create a consistent virtual space data, which is then sent to the user's device, where it is displayed.

[0741] Users can explore generated virtual spaces and enjoy experiences, such as walking around a virtual store specializing in high-end jewelry and interacting with elven characters.

[0742] Specific examples

[0743] If a user requests a medieval jewelry shop with elves selling ornaments, the system will:

[0744] The user enters a request.

[0745] The device sends a request to the server.

[0746] The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[0747] The server instructs the text generation AI to create the store scenario, the image generation AI to create the store design, and the voice generation AI to create environmental sounds.

[0748] Each AI generates its own elements.

[0749] The server integrates all the components and creates virtual space data.

[0750] The server sends the integrated data to the terminal.

[0751] The device displays the data to the user, who then explores the virtual store.

[0752] The user enters feedback into the device, which then sends it to the server.

[0753] The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[0754] Example prompt sentences to use

[0755] Create a medieval-style jewelry shop where elves sell decorative items. Provide the story, visuals, and audio for the shop.

[0756] In this way, it is possible to efficiently generate and provide highly customizable virtual spaces that can adapt to the diverse needs of users.

[0757] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0758] Step 1:

[0759] A user requests the creation of a virtual space. Specifically, the user inputs a request for creation, such as "Please create a virtual store specializing in luxury jewelry," using a smartphone or other device. The input request for creation is sent from the device to the server for processing in the next step.

[0760] Input: User's creation request (e.g., "Create a virtual store specializing in high-end jewelry")

[0761] Output: The generation request is sent to the server

[0762] Step 2:

[0763] The server analyzes the generation request received from the device. Specifically, it uses a text analysis algorithm to identify keywords and necessary components in the request. This analysis determines which generation operation (text generation, image generation, or audio generation) is required.

[0764] Input: Text data of the generation request

[0765] Output: Information about the required generation operations (scenario generation, visual generation, audio generation)

[0766] Step 3:

[0767] The server issues instructions to each generative AI model to execute the generation operations. Specifically, using OpenAI's API, it requests the text generation AI to generate the store scenario, the image generation AI to generate the store design, and the voice generation AI to generate the store's environmental sounds and character dialogue.

[0768] Input: Information about the generation operation, prompt

[0769] Output: Scenarios, visuals, and audio data generated by each generative AI model

[0770] Step 4:

[0771] The server integrates the generated scenarios, visuals, and audio. Specifically, it combines each generated data into a consistent virtual space data, which includes data format conversion and adjustment, and data association.

[0772] Input: Generated scenario, visual and audio data

[0773] Output: Integrated virtual space data

[0774] Step 5:

[0775] The server transmits the integrated virtual space data to the user's device. Specifically, it uses a data transfer protocol to deliver the virtual space data quickly and securely to the device. The device interprets the received data and provides the user with a visual and auditory virtual space experience.

[0776] Input: Integrated virtual space data

[0777] Output: The virtual space is displayed on the user's device.

[0778] Step 6:

[0779] Users can explore the generated virtual space and enjoy the experience, for example, walking around a virtual store specializing in high-end jewelry, checking out the products, and interacting with the characters.

[0780] Input: Virtual space experience (user operation and interaction)

[0781] Output: User experience and feedback

[0782] Step 7:

[0783] Users provide feedback about their experiences by entering ratings and comments on their devices, which are then sent to the server, which analyzes the feedback and uses it to improve the generation process.

[0784] Input: User feedback (text data)

[0785] Output: Feedback data for improvement

[0786] 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.

[0787] The system of the present invention includes a process for analyzing a generation request, performing multiple generation operations, integrating the generated components, and transmitting the integrated components to a user terminal. Furthermore, by combining an emotion engine that recognizes the user's emotions, the system can provide a customized virtual space according to the user's emotional state. The following is a description of a specific embodiment of the present invention.

[0788] overview

[0789] This invention receives a request (generation request) for the creation of a user's desired virtual space, analyzes it, and then executes multiple generation operations to generate components (scenario, visuals, audio, etc.), integrating them and providing them to the user. It also uses an emotion engine to recognize the user's emotions and adjust the created virtual space according to their emotional state. Furthermore, it collects user ratings and feedback, analyzes them, and feeds them back to the generation AI to improve the accuracy and quality of future generation operations.

[0790] Detailed embodiment

[0791] 1. Receiving a User Request

[0792] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[0793] Terminal: Sends the request entered by the user to the server.

[0794] 2. Parsing the Request

[0795] Server: Analyzes the generation request received from the device and identifies the required generation operations (e.g., scenario generation, visual generation, audio generation).

[0796] 3. Emotion Recognition by Emotion Engine

[0797] On the device: Uses an emotion engine to analyze the user's facial expressions, voice tone, and behavior to recognize the user's emotional state.

[0798] Emotion engine: Determines the user's emotional state (e.g., happy, excited, calm) based on the data obtained.

[0799] 4. Performing the Generate Operation

[0800] Server: Instructs the text generation AI, image generation AI, and voice generation AI to generate each element.

[0801] Text generation AI: Generates scenarios such as the city's history, backstories of main characters, and events that occur in the city.

[0802] Image generation AI: Generates visual elements such as city buildings, landscapes, and character designs.

[0803] Voice generation AI: Generates city environmental sounds and character dialogue.

[0804] 5. Integration of Components

[0805] Server: Integrates the generated scenario, visual, and audio data to create consistent virtual space data.

[0806] 6. Adjusting to your emotional state

[0807] Server: Adjusts elements of the virtual space (e.g., colors, music, and environment) based on the user's emotional state obtained from the emotion engine. For example, if the user is determined to be relaxed, the colors and music will be changed to calmer ones.

[0808] 7. Transmission and Display of Aggregated Data

[0809] Server: The server transmits the integrated virtual space data, adjusted according to the user's emotional state, to the device.

[0810] Device: Provides users with visual, auditory, and other experiences based on the virtual space data received from the server. For example, the device allows users to explore a city through VR goggles.

[0811] 8. User Experience and Feedback

[0812] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[0813] User: Enters their experience rating and feedback into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[0814] Device: Sends user feedback to the server.

[0815] 9. Feedback processing and AI training

[0816] Server: Analyzes the feedback received from the device and provides the generated AI with data on areas that need improvement.

[0817] Generative AI: Based on the feedback received, it learns and improves the quality of the next generation operation.

[0818] Specific examples

[0819] For example, if a user requests, "Generate a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[0820] 1. The user enters a request.

[0821] 2. The device sends a request to the server.

[0822] 3. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[0823] 4. The device uses an emotion engine to recognize the user's emotions.

[0824] 5. The emotion engine determines the user's emotional state and sends it to the server.

[0825] 6. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[0826] 7. Each AI generates its own elements.

[0827] 8. The server integrates all components and creates virtual space data.

[0828] 9. The server adjusts the virtual space based on data from the emotion engine.

[0829] 10. The server sends the integrated data to the device.

[0830] 11. The device displays the data to the user, who then explores the pyramid city through VR goggles.

[0831] 12. The user enters feedback into the device, which then sends it to the server.

[0832] 13. The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[0833] In this way, by combining the emotion engine, this system can efficiently generate and provide a highly customized virtual space that corresponds to the user's emotional state.

[0834] The processing flow will be explained below.

[0835] Step 1:

[0836] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[0837] Terminal: Sends the request entered by the user to the server.

[0838] Step 2:

[0839] Server: Analyzes the generation request received from the device, performs text analysis on the request content, and identifies the required generation operation (e.g., scenario generation, visual generation, audio generation).

[0840] Step 3:

[0841] On the device: Uses an emotion engine to recognize the user's emotional state by analyzing their facial expressions, voice tone, and behavior in real time.

[0842] Emotion engine: Determines the user's emotions (e.g., happy, relaxed, excited) based on facial expressions, vocal tone, and behavioral data such as excitement and calm.

[0843] Step 4:

[0844] Emotion engine: Sends data indicating the user's emotional state to the server.

[0845] Step 5:

[0846] Server: Issues instructions to the text generation AI to generate a scenario, including the town's setting and history, background information for the main characters, and events that will occur.

[0847] Text generation AI: Generates text data based on a specified scenario and sends it back to the server.

[0848] Step 6:

[0849] Server: Based on the scenario data received from the text generation AI, the server issues instructions to the image generation AI to generate visuals. These instructions include the design of city buildings, scenery, characters, etc.

[0850] Image generation AI: Generates appropriate visual elements based on scenario data and sends them back to the server.

[0851] Step 7:

[0852] Server: Based on the visual data received from the image generation AI, it issues instructions to the sound generation AI to generate sounds, including the city's ambient sounds and character dialogue.

[0853] Voice generation AI: Generates the necessary acoustic data based on a specified scenario and sends it back to the server.

[0854] Step 8:

[0855] Server: Integrates the generated scenario, visual, and audio data to create a consistent virtual space.

[0856] Step 9:

[0857] Server: Adjusts elements of the virtual space (e.g., colors, music, and environmental settings) based on the user's emotional state data obtained from the emotion engine. For example, if the user is in a relaxed state, soften the colors and change the background music to a calmer one.

[0858] Step 10:

[0859] Server: The server transmits the integrated virtual space data, adjusted according to the user's emotional state, to the device.

[0860] Step 11:

[0861] Device: Provides users with visual, auditory, and other experiences based on the virtual space data received from the server. For example, the device allows users to explore a city through VR goggles.

[0862] Step 12:

[0863] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[0864] Step 13:

[0865] User: Enters their experience rating and feedback into the device, for example, "The building design is great, but the background noise is a bit too loud."

[0866] Terminal: Sends user-entered feedback to the server.

[0867] Step 14:

[0868] Server: Analyzes the feedback received from the device and provides it as data on areas for improvement to the generative AI and emotion engine.

[0869] Generative AI: Based on the received feedback data, it learns to help with the next generation operation and aims to improve quality.

[0870] Emotion Engine: Improves the user emotion recognition algorithm based on feedback data, improving recognition accuracy.

[0871] Through the above steps, the system of the present invention can efficiently generate and provide a high-quality, customized virtual space that meets the user's requirements and emotional state.

[0872] Example 2

[0873] 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."

[0874] Conventional virtual space generation systems provide virtual spaces by generating and integrating components based on user requests, but they have the problem of making it difficult to increase user satisfaction because they do not adjust according to the user's emotional state.Furthermore, there is also the problem of not providing appropriate feedback based on evaluations of the generated virtual space, which makes continuous quality improvement insufficient.

[0875] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0876] In this invention, the server includes means for analyzing the generation request and identifying a predetermined task, means for executing a plurality of generation operations, means for integrating the generated components, means for transmitting the integrated components to the user terminal, means for analyzing the user's evaluation and providing feedback for improving the generation operations, means for recognizing the user's emotional state, and means for adjusting the components according to the emotional state, thereby enabling the provision of a virtual space according to the user's emotional state and continuous quality improvement based on the user's evaluation.

[0877] A "generation request" is a specific request that a user inputs to request the generation of a virtual space.

[0878] The "predetermined work" refers to the various operations and processes required to generate a virtual space, which are identified as a result of analyzing the generation request.

[0879] A "creation operation" is an operation or procedure for generating content such as text, images, or audio.

[0880] "Components" refer to the individual elements such as scenarios, visuals, and sounds that make up a virtual space.

[0881] "Synthesis" refers to the process of combining the components generated by individual generation operations into a coherent virtual space data set.

[0882] "User terminal" refers to the device that a user uses to experience a virtual space, and specifically includes a PC, smartphone, VR goggles, etc.

[0883] An "emotion engine" is a technology or algorithm that analyzes a user's facial expressions, tone of voice, behavior, etc. to determine their emotional state.

[0884] "Feedback" refers to the evaluations and opinions that users give about their virtual space experiences, and is information that is used to improve and optimize the system.

[0885] A "text generation operation" is an operation that generates a sentence or scenario based on a specific prompt.

[0886] An "image generation operation" is an operation that generates visual content based on a particular prompt.

[0887] An "audio generation operation" is an operation that generates audio content based on a particular prompt.

[0888] "Tuning" refers to the process of optimizing each element of the generated virtual space based on the user's emotional state as determined by the emotion engine.

[0889] "Analysis" is the process of extracting and understanding specific information from input data.

[0890] The present invention is a system that generates a virtual space based on a user's request, integrates its components, and provides the virtual space to the user. This system also has the ability to recognize the user's emotional state and adjust the generated virtual space accordingly. Specific embodiments of this system are described below.

[0891] Hardware and software used

[0892] Hardware

[0893] Server: Parses requests, directs production operations, integrates the generated data, and coordinates with the emotion engine.

[0894] Terminal: The device used by the user, including PCs, smartphones, VR goggles, etc.

[0895] software

[0896] Generative AI models: Includes text generation AI, image generation AI, and speech generation AI, and performs each generation operation.

[0897] Emotion engine: Software that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state.

[0898] Database Management System (DBMS): A system for storing and integrating generated data in a consistent format.

[0899] Process Overview

[0900] Receiving and sending user requests

[0901] The user inputs a specific request for generating a virtual space. For example, the user inputs a prompt statement such as "Please generate a medieval fantasy town."

[0902] The device sends a request to the server, sending data using an HTTP POST request.

[0903] Parsing the request

[0904] The server analyzes the received request and extracts the information needed for the generation operation. It uses a natural language processing (NLP) engine to identify key keywords.

[0905] Emotion recognition by emotion engine

[0906] The device uses an emotion engine to analyze the user's facial expressions and tone of voice.

[0907] The emotion engine determines the user's emotional state based on the analysis results and generates emotion labels such as "fun" or "excited."

[0908] Running the generate operation

[0909] The server issues generation instructions to the text generation AI, image generation AI, and voice generation AI.

[0910] The text generation AI generates the city's history and backstories for the main characters.

[0911] Image generation AI generates visuals of city buildings, landscapes, and characters.

[0912] The voice generation AI generates the city's environmental sounds and character dialogue.

[0913] Integration of each element

[0914] The server integrates the generated scenario, visual and audio data, and uses a DBMS to organize the data into a consistent format.

