System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a plurality of forms of input such as text, voice, image, and video from a user; data analysis means for analyzing the plurality of forms of input and understanding the content thereof; generation means for generating virtual reality content based on the analyzed data; and provision means for providing the generated virtual reality content to the user.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] Modern virtual reality (VR) content creation requires advanced technical skills, presenting a significant hurdle for general consumers and non-technical creators. This poses a challenge, making it difficult to provide personalized VR experiences tailored to individual needs and limiting diverse creative expression. This invention aims to reduce these technical barriers and enable anyone to easily create and experience their own unique VR content. [Means for solving the problem]

[0005] The present invention solves the above problems by the following means. It provides a means for receiving input from users in multiple formats, such as text, audio, images, and videos, allowing users to customize their VR experiences using a variety of materials. It then provides a data analysis means for analyzing the received input in multiple formats and understanding its content. This analysis means performs more accurate and effective analysis by using dedicated analysis modules corresponding to each format. It further provides a generation means for generating virtual reality content based on the analyzed data, thereby realizing a personalized VR experience based on the materials provided by the user. Finally, it configures a system including a provision means for providing the generated virtual reality content to users. This allows users to easily create and enjoy their own unique VR experiences, even without technical knowledge.

[0006] "Text" refers to character information entered by the user, and is primarily used as a scenario or explanatory text.

[0007] "Audio" refers to sound data provided by the user, including acoustic information such as ambient sounds, sound effects, and narration.

[0008] "Images" are still images uploaded by users that provide visual material such as scenes, characters, objects, etc.

[0009] "Video" refers to video data uploaded by users, and is a material used to provide moving visual information.

[0010] "Means for receiving input" refers to the functionality that provides an interface for users to upload text, audio, images, and video and provide them to the system.

[0011] "Data analysis means" is a function that analyzes text, audio, images, videos, etc. received from users and understands their content and meaning.

[0012] An "analysis module" is a software or hardware component that specializes in analyzing the content of a particular data type (text, audio, image, video).

[0013] "Generation means" is a function for generating virtual reality content based on analyzed data.

[0014] "Virtual Reality Content" means digital content that provides an interactive visual and auditory experience generated based on material provided by the user.

[0015] "Provision means" refers to a function for delivering the generated virtual reality content to users so that they can experience it. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The system of the present invention receives inputs such as text, voice, images, and videos provided by users, analyzes and integrates them to generate virtual reality (VR) content, and provides it to users. This system mainly consists of three main components: a terminal, a server, and a user.

[0038] System Configuration

[0039] 1. Terminal functions

[0040] The terminal provides an interface for receiving input from the user. Through this interface, the user can send data such as text, audio, images, and video to the system. The terminal also temporarily stores the received data and sends it to the server.

[0041] 2. Server-side functionality

[0042] The server has many analysis modules that receive and analyze data sent from the device. The server uses text analysis, voice analysis, image analysis, and video analysis modules to perform detailed analysis of user input, making it easier to understand the user's intent and the context of the data.

[0043] The analyzed data is then passed to the generation AI, which generates scenarios, characters, and environments based on the analysis results to create virtual reality content. The generated content is then packaged on the server and converted into a format that can be provided to users.

[0044] 3. Providing a user experience

[0045] Users experience the generated content through a VR device. The server sends the completed VR content to the terminal, which then displays it on the VR device. Users can then use the VR device to enjoy the virtual experience.

[0046] Program processing explanation

[0047] The specific process is as follows:

[0048] Getting User Input

[0049] The device receives text, audio, images, and video through the user interface. When the user uploads this data, the device temporarily stores it and sends it to the server.

[0050] Data analysis and integration

[0051] The server receives data sent from the device and assigns it to an analysis module according to the data format. The text analysis module analyzes the input text and understands the context. The audio analysis module analyzes the provided audio data and understands the sound content. The image analysis module extracts image features, and the video analysis module analyzes video scenes.

[0052] The data obtained from the analysis module is integrated on the server and passed to a generative AI model, which uses the integrated data to generate scenarios, characters, and environments, building the overall VR content.

[0053] VR content generation and provision

[0054] Generative AI creates a personalized VR experience based on the user's intent, including a pirate treasure hunt story, realistic ocean sounds, ship images, and a treasure hunt movie.

[0055] The server packages the generated VR content and converts it into a format that can be experienced by the user. The packaged VR content is then sent to the terminal, which displays it on the VR device.

[0056] Specific examples

[0057] For example, suppose a user wants to create a "pirate treasure hunting story" and provides the text "pirate treasure hunting adventure," the audio "sound of waves," the image "ship," and the video "treasure hunting scene." This input data is sent to the server and analyzed appropriately by each analysis module. Based on the analysis results, the generation AI generates an active pirate scenario and environment, adding the sound of waves as a sound effect. The server integrates this and packages it into a single VR content, which is then sent to the device. The user can then experience this customized adventure through their VR device.

[0058] As described above, the system of the present invention allows users to easily create and enjoy personalized VR experiences.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] The device displays a screen for uploading text, audio, images, and videos to the user, allowing them to select and upload the materials for the VR experience they want to create.

[0062] Step 2:

[0063] Users select the desired material and upload it to their device in the form of text, audio, images, or video. For example, text can be used to provide a story, audio can be used to provide an ambient sound, images can be used to provide a scene, and video can be used to provide a moving sequence.

[0064] Step 3:

[0065] The device temporarily stores the text, audio, images, and video provided by the user and prepares them for transmission. In this step, the data format of each material is checked for any errors.

[0066] Step 4:

[0067] The device sends the saved data to the server, along with the classification information of the data.

[0068] Step 5:

[0069] The server receives the data sent from the device, classifies it by type, and assigns it to the appropriate analysis module.

[0070] Step 6:

[0071] The server sends the text data to the text analysis module, which then extracts the context and keywords from the text and creates the outline of the scenario.

[0072] Step 7:

[0073] The server sends the audio data to the audio analysis module, which then extracts the audio characteristics and recognizes them as environmental sounds or sound effects.

[0074] Step 8:

[0075] The server sends the image data to the image analysis module, which analyzes the image for features and components and uses them as scene and character designs.