[0915] Adjusting according to emotional state

[0916] The server adjusts the elements of the generated virtual space based on the emotional data obtained from the emotion engine. For example, if the user is feeling relaxed, it will change the colors and music to calmer ones.

[0917] Sending and displaying consolidated data

[0918] The server sends the adjusted virtual space data to the terminal.

[0919] The device displays a virtual space to the user, allowing them to explore a city using VR goggles, for example.

[0920] User Experience and Feedback

[0921] The user explores the generated virtual space and provides feedback on their experience.

[0922] The device sends feedback to the server, which is analyzed and used to improve future generation operations.

[0923] Specific examples

[0924] If the user enters the prompt "Generate a city centered around an ancient Egyptian pyramid," the system will:

[0925] 1. The user enters a prompt and the terminal sends a request to the server.

[0926] 2. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[0927] 3. The device uses an emotion engine to analyze the user's emotional state.

[0928] 4. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[0929] 5. Each AI generates its own element.

[0930] 6. The server integrates all components to create virtual space data and adjusts it based on data from the emotion engine.

[0931] 7. The server sends the integrated data to the device, which displays it to the user, who then explores the pyramid city through the VR goggles.

[0932] 8. The user enters feedback and the device sends it to the server.

[0933] 9. The server analyzes the feedback and provides it to the generation AI to help improve the quality of future generation.

[0934] In this way, the system of the present invention can generate highly customized virtual spaces and continuously improve their quality based on the user's emotional state and feedback.

[0935] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0936] Step 1: Receiving a user request

[0937] The user inputs a specific request for generating a virtual space into the terminal, for example, a prompt sentence such as "Please generate a medieval fantasy town."

[0938] The terminal sends the input request to the server using an HTTP POST request, and sends the prompt received from the user to the server.

[0939] Input: The prompt text entered by the user.

[0940] Output: Sends a request to the server.

[0941] Step 2: Parsing the request

[0942] The server analyzes the request received from the terminal. First, it parses the received data and checks its contents.

[0943] The server analyzes the request and identifies the required generation operations (scenario generation, visual generation, audio generation). A natural language processing (NLP) engine is used for the analysis to extract key keywords. For example, keywords such as "medieval fantasy," "town," and "generation" are extracted.

[0944] Input: The prompt text sent to the server.

[0945] Output: A list of the required generation operations.

[0946] Step 3: Emotion recognition by the emotion engine

[0947] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, and captures the user's facial expressions and voice through the built-in camera and microphone.

[0948] The emotion engine analyzes the captured data and determines the user's emotion using a machine learning model (e.g., a CNN model for emotion recognition).

[0949] Input: User facial and voice capture data.

[0950] Output: The user's emotional state (happy, excited, relaxed, etc.).

[0951] Step 4: Run the generate operation

[0952] The server issues instructions to the text generation AI, image generation AI, and voice generation AI to generate each element.

[0953] The text generation AI generates a scenario based on the request, such as the history of the town, the backstories of the main characters, and events that occur in the town.

[0954] Image generation AI generates visual elements based on requests, such as city buildings, landscapes, and character designs.

[0955] The voice generation AI generates audio elements based on requests, such as city ambient sounds and character dialogue.

[0956] Input: Request parsing results.

[0957] Output: Generated scenarios, visuals, and audio data.

[0958] Step 5: Putting the Components Together

[0959] The server integrates the generated scenario, visual, and audio data, and uses a DBMS to organize the data into a consistent format, for example, to create a unified design and background story, linking the entire virtual space.

[0960] Input: Generated scenario, visual and audio data.

[0961] Output: Integrated virtual space data.

[0962] Step 6: Adjust according to your emotional state

[0963] The server adjusts the virtual space based on the emotional data it obtains from the emotion engine. For example, if the user is feeling relaxed, it will change the background music to a calmer one and use a more subdued color scheme.

[0964] Input: Integrated virtual space data, user emotional state.

[0965] Output: Calibrated virtual space data.

[0966] Step 7: Send and view integrated data

[0967] The server sends the adjusted virtual space data to the device, using the WebSocket communication protocol for real-time data transfer.

[0968] The device displays a virtual space to the user based on the data received, allowing the user to explore a city using VR goggles, for example.

[0969] Input: Calibrated virtual space data.

[0970] Output: A display of the virtual space.

[0971] Step 8: User experience and feedback

[0972] Users explore generated virtual spaces and enjoy experiences, such as walking around a medieval fantasy town and interacting with its inhabitants.

[0973] The user enters feedback about their experience into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[0974] The device sends feedback data to the server in JSON format.

[0975] Input: User feedback.

[0976] Output: Send feedback to the server.

[0977] Step 9: Processing feedback and training the AI

[0978] The server receives the feedback and analyzes it. For example, it uses a text analysis engine to extract content such as "background noise is too loud."

[0979] The generation AI uses the feedback to learn and improve its next generation operation, for example by improving the background sound volume adjustment algorithm.

[0980] Input: User feedback.

[0981] Output: Improved generation algorithm.

[0982] (Application example 2)

[0983] 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."

[0984] Current virtual space generation technology faces challenges, such as inconsistent quality of content and user experience generated automatically based on user requests, particularly difficulty in flexibly adjusting content in response to user emotions and feedback. Furthermore, the generated virtual space may not be optimized for the user's emotional state, potentially resulting in reduced user satisfaction. Furthermore, insufficient analysis of feedback can make future improvements difficult.

[0985] 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.

[0986] In this invention, the server includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for analyzing a user's evaluation and providing feedback for improving the generation operation, a means for performing emotion recognition, and a means for adjusting the integrated components according to the user's emotional state. This not only enables the generation of a high-quality virtual space based on the user's generation request, but also improves user satisfaction by customizing the virtual space according to the user's emotional state. Furthermore, by analyzing user feedback, the accuracy and quality of the generation operation are continuously improved.

[0987] A "generation request" is a request from a user to generate a virtual space.

[0988] A "predetermined task" is a series of production operations that are specified based on a production request.

[0989] "Generation operations" refers to the various generation processes that are carried out to construct a virtual space.

[0990] "Components" refer to elements such as scenarios, visuals, and sounds that are generated to form a virtual space.

[0991] "User terminal" means the device used by a user to receive and experience a virtual space.

[0992] "Evaluation" refers to the feedback and reviews that users give about the virtual space they have experienced.

[0993] "Emotion recognition" is the process of identifying a user's emotional state from their facial expressions, vocal tone, behavior, etc.

[0994] "Emotional state" refers to the user's current emotional state, such as happy, excited, calm, etc.

[0995] The "means for analyzing user evaluations and providing feedback to improve the generation operation" refers to a means for collecting and analyzing evaluations from users to help improve the quality of the generation operation from the next time onwards.

[0996] System Program

[0997] The system of the present invention includes a series of processes, including analyzing a generation request, performing multiple generation operations, integrating the generated components, and transmitting the components to a user terminal. It also has the function of performing emotion recognition and adjusting the components according to the user's emotional state. The following describes specific means for realizing this application example.

[0998] System configuration

[0999] Hardware and software used

[1000] 1. Hardware

[1001] User device: A device used by a user, such as smart glasses or a head-mounted display.

[1002] Server: A back-end server for generating operations and data processing.

[1003] 2. Software

[1004] Emotion Recognition Engine (EmotionEngine): An engine that analyzes a user's facial expressions, tone of voice, and behavior to identify their emotional state.

[1005] Virtual Space Generator: An engine that integrates generated scenarios, visuals, and sounds to generate virtual spaces.

[1006] Text generation AI (e.g., OpenAI GPT-3): An AI model for generating scenarios and stories.

[1007] Image generation AI (e.g., DeepDream): An AI model for generating visual elements of virtual spaces.

[1008] Audio generation AI: An AI model for generating acoustic elements in virtual spaces.

[1009] Program processing

[1010] Natural language explanations

[1011] After receiving a generation request from the user, the server analyzes it and performs multiple generation operations using text generation AI, image generation AI, and voice generation AI. The generated scenario, visuals, and audio are integrated by the virtual space generation engine to create consistent virtual space data.

[1012] The system then uses an emotion recognition engine to identify the user's emotional state and adjusts the colors, music, and other aspects of the virtual space based on that data, creating a personalized virtual space that reflects the user's emotional state.

[1013] Finally, the generated virtual space data is sent to the user's device, where the user experiences the virtual space through smart glasses or a head-mounted display. The user provides evaluations and feedback on the virtual space they experienced, which is then sent back to the server to help improve the quality of future generation operations.

[1014] Examples of concrete examples and prompts

[1015] Examples:

[1016] The user inputs a request such as "Show me clothes from the summer collection." Based on this request, the system generates products from the summer collection in a virtual store and uses an emotion recognition engine to identify the user's emotional state. The atmosphere and presentation of the virtual store are then adjusted to match the user's emotions, and the store is presented to the user through smart glasses.

[1017] Example prompt sentence:

[1018] "User request: Show me clothes from the summer collection"

[1019] "User's emotional state: excited"

[1020] In this way, the system of the present invention can provide a high-quality virtual space that responds to the user's emotions, achieving a highly satisfying experience.

[1021] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1022] Step 1:

[1023] The user enters a generation request.

[1024] The user inputs a generation request, for example, "Show me the clothes from the summer collection," through smart glasses or a head-mounted display, and the terminal sends this generation request to the server.

[1025] Step 2:

[1026] The server parses the create request.

[1027] The server analyzes the input generation request and extracts the data necessary for the generation operation (text generation, image generation, voice generation). Specifically, it generates prompts for the text generation AI, image generation AI, and voice generation AI.

[1028] Step 3:

[1029] The server performs the text generation operation.

[1030] The server instructs the text generation AI to create a scenario based on the generation request. The input is a prompt sentence, which the text generation AI processes and calculates to output a scenario such as a description of the clothing or a product story.

[1031] Step 4:

[1032] The server performs the image generation operation.

[1033] The server instructs the image generation AI to create visuals based on the generation request. The input is the output of the text generation AI and the generation request itself, and the image generation AI processes and calculates it to output images of clothing designs and the exterior of a virtual store.

[1034] Step 5:

[1035] The server performs the audio generation operations.

[1036] The server instructs the voice generation AI to create audio based on the generation request. The input is the output of the text generation AI and the generation request itself, and the voice generation AI processes and calculates it to output audio elements such as background sounds and narration.

[1037] Step 6:

[1038] The server performs emotion recognition.

[1039] The device collects the user's facial expressions, voice tone, and behavior, and sends them to an emotion recognition engine, which analyzes this data as input and outputs the user's emotional state (e.g., excited, relaxed, etc.).

[1040] Step 7:

[1041] The server integrates the generated components.

[1042] The server uses the outputs from the text generation AI, image generation AI, and voice generation AI to integrate each component in a virtual space generation engine and generate a unified virtual space.

[1043] Step 8:

[1044] The server adjusts based on the emotional state.

[1045] Based on the emotional state data obtained from the emotion recognition engine, the server adjusts each element of the virtual space (color, music, visual effects, etc.) to match the user's emotional state.

[1046] Step 9:

[1047] The server sends the integrated and adjusted virtual space data to the terminal.

[1048] The server transmits the completed virtual space data to the user's terminal, which displays it, providing the user with a virtual shopping experience.

[1049] Step 10:

[1050] The user enters feedback.

[1051] The user inputs their evaluation and feedback on the virtual space they experienced into the terminal, which then transmits this information to the server.

[1052] Step 11:

[1053] The server analyzes the feedback and improves the AI ​​model.

[1054] The server analyzes the feedback received from users and feeds that data back into the generative AI model to improve the quality of future generations.

[1055] In this way, users can enjoy a high-quality virtual shopping experience that is emotionally customized.

[1056] 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.

[1057] 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.

[1058] 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.

[1059] [Third embodiment]

[1060] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1061] 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.

[1062] 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).

[1063] 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.

[1064] 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.

[1065] 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).

[1066] 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.

[1067] 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.

[1068] 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.

[1069] 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.

[1070] 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.

[1071] 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."

[1072] The system of the present invention includes a process for analyzing a generation request, performing multiple generation operations, integrating the generated components, and sending the components to a user terminal. The following is a description of a specific embodiment.

[1073] overview

[1074] In this invention, we have constructed a system that receives a user's request (generation request) for the generation of a virtual space, analyzes it, and then executes multiple generation operations to generate components (scenario, visuals, audio, etc.), integrating them and providing them to the user. In addition, we collect user ratings and feedback, analyze them, and feed them back to the generation AI to improve the accuracy and quality of future generation operations.

[1075] Detailed embodiment

[1076] 1. Receiving a User Request

[1077] User: The user requests the creation of a virtual space. For example, the user inputs a request such as "Please create a medieval fantasy town" into the device.

[1078] Terminal: Receives requests typed by the user and sends them to the server.

[1079] 2. Parsing the Request

[1080] Server: Analyzes the generation request received from the device and identifies the required generation operations. For example, from the request for a "medieval fantasy town," it determines that the town's scenario, visuals, and audio must be generated.

[1081] 3. Performing the Generate Operation

[1082] Server: Instructs the text generation AI, image generation AI, and voice generation AI to generate each element.

[1083] Text generation AI: Generates scenarios such as the city's history, backstories of main characters, and events that occur in the city.

[1084] Image generation AI: Generates visual elements such as city buildings, landscapes, and character designs.

[1085] Voice generation AI: Generates city environmental sounds and character dialogue.

[1086] 4. Integration of Components

[1087] Server: Integrates the generated scenarios, visuals, and audio to create consistent virtual space data.

[1088] 5. Transmission and Display of Aggregated Data

[1089] Server: Sends the integrated virtual space data to the device.

[1090] Device: Displays a virtual space to the user based on the data received from the server. For example, the device allows the user to explore a city through VR goggles.

[1091] 6. User Experience and Feedback

[1092] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[1093] User: Enters their experience rating and feedback into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[1094] Device: Sends user feedback to the server.

[1095] 7. Feedback processing and AI training

[1096] Server: Analyzes the feedback received from the device and provides it as feedback data to the generation AI.

[1097] Generative AI: Learns from the feedback it receives to improve its generative process and generate better results in the future.

[1098] Specific examples

[1099] For example, if a user requests, "Generate a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[1100] 1. The user enters a request.

[1101] 2. The device sends a request to the server.

[1102] 3. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[1103] 4. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[1104] 5. Each AI generates its own elements.

[1105] 6. The server integrates all components and creates virtual space data.

[1106] 7. The server sends the integrated data to the device.

[1107] 8. The device displays the data to the user, who then explores the pyramid city through VR goggles.

[1108] 9. The user enters feedback into the device, which then sends it to the server.

[1109] 10. The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[1110] In this way, this system can efficiently generate and provide highly customizable virtual spaces that meet the diverse needs of users.

[1111] The processing flow will be explained below.

[1112] Step 1:

[1113] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[1114] Terminal: Sends the request entered by the user to the server.

[1115] Step 2:

[1116] Server: Analyzes the generation request received from the device, performs text analysis on the request content, and identifies the required generation operation (e.g., scenario generation, visual generation, audio generation).

[1117] Step 3:

[1118] Server: Issues instructions to the text generation AI to generate a scenario, including the town's setting and history, background information for the main characters, and events that will occur.

[1119] Text generation AI: Generates text data based on a specified scenario and sends it back to the server.

[1120] Step 4:

[1121] Server: Based on the scenario data received from the text generation AI, the server issues instructions to the image generation AI to generate visuals. These instructions include the design of city buildings, scenery, characters, etc.

[1122] Image generation AI: Generates appropriate visual elements based on scenario data and sends them back to the server.

[1123] Step 5:

[1124] Server: Based on the visual data received from the image generation AI, it issues instructions to the audio generation AI to generate sounds, including the city's ambient sounds and character dialogue.

[1125] Voice generation AI: Generates the necessary acoustic data based on a specified scenario and sends it back to the server.

[1126] Step 6:

[1127] Server: Integrates the generated scenario, visual, and audio data to create a consistent virtual space.

[1128] Step 7:

[1129] Server: Sends the integrated virtual space data to the device.

[1130] Step 8:

[1131] Device: Provides users with visual and auditory experiences based on the virtual space data received from the server. For example, it allows users to explore a city through VR goggles.

[1132] Step 9:

[1133] User: Enters their evaluation and feedback about the virtual space they experienced into the device. For example, they may say, "The building design is great, but the background noise is a little too loud."

[1134] Device: Sends user feedback to the server.

[1135] Step 10:

[1136] Server: Analyzes the feedback received from the device and provides the generated AI with data on areas that need improvement.

[1137] Generative AI: Based on the feedback received, it learns and improves the quality of its next generation operation.

[1138] By using the above steps, the system of the present invention can efficiently generate and provide a high-quality virtual space that meets the user's requirements.

[1139] Example 1

[1140] 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."

[1141] Conventional virtual space generation systems have difficulty generating and integrating individual elements (scenario, visuals, audio) consistently, making it difficult to provide a high-quality virtual experience that meets user demands. Furthermore, they lacked mechanisms for effectively incorporating user feedback and continuously improving the generation process. This resulted in inconsistent quality in the generated virtual spaces, leading to problems with reduced user satisfaction.

[1142] 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.

[1143] In this invention, the server includes means for analyzing a generation request and identifying a predetermined generation operation, means for executing multiple generation operations using a text generation AI, an image generation AI, and a voice generation AI, means for integrating the generated scenario, visual, and voice components, means for transmitting the integrated components to a user terminal, and means for collecting user experience evaluations and feedback and feeding them back to improve the generation AI model. This enables the generation of high-quality virtual spaces according to user requests and realizes continuous quality improvement.

[1144] A "generation request" is a request entered by a user wishing to create a specific virtual space.

[1145] "Analysis" refers to the process of decomposing an input production request and identifying the required production operations.

[1146] "Generation operations" refer to the procedures and means for generating the individual elements that make up a virtual space, such as text, images, and sounds.

[1147] "Text generation AI" is an artificial intelligence technology that generates text data such as scenarios and backstories based on requests entered by users.

[1148] "Image generation AI" is an artificial intelligence technology that generates visual elements such as buildings, landscapes, and characters in a virtual space in response to user requests.

[1149] "Voice generation AI" refers to artificial intelligence technology for generating background sounds and character dialogue used in virtual spaces.

[1150] "Components" refer to the individual data elements such as scenarios, visuals, and sounds that make up a virtual space.

[1151] "Synthesis" refers to the process of combining the individual generated components into a coherent virtual space.

[1152] "User device" means the device a user uses to request and experience a virtual space, such as a PC, smartphone, or VR goggles.

[1153] "Feedback" refers to evaluations and suggestions for improvement provided by users based on their experience in a virtual space.

[1154] A "generative AI model" is an overall artificial intelligence framework or methodology for performing text, image, and audio generation operations.

[1155] This invention is a system that generates a virtual space based on a user's generation request and provides the virtual space to the user. This system includes processes that analyze the generation request, perform multiple generation operations, integrate the generated components, and send them to the user's terminal. It also has a function that collects user feedback and reflects it in the generative AI model to continuously improve the generation process.

[1156] The system is mainly composed of the interaction between the server, terminals, and users. Below, we will explain each component of the system and its role.

[1157] Components and Roles

[1158] server

[1159] The server is the central control unit of this system. The server has the following roles:

[1160] Analysis of the generation request: The server has a special software module that receives and analyzes the generation request from the user. For example, if a user requests "Please generate a medieval fantasy town," the server analyzes it and identifies the required generation operations (scenario, visuals, audio).

[1161] Execution of generation operations: The server executes the necessary generation operations using text generation AI, image generation AI, and voice generation AI. Each AI module is responsible for generating a specific generation element (text, image, voice).

[1162] Text Generation AI: Generates text data. This AI creates city scenarios, character backstories, event details, etc.

[1163] Image generation AI: Generates image data. This AI creates visual elements such as city buildings, landscapes, and character designs.

[1164] Voice generation AI: Generates voice data. This AI creates the city's environmental sounds, character dialogue, and more.

[1165] Integration of components: The server integrates the scenario, visual, and audio data generated by each AI module to create a consistent virtual space.

[1166] Data transmission: The integrated virtual space data is transmitted to the user's terminal using a high-speed data transfer protocol.

[1167] Feedback processing: The server collects user feedback and feeds it back into the generative AI model. This feedback is used as data to improve the generation process in the future.

[1168] Terminal

[1169] A terminal is a device through which a user interacts with the system. It has the following functions:

[1170] Sending a request: The creation request entered by the user is sent to the server. For example, the user enters a request such as "Create an ancient Egyptian city centered around a pyramid."

[1171] Data display: The virtual space data sent from the server is displayed to the user. The terminal displays the virtual space using a device such as a VR goggle, smartphone, or PC.

[1172] Feedback collection: Users input ratings and suggestions for improvement based on their experience in the virtual space and send them to the server.

[1173] user

[1174] Users use the system to explore and experience virtual spaces.

[1175] Inputting a request: The user inputs a request for the creation of the desired virtual space into the terminal.

[1176] Explore the virtual space: Explore the generated virtual space and enjoy the experience.

[1177] Providing feedback: Provide feedback on the virtual space you have experienced.

[1178] Specific examples

[1179] For example, if a user enters the prompt "Create a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[1180] The user enters a prompt.

[1181] The terminal sends a prompt to the server.

[1182] The server parses the prompt statement and determines the required generation operation.

[1183] The server instructs the text generation AI to generate the scenario, the image generation AI to generate the visuals, and the voice generation AI to generate the voice.

[1184] Each generation AI generates elements.

[1185] The server integrates the generated elements to create virtual space data.

[1186] The server sends the integrated data to the terminal.

[1187] The device displays the data, and users explore the pyramid city with VR goggles.

[1188] The user enters feedback into the device, which then sends it to the server.

[1189] The server then applies the feedback to the generated AI model.

[1190] In this way, the system can generate and provide high-quality virtual spaces that meet the diverse needs of users. Furthermore, by continuously incorporating user feedback, the quality of the generation process can be improved.

[1191] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1192] Step 1: Receiving a user request

[1193] The user inputs a request to generate a virtual space into the device. For example, the user inputs the prompt "Please generate a medieval fantasy town."

[1194] The terminal receives a generation request from the user, converts it into JSON format, and sends it to the server. At this time, the input is the user's prompt, and the output is the JSON format data sent to the server.

[1195] Step 2: Parsing the request

[1196] The server parses the JSON data of the generation request received from the device. The input is the JSON formatted generation request data, and the server parses it to identify the necessary generation elements (scenario, visual, audio).

[1197] As a result of the analysis, the server determines that, for example, a request for a "medieval fantasy town" requires the generation of a town's scenario, visuals, and audio. The output is a list of elements to be generated as a result of the analysis.

[1198] Step 3: Specify the generation operation

[1199] The server instructs the text generation AI, image generation AI, and speech generation AI to generate each element. The input is a list of generated elements as the analysis result, and the output is the generation instruction sent to each generation AI.

[1200] The server instructs the text generation AI to generate the city's scenario (history, character backstories, events, etc.).

[1201] The server instructs the image generation AI to generate visual elements such as city buildings, scenery, and characters.

[1202] The server instructs the voice generation AI to generate the city's environmental sounds and character dialogue.

[1203] Step 4: Run the generate operation

[1204] Each generation AI generates each element based on the generation instructions received from the server. The input is the generation instructions from the server, and the output is the generated data (scenario, visuals, audio).

[1205] Text generation AI generates and outputs scenarios.

[1206] Image generation AI generates and outputs visual elements.

[1207] The voice generation AI generates and outputs voice data.

[1208] Step 5: Putting the Components Together

[1209] The server integrates the scenario, visual, and audio data received from each generation AI. The input is the generated data from each generation AI, and the server integrates them into a single virtual space data.

[1210] The server creates consistent virtual space data, and the output is integrated virtual space data.

[1211] Step 6: Send and view the integrated data

[1212] The server sends the integrated virtual space data to the terminal. The input is the integrated virtual space data, and the output is the data sent to the terminal.

[1213] The device analyzes the virtual space data received from the server and displays it to the user. Specifically, the device displays the virtual space to the user in real time using VR goggles. The input is the virtual space data from the server, and the output is the virtual space displayed to the user.

[1214] Step 7: User experience and feedback

[1215] Users explore generated virtual spaces and enjoy experiences, such as walking around a medieval fantasy town and interacting with its inhabitants.

[1216] The user inputs their experience evaluation and feedback into the device. The input is the user's feedback content, and the output is the feedback data input into the device.

[1217] The terminal sends the user's feedback to the server. The input is the feedback data entered into the terminal, and the output is the feedback data sent to the server.

[1218] Step 8: Processing feedback and training the AI

[1219] The server analyzes the feedback received from the device and reflects it in the generative AI model. The input is the user's feedback data, which the server analyzes and uses to improve the generative AI model.

[1220] The generative AI model learns from the feedback data and improves the generation process in the future, resulting in a higher quality virtual space the next time it is generated.

[1221] (Application example 1)

[1222] 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."

[1223] In today's digital society, there is a demand for efficient generation of virtual spaces and improved user experiences. However, with conventional technologies, the virtual space generation process is complex and time-consuming, making it difficult to provide an integrated and consistent virtual experience. Furthermore, there was a lack of a mechanism for incorporating user feedback into the generation process, which hindered the improvement of the quality of the generation AI.

[1224] 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.

[1225] In this invention, the server includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for collecting feedback from the user and providing the feedback for improving the generation operations, and a means for generating and integrating visual, scenario, and audio elements to provide a virtual space. This enables the virtual space desired by the user to be generated quickly and consistently, improving the user experience. Furthermore, the collected feedback can be used to continuously improve the quality of the generation AI.

[1226] A "generation request" is a request in which the user specifies the details and elements of the virtual space they desire.

[1227] "Predetermined work" is a set of specific tasks that include the required creation operations, identified by analyzing the creation request.

[1228] "Generation operations" are processes for creating components of virtual space, such as text generation, image generation, and sound generation.

[1229] "Visuals" refers to visual elements in a virtual space, such as images and designs of buildings, characters, landscapes, etc.

[1230] "Scenario" refers to the content of the story or events that unfold within a virtual space, and includes text information and storylines to guide the user's experience.

[1231] "Audio" refers to auditory elements such as character dialogue, environmental sounds, and sound effects within the virtual space.

[1232] "User terminal" means a device used by a user to display and manipulate a virtual space, including a smartphone, smart glasses, or a head-mounted display.

[1233] "Feedback" refers to the evaluations and comments provided by users after experiencing a virtual space, and is information that is used to improve the quality of the generation operation.

[1234] An "integrated component" is a set of visuals, scenarios, and sounds created through generative operations that come together to form a coherent virtual space.

[1235] A "virtual space" is an imaginary space or world that users can experience interactively within a digital environment.

[1236] The present invention relates to a system for generating a virtual space based on a user request, which includes a means for analyzing the generation request and identifying a predetermined task, a means for performing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for collecting feedback from the user and providing the feedback for improving the generation operations, and a means for generating and integrating visual, scenario, and audio elements to provide the virtual space.

[1237] 1. Basic configuration

[1238] The system mainly consists of the following hardware and software:

[1239] Hardware: Smartphones, smart glasses, head-mounted displays

[1240] software:

[1241] OpenAI API library: for using generative AI (text, image, audio)

[1242] PIL (Python Imaging Library): Displaying images

[1243] pyttsx3: Audio playback

[1244] pydub: Audio data processing

[1245] 2. Overview of the processing flow

[1246] a. Receiving User Requests

[1247] The user requests the creation of a virtual space. For example, they input a request such as "Please create a virtual store specializing in high-end jewelry." This request is then sent from the device to the server.

[1248] b. Request Parsing

[1249] The server analyzes the request and determines the necessary operations. Specifically, it determines that the request for a "virtual store specializing in luxury jewelry" requires the creation of a store scenario, visuals, and audio.

[1250] c. Performing the generate operation

[1251] The server instructs the generation AI to generate each element.