[0076] Step 9:

[0077] The server sends the video data to the video analysis module, which then extracts movie sequences and uses them as material for storyboards and animations.

[0078] Step 10:

[0079] The analysis results sent from the analysis modules are integrated into the server, which then aggregates them and passes the unified data set to the generative AI model.

[0080] Step 11:

[0081] The generative AI model generates VR content such as scenarios, characters, and environments based on the integrated dataset, and interactive elements are also created during this step.

[0082] Step 12:

[0083] The server packages the generated VR content and converts it into a format that can be experienced by the user, and saves the packaged content in the optimal format.

[0084] Step 13:

[0085] The server transmits the packaged VR content to the device, which receives the data.

[0086] Step 14:

[0087] The terminal transfers the received VR content to the VR device and prepares it for display, at which point the user interface is updated to display the option to start the experience.

[0088] Step 15:

[0089] Users use VR devices to experience the generated content, and their movements and reactions are collected and reflected in the interactive elements.

[0090] Step 16:

[0091] Users can provide feedback after their experience, which is sent to the server via their device and used to improve the experience and generate new content.

[0092] Example 1

[0093] 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."

[0094] Conventional virtual reality content generation systems have difficulty effectively analyzing and integrating diverse forms of data from users to provide personalized virtual reality experiences tailored to their individual needs. Furthermore, the content generation process is complex, making it difficult to generate consistent scenarios and characters.

[0095] 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.

[0096] In this invention, the server includes a means for receiving input in multiple forms from a user, such as text, audio, images, and videos, a data analysis means for analyzing the input in multiple forms and understanding its content, a means for integrating the analyzed data and generating virtual reality content based on a generative AI model, and a means for packaging the generated virtual reality content and providing it to the user, thereby enabling the user to easily generate and enjoy a personalized virtual reality experience using data in various forms.

[0097] A "means for receiving multiple forms of input from a user, such as text, audio, images, and video" is a device or method that provides an interface for receiving different forms of data, such as text, audio, images, and video, input from a user.

[0098] "Data analysis means" refers to a device or method for analyzing received data in multiple formats, such as text, audio, images, and video, and understanding its content.

[0099] A "generative AI model" is an artificial intelligence model that generates scenarios, characters, and environments based on analyzed data, and builds overall virtual reality content.

[0100] A "means for generating virtual reality content" is a device or method for generating a virtual reality experience based on the analyzed and synthesized data.

[0101] A "means for packaging and providing virtual reality content to a user" is a device or method for converting the generated virtual reality content into a format that can be experienced by a user and providing it to a user.

[0102] A "dedicated analysis module" is a separate piece of software or equipment that is specialized for analyzing each data format, such as text, audio, images, and video.

[0103] "Virtual reality experience" refers to interactive content that allows users to immerse themselves in a virtual environment and experience it as if it were real through their senses, such as sight and hearing.

[0104] The system of the present invention receives input data such as text, audio, images, and videos provided by users, analyzes and integrates them to generate virtual reality (VR) content, and provides it to users. This system mainly consists of three main components: a terminal, a server, and a user.

[0105] System Configuration

[0106] Terminal functions

[0107] The terminal provides an interface for receiving input from the user. Through the user interface, the user can send data such as text, audio, images, and videos to the system. The terminal temporarily stores the received data and sends it to the server. Specifically, the user can enter text such as "A pirate's treasure-hunting adventure" through the application, record the "sound of waves" using the voice recording function, and upload images and videos using the file selection dialog.

[0108] Server-side features

[0109] The server receives data sent from the terminal and has many analysis modules for analyzing it. The server uses the following analysis modules to analyze the data in detail.

[0110] The text analysis module uses natural language processing technology to analyze the input text and understand the meaning and context of the text.

[0111] The speech analysis module converts the provided speech data into acoustic features and understands the content.

[0112] The image analysis module extracts object and scene features from images.

[0113] The video analysis module analyzes the video frame by frame to understand the content of the scene.

[0114] The analyzed data is integrated on the server and passed to a generative AI model. The generative AI model generates scenarios, characters, and environments based on the integrated data to build the overall VR content. For example, a pirate adventure may unfold based on the generated scenario, with sound effects like the sound of waves playing in real time. Images of ships may also be set as backgrounds, and treasure hunt videos may be incorporated as part of the scenario.

[0115] Providing VR content

[0116] The server packages the generated VR content and converts it into a format that can be experienced by the user. This packaged VR content is sent to the terminal, which displays it on the VR device. The user can then experience a customized pirate adventure using the VR device. For example, when the user puts on the VR goggles, they can immerse themselves in the pirate world and enjoy the adventure through realistic sights and sounds.

[0117] Prompt Sentence Examples

[0118] Examples of prompts to input into a generative AI model include:

[0119] example:

[0120] "Generate virtual reality content for a story about pirates searching for treasure. Use 'A pirate's treasure-hunting adventure' for the text, 'The sound of waves' for the audio, 'A ship' for the image, and 'A treasure-hunting scene' for the video."

[0121] In this way, users can easily create and enjoy personalized VR experiences using data in a variety of formats.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Program processing flow

[0124] Step 1: Getting User Input

[0125] Step 2: Sending data

[0126] Step 3: Analyze the data

[0127] Step 4: Integrate the data

[0128] Step 5: Generate VR content

[0129] Step 6: Providing VR content

[0130] Detailed explanation of the processing steps

[0131] Step 1: Getting User Input

[0132] The terminal receives input data such as text, audio, images, and video through a user interface.

[0133] Input: User input of text, audio, images, and video

[0134] How it works: A user interacts with the application, enters "A pirate's treasure hunting adventure" into the text field, records the sound of "waves" using the voice recorder, and uploads image and video files.

[0135] Output: Text, audio, image, and video data temporarily stored on the device

[0136] Step 2: Sending data

[0137] The terminal transmits the temporarily stored data to the server.

[0138] Input: Stored text, audio, image, and video data

[0139] How it works: When the user presses the "upload" button, the device makes an HTTP request and sends the data to the server.

[0140] Output: Text, audio, image, and video data sent to the server

[0141] Step 3: Analyze the data

[0142] The server allocates the received data to each dedicated analysis module for analysis.