[1252] Text generation AI: Generates store scenarios and stories.

[1253] Image generation AI: Generates store designs and product images.

[1254] Voice generation AI: Generates environmental sounds within the store and character dialogue.

[1255] d. Integration of Components

[1256] The server integrates the generated scenarios, visuals, and audio to create a consistent virtual space data, which is then sent to the user's device, where it is displayed.

[1257] Users can explore generated virtual spaces and enjoy experiences, such as walking around a virtual store specializing in high-end jewelry and interacting with elven characters.

[1258] Specific examples

[1259] If a user requests a medieval jewelry shop with elves selling ornaments, the system will:

[1260] The user enters a request.

[1261] The device sends a request to the server.

[1262] The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[1263] The server instructs the text generation AI to create the store scenario, the image generation AI to create the store design, and the voice generation AI to create environmental sounds.

[1264] Each AI generates its own elements.

[1265] The server integrates all the components and creates virtual space data.

[1266] The server sends the integrated data to the terminal.

[1267] The device displays the data to the user, who then explores the virtual store.

[1268] The user enters feedback into the device, which then sends it to the server.

[1269] The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[1270] Example prompt sentences to use

[1271] Create a medieval-style jewelry shop where elves sell decorative items. Provide the story, visuals, and audio for the shop.

[1272] In this way, it is possible to efficiently generate and provide highly customizable virtual spaces that can adapt to the diverse needs of users.

[1273] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1274] Step 1:

[1275] A user requests the creation of a virtual space. Specifically, the user inputs a request for creation, such as "Please create a virtual store specializing in luxury jewelry," using a smartphone or other device. The input request for creation is sent from the device to the server for processing in the next step.

[1276] Input: User's creation request (e.g., "Create a virtual store specializing in high-end jewelry")

[1277] Output: The generation request is sent to the server

[1278] Step 2:

[1279] The server analyzes the generation request received from the device. Specifically, it uses a text analysis algorithm to identify keywords and necessary components in the request. This analysis determines which generation operation (text generation, image generation, or audio generation) is required.

[1280] Input: Text data of the generation request

[1281] Output: Information about the required generation operations (scenario generation, visual generation, audio generation)

[1282] Step 3:

[1283] The server issues instructions to each generative AI model to execute the generation operations. Specifically, using OpenAI's API, it requests the text generation AI to generate the store scenario, the image generation AI to generate the store design, and the voice generation AI to generate the store's environmental sounds and character dialogue.

[1284] Input: Information about the generation operation, prompt

[1285] Output: Scenarios, visuals, and audio data generated by each generative AI model

[1286] Step 4:

[1287] The server integrates the generated scenarios, visuals, and audio. Specifically, it combines each generated data into a consistent virtual space data, which includes data format conversion and adjustment, and data association.

[1288] Input: Generated scenario, visual and audio data

[1289] Output: Integrated virtual space data

[1290] Step 5:

[1291] The server transmits the integrated virtual space data to the user's device. Specifically, it uses a data transfer protocol to deliver the virtual space data quickly and securely to the device. The device interprets the received data and provides the user with a visual and auditory virtual space experience.

[1292] Input: Integrated virtual space data

[1293] Output: The virtual space is displayed on the user's device.

[1294] Step 6:

[1295] Users can explore the generated virtual space and enjoy the experience, for example, walking around a virtual store specializing in high-end jewelry, checking out the products, and interacting with the characters.

[1296] Input: Virtual space experience (user operation and interaction)

[1297] Output: User experience and feedback

[1298] Step 7:

[1299] Users provide feedback about their experiences by entering ratings and comments on their devices, which are then sent to the server, which analyzes the feedback and uses it to improve the generation process.

[1300] Input: User feedback (text data)

[1301] Output: Feedback data for improvement

[1302] 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.

[1303] The system of the present invention includes a process for analyzing a generation request, performing multiple generation operations, integrating the generated components, and transmitting the integrated components to a user terminal. Furthermore, by combining an emotion engine that recognizes the user's emotions, the system can provide a customized virtual space according to the user's emotional state. The following is a description of a specific embodiment of the present invention.

[1304] overview

[1305] This invention receives a request (generation request) for the creation of a user's desired virtual space, analyzes it, and then executes multiple generation operations to generate components (scenario, visuals, audio, etc.), integrating them and providing them to the user. It also uses an emotion engine to recognize the user's emotions and adjust the created virtual space according to their emotional state. Furthermore, it collects user ratings and feedback, analyzes them, and feeds them back to the generation AI to improve the accuracy and quality of future generation operations.

[1306] Detailed embodiment

[1307] 1. Receiving a User Request

[1308] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[1309] Terminal: Sends the request entered by the user to the server.

[1310] 2. Parsing the Request

[1311] Server: Analyzes the generation request received from the device and identifies the required generation operations (e.g., scenario generation, visual generation, audio generation).

[1312] 3. Emotion Recognition by Emotion Engine

[1313] On the device: Uses an emotion engine to analyze the user's facial expressions, voice tone, and behavior to recognize the user's emotional state.

[1314] Emotion engine: Determines the user's emotional state (e.g., happy, excited, calm) based on the data obtained.

[1315] 4. Performing the Generate Operation

[1316] Server: Instructs the text generation AI, image generation AI, and voice generation AI to generate each element.

[1317] Text generation AI: Generates scenarios such as the city's history, backstories of main characters, and events that occur in the city.

[1318] Image generation AI: Generates visual elements such as city buildings, landscapes, and character designs.

[1319] Voice generation AI: Generates city environmental sounds and character dialogue.

[1320] 5. Integration of Components

[1321] Server: Integrates the generated scenario, visual, and audio data to create consistent virtual space data.

[1322] 6. Adjusting to your emotional state

[1323] Server: Adjusts elements of the virtual space (e.g., colors, music, and environment) based on the user's emotional state obtained from the emotion engine. For example, if the user is determined to be relaxed, the colors and music will be changed to calmer ones.

[1324] 7. Transmission and Display of Aggregated Data

[1325] Server: The server transmits the integrated virtual space data, adjusted according to the user's emotional state, to the device.

[1326] Device: Provides users with visual, auditory, and other experiences based on the virtual space data received from the server. For example, the device allows users to explore a city through VR goggles.

[1327] 8. User Experience and Feedback

[1328] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[1329] User: Enters their experience rating and feedback into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[1330] Device: Sends user feedback to the server.

[1331] 9. Feedback processing and AI training

[1332] Server: Analyzes the feedback received from the device and provides the generated AI with data on areas that need improvement.

[1333] Generative AI: Based on the feedback received, it learns and improves the quality of the next generation operation.

[1334] Specific examples

[1335] For example, if a user requests, "Generate a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[1336] 1. The user enters a request.

[1337] 2. The device sends a request to the server.

[1338] 3. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[1339] 4. The device uses an emotion engine to recognize the user's emotions.

[1340] 5. The emotion engine determines the user's emotional state and sends it to the server.

[1341] 6. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[1342] 7. Each AI generates its own elements.

[1343] 8. The server integrates all components and creates virtual space data.

[1344] 9. The server adjusts the virtual space based on data from the emotion engine.

[1345] 10. The server sends the integrated data to the device.

[1346] 11. The device displays the data to the user, who then explores the pyramid city through VR goggles.

[1347] 12. The user enters feedback into the device, which then sends it to the server.

[1348] 13. The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[1349] In this way, by combining the emotion engine, this system can efficiently generate and provide a highly customized virtual space that corresponds to the user's emotional state.

[1350] The processing flow will be explained below.

[1351] Step 1:

[1352] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[1353] Terminal: Sends the request entered by the user to the server.

[1354] Step 2:

[1355] Server: Analyzes the generation request received from the device, performs text analysis on the request content, and identifies the required generation operation (e.g., scenario generation, visual generation, audio generation).

[1356] Step 3:

[1357] On the device: Uses an emotion engine to recognize the user's emotional state by analyzing their facial expressions, voice tone, and behavior in real time.

[1358] Emotion engine: Determines the user's emotions (e.g., happy, relaxed, excited) based on facial expressions, vocal tone, and behavioral data such as excitement and calm.

[1359] Step 4:

[1360] Emotion engine: Sends data indicating the user's emotional state to the server.

[1361] Step 5:

[1362] Server: Issues instructions to the text generation AI to generate a scenario, including the town's setting and history, background information for the main characters, and events that will occur.

[1363] Text generation AI: Generates text data based on a specified scenario and sends it back to the server.

[1364] Step 6:

[1365] Server: Based on the scenario data received from the text generation AI, the server issues instructions to the image generation AI to generate visuals. These instructions include the design of city buildings, scenery, characters, etc.

[1366] Image generation AI: Generates appropriate visual elements based on scenario data and sends them back to the server.

[1367] Step 7:

[1368] Server: Based on the visual data received from the image generation AI, it issues instructions to the sound generation AI to generate sounds, including the city's ambient sounds and character dialogue.

[1369] Voice generation AI: Generates the necessary acoustic data based on a specified scenario and sends it back to the server.

[1370] Step 8:

[1371] Server: Integrates the generated scenario, visual, and audio data to create a consistent virtual space.

[1372] Step 9:

[1373] Server: Adjusts elements of the virtual space (e.g., colors, music, and environmental settings) based on the user's emotional state data obtained from the emotion engine. For example, if the user is in a relaxed state, soften the colors and change the background music to a calmer one.

[1374] Step 10:

[1375] Server: The server transmits the integrated virtual space data, adjusted according to the user's emotional state, to the device.

[1376] Step 11:

[1377] Device: Provides users with visual, auditory, and other experiences based on the virtual space data received from the server. For example, the device allows users to explore a city through VR goggles.

[1378] Step 12:

[1379] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[1380] Step 13:

[1381] User: Enters their experience rating and feedback into the device, for example, "The building design is great, but the background noise is a bit too loud."

[1382] Terminal: Sends user-entered feedback to the server.

[1383] Step 14:

[1384] Server: Analyzes the feedback received from the device and provides it as data on areas for improvement to the generative AI and emotion engine.

[1385] Generative AI: Based on the received feedback data, it learns to help with the next generation operation and aims to improve quality.

[1386] Emotion Engine: Improves the user emotion recognition algorithm based on feedback data, improving recognition accuracy.

[1387] Through the above steps, the system of the present invention can efficiently generate and provide a high-quality, customized virtual space that meets the user's requirements and emotional state.

[1388] Example 2

[1389] 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."

[1390] Conventional virtual space generation systems provide virtual spaces by generating and integrating components based on user requests, but they have the problem of making it difficult to increase user satisfaction because they do not adjust according to the user's emotional state.Furthermore, there is also the problem of not providing appropriate feedback based on evaluations of the generated virtual space, which makes continuous quality improvement insufficient.

[1391] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1392] In this invention, the server includes means for analyzing the generation request and identifying a predetermined task, means for executing a plurality of generation operations, means for integrating the generated components, means for transmitting the integrated components to the user terminal, means for analyzing the user's evaluation and providing feedback for improving the generation operations, means for recognizing the user's emotional state, and means for adjusting the components according to the emotional state, thereby enabling the provision of a virtual space according to the user's emotional state and continuous quality improvement based on the user's evaluation.

[1393] A "generation request" is a specific request that a user inputs to request the generation of a virtual space.

[1394] The "predetermined work" refers to the various operations and processes required to generate a virtual space, which are identified as a result of analyzing the generation request.

[1395] A "creation operation" is an operation or procedure for generating content such as text, images, or audio.

[1396] "Components" refer to the individual elements such as scenarios, visuals, and sounds that make up a virtual space.

[1397] "Synthesis" refers to the process of combining the components generated by individual generation operations into a coherent virtual space data set.

[1398] "User terminal" refers to the device that a user uses to experience a virtual space, and specifically includes a PC, smartphone, VR goggles, etc.

[1399] An "emotion engine" is a technology or algorithm that analyzes a user's facial expressions, tone of voice, behavior, etc. to determine their emotional state.

[1400] "Feedback" refers to the evaluations and opinions that users give about their virtual space experiences, and is information that is used to improve and optimize the system.

[1401] A "text generation operation" is an operation that generates a sentence or scenario based on a specific prompt.

[1402] An "image generation operation" is an operation that generates visual content based on a particular prompt.

[1403] An "audio generation operation" is an operation that generates audio content based on a particular prompt.

[1404] "Tuning" refers to the process of optimizing each element of the generated virtual space based on the user's emotional state as determined by the emotion engine.

[1405] "Analysis" is the process of extracting and understanding specific information from input data.

[1406] The present invention is a system that generates a virtual space based on a user's request, integrates its components, and provides the virtual space to the user. This system also has the ability to recognize the user's emotional state and adjust the generated virtual space accordingly. Specific embodiments of this system are described below.

[1407] Hardware and software used

[1408] Hardware

[1409] Server: Parses requests, directs production operations, integrates the generated data, and coordinates with the emotion engine.

[1410] Terminal: The device used by the user, including PCs, smartphones, VR goggles, etc.

[1411] software

[1412] Generative AI models: Includes text generation AI, image generation AI, and speech generation AI, and performs each generation operation.

[1413] Emotion engine: Software that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state.

[1414] Database Management System (DBMS): A system for storing and integrating generated data in a consistent format.

[1415] Process Overview

[1416] Receiving and sending user requests

[1417] The user inputs a specific request for generating a virtual space. For example, the user inputs a prompt statement such as "Please generate a medieval fantasy town."

[1418] The device sends a request to the server, sending data using an HTTP POST request.

[1419] Parsing the request

[1420] The server analyzes the received request and extracts the information needed for the generation operation. It uses a natural language processing (NLP) engine to identify key keywords.

[1421] Emotion recognition by emotion engine

[1422] The device uses an emotion engine to analyze the user's facial expressions and tone of voice.

[1423] The emotion engine determines the user's emotional state based on the analysis results and generates emotion labels such as "fun" or "excited."

[1424] Running the generate operation

[1425] The server issues generation instructions to the text generation AI, image generation AI, and voice generation AI.

[1426] The text generation AI generates the city's history and backstories for the main characters.

[1427] Image generation AI generates visuals of city buildings, landscapes, and characters.

[1428] The voice generation AI generates the city's environmental sounds and character dialogue.

[1429] Integration of each element

[1430] The server integrates the generated scenario, visual and audio data, and uses a DBMS to organize the data into a consistent format.

[1431] Adjusting according to emotional state

[1432] The server adjusts the elements of the generated virtual space based on the emotional data obtained from the emotion engine. For example, if the user is feeling relaxed, it will change the colors and music to calmer ones.

[1433] Sending and displaying consolidated data

[1434] The server sends the adjusted virtual space data to the terminal.

[1435] The device displays a virtual space to the user, allowing them to explore a city using VR goggles, for example.

[1436] User Experience and Feedback

[1437] The user explores the generated virtual space and provides feedback on their experience.

[1438] The device sends feedback to the server, which is analyzed and used to improve future generation operations.

[1439] Specific examples

[1440] If the user enters the prompt "Generate a city centered around an ancient Egyptian pyramid," the system will:

[1441] 1. The user enters a prompt and the terminal sends a request to the server.

[1442] 2. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[1443] 3. The device uses an emotion engine to analyze the user's emotional state.

[1444] 4. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[1445] 5. Each AI generates its own element.

[1446] 6. The server integrates all components to create virtual space data and adjusts it based on data from the emotion engine.

[1447] 7. The server sends the integrated data to the device, which displays it to the user, who then explores the pyramid city through the VR goggles.

[1448] 8. The user enters feedback and the device sends it to the server.

[1449] 9. The server analyzes the feedback and provides it to the generation AI to help improve the quality of future generation.

[1450] In this way, the system of the present invention can generate highly customized virtual spaces and continuously improve their quality based on the user's emotional state and feedback.

[1451] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1452] Step 1: Receiving a user request

[1453] The user inputs a specific request for generating a virtual space into the terminal, for example, a prompt sentence such as "Please generate a medieval fantasy town."

[1454] The terminal sends the input request to the server using an HTTP POST request, and sends the prompt received from the user to the server.

[1455] Input: The prompt text entered by the user.

[1456] Output: Sends a request to the server.

[1457] Step 2: Parsing the request

[1458] The server analyzes the request received from the terminal. First, it parses the received data and checks its contents.

[1459] The server analyzes the request and identifies the required generation operations (scenario generation, visual generation, audio generation). A natural language processing (NLP) engine is used for the analysis to extract key keywords. For example, keywords such as "medieval fantasy," "town," and "generation" are extracted.

[1460] Input: The prompt text sent to the server.

[1461] Output: A list of the required generation operations.

[1462] Step 3: Emotion recognition by the emotion engine

[1463] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, and captures the user's facial expressions and voice through the built-in camera and microphone.

[1464] The emotion engine analyzes the captured data and determines the user's emotion using a machine learning model (e.g., a CNN model for emotion recognition).

[1465] Input: User facial and voice capture data.

[1466] Output: The user's emotional state (happy, excited, relaxed, etc.).

[1467] Step 4: Run the generate operation

[1468] The server issues instructions to the text generation AI, image generation AI, and voice generation AI to generate each element.

[1469] The text generation AI generates a scenario based on the request, such as the history of the town, the backstories of the main characters, and events that occur in the town.

[1470] Image generation AI generates visual elements based on requests, such as city buildings, landscapes, and character designs.

[1471] The voice generation AI generates audio elements based on requests, such as city ambient sounds and character dialogue.

[1472] Input: Request parsing results.

[1473] Output: Generated scenarios, visuals, and audio data.

[1474] Step 5: Putting the Components Together

[1475] The server integrates the generated scenario, visual, and audio data, and uses a DBMS to organize the data into a consistent format, for example, to create a unified design and background story, linking the entire virtual space.

[1476] Input: Generated scenario, visual and audio data.

[1477] Output: Integrated virtual space data.

[1478] Step 6: Adjust according to your emotional state

[1479] The server adjusts the virtual space based on the emotional data it obtains from the emotion engine. For example, if the user is feeling relaxed, it will change the background music to a calmer one and use a more subdued color scheme.

[1480] Input: Integrated virtual space data, user emotional state.

[1481] Output: Calibrated virtual space data.

[1482] Step 7: Send and view integrated data

[1483] The server sends the adjusted virtual space data to the device, using the WebSocket communication protocol for real-time data transfer.

[1484] The device displays a virtual space to the user based on the data received, allowing the user to explore a city using VR goggles, for example.

[1485] Input: Calibrated virtual space data.

[1486] Output: A display of the virtual space.

[1487] Step 8: User experience and feedback

[1488] Users explore generated virtual spaces and enjoy experiences, such as walking around a medieval fantasy town and interacting with its inhabitants.

[1489] The user enters feedback about their experience into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[1490] The device sends feedback data to the server in JSON format.

[1491] Input: User feedback.

[1492] Output: Send feedback to the server.

[1493] Step 9: Processing feedback and training the AI

[1494] The server receives the feedback and analyzes it. For example, it uses a text analysis engine to extract content such as "background noise is too loud."

[1495] The generation AI uses the feedback to learn and improve its next generation operation, for example by improving the background sound volume adjustment algorithm.

[1496] Input: User feedback.

[1497] Output: Improved generation algorithm.

[1498] (Application example 2)

[1499] 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."

[1500] Current virtual space generation technology faces challenges, such as inconsistent quality of content and user experience generated automatically based on user requests, particularly difficulty in flexibly adjusting content in response to user emotions and feedback. Furthermore, the generated virtual space may not be optimized for the user's emotional state, potentially resulting in reduced user satisfaction. Furthermore, insufficient analysis of feedback can make future improvements difficult.

[1501] 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.

[1502] In this invention, the server includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for analyzing a user's evaluation and providing feedback for improving the generation operation, a means for performing emotion recognition, and a means for adjusting the integrated components according to the user's emotional state. This not only enables the generation of a high-quality virtual space based on the user's generation request, but also improves user satisfaction by customizing the virtual space according to the user's emotional state. Furthermore, by analyzing user feedback, the accuracy and quality of the generation operation are continuously improved.

[1503] A "generation request" is a request from a user to generate a virtual space.

[1504] A "predetermined task" is a series of production operations that are specified based on a production request.

[1505] "Generation operations" refers to the various generation processes that are carried out to construct a virtual space.

[1506] "Components" refer to elements such as scenarios, visuals, and sounds that are generated to form a virtual space.

[1507] "User terminal" means the device used by a user to receive and experience a virtual space.

[1508] "Evaluation" refers to the feedback and reviews that users give about the virtual space they have experienced.

[1509] "Emotion recognition" is the process of identifying a user's emotional state from their facial expressions, vocal tone, behavior, etc.

[1510] "Emotional state" refers to the user's current emotional state, such as happy, excited, calm, etc.

[1511] The "means for analyzing user evaluations and providing feedback to improve the generation operation" refers to a means for collecting and analyzing evaluations from users to help improve the quality of the generation operation from the next time onwards.

[1512] System Program

[1513] The system of the present invention includes a series of processes, including analyzing a generation request, performing multiple generation operations, integrating the generated components, and transmitting the components to a user terminal. It also has the function of performing emotion recognition and adjusting the components according to the user's emotional state. The following describes specific means for realizing this application example.

[1514] System configuration

[1515] Hardware and software used

[1516] 1. Hardware

[1517] User device: A device used by a user, such as smart glasses or a head-mounted display.

[1518] Server: A back-end server for generating operations and data processing.

[1519] 2. Software

[1520] Emotion Recognition Engine (EmotionEngine): An engine that analyzes a user's facial expressions, tone of voice, and behavior to identify their emotional state.

[1521] Virtual Space Generator: An engine that integrates generated scenarios, visuals, and sounds to generate virtual spaces.

[1522] Text generation AI (e.g., OpenAI GPT-3): An AI model for generating scenarios and stories.

[1523] Image generation AI (e.g., DeepDream): An AI model for generating visual elements of virtual spaces.

[1524] Audio generation AI: An AI model for generating acoustic elements in virtual spaces.

[1525] Program processing

[1526] Natural language explanations

[1527] After receiving a generation request from the user, the server analyzes it and performs multiple generation operations using text generation AI, image generation AI, and voice generation AI. The generated scenario, visuals, and audio are integrated by the virtual space generation engine to create consistent virtual space data.

[1528] The system then uses an emotion recognition engine to identify the user's emotional state and adjusts the colors, music, and other aspects of the virtual space based on that data, creating a personalized virtual space that reflects the user's emotional state.

[1529] Finally, the generated virtual space data is sent to the user's device, where the user experiences the virtual space through smart glasses or a head-mounted display. The user provides evaluations and feedback on the virtual space they experienced, which is then sent back to the server to help improve the quality of future generation operations.

[1530] Examples of concrete examples and prompts

[1531] Examples:

[1532] The user inputs a request such as "Show me clothes from the summer collection." Based on this request, the system generates products from the summer collection in a virtual store and uses an emotion recognition engine to identify the user's emotional state. The atmosphere and presentation of the virtual store are then adjusted to match the user's emotions, and the store is presented to the user through smart glasses.

[1533] Example prompt sentence:

[1534] "User request: Show me clothes from the summer collection"

[1535] "User's emotional state: excited"

[1536] In this way, the system of the present invention can provide a high-quality virtual space that responds to the user's emotions, achieving a highly satisfying experience.

[1537] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1538] Step 1:

[1539] The user enters a generation request.

[1540] The user inputs a generation request, for example, "Show me the clothes from the summer collection," through smart glasses or a head-mounted display, and the terminal sends this generation request to the server.

[1541] Step 2:

[1542] The server parses the create request.

[1543] The server analyzes the input generation request and extracts the data necessary for the generation operation (text generation, image generation, voice generation). Specifically, it generates prompts for the text generation AI, image generation AI, and voice generation AI.

[1544] Step 3:

[1545] The server performs the text generation operation.

[1546] The server instructs the text generation AI to create a scenario based on the generation request. The input is a prompt sentence, which the text generation AI processes and calculates to output a scenario such as a description of the clothing or a product story.

[1547] Step 4:

[1548] The server performs the image generation operation.

[1549] The server instructs the image generation AI to create visuals based on the generation request. The input is the output of the text generation AI and the generation request itself, and the image generation AI processes and calculates it to output images of clothing designs and the exterior of a virtual store.

[1550] Step 5:

[1551] The server performs the audio generation operations.

[1552] The server instructs the voice generation AI to create audio based on the generation request. The input is the output of the text generation AI and the generation request itself, and the voice generation AI processes and calculates it to output audio elements such as background sounds and narration.

[1553] Step 6:

[1554] The server performs emotion recognition.

[1555] The device collects the user's facial expressions, voice tone, and behavior, and sends them to an emotion recognition engine, which analyzes this data as input and outputs the user's emotional state (e.g., excited, relaxed, etc.).

[1556] Step 7:

[1557] The server integrates the generated components.

[1558] The server uses the outputs from the text generation AI, image generation AI, and voice generation AI to integrate each component in a virtual space generation engine and generate a unified virtual space.

[1559] Step 8:

[1560] The server adjusts based on the emotional state.

[1561] Based on the emotional state data obtained from the emotion recognition engine, the server adjusts each element of the virtual space (color, music, visual effects, etc.) to match the user's emotional state.

[1562] Step 9:

[1563] The server sends the integrated and adjusted virtual space data to the terminal.

[1564] The server transmits the completed virtual space data to the user's terminal, which displays it, providing the user with a virtual shopping experience.

[1565] Step 10:

[1566] The user enters feedback.

[1567] The user inputs their evaluation and feedback on the virtual space they experienced into the terminal, which then transmits this information to the server.

[1568] Step 11:

[1569] The server analyzes the feedback and improves the AI ​​model.

[1570] The server analyzes the feedback received from users and feeds that data back into the generative AI model to improve the quality of future generations.

[1571] In this way, users can enjoy a high-quality virtual shopping experience that is emotionally customized.

[1572] 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.

[1573] 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.

[1574] 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.

[1575] [Fourth embodiment]

[1576] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1577] 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.

[1578] 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).

[1579] 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.

[1580] 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.

[1581] 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).

[1582] 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.

[1583] 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.

[1584] 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.

[1585] 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.

[1586] 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.

[1587] 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.

[1588] 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."

[1589] The system of the present invention includes a process for analyzing a generation request, performing multiple generation operations, integrating the generated components, and sending the components to a user terminal. The following is a description of a specific embodiment.

[1590] overview

[1591] In this invention, we have constructed a system that receives a user's request (generation request) for the generation of a virtual space, analyzes it, and then executes multiple generation operations to generate components (scenario, visuals, audio, etc.), integrating them and providing them to the user. In addition, we collect user ratings and feedback, analyze them, and feed them back to the generation AI to improve the accuracy and quality of future generation operations.

[1592] Detailed embodiment

[1593] 1. Receiving a User Request

[1594] User: The user requests the creation of a virtual space. For example, the user inputs a request such as "Please create a medieval fantasy town" into the device.

[1595] Terminal: Receives requests typed by the user and sends them to the server.

[1596] 2. Parsing the Request

[1597] Server: Analyzes the generation request received from the device and identifies the required generation operations. For example, from the request for a "medieval fantasy town," it determines that the town's scenario, visuals, and audio must be generated.

[1598] 3. Performing the Generate Operation

[1599] Server: Instructs the text generation AI, image generation AI, and voice generation AI to generate each element.

[1600] Text generation AI: Generates scenarios such as the city's history, backstories of main characters, and events that occur in the city.

[1601] Image generation AI: Generates visual elements such as city buildings, landscapes, and character designs.

[1602] Voice generation AI: Generates city environmental sounds and character dialogue.

[1603] 4. Integration of Components

[1604] Server: Integrates the generated scenarios, visuals, and audio to create consistent virtual space data.

[1605] 5. Transmission and Display of Aggregated Data

[1606] Server: Sends the integrated virtual space data to the device.

[1607] Device: Displays a virtual space to the user based on the data received from the server. For example, the device allows the user to explore a city through VR goggles.