[0143] Input: Text, audio, image, and video data sent from your device

[0144] Operation: The server analyzes text using the text analysis module, converts audio data into acoustic features using the audio analysis module, extracts image features using the image analysis module, and analyzes video scenes using the video analysis module.

[0145] Output: Analysis result data from each analysis module

[0146] Step 4: Integrate the data

[0147] The server integrates the data obtained from each analysis module.

[0148] Input: Analysis result data from the analysis module

[0149] How it works: The analysis results are compiled into a single data structure, adjusted into a unified scenario and character configuration, and passed to a generative AI model.

[0150] Output: The aggregated data passed to the generative AI model

[0151] Step 5: Generate VR content

[0152] The generative AI generates VR content based on the integrated data.

[0153] Input: Integrated data

[0154] How it works: Generative AI generates scenarios, characters, and environments, combining content such as pirate adventures and the sound of waves to build an overall VR story.

[0155] Output: Generated VR content

[0156] Step 6: Providing VR content

[0157] The server packages the generated VR content and converts it into a format that can be delivered to the user.

[0158] Input: Generated VR content

[0159] How it works: The server packages the VR content and sends it to the device. The device displays the received content on the VR device. The user puts on the VR device and experiences the content.

[0160] Output: VR content that users can experience

[0161] Through these steps, users can create and enjoy personalized virtual reality experiences using data in a variety of formats.

[0162] (Application example 1)

[0163] 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."

[0164] In recent years, the demand for personalized content based on user interests and preferences has been growing rapidly. However, traditional content delivery services are limited to static text, images, and standard video streaming, making it difficult for users to achieve a more immersive experience. Furthermore, technologies for analyzing and integrating diverse inputs from multiple media formats to generate high-quality virtual reality (VR) content are limited. This calls for innovation to improve user satisfaction.

[0165] 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.

[0166] In this invention, the server includes means for receiving input in multiple forms such as text, audio, images, and videos from the user, data analysis means for analyzing the input in multiple forms and understanding its content, generation means for generating virtual reality content based on the analyzed data, and provision means for providing the generated virtual reality content to the user. This makes it possible to generate a personalized and immersive virtual reality experience based on the various data provided by the user and quickly provide it to the user.

[0167] 1. "Multiple forms of input" refers to different types of data provided by users, such as text, audio, images, and video.

[0168] 2. "Data Analysis Tools" are modules and algorithms used to analyze and understand multiple forms of input.

[0169] 3. "Generation means" means modules or algorithms for generating virtual reality content based on analyzed data.

[0170] 4. "Provision means" refers to the interface and communication means used to provide the generated virtual reality content to the user.

[0171] 5. "Data for customizing news content" refers to input data used to identify news and information that the user is interested in and reflect that in the VR footage.

[0172] 6. "Analysis module" refers to a program or algorithm for performing specialized analysis for each format, such as text, audio, image, or video.

[0173] 7. "Interface" means the operating screen or input device through which a user uploads text, audio, images, or video.

[0174] 8. "VR Video" means visual content created to provide users with a virtual reality experience.

[0175] 9. "Server" means a computer system that receives input data from users, analyzes it, and provides generated VR content.

[0176] The system of this invention generates virtual reality (VR) content based on input data in various formats and provides it to users. The system mainly consists of the following elements.

[0177] 1. Getting User Input

[0178] The terminal provides a means to receive multiple forms of input from the user, including text, audio, images, video, etc. Through this interface, the user can upload data in various forms.

[0179] 2. Data Analysis

[0180] The server receives the data sent from the device and analyzes it using a dedicated analysis module for each format. Different modules, such as text analysis, audio analysis, image analysis, and video analysis, are combined to gain a detailed understanding of the data's content. Specifically, natural language processing (NLP) models are used for text analysis, speech recognition APIs for audio analysis, image recognition algorithms (e.g., TensorFlow) for image analysis, and frame analysis tools (e.g., OpenCV) for video analysis.

[0181] 3. VR content generation

[0182] The analyzed data is integrated and input into a generative AI model, which generates scenarios, characters, and environments based on the integrated data to construct the overall VR content, which is then packaged on a server and converted into a tangible form.

[0183] 4. Provision of VR content

[0184] The server sends the generated VR content to the terminal, which then displays it on the VR device. The user experiences the generated content through the VR device. For example, they can immerse themselves in the virtual reality world using a VR headset (e.g., Oculus Quest).

[0185] Specific examples

[0186] Let's say a user wants to create a "pirate treasure hunting story" and provides the text "pirate treasure hunting adventure," the audio "sound of waves," the image "ship," and the video "treasure hunting scene." This input data is sent to the server and analyzed appropriately by each analysis module. Based on the analysis results, the generation AI generates an active pirate scenario and environment, adding the sound of waves as a sound effect. The server integrates this and packages it into a single VR content, which is then sent to the device. The user can then experience this customized adventure through their VR device.

[0187] Prompt Sentence Examples

[0188] The prompt text that the user enters will be in the following format:

[0189] "Text": "Pirate Treasure Adventure",

[0190] "Audio file": "wave_sound.mp3",

[0191] "Image file": "pirate_ship.png",

[0192] "video file": "treasure_hunt.mp4"

[0193] In this way, a personalized virtual reality experience tailored to individual preferences is generated based on the data provided by the user.

[0194] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0195] Step 1:

[0196] User data entry and upload

[0197] The user provides input data in multiple formats, including text, audio, images, and video, through the device interface. This data is temporarily stored on the device. Specifically, the user uploads the text "Pirate's Treasure Hunt Adventure," the audio "Sound of Waves," the image "Ship," and the video "Treasure Hunt Scene." The input data at this point is in the form of files or strings of various formats, and the output is a temporary file or memory storage.

[0198] Step 2:

[0199] Sending data to the server

[0200] The device sends the temporarily stored user data to the server. The server receives the data sent from the device and prepares it for analysis. At this time, each piece of data is assigned to the appropriate analysis module. The input is the user's data file, and the output is the transfer of data to the analysis module on the server.

[0201] Step 3:

[0202] Data analysis

[0203] Each analysis module in the server analyzes the received data. Specifically, the text analysis module uses natural language processing (NLP) to analyze text based on context, the audio analysis module converts audio content into text using a speech recognition API, the image analysis module extracts image features using an image recognition algorithm, and the video analysis module analyzes video scenes using a frame analysis tool. The input data are files of various formats and their content information, and the output is the analysis results (e.g., text, metadata, feature vectors, etc.).