[1608] 6. User Experience and Feedback

[1609] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[1610] User: Enters their experience rating and feedback into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[1611] Device: Sends user feedback to the server.

[1612] 7. Feedback processing and AI training

[1613] Server: Analyzes the feedback received from the device and provides it as feedback data to the generation AI.

[1614] Generative AI: Learns from the feedback it receives to improve its generative process and generate better results in the future.

[1615] Specific examples

[1616] For example, if a user requests, "Generate a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[1617] 1. The user enters a request.

[1618] 2. The device sends a request to the server.

[1619] 3. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[1620] 4. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[1621] 5. Each AI generates its own elements.

[1622] 6. The server integrates all components and creates virtual space data.

[1623] 7. The server sends the integrated data to the device.

[1624] 8. The device displays the data to the user, who then explores the pyramid city through VR goggles.

[1625] 9. The user enters feedback into the device, which then sends it to the server.

[1626] 10. The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[1627] In this way, this system can efficiently generate and provide highly customizable virtual spaces that meet the diverse needs of users.

[1628] The processing flow will be explained below.

[1629] Step 1:

[1630] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[1631] Terminal: Sends the request entered by the user to the server.

[1632] Step 2:

[1633] Server: Analyzes the generation request received from the device, performs text analysis on the request content, and identifies the required generation operation (e.g., scenario generation, visual generation, audio generation).

[1634] Step 3:

[1635] Server: Issues instructions to the text generation AI to generate a scenario, including the town's setting and history, background information for the main characters, and events that will occur.

[1636] Text generation AI: Generates text data based on a specified scenario and sends it back to the server.

[1637] Step 4:

[1638] Server: Based on the scenario data received from the text generation AI, the server issues instructions to the image generation AI to generate visuals. These instructions include the design of city buildings, scenery, characters, etc.

[1639] Image generation AI: Generates appropriate visual elements based on scenario data and sends them back to the server.

[1640] Step 5:

[1641] Server: Based on the visual data received from the image generation AI, it issues instructions to the audio generation AI to generate sounds, including the city's ambient sounds and character dialogue.

[1642] Voice generation AI: Generates the necessary acoustic data based on a specified scenario and sends it back to the server.

[1643] Step 6:

[1644] Server: Integrates the generated scenario, visual, and audio data to create a consistent virtual space.

[1645] Step 7:

[1646] Server: Sends the integrated virtual space data to the device.

[1647] Step 8:

[1648] Device: Provides users with visual and auditory experiences based on the virtual space data received from the server. For example, it allows users to explore a city through VR goggles.

[1649] Step 9:

[1650] User: Enters their evaluation and feedback about the virtual space they experienced into the device. For example, they may say, "The building design is great, but the background noise is a little too loud."

[1651] Device: Sends user feedback to the server.

[1652] Step 10:

[1653] Server: Analyzes the feedback received from the device and provides the generated AI with data on areas that need improvement.

[1654] Generative AI: Based on the feedback received, it learns and improves the quality of its next generation operation.

[1655] By using the above steps, the system of the present invention can efficiently generate and provide a high-quality virtual space that meets the user's requirements.

[1656] Example 1

[1657] 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."

[1658] Conventional virtual space generation systems have difficulty generating and integrating individual elements (scenario, visuals, audio) consistently, making it difficult to provide a high-quality virtual experience that meets user demands. Furthermore, they lacked mechanisms for effectively incorporating user feedback and continuously improving the generation process. This resulted in inconsistent quality in the generated virtual spaces, leading to problems with reduced user satisfaction.

[1659] 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.

[1660] In this invention, the server includes means for analyzing a generation request and identifying a predetermined generation operation, means for executing multiple generation operations using a text generation AI, an image generation AI, and a voice generation AI, means for integrating the generated scenario, visual, and voice components, means for transmitting the integrated components to a user terminal, and means for collecting user experience evaluations and feedback and feeding them back to improve the generation AI model. This enables the generation of high-quality virtual spaces according to user requests and realizes continuous quality improvement.

[1661] A "generation request" is a request entered by a user wishing to create a specific virtual space.

[1662] "Analysis" refers to the process of decomposing an input production request and identifying the required production operations.

[1663] "Generation operations" refer to the procedures and means for generating the individual elements that make up a virtual space, such as text, images, and sounds.

[1664] "Text generation AI" is an artificial intelligence technology that generates text data such as scenarios and backstories based on requests entered by users.

[1665] "Image generation AI" is an artificial intelligence technology that generates visual elements such as buildings, landscapes, and characters in a virtual space in response to user requests.

[1666] "Voice generation AI" refers to artificial intelligence technology for generating background sounds and character dialogue used in virtual spaces.

[1667] "Components" refer to the individual data elements such as scenarios, visuals, and sounds that make up a virtual space.

[1668] "Synthesis" refers to the process of combining the individual generated components into a coherent virtual space.

[1669] "User device" means the device a user uses to request and experience a virtual space, such as a PC, smartphone, or VR goggles.

[1670] "Feedback" refers to evaluations and suggestions for improvement provided by users based on their experience in a virtual space.

[1671] A "generative AI model" is an overall artificial intelligence framework or methodology for performing text, image, and audio generation operations.

[1672] This invention is a system that generates a virtual space based on a user's generation request and provides the virtual space to the user. This system includes processes that analyze the generation request, perform multiple generation operations, integrate the generated components, and send them to the user's terminal. It also has a function that collects user feedback and reflects it in the generative AI model to continuously improve the generation process.

[1673] The system is mainly composed of the interaction between the server, terminals, and users. Below, we will explain each component of the system and its role.

[1674] Components and Roles

[1675] server

[1676] The server is the central control unit of this system. The server has the following roles:

[1677] Analysis of the generation request: The server has a special software module that receives and analyzes the generation request from the user. For example, if a user requests "Please generate a medieval fantasy town," the server analyzes it and identifies the required generation operations (scenario, visuals, audio).

[1678] Execution of generation operations: The server executes the necessary generation operations using text generation AI, image generation AI, and voice generation AI. Each AI module is responsible for generating a specific generation element (text, image, voice).

[1679] Text Generation AI: Generates text data. This AI creates city scenarios, character backstories, event details, etc.

[1680] Image generation AI: Generates image data. This AI creates visual elements such as city buildings, landscapes, and character designs.

[1681] Voice generation AI: Generates voice data. This AI creates the city's environmental sounds, character dialogue, and more.

[1682] Integration of components: The server integrates the scenario, visual, and audio data generated by each AI module to create a consistent virtual space.

[1683] Data transmission: The integrated virtual space data is transmitted to the user's terminal using a high-speed data transfer protocol.

[1684] Feedback processing: The server collects user feedback and feeds it back into the generative AI model. This feedback is used as data to improve the generation process in the future.

[1685] Terminal

[1686] A terminal is a device through which a user interacts with the system. It has the following functions:

[1687] Sending a request: The creation request entered by the user is sent to the server. For example, the user enters a request such as "Create an ancient Egyptian city centered around a pyramid."

[1688] Data display: The virtual space data sent from the server is displayed to the user. The terminal displays the virtual space using a device such as a VR goggle, smartphone, or PC.

[1689] Feedback collection: Users input ratings and suggestions for improvement based on their experience in the virtual space and send them to the server.

[1690] user

[1691] Users use the system to explore and experience virtual spaces.

[1692] Inputting a request: The user inputs a request for the creation of the desired virtual space into the terminal.

[1693] Explore the virtual space: Explore the generated virtual space and enjoy the experience.

[1694] Providing feedback: Provide feedback on the virtual space you have experienced.

[1695] Specific examples

[1696] For example, if a user enters the prompt "Create a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[1697] The user enters a prompt.

[1698] The terminal sends a prompt to the server.

[1699] The server parses the prompt statement and determines the required generation operation.

[1700] The server instructs the text generation AI to generate the scenario, the image generation AI to generate the visuals, and the voice generation AI to generate the voice.

[1701] Each generation AI generates elements.

[1702] The server integrates the generated elements to create virtual space data.

[1703] The server sends the integrated data to the terminal.

[1704] The device displays the data, and users explore the pyramid city with VR goggles.

[1705] The user enters feedback into the device, which then sends it to the server.

[1706] The server then applies the feedback to the generated AI model.

[1707] In this way, the system can generate and provide high-quality virtual spaces that meet the diverse needs of users. Furthermore, by continuously incorporating user feedback, the quality of the generation process can be improved.

[1708] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1709] Step 1: Receiving a user request

[1710] The user inputs a request to generate a virtual space into the device. For example, the user inputs the prompt "Please generate a medieval fantasy town."

[1711] The terminal receives a generation request from the user, converts it into JSON format, and sends it to the server. At this time, the input is the user's prompt, and the output is the JSON format data sent to the server.

[1712] Step 2: Parsing the request

[1713] The server parses the JSON data of the generation request received from the device. The input is the JSON formatted generation request data, and the server parses it to identify the necessary generation elements (scenario, visual, audio).

[1714] As a result of the analysis, the server determines that, for example, a request for a "medieval fantasy town" requires the generation of a town's scenario, visuals, and audio. The output is a list of elements to be generated as a result of the analysis.

[1715] Step 3: Specify the generation operation

[1716] The server instructs the text generation AI, image generation AI, and speech generation AI to generate each element. The input is a list of generated elements as the analysis result, and the output is the generation instruction sent to each generation AI.

[1717] The server instructs the text generation AI to generate the city's scenario (history, character backstories, events, etc.).

[1718] The server instructs the image generation AI to generate visual elements such as city buildings, scenery, and characters.

[1719] The server instructs the voice generation AI to generate the city's environmental sounds and character dialogue.

[1720] Step 4: Run the generate operation

[1721] Each generation AI generates each element based on the generation instructions received from the server. The input is the generation instructions from the server, and the output is the generated data (scenario, visuals, audio).

[1722] Text generation AI generates and outputs scenarios.

[1723] Image generation AI generates and outputs visual elements.

[1724] The voice generation AI generates and outputs voice data.

[1725] Step 5: Putting the Components Together

[1726] The server integrates the scenario, visual, and audio data received from each generation AI. The input is the generated data from each generation AI, and the server integrates them into a single virtual space data.

[1727] The server creates consistent virtual space data, and the output is integrated virtual space data.

[1728] Step 6: Send and view the integrated data

[1729] The server sends the integrated virtual space data to the terminal. The input is the integrated virtual space data, and the output is the data sent to the terminal.

[1730] The device analyzes the virtual space data received from the server and displays it to the user. Specifically, the device displays the virtual space to the user in real time using VR goggles. The input is the virtual space data from the server, and the output is the virtual space displayed to the user.

[1731] Step 7: User experience and feedback

[1732] Users explore generated virtual spaces and enjoy experiences, such as walking around a medieval fantasy town and interacting with its inhabitants.

[1733] The user inputs their experience evaluation and feedback into the device. The input is the user's feedback content, and the output is the feedback data input into the device.

[1734] The terminal sends the user's feedback to the server. The input is the feedback data entered into the terminal, and the output is the feedback data sent to the server.

[1735] Step 8: Processing feedback and training the AI

[1736] The server analyzes the feedback received from the device and reflects it in the generative AI model. The input is the user's feedback data, which the server analyzes and uses to improve the generative AI model.

[1737] The generative AI model learns from the feedback data and improves the generation process in the future, resulting in a higher quality virtual space the next time it is generated.

[1738] (Application example 1)

[1739] 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."

[1740] In today's digital society, there is a demand for efficient generation of virtual spaces and improved user experiences. However, with conventional technologies, the virtual space generation process is complex and time-consuming, making it difficult to provide an integrated and consistent virtual experience. Furthermore, there was a lack of a mechanism for incorporating user feedback into the generation process, which hindered the improvement of the quality of the generation AI.

[1741] 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.

[1742] In this invention, the server includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for collecting feedback from the user and providing the feedback for improving the generation operations, and a means for generating and integrating visual, scenario, and audio elements to provide a virtual space. This enables the virtual space desired by the user to be generated quickly and consistently, improving the user experience. Furthermore, the collected feedback can be used to continuously improve the quality of the generation AI.

[1743] A "generation request" is a request in which the user specifies the details and elements of the virtual space they desire.

[1744] "Predetermined work" is a set of specific tasks that include the required creation operations, identified by analyzing the creation request.

[1745] "Generation operations" are processes for creating components of virtual space, such as text generation, image generation, and sound generation.

[1746] "Visuals" refers to visual elements in a virtual space, such as images and designs of buildings, characters, landscapes, etc.

[1747] "Scenario" refers to the content of the story or events that unfold within a virtual space, and includes text information and storylines to guide the user's experience.

[1748] "Audio" refers to auditory elements such as character dialogue, environmental sounds, and sound effects within the virtual space.

[1749] "User terminal" means a device used by a user to display and manipulate a virtual space, including a smartphone, smart glasses, or a head-mounted display.

[1750] "Feedback" refers to the evaluations and comments provided by users after experiencing a virtual space, and is information that is used to improve the quality of the generation operation.

[1751] An "integrated component" is a set of visuals, scenarios, and sounds created through generative operations that come together to form a coherent virtual space.

[1752] A "virtual space" is an imaginary space or world that users can experience interactively within a digital environment.

[1753] The present invention relates to a system for generating a virtual space based on a user request, which includes a means for analyzing the generation request and identifying a predetermined task, a means for performing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for collecting feedback from the user and providing the feedback for improving the generation operations, and a means for generating and integrating visual, scenario, and audio elements to provide the virtual space.

[1754] 1. Basic configuration

[1755] The system mainly consists of the following hardware and software:

[1756] Hardware: Smartphones, smart glasses, head-mounted displays

[1757] software:

[1758] OpenAI API library: for using generative AI (text, image, audio)

[1759] PIL (Python Imaging Library): Displaying images

[1760] pyttsx3: Audio playback

[1761] pydub: Audio data processing

[1762] 2. Overview of the processing flow

[1763] a. Receiving User Requests

[1764] The user requests the creation of a virtual space. For example, they input a request such as "Please create a virtual store specializing in high-end jewelry." This request is then sent from the device to the server.

[1765] b. Request Parsing

[1766] The server analyzes the request and determines the necessary operations. Specifically, it determines that the request for a "virtual store specializing in luxury jewelry" requires the creation of a store scenario, visuals, and audio.

[1767] c. Performing the generate operation

[1768] The server instructs the generation AI to generate each element.

[1769] Text generation AI: Generates store scenarios and stories.

[1770] Image generation AI: Generates store designs and product images.

[1771] Voice generation AI: Generates environmental sounds within the store and character dialogue.

[1772] d. Integration of Components

[1773] The server integrates the generated scenarios, visuals, and audio to create a consistent virtual space data, which is then sent to the user's device, where it is displayed.

[1774] Users can explore generated virtual spaces and enjoy experiences, such as walking around a virtual store specializing in high-end jewelry and interacting with elven characters.

[1775] Specific examples

[1776] If a user requests a medieval jewelry shop with elves selling ornaments, the system will:

[1777] The user enters a request.

[1778] The device sends a request to the server.

[1779] The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[1780] The server instructs the text generation AI to create the store scenario, the image generation AI to create the store design, and the voice generation AI to create environmental sounds.

[1781] Each AI generates its own elements.

[1782] The server integrates all the components and creates virtual space data.

[1783] The server sends the integrated data to the terminal.

[1784] The device displays the data to the user, who then explores the virtual store.

[1785] The user enters feedback into the device, which then sends it to the server.

[1786] The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[1787] Example prompt sentences to use

[1788] Create a medieval-style jewelry shop where elves sell decorative items. Provide the story, visuals, and audio for the shop.

[1789] In this way, it is possible to efficiently generate and provide highly customizable virtual spaces that can adapt to the diverse needs of users.

[1790] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1791] Step 1:

[1792] A user requests the creation of a virtual space. Specifically, the user inputs a request for creation, such as "Please create a virtual store specializing in luxury jewelry," using a smartphone or other device. The input request for creation is sent from the device to the server for processing in the next step.

[1793] Input: User's creation request (e.g., "Create a virtual store specializing in high-end jewelry")

[1794] Output: The generation request is sent to the server

[1795] Step 2:

[1796] The server analyzes the generation request received from the device. Specifically, it uses a text analysis algorithm to identify keywords and necessary components in the request. This analysis determines which generation operation (text generation, image generation, or audio generation) is required.

[1797] Input: Text data of the generation request

[1798] Output: Information about the required generation operations (scenario generation, visual generation, audio generation)

[1799] Step 3:

[1800] The server issues instructions to each generative AI model to execute the generation operations. Specifically, using OpenAI's API, it requests the text generation AI to generate the store scenario, the image generation AI to generate the store design, and the voice generation AI to generate the store's environmental sounds and character dialogue.

[1801] Input: Information about the generation operation, prompt

[1802] Output: Scenarios, visuals, and audio data generated by each generative AI model

[1803] Step 4:

[1804] The server integrates the generated scenarios, visuals, and audio. Specifically, it combines each generated data into a consistent virtual space data, which includes data format conversion and adjustment, and data association.

[1805] Input: Generated scenario, visual and audio data

[1806] Output: Integrated virtual space data

[1807] Step 5:

[1808] The server transmits the integrated virtual space data to the user's device. Specifically, it uses a data transfer protocol to deliver the virtual space data quickly and securely to the device. The device interprets the received data and provides the user with a visual and auditory virtual space experience.

[1809] Input: Integrated virtual space data

[1810] Output: The virtual space is displayed on the user's device.

[1811] Step 6:

[1812] Users can explore the generated virtual space and enjoy the experience, for example, walking around a virtual store specializing in high-end jewelry, checking out the products, and interacting with the characters.

[1813] Input: Virtual space experience (user operation and interaction)

[1814] Output: User experience and feedback

[1815] Step 7:

[1816] Users provide feedback about their experiences by entering ratings and comments on their devices, which are then sent to the server, which analyzes the feedback and uses it to improve the generation process.

[1817] Input: User feedback (text data)

[1818] Output: Feedback data for improvement

[1819] 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.

[1820] The system of the present invention includes a process for analyzing a generation request, performing multiple generation operations, integrating the generated components, and transmitting the integrated components to a user terminal. Furthermore, by combining an emotion engine that recognizes the user's emotions, the system can provide a customized virtual space according to the user's emotional state. The following is a description of a specific embodiment of the present invention.

[1821] overview

[1822] This invention receives a request (generation request) for the creation of a user's desired virtual space, analyzes it, and then executes multiple generation operations to generate components (scenario, visuals, audio, etc.), integrating them and providing them to the user. It also uses an emotion engine to recognize the user's emotions and adjust the created virtual space according to their emotional state. Furthermore, it collects user ratings and feedback, analyzes them, and feeds them back to the generation AI to improve the accuracy and quality of future generation operations.

[1823] Detailed embodiment

[1824] 1. Receiving a User Request

[1825] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[1826] Terminal: Sends the request entered by the user to the server.

[1827] 2. Parsing the Request

[1828] Server: Analyzes the generation request received from the device and identifies the required generation operations (e.g., scenario generation, visual generation, audio generation).

[1829] 3. Emotion Recognition by Emotion Engine

[1830] On the device: Uses an emotion engine to analyze the user's facial expressions, voice tone, and behavior to recognize the user's emotional state.

[1831] Emotion engine: Determines the user's emotional state (e.g., happy, excited, calm) based on the data obtained.

[1832] 4. Performing the Generate Operation

[1833] Server: Instructs the text generation AI, image generation AI, and voice generation AI to generate each element.

[1834] Text generation AI: Generates scenarios such as the city's history, backstories of main characters, and events that occur in the city.

[1835] Image generation AI: Generates visual elements such as city buildings, landscapes, and character designs.

[1836] Voice generation AI: Generates city environmental sounds and character dialogue.

[1837] 5. Integration of Components

[1838] Server: Integrates the generated scenario, visual, and audio data to create consistent virtual space data.

[1839] 6. Adjusting to your emotional state

[1840] Server: Adjusts elements of the virtual space (e.g., colors, music, and environment) based on the user's emotional state obtained from the emotion engine. For example, if the user is determined to be relaxed, the colors and music will be changed to calmer ones.

[1841] 7. Transmission and Display of Aggregated Data

[1842] Server: The server transmits the integrated virtual space data, adjusted according to the user's emotional state, to the device.

[1843] Device: Provides users with visual, auditory, and other experiences based on the virtual space data received from the server. For example, the device allows users to explore a city through VR goggles.

[1844] 8. User Experience and Feedback

[1845] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[1846] User: Enters their experience rating and feedback into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[1847] Device: Sends user feedback to the server.

[1848] 9. Feedback processing and AI training

[1849] Server: Analyzes the feedback received from the device and provides the generated AI with data on areas that need improvement.

[1850] Generative AI: Based on the feedback received, it learns and improves the quality of the next generation operation.

[1851] Specific examples

[1852] For example, if a user requests, "Generate a city centered around an ancient Egyptian pyramid," the system will operate as follows:

[1853] 1. The user enters a request.

[1854] 2. The device sends a request to the server.

[1855] 3. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[1856] 4. The device uses an emotion engine to recognize the user's emotions.

[1857] 5. The emotion engine determines the user's emotional state and sends it to the server.

[1858] 6. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[1859] 7. Each AI generates its own elements.

[1860] 8. The server integrates all components and creates virtual space data.

[1861] 9. The server adjusts the virtual space based on data from the emotion engine.

[1862] 10. The server sends the integrated data to the device.

[1863] 11. The device displays the data to the user, who then explores the pyramid city through VR goggles.

[1864] 12. The user enters feedback into the device, which then sends it to the server.

[1865] 13. The server analyzes the feedback and provides it to the generating AI to help improve it in the future.

[1866] In this way, by combining the emotion engine, this system can efficiently generate and provide a highly customized virtual space that corresponds to the user's emotional state.

[1867] The processing flow will be explained below.

[1868] Step 1:

[1869] User: Enter a request for a scenario in which they would like to generate a virtual space (e.g., "Please generate a medieval fantasy town").

[1870] Terminal: Sends the request entered by the user to the server.

[1871] Step 2:

[1872] Server: Analyzes the generation request received from the device, performs text analysis on the request content, and identifies the required generation operation (e.g., scenario generation, visual generation, audio generation).

[1873] Step 3:

[1874] On the device: Uses an emotion engine to recognize the user's emotional state by analyzing their facial expressions, voice tone, and behavior in real time.

[1875] Emotion engine: Determines the user's emotions (e.g., happy, relaxed, excited) based on facial expressions, vocal tone, and behavioral data such as excitement and calm.

[1876] Step 4:

[1877] Emotion engine: Sends data indicating the user's emotional state to the server.

[1878] Step 5:

[1879] Server: Issues instructions to the text generation AI to generate a scenario, including the town's setting and history, background information for the main characters, and events that will occur.

[1880] Text generation AI: Generates text data based on a specified scenario and sends it back to the server.

[1881] Step 6:

[1882] Server: Based on the scenario data received from the text generation AI, the server issues instructions to the image generation AI to generate visuals. These instructions include the design of city buildings, scenery, characters, etc.

[1883] Image generation AI: Generates appropriate visual elements based on scenario data and sends them back to the server.

[1884] Step 7:

[1885] Server: Based on the visual data received from the image generation AI, it issues instructions to the sound generation AI to generate sounds, including the city's ambient sounds and character dialogue.

[1886] Voice generation AI: Generates the necessary acoustic data based on a specified scenario and sends it back to the server.

[1887] Step 8:

[1888] Server: Integrates the generated scenario, visual, and audio data to create a consistent virtual space.

[1889] Step 9:

[1890] Server: Adjusts elements of the virtual space (e.g., colors, music, and environmental settings) based on the user's emotional state data obtained from the emotion engine. For example, if the user is in a relaxed state, soften the colors and change the background music to a calmer one.

[1891] Step 10:

[1892] Server: The server transmits the integrated virtual space data, adjusted according to the user's emotional state, to the device.

[1893] Step 11:

[1894] Device: Provides users with visual, auditory, and other experiences based on the virtual space data received from the server. For example, the device allows users to explore a city through VR goggles.

[1895] Step 12:

[1896] User: Explore the generated virtual space and enjoy the experience, for example, walking around a medieval fantasy town and interacting with its inhabitants.

[1897] Step 13:

[1898] User: Enters their experience rating and feedback into the device, for example, "The building design is great, but the background noise is a bit too loud."

[1899] Terminal: Sends user-entered feedback to the server.

[1900] Step 14:

[1901] Server: Analyzes the feedback received from the device and provides it as data on areas for improvement to the generative AI and emotion engine.

[1902] Generative AI: Based on the received feedback data, it learns to help with the next generation operation and aims to improve quality.

[1903] Emotion Engine: Improves the user emotion recognition algorithm based on feedback data, improving recognition accuracy.

[1904] Through the above steps, the system of the present invention can efficiently generate and provide a high-quality, customized virtual space that meets the user's requirements and emotional state.

[1905] Example 2

[1906] 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."

[1907] Conventional virtual space generation systems provide virtual spaces by generating and integrating components based on user requests, but they have the problem of making it difficult to increase user satisfaction because they do not adjust according to the user's emotional state.Furthermore, there is also the problem of not providing appropriate feedback based on evaluations of the generated virtual space, which makes continuous quality improvement insufficient.

[1908] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1909] In this invention, the server includes means for analyzing the generation request and identifying a predetermined task, means for executing a plurality of generation operations, means for integrating the generated components, means for transmitting the integrated components to the user terminal, means for analyzing the user's evaluation and providing feedback for improving the generation operations, means for recognizing the user's emotional state, and means for adjusting the components according to the emotional state, thereby enabling the provision of a virtual space according to the user's emotional state and continuous quality improvement based on the user's evaluation.

[1910] A "generation request" is a specific request that a user inputs to request the generation of a virtual space.

[1911] The "predetermined work" refers to the various operations and processes required to generate a virtual space, which are identified as a result of analyzing the generation request.

[1912] A "creation operation" is an operation or procedure for generating content such as text, images, or audio.

[1913] "Components" refer to the individual elements such as scenarios, visuals, and sounds that make up a virtual space.

[1914] "Synthesis" refers to the process of combining the components generated by individual generation operations into a coherent virtual space data set.

[1915] "User terminal" refers to the device that a user uses to experience a virtual space, and specifically includes a PC, smartphone, VR goggles, etc.

[1916] An "emotion engine" is a technology or algorithm that analyzes a user's facial expressions, tone of voice, behavior, etc. to determine their emotional state.

[1917] "Feedback" refers to the evaluations and opinions that users give about their virtual space experiences, and is information that is used to improve and optimize the system.

[1918] A "text generation operation" is an operation that generates a sentence or scenario based on a specific prompt.

[1919] An "image generation operation" is an operation that generates visual content based on a particular prompt.

[1920] An "audio generation operation" is an operation that generates audio content based on a particular prompt.

[1921] "Tuning" refers to the process of optimizing each element of the generated virtual space based on the user's emotional state as determined by the emotion engine.

[1922] "Analysis" is the process of extracting and understanding specific information from input data.

[1923] The present invention is a system that generates a virtual space based on a user's request, integrates its components, and provides the virtual space to the user. This system also has the ability to recognize the user's emotional state and adjust the generated virtual space accordingly. Specific embodiments of this system are described below.

[1924] Hardware and software used

[1925] Hardware

[1926] Server: Parses requests, directs production operations, integrates the generated data, and coordinates with the emotion engine.

[1927] Terminal: The device used by the user, including PCs, smartphones, VR goggles, etc.

[1928] software

[1929] Generative AI models: Includes text generation AI, image generation AI, and speech generation AI, and performs each generation operation.

[1930] Emotion engine: Software that analyzes a user's facial expressions, tone of voice, etc. to recognize their emotional state.

[1931] Database Management System (DBMS): A system for storing and integrating generated data in a consistent format.