[0204] Step 4:

[0205] Input to generative AI models

[0206] The analysis results of each data obtained from the analysis module are integrated and input into the generative AI model. The generative AI model generates scenarios, characters, and environments based on the integrated data to construct the overall VR content. The input of this step is the integrated analysis results, and the output is the constituent data of the generated VR content.

[0207] Step 5:

[0208] Packaging VR content and converting it on the server

[0209] The server packages the generated VR content and converts it into a format that can be displayed on the user's device, such as packaging scenario text, audio files, 3D models, scene data, etc. The input of this step is the configuration data of the generated VR content, and the output is a packaged VR content file.

[0210] Step 6:

[0211] Content provision

[0212] The server sends the packaged VR content to the terminal. The terminal displays the received VR content on a VR device (e.g., a VR headset) and provides it to the user. At this point, the user can enjoy the generated virtual reality experience. The input is the packaged VR content file, and the output is a display of the content.

[0213] Through these steps, a personalized and immersive virtual reality experience is generated based on the data provided by the user. For example, a virtual reality experience of a pirate's treasure hunt can be created.

[0214] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0215] The system of the present invention analyzes and integrates user inputs such as text, voice, images, and video to generate and provide personalized virtual reality (VR) content. Furthermore, by incorporating an emotion engine, the system is equipped with the ability to recognize user emotions and adjust content accordingly. The system primarily consists of three main components: a terminal, a server, and a user.

[0216] System Configuration

[0217] 1. Terminal functions

[0218] The device provides an interface that receives input from the user. Through this interface, the user can upload data such as text, audio, images, and video. The device temporarily stores the received data and transmits it to the server.

[0219] 2. Server-side functionality

[0220] The server receives the data sent from the device and distributes it to the analysis module corresponding to each format. It also has a built-in emotion engine that analyzes emotions based on the user's input data.

[0221] Data Analysis Modules: The text analysis module understands the context and keywords of a sentence, the audio analysis module analyzes sound features, the image analysis module recognizes image features, and the video analysis module analyzes movie sequences.

[0222] Emotion Engine: Analyzes emotions from text and voice to determine the user's state. The emotion engine can understand whether the user is amused, surprised, or in any other emotional state.

[0223] The analysis results are then integrated and fed into a generative AI model, which generates VR content such as scenarios, characters, and environments based on the analysis results, adjusting the content to suit the user's emotional state as needed.

[0224] 3. Providing a user experience

[0225] The user experiences the generated content through a VR device. The server sends the generated VR content to the terminal, which then displays it on the VR device. The user's emotional feedback is also taken into account, and the content is adjusted in real time as needed.

[0226] Program processing explanation

[0227] The specific process flow for a user to customize their VR experience is as follows:

[0228] Getting User Input

[0229] The device receives text, audio, image, and video input through a user interface. The user uploads these materials, which the device temporarily stores.

[0230] Data analysis and emotion recognition

[0231] The server receives the data sent from the terminal and assigns the data to an analysis module corresponding to each format: text analysis module, audio analysis module, image analysis module, and video analysis module.

[0232] The emotion engine performs emotional analysis based on user input data (especially text and voice) to identify emotional states. For example, it analyzes the tone and pitch of a user's voice to determine whether they are excited or relaxed.

[0233] Data integration and VR content generation

[0234] The server integrates the data obtained from the analysis module and emotion engine and passes it to the generative AI model. The generative AI generates virtual reality content based on this data. Based on the results of the emotion engine, a scenario and environment adapted to the user's emotional state are set up.

[0235] Providing VR content

[0236] The generative AI generates a personalized VR experience based on the user's emotional state, and this generated content is packaged on the server and sent to the device.

[0237] The terminal prepares the received VR content for display on the VR device. The user experiences the generated content through the VR device, and emotional changes are monitored in real time.

[0238] Specific examples

[0239] For example, if a user wants to create a "story about pirates searching for treasure," and provides "pirate's treasure-hunting adventure" in text, "sound of waves" in audio, "ship" in images, and "treasure hunting scene" in video, this input data is sent to the server.

[0240] The server analyzes this data through each analysis module, and the emotion engine analyzes the user's expectations and excitement. The analysis results are integrated and a personalized VR experience is generated by the generative AI. This generated content is sent to the terminal and displayed on the VR device.

[0241] As the user experiences this customized adventure through the VR device, their emotional state is continuously monitored and the content is adjusted accordingly. For example, if the system determines that the user is bored, it will add new, interesting scenarios or surprise elements. In this way, the system provides a personalized VR experience that dynamically changes based on the user's emotions.

[0242] The processing flow will be explained below.

[0243] Step 1:

[0244] The device displays a screen for uploading text, audio, images, and videos to the user, allowing them to select and upload the materials for their desired VR experience.

[0245] Step 2:

[0246] Users select the material they want and upload it to their device in the form of text, audio, images, or video. For example, text can be used to provide a story, audio can be used to provide an ambient sound, images can be used to provide a scene, and video can be used to provide a moving sequence.

[0247] Step 3:

[0248] The device temporarily stores the text, audio, images, and video provided by the user and prepares them for transmission. During this step, the data format of each material is checked for any errors.

[0249] Step 4:

[0250] The terminal transmits the saved data to the server, along with the data format information.

[0251] Step 5:

[0252] The server receives the data sent from the device, classifies it by type, and assigns it to the appropriate analysis module.

[0253] Step 6:

[0254] The server sends the text data to the text analysis module, which then extracts the context and keywords from the text and creates the outline of the scenario.

[0255] Step 7:

[0256] The server sends the audio data to the audio analysis module, which then extracts the audio characteristics and recognizes them as environmental sounds or sound effects.

[0257] Step 8:

[0258] The server sends the image data to the image analysis module, which analyzes the image for features and components and uses them to design scenes and characters.

[0259] Step 9:

[0260] The server sends the video data to the video analysis module, which then extracts movie sequences and uses them as material for storyboards and animations.

[0261] Step 10:

[0262] The analysis results sent from the analysis modules are integrated into the server, which then aggregates them and passes the unified data set to the generative AI model.

[0263] Step 11:

[0264] The server sends the text and voice data to the emotion engine, which then analyzes the user's emotional state from the text and voice data to determine emotions such as joy, surprise, and sadness.

[0265] Step 12:

[0266] The generative AI model generates VR content such as scenarios, characters, and environments based on the results of the integrated dataset and emotion engine, and can also adjust the content based on the user's emotional state.

[0267] Step 13:

[0268] The server packages the generated VR content in real time and converts it into a format that can be experienced by the user, and the packaged content is saved in the optimal format.

[0269] Step 14:

[0270] The server transmits the packaged VR content to the device, which receives the data.

[0271] Step 15:

[0272] The terminal transfers the received VR content to the VR device and prepares it for display, at which point the user interface is updated to display the option to start the experience.

[0273] Step 16:

[0274] The user experiences the generated content using a VR device, and the emotion engine monitors the user's emotional state during the experience and adjusts the content accordingly.

[0275] Step 17:

[0276] Users can provide feedback after their experience, which is sent to the server via their device and used to improve the experience and generate new content.

[0277] Example 2

[0278] 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."

[0279] In modern virtual reality (VR) technology, it is important to provide users with personalized content. However, there are still many shortcomings in the technology for receiving and analyzing user input data in multiple formats, and then generating and adjusting content based on the user's emotional state. In particular, implementing a system that adapts to the user's emotional feedback in real time is challenging. Therefore, more advanced and flexible analysis and generation mechanisms are needed to improve the quality of the user experience.

[0280] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving input in multiple forms, such as text, audio, images, and videos, from the user; data analysis and emotion analysis means for analyzing the input in multiple forms, understanding its content, and determining the user's emotional state; generation means for generating virtual reality content using a generative AI model based on the analyzed data and the emotion analysis results; and provision means for providing the generated virtual reality content to the user. This makes it possible to analyze the user's input data in multiple forms in detail and generate and provide personalized VR content based on the results and the user's emotional state.

[0281] "User Input" refers to information provided by users in multiple formats, including text, audio, images, and video.

[0282] "Data analysis and emotion analysis means" refers to technology that analyzes multiple forms of input from users, understands their content, and determines their emotional state.

[0283] A "generative AI model" is an artificial intelligence technology that automatically generates virtual reality content based on analyzed data and emotion analysis results.

[0284] "Virtual reality content" refers to digital content, including scenarios, characters, environments, etc., that users experience through VR devices.

[0285] "Providing means" refers to the technology used to transmit the generated virtual reality content to the user's terminal and display it on the VR device.

[0286] "Emotional feedback" refers to the emotional changes and reactions that users display while experiencing virtual reality content.

[0287] The system of the present invention analyzes and integrates user inputs such as text, voice, images, and video to generate and provide personalized virtual reality (VR) content. Furthermore, by incorporating an emotion engine, the system is equipped with the ability to recognize user emotions and adjust content accordingly.

[0288] System Configuration

[0289] This system mainly consists of three main elements: terminals, servers, and users.

[0290] 1. Terminal functions

[0291] The device provides an interface that receives input from the user. Through this interface, the user can upload data such as text, audio, images, and video. The device temporarily stores the received data and transmits it to the server.

[0292] 2. Server-side functionality

[0293] The server receives the data sent from the device and distributes it to the analysis module corresponding to each format. It also has a built-in emotion engine that analyzes emotions based on the user's input data.

[0294] Data Analysis Module

[0295] The text analysis module understands the context and keywords of the text.

[0296] The audio analysis module analyzes the characteristics of the sound.

[0297] The image analysis module recognizes features in the image.

[0298] The video analysis module analyzes movie sequences.

[0299] Emotion Engine

[0300] Emotions are analyzed from text and voice to determine the user's state. The emotion engine can determine whether the user is amused, surprised, or in some other emotional state. The analysis results are integrated and passed to a generative AI model. This generative AI generates VR content such as scenarios, characters, and environments based on the analysis results, and adjusts the content to match the user's emotional state as needed.

[0301] 3. Providing a user experience

[0302] The user experiences the generated content through a VR device. The server sends the generated VR content to the terminal, which then displays it on the VR device. The user's emotional feedback is also taken into account, and the content is adjusted in real time as needed.

[0303] Specific examples

[0304] For example, if a user wants to create a "pirate treasure hunting story" and provides the following input:

[0305] Text: "A pirate's treasure hunting adventure"

[0306] Audio: "Sound of waves"

[0307] Image: "Ship"

[0308] Video: "Treasure Hunt Scene"

[0309] These input data are sent to the server, where each analysis module analyzes the data, and the emotion engine analyzes the user's expectations and excitement. The analysis results are integrated, and a personalized VR experience is generated by the generative AI. This generated content is sent to the terminal, where it is displayed on the VR device.

[0310] As the user experiences this customized adventure through the VR device, their emotional state is continuously monitored and the content is adjusted accordingly. For example, if the system determines that the user is bored, it will add new, interesting scenarios or surprise elements. In this way, the system provides a personalized VR experience that dynamically changes based on the user's emotions.

[0311] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0312] Step 1:

[0313] The terminal receives text, audio, image, and video input through a user interface. The user provides these materials to the terminal by entering text in a text field and uploading audio files, image files, and video files. For example, the user enters "A pirate's treasure hunting adventure" in a text field and uploads an audio file of the sound of waves, an image file of a ship, and a video file of a treasure hunting scene. The terminal temporarily stores them and compiles them to be sent to the server as a transaction.

[0314] Step 2:

[0315] The device sends the temporarily stored data to the server. Communication is performed using a secure protocol (e.g., HTTPS). For example, the device compresses text, audio, image, and video files and sends them to the server. The input is various media files obtained from the user, and the output is a data package sent to the server.

[0316] Step 3:

[0317] The server receives data packages sent from the terminal. The data packages include text, audio, image, and video files. The server then assigns these different types of data to the respective analysis modules. The input is the data package received from the terminal, and the output is the data of each type assigned to the analysis module.

[0318] Step 4:

[0319] The text analysis module analyzes the received text data. For example, it analyzes the text "A pirate's treasure-hunting adventure" and extracts key keywords such as "pirate," "treasure," and "adventure." Based on this, it identifies the basic elements for generating a scenario. The input is text data, and the output is the extracted keywords and contextual information.

[0320] Step 5:

[0321] The audio analysis module analyzes the received audio data. For example, it analyzes the sound of waves, identifies their rhythm and pitch, and extracts elements that recreate a seaside environment. The input is audio data, and the output is sound feature information.

[0322] Step 6:

[0323] The image analysis module analyzes the received image data. For example, it analyzes an image of a ship to identify its shape, color, and background information, which are then used to create a 3D model. The input is image data, and the output is image feature information.

[0324] Step 7:

[0325] The video analysis module analyzes the received video data. For example, it analyzes a video of a treasure hunt scene frame by frame to identify sequences and important actions. The input is the video data, and the output is sequence information and information identifying important actions.

[0326] Step 8:

[0327] The emotion engine analyzes the user's emotional state based on the received text and voice data. For example, if the user speaks in an excited tone, it determines that the user is excited. The input is text and voice data, and the output is information about the user's emotional state.

[0328] Step 9:

[0329] The server integrates the data obtained from the analysis modules and emotion engine and passes it to the generative AI model. For example, it combines the analysis results of text, audio, images, and video, along with emotional state information, into a single data package. The input is the output from each analysis module and emotion engine, and the output is the integrated data package.

[0330] Step 10:

[0331] The generative AI model generates virtual reality content based on a provided data package. For example, it creates a 3D model, scenario, and environment setting based on a "pirate treasure hunting adventure" scenario. The input is the integrated data package, and the output is the generated virtual reality content.

[0332] Step 11:

[0333] The server packages the generated virtual reality content and transmits it to the terminal, for example, by encoding the generated content into an appropriate format and compressing it for transmission to the terminal, where the input is the generated virtual reality content and the output is the data package transmitted to the terminal.

[0334] Step 12:

[0335] The terminal provides the received virtual reality content to the VR device. The terminal unpacks the received content and streams it to the VR device for display. The input is the data package received from the server, and the output is the virtual reality content experienced by the user.

[0336] Step 13:

[0337] The server monitors emotional changes during the user experience and adjusts the content in real time as needed. For example, if it determines that the user is bored, it adds new, interesting scenarios or surprise elements. It issues commands to the generative AI to do so. The input is the user's emotional feedback, and the output is the adjusted virtual reality content.

[0338] (Application example 2)

[0339] 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."

[0340] Conventional virtual reality (VR) content generation systems have the ability to analyze user input data and generate content, but it is difficult to dynamically adjust the content according to the user's emotions. Furthermore, to improve the shopping experience in brick-and-mortar stores, personalized information provision that takes into account the user's emotional state is required. Therefore, a system that recognizes the user's emotions and dynamically adjusts VR content based on those emotions is needed.

[0341] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input in multiple forms from the user, such as text, audio, images, and videos; data analysis means for analyzing the input in multiple forms and understanding its content; generation means for generating virtual reality content based on the analyzed data; and emotion recognition means for analyzing the user's emotions and dynamically adjusting the virtual reality content based on the analysis results. This makes it possible to provide seamless and personalized VR content according to the user's emotional state.

[0342] "Text input" is data in the form of text from the user.

[0343] "Voice input" refers to sound data from a user, particularly data that refers to spoken words.

[0344] "Image input" is still image data from the user.

[0345] "Video input" is video data from the user.

[0346] "Data analysis means" is a function for analyzing input data in multiple formats and understanding its contents.

[0347] "Generation means" is a function for generating virtual reality content based on analyzed data.

[0348] "Providing means" is a function for providing the generated virtual reality content to the user.

[0349] The "emotion recognition means" is a function for analyzing the user's emotions and dynamically adjusting the virtual reality content based on the analysis results.

[0350] "Interface" means the means by which a User can upload text, audio, image, or video data.

[0351] An "analysis module" is a dedicated function for analyzing data in a specific format (text, audio, image, video).

[0352] The system of the present invention is designed to enhance the user's shopping experience in a physical store. Specifically, smart glasses can be used to provide detailed product information and related content in real time when the user views the product. The system consists of the following main components: a user, a terminal (smart glasses), and a server.

[0353] System Configuration

[0354] 1. Terminal features:

[0355] The smart glasses, which are the terminal, provide an interface that receives text, voice, image, and video input from the user. When a user sees a product, they can ask questions by voice or input text to get more information about it. The smart glasses are equipped with a camera and microphone, which capture video and audio data.

[0356] 2. Server-side functionality:

[0357] The server receives and analyzes data sent from the device. Specifically, it has the following functions:

[0358] - Data Analysis Modules: Data is analyzed using dedicated analysis modules for text, audio, image, and video formats. The text analysis module understands the context and keywords of the text, the audio analysis module analyzes sound features, the image analysis module recognizes image features, and the video analysis module analyzes movie sequences.

[0359] - Emotion recognition means: The device incorporates an emotion engine to analyze emotions from user input data, for example, analyzing the tone and pitch of a user's voice from audio data to identify the user's emotional state.

[0360] - Generation method: Based on the analysis results, a generative AI model is used to generate personalized virtual reality content for the user, dynamically adjusting the scenario, characters, environment, etc. based on the user's emotional state.

[0361] Specific examples

[0362] As a user looks at clothes in a store, detailed information about the clothes is displayed through the smart glasses. For example, they can input text such as "What are the characteristics of this clothing?" and ask by voice, "Is this color trendy?". Furthermore, the glasses provide data such as "This is my favorite color" through images and "This is the latest trend in styles" through videos.

[0363] The server receives this data and analyzes it using the data analysis module. The emotion engine analyzes the user's excitement and interest, and the generative AI model generates appropriate VR content based on the analysis results. The generated content is instantly sent to the smart glasses and displayed in the user's field of view. The user's emotional state is monitored in real time, and if they are excited, new promotional information or interesting products are recommended.

[0364] Prompt Sentence Examples

[0365] "Generate a program for a system that inputs and analyzes detailed text information, related audio descriptions, and related images and videos about the clothes a user is looking at through smart glasses, and provides personalized information in real time according to the user's level of excitement and interest."

[0366] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0367] Step 1:

[0368] Users input text, voice, image, and video data through the smart glasses, which are then captured by the user interface and temporarily stored on the device. For example, a user might enter text such as "What are the characteristics of this clothing item?" and ask a voice question such as "Is this color trendy?"

[0369] Step 2:

[0370] The device sends the captured data to the server. Specifically, audio data, text data, image data, and video data are transferred to the server. At this stage, the input data arrives at the server.

[0371] Step 3:

[0372] The server distributes the received data to the data analysis modules. The text analysis module understands the context and keywords of the text, the audio analysis module analyzes the sound characteristics, the image analysis module recognizes the image characteristics, and the video analysis module analyzes the movie sequence. This analyzes the input data and provides the analysis results corresponding to each type of data. The output is the analyzed text, audio, image, and video information.

[0373] Step 4:

[0374] The server's emotion recognition means identifies the user's emotional state from the analyzed data. It analyzes the user's emotions, such as excitement or relaxation, based on the tone and pitch of the voice data and the content of the text data. The user's emotional state is identified as the output.

[0375] Step 5:

[0376] The server passes the analysis results and emotional state data to a generative AI model to generate personalized VR content for the user. The generative AI model then configures a scenario, characters, and environment that adapts to the user's emotional state. This generates personalized VR content. The output is VR content that matches the user's emotional state.

[0377] Step 6:

[0378] The server sends the generated VR content to the device, which then prepares the received VR content for display on the smart glasses. As an output, the displayable VR content is prepared.

[0379] Step 7:

[0380] The device displays the user-generated VR content through smart glasses. As the user experiences the VR content, their emotional state is monitored in real time based on their experience. If the user's excitement level is high, new information or interesting promotions will be displayed. In this way, the user receives a dynamically generated personalized shopping experience.

[0381] This processing step allows users to enjoy a personalized shopping experience in physical stores that is tailored to their emotional state.

[0382] 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.

[0383] 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.

[0384] 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.

[0385] [Second embodiment]

[0386] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0387] 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.

[0388] 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).

[0389] 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.

[0390] 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.

[0391] 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).

[0392] 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.

[0393] 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.

[0394] 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.

[0395] 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.

[0396] In the smart glasses 214, 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.

[0397] 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."

[0398] The system of the present invention receives inputs such as text, voice, images, and videos provided by users, analyzes and integrates them to generate virtual reality (VR) content, and provides it to users. This system mainly consists of three main components: a terminal, a server, and a user.

[0399] System Configuration

[0400] 1. Terminal functions

[0401] The terminal provides an interface for receiving input from the user. Through this interface, the user can send data such as text, audio, images, and video to the system. The terminal also temporarily stores the received data and sends it to the server.

[0402] 2. Server-side functionality

[0403] The server has many analysis modules that receive and analyze data sent from the device. The server uses text analysis, voice analysis, image analysis, and video analysis modules to perform detailed analysis of user input, making it easier to understand the user's intent and the context of the data.

[0404] The analyzed data is then passed to the generation AI, which generates scenarios, characters, and environments based on the analysis results to create virtual reality content. The generated content is then packaged on the server and converted into a format that can be provided to users.

[0405] 3. Providing a user experience

[0406] Users experience the generated content through a VR device. The server sends the completed VR content to the terminal, which then displays it on the VR device. Users can then use the VR device to enjoy the virtual experience.

[0407] Program processing explanation

[0408] The specific process is as follows:

[0409] Getting User Input

[0410] The device receives text, audio, images, and video through the user interface. When the user uploads this data, the device temporarily stores it and sends it to the server.

[0411] Data analysis and integration

[0412] The server receives data sent from the device and assigns it to an analysis module according to the data format. The text analysis module analyzes the input text and understands the context. The audio analysis module analyzes the provided audio data and understands the sound content. The image analysis module extracts image features, and the video analysis module analyzes video scenes.

[0413] The data obtained from the analysis module is integrated on the server and passed to a generative AI model, which uses the integrated data to generate scenarios, characters, and environments, building the overall VR content.

[0414] VR content generation and provision

[0415] Generative AI creates a personalized VR experience based on the user's intent, including a pirate treasure hunt story, realistic ocean sounds, ship images, and a treasure hunt movie.

[0416] The server packages the generated VR content and converts it into a format that can be experienced by the user. The packaged VR content is then sent to the terminal, which displays it on the VR device.

[0417] Specific examples

[0418] For example, suppose a user wants to create a "pirate treasure hunting story" and provides the text "pirate treasure hunting adventure," the audio "sound of waves," the image "ship," and the video "treasure hunting scene." This input data is sent to the server and analyzed appropriately by each analysis module. Based on the analysis results, the generation AI generates an active pirate scenario and environment, adding the sound of waves as a sound effect. The server integrates this and packages it into a single VR content, which is then sent to the device. The user can then experience this customized adventure through their VR device.

[0419] As described above, the system of the present invention allows users to easily create and enjoy personalized VR experiences.

[0420] The processing flow will be explained below.

[0421] Step 1:

[0422] The device displays a screen for uploading text, audio, images, and videos to the user, allowing them to select and upload the materials for the VR experience they want to create.

[0423] Step 2:

[0424] Users select the desired material and upload it to their device in the form of text, audio, images, or video. For example, text can be used to provide a story, audio can be used to provide an ambient sound, images can be used to provide a scene, and video can be used to provide a moving sequence.

[0425] Step 3:

[0426] The device temporarily stores the text, audio, images, and video provided by the user and prepares them for transmission. In this step, the data format of each material is checked for any errors.

[0427] Step 4:

[0428] The device sends the saved data to the server, along with the classification information of the data.

[0429] Step 5:

[0430] The server receives the data sent from the device, classifies it by type, and assigns it to the appropriate analysis module.

[0431] Step 6:

[0432] The server sends the text data to the text analysis module, which then extracts the context and keywords from the text and creates the outline of the scenario.

[0433] Step 7:

[0434] The server sends the audio data to the audio analysis module, which then extracts the audio characteristics and recognizes them as environmental sounds or sound effects.

[0435] Step 8:

[0436] The server sends the image data to the image analysis module, which analyzes the image for features and components and uses them as scene and character designs.

[0437] Step 9:

[0438] The server sends the video data to the video analysis module, which then extracts movie sequences and uses them as material for storyboards and animations.

[0439] Step 10:

[0440] The analysis results sent from the analysis modules are integrated into the server, which then aggregates them and passes the unified data set to the generative AI model.

[0441] Step 11:

[0442] The generative AI model generates VR content such as scenarios, characters, and environments based on the integrated dataset, and interactive elements are also created during this step.

[0443] Step 12:

[0444] The server packages the generated VR content and converts it into a format that can be experienced by the user, and saves the packaged content in the optimal format.

[0445] Step 13:

[0446] The server transmits the packaged VR content to the device, which receives the data.

[0447] Step 14:

[0448] The terminal transfers the received VR content to the VR device and prepares it for display, at which point the user interface is updated to display the option to start the experience.

[0449] Step 15:

[0450] Users use VR devices to experience the generated content, and their movements and reactions are collected and reflected in the interactive elements.

[0451] Step 16:

[0452] Users can provide feedback after their experience, which is sent to the server via their device and used to improve the experience and generate new content.

[0453] Example 1

[0454] 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."

[0455] Conventional virtual reality content generation systems have difficulty effectively analyzing and integrating diverse forms of data from users to provide personalized virtual reality experiences tailored to their individual needs. Furthermore, the content generation process is complex, making it difficult to generate consistent scenarios and characters.

[0456] 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.

[0457] In this invention, the server includes a means for receiving input in multiple forms from a user, such as text, audio, images, and videos, a data analysis means for analyzing the input in multiple forms and understanding its content, a means for integrating the analyzed data and generating virtual reality content based on a generative AI model, and a means for packaging the generated virtual reality content and providing it to the user, thereby enabling the user to easily generate and enjoy a personalized virtual reality experience using data in various forms.

[0458] A "means for receiving multiple forms of input from a user, such as text, audio, images, and video" is a device or method that provides an interface for receiving different forms of data, such as text, audio, images, and video, input from a user.

[0459] "Data analysis means" refers to a device or method for analyzing received data in multiple formats, such as text, audio, images, and video, and understanding its content.

[0460] A "generative AI model" is an artificial intelligence model that generates scenarios, characters, and environments based on analyzed data, and builds overall virtual reality content.

[0461] A "means for generating virtual reality content" is a device or method for generating a virtual reality experience based on the analyzed and synthesized data.

[0462] A "means for packaging and providing virtual reality content to a user" is a device or method for converting the generated virtual reality content into a format that can be experienced by a user and providing it to a user.

[0463] A "dedicated analysis module" is a separate piece of software or equipment that is specialized for analyzing each data format, such as text, audio, images, and video.

[0464] "Virtual reality experience" refers to interactive content that allows users to immerse themselves in a virtual environment and experience it as if it were real through their senses, such as sight and hearing.

[0465] The system of the present invention receives input data such as text, audio, images, and videos provided by users, analyzes and integrates them to generate virtual reality (VR) content, and provides it to users. This system mainly consists of three main components: a terminal, a server, and a user.

[0466] System Configuration

[0467] Terminal functions

[0468] The terminal provides an interface for receiving input from the user. Through the user interface, the user can send data such as text, audio, images, and videos to the system. The terminal temporarily stores the received data and sends it to the server. Specifically, the user can enter text such as "A pirate's treasure-hunting adventure" through the application, record the "sound of waves" using the voice recording function, and upload images and videos using the file selection dialog.

[0469] Server-side features

[0470] The server receives data sent from the terminal and has many analysis modules for analyzing it. The server uses the following analysis modules to analyze the data in detail.

[0471] The text analysis module uses natural language processing technology to analyze the input text and understand the meaning and context of the text.

[0472] The speech analysis module converts the provided speech data into acoustic features and understands the content.

[0473] The image analysis module extracts object and scene features from images.

[0474] The video analysis module analyzes the video frame by frame to understand the content of the scene.

[0475] The analyzed data is integrated on the server and passed to a generative AI model. The generative AI model generates scenarios, characters, and environments based on the integrated data to build the overall VR content. For example, a pirate adventure may unfold based on the generated scenario, with sound effects like the sound of waves playing in real time. Images of ships may also be set as backgrounds, and treasure hunt videos may be incorporated as part of the scenario.

[0476] Providing VR content

[0477] The server packages the generated VR content and converts it into a format that can be experienced by the user. This packaged VR content is sent to the terminal, which displays it on the VR device. The user can then experience a customized pirate adventure using the VR device. For example, when the user puts on the VR goggles, they can immerse themselves in the pirate world and enjoy the adventure through realistic sights and sounds.

[0478] Prompt Sentence Examples

[0479] Examples of prompts to input into a generative AI model include:

[0480] example:

[0481] "Generate virtual reality content for a story about pirates searching for treasure. Use 'A pirate's treasure-hunting adventure' for the text, 'The sound of waves' for the audio, 'A ship' for the image, and 'A treasure-hunting scene' for the video."

[0482] In this way, users can easily create and enjoy personalized VR experiences using data in a variety of formats.

[0483] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0484] Program processing flow

[0485] Step 1: Getting User Input

[0486] Step 2: Sending data

[0487] Step 3: Analyze the data

[0488] Step 4: Integrate the data

[0489] Step 5: Generate VR content

[0490] Step 6: Providing VR content

[0491] Detailed explanation of the processing steps

[0492] Step 1: Getting User Input

[0493] The terminal receives input data such as text, audio, images, and video through a user interface.

[0494] Input: User input of text, audio, images, and video

[0495] How it works: A user interacts with the application, enters "A pirate's treasure hunting adventure" into the text field, records the sound of "waves" using the voice recorder, and uploads image and video files.

[0496] Output: Text, audio, image, and video data temporarily stored on the device

[0497] Step 2: Sending data

[0498] The terminal transmits the temporarily stored data to the server.

[0499] Input: Stored text, audio, image, and video data

[0500] How it works: When the user presses the "upload" button, the device makes an HTTP request and sends the data to the server.

[0501] Output: Text, audio, image, and video data sent to the server

[0502] Step 3: Analyze