[1932] Process Overview

[1933] Receiving and sending user requests

[1934] The user inputs a specific request for generating a virtual space. For example, the user inputs a prompt statement such as "Please generate a medieval fantasy town."

[1935] The device sends a request to the server, sending data using an HTTP POST request.

[1936] Parsing the request

[1937] The server analyzes the received request and extracts the information needed for the generation operation. It uses a natural language processing (NLP) engine to identify key keywords.

[1938] Emotion recognition by emotion engine

[1939] The device uses an emotion engine to analyze the user's facial expressions and tone of voice.

[1940] The emotion engine determines the user's emotional state based on the analysis results and generates emotion labels such as "fun" or "excited."

[1941] Running the generate operation

[1942] The server issues generation instructions to the text generation AI, image generation AI, and voice generation AI.

[1943] The text generation AI generates the city's history and backstories for the main characters.

[1944] Image generation AI generates visuals of city buildings, landscapes, and characters.

[1945] The voice generation AI generates the city's environmental sounds and character dialogue.

[1946] Integration of each element

[1947] The server integrates the generated scenario, visual and audio data, and uses a DBMS to organize the data into a consistent format.

[1948] Adjusting according to emotional state

[1949] The server adjusts the elements of the generated virtual space based on the emotional data obtained from the emotion engine. For example, if the user is feeling relaxed, it will change the colors and music to calmer ones.

[1950] Sending and displaying consolidated data

[1951] The server sends the adjusted virtual space data to the terminal.

[1952] The device displays a virtual space to the user, allowing them to explore a city using VR goggles, for example.

[1953] User Experience and Feedback

[1954] The user explores the generated virtual space and provides feedback on their experience.

[1955] The device sends feedback to the server, which is analyzed and used to improve future generation operations.

[1956] Specific examples

[1957] If the user enters the prompt "Generate a city centered around an ancient Egyptian pyramid," the system will:

[1958] 1. The user enters a prompt and the terminal sends a request to the server.

[1959] 2. The server analyzes the request and identifies the required generation operations (scenario, visual, audio).

[1960] 3. The device uses an emotion engine to analyze the user's emotional state.

[1961] 4. The server instructs the text generation AI to create a city scenario, the image generation AI to create pyramid and cityscapes, and the audio generation AI to create background sounds.

[1962] 5. Each AI generates its own element.

[1963] 6. The server integrates all components to create virtual space data and adjusts it based on data from the emotion engine.

[1964] 7. The server sends the integrated data to the device, which displays it to the user, who then explores the pyramid city through the VR goggles.

[1965] 8. The user enters feedback and the device sends it to the server.

[1966] 9. The server analyzes the feedback and provides it to the generation AI to help improve the quality of future generation.

[1967] In this way, the system of the present invention can generate highly customized virtual spaces and continuously improve their quality based on the user's emotional state and feedback.

[1968] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1969] Step 1: Receiving a user request

[1970] The user inputs a specific request for generating a virtual space into the terminal, for example, a prompt sentence such as "Please generate a medieval fantasy town."

[1971] The terminal sends the input request to the server using an HTTP POST request, and sends the prompt received from the user to the server.

[1972] Input: The prompt text entered by the user.

[1973] Output: Sends a request to the server.

[1974] Step 2: Parsing the request

[1975] The server analyzes the request received from the terminal. First, it parses the received data and checks its contents.

[1976] The server analyzes the request and identifies the required generation operations (scenario generation, visual generation, audio generation). A natural language processing (NLP) engine is used for the analysis to extract key keywords. For example, keywords such as "medieval fantasy," "town," and "generation" are extracted.

[1977] Input: The prompt text sent to the server.

[1978] Output: A list of the required generation operations.

[1979] Step 3: Emotion recognition by the emotion engine

[1980] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, and captures the user's facial expressions and voice through the built-in camera and microphone.

[1981] The emotion engine analyzes the captured data and determines the user's emotion using a machine learning model (e.g., a CNN model for emotion recognition).

[1982] Input: User facial and voice capture data.

[1983] Output: The user's emotional state (happy, excited, relaxed, etc.).

[1984] Step 4: Run the generate operation

[1985] The server issues instructions to the text generation AI, image generation AI, and voice generation AI to generate each element.

[1986] The text generation AI generates a scenario based on the request, such as the history of the town, the backstories of the main characters, and events that occur in the town.

[1987] Image generation AI generates visual elements based on requests, such as city buildings, landscapes, and character designs.

[1988] The voice generation AI generates audio elements based on requests, such as city ambient sounds and character dialogue.

[1989] Input: Request parsing results.

[1990] Output: Generated scenarios, visuals, and audio data.

[1991] Step 5: Putting the Components Together

[1992] The server integrates the generated scenario, visual, and audio data, and uses a DBMS to organize the data into a consistent format, for example, to create a unified design and background story, linking the entire virtual space.

[1993] Input: Generated scenario, visual and audio data.

[1994] Output: Integrated virtual space data.

[1995] Step 6: Adjust according to your emotional state

[1996] The server adjusts the virtual space based on the emotional data it obtains from the emotion engine. For example, if the user is feeling relaxed, it will change the background music to a calmer one and use a more subdued color scheme.

[1997] Input: Integrated virtual space data, user emotional state.

[1998] Output: Calibrated virtual space data.

[1999] Step 7: Send and view integrated data

[2000] The server sends the adjusted virtual space data to the device, using the WebSocket communication protocol for real-time data transfer.

[2001] The device displays a virtual space to the user based on the data received, allowing the user to explore a city using VR goggles, for example.

[2002] Input: Calibrated virtual space data.

[2003] Output: A display of the virtual space.

[2004] Step 8: User experience and feedback

[2005] Users explore generated virtual spaces and enjoy experiences, such as walking around a medieval fantasy town and interacting with its inhabitants.

[2006] The user enters feedback about their experience into the device (e.g., "The building design is great, but the background noise is a bit too loud").

[2007] The device sends feedback data to the server in JSON format.

[2008] Input: User feedback.

[2009] Output: Send feedback to the server.

[2010] Step 9: Processing feedback and training the AI

[2011] The server receives the feedback and analyzes it. For example, it uses a text analysis engine to extract content such as "background noise is too loud."

[2012] The generation AI uses the feedback to learn and improve its next generation operation, for example by improving the background sound volume adjustment algorithm.

[2013] Input: User feedback.

[2014] Output: Improved generation algorithm.

[2015] (Application example 2)

[2016] 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."

[2017] Current virtual space generation technology faces challenges, such as inconsistent quality of content and user experience generated automatically based on user requests, particularly difficulty in flexibly adjusting content in response to user emotions and feedback. Furthermore, the generated virtual space may not be optimized for the user's emotional state, potentially resulting in reduced user satisfaction. Furthermore, insufficient analysis of feedback can make future improvements difficult.

[2018] 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.

[2019] In this invention, the server includes a means for analyzing a generation request and identifying a predetermined task, a means for executing a plurality of generation operations, a means for integrating the generated components, a means for transmitting the integrated components to a user terminal, a means for analyzing a user's evaluation and providing feedback for improving the generation operation, a means for performing emotion recognition, and a means for adjusting the integrated components according to the user's emotional state. This not only enables the generation of a high-quality virtual space based on the user's generation request, but also improves user satisfaction by customizing the virtual space according to the user's emotional state. Furthermore, by analyzing user feedback, the accuracy and quality of the generation operation are continuously improved.

[2020] A "generation request" is a request from a user to generate a virtual space.

[2021] A "predetermined task" is a series of production operations that are specified based on a production request.

[2022] "Generation operations" refers to the various generation processes that are carried out to construct a virtual space.

[2023] "Components" refer to elements such as scenarios, visuals, and sounds that are generated to form a virtual space.

[2024] "User terminal" means the device used by a user to receive and experience a virtual space.

[2025] "Evaluation" refers to the feedback and reviews that users give about the virtual space they have experienced.

[2026] "Emotion recognition" is the process of identifying a user's emotional state from their facial expressions, vocal tone, behavior, etc.

[2027] "Emotional state" refers to the user's current emotional state, such as happy, excited, calm, etc.

[2028] The "means for analyzing user evaluations and providing feedback to improve the generation operation" refers to a means for collecting and analyzing evaluations from users to help improve the quality of the generation operation from the next time onwards.

[2029] System Program

[2030] The system of the present invention includes a series of processes, including analyzing a generation request, performing multiple generation operations, integrating the generated components, and transmitting the components to a user terminal. It also has the function of performing emotion recognition and adjusting the components according to the user's emotional state. The following describes specific means for realizing this application example.

[2031] System configuration

[2032] Hardware and software used

[2033] 1. Hardware

[2034] User device: A device used by a user, such as smart glasses or a head-mounted display.

[2035] Server: A back-end server for generating operations and data processing.

[2036] 2. Software

[2037] Emotion Recognition Engine (EmotionEngine): An engine that analyzes a user's facial expressions, tone of voice, and behavior to identify their emotional state.

[2038] Virtual Space Generator: An engine that integrates generated scenarios, visuals, and sounds to generate virtual spaces.

[2039] Text generation AI (e.g., OpenAI GPT-3): An AI model for generating scenarios and stories.

[2040] Image generation AI (e.g., DeepDream): An AI model for generating visual elements of virtual spaces.

[2041] Audio generation AI: An AI model for generating acoustic elements in virtual spaces.

[2042] Program processing

[2043] Natural language explanations

[2044] After receiving a generation request from the user, the server analyzes it and performs multiple generation operations using text generation AI, image generation AI, and voice generation AI. The generated scenario, visuals, and audio are integrated by the virtual space generation engine to create consistent virtual space data.

[2045] The system then uses an emotion recognition engine to identify the user's emotional state and adjusts the colors, music, and other aspects of the virtual space based on that data, creating a personalized virtual space that reflects the user's emotional state.

[2046] Finally, the generated virtual space data is sent to the user's device, where the user experiences the virtual space through smart glasses or a head-mounted display. The user provides evaluations and feedback on the virtual space they experienced, which is then sent back to the server to help improve the quality of future generation operations.

[2047] Examples of concrete examples and prompts

[2048] Examples:

[2049] The user inputs a request such as "Show me clothes from the summer collection." Based on this request, the system generates products from the summer collection in a virtual store and uses an emotion recognition engine to identify the user's emotional state. The atmosphere and presentation of the virtual store are then adjusted to match the user's emotions, and the store is presented to the user through smart glasses.

[2050] Example prompt sentence:

[2051] "User request: Show me clothes from the summer collection"

[2052] "User's emotional state: excited"

[2053] In this way, the system of the present invention can provide a high-quality virtual space that responds to the user's emotions, achieving a highly satisfying experience.

[2054] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2055] Step 1:

[2056] The user enters a generation request.

[2057] The user inputs a generation request, for example, "Show me the clothes from the summer collection," through smart glasses or a head-mounted display, and the terminal sends this generation request to the server.

[2058] Step 2:

[2059] The server parses the create request.

[2060] The server analyzes the input generation request and extracts the data necessary for the generation operation (text generation, image generation, voice generation). Specifically, it generates prompts for the text generation AI, image generation AI, and voice generation AI.

[2061] Step 3:

[2062] The server performs the text generation operation.

[2063] The server instructs the text generation AI to create a scenario based on the generation request. The input is a prompt sentence, which the text generation AI processes and calculates to output a scenario such as a description of the clothing or a product story.

[2064] Step 4:

[2065] The server performs the image generation operation.

[2066] The server instructs the image generation AI to create visuals based on the generation request. The input is the output of the text generation AI and the generation request itself, and the image generation AI processes and calculates it to output images of clothing designs and the exterior of a virtual store.

[2067] Step 5:

[2068] The server performs the audio generation operations.

[2069] The server instructs the voice generation AI to create audio based on the generation request. The input is the output of the text generation AI and the generation request itself, and the voice generation AI processes and calculates it to output audio elements such as background sounds and narration.

[2070] Step 6:

[2071] The server performs emotion recognition.

[2072] The device collects the user's facial expressions, voice tone, and behavior, and sends them to an emotion recognition engine, which analyzes this data as input and outputs the user's emotional state (e.g., excited, relaxed, etc.).

[2073] Step 7:

[2074] The server integrates the generated components.

[2075] The server uses the outputs from the text generation AI, image generation AI, and voice generation AI to integrate each component in a virtual space generation engine and generate a unified virtual space.

[2076] Step 8:

[2077] The server adjusts based on the emotional state.

[2078] Based on the emotional state data obtained from the emotion recognition engine, the server adjusts each element of the virtual space (color, music, visual effects, etc.) to match the user's emotional state.

[2079] Step 9:

[2080] The server sends the integrated and adjusted virtual space data to the terminal.

[2081] The server transmits the completed virtual space data to the user's terminal, which displays it, providing the user with a virtual shopping experience.

[2082] Step 10:

[2083] The user enters feedback.

[2084] The user inputs their evaluation and feedback on the virtual space they experienced into the terminal, which then transmits this information to the server.

[2085] Step 11:

[2086] The server analyzes the feedback and improves the AI ​​model.

[2087] The server analyzes the feedback received from users and feeds that data back into the generative AI model to improve the quality of future generations.

[2088] In this way, users can enjoy a high-quality virtual shopping experience that is emotionally customized.

[2089] 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.

[2090] 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.

[2091] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2092] 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.

[2093] 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.

[2094] 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.

[2095] 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).

[2096] 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.

[2097] 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."

[2098] 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.

[2099] 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).

[2100] 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.

[2101] 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.

[2102] 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.

[2103] 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.

[2104] 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.

[2105] 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.

[2106] 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.

[2107] 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.

[2108] 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 disc...

Claims

1. means for analyzing the production request to identify a predetermined operation; means for performing a plurality of generating operations; means for integrating the generated components; means for transmitting the integrated components to a user terminal; A means for analyzing user evaluations and providing feedback to improve the generation operation; A system including:

2. 2. The system of claim 1, wherein the means for performing a plurality of generation operations includes a text generation operation, an image generation operation, and a voice generation operation.

3. 2. The system of claim 1, further comprising means for receiving a generation request input by a user on a terminal.

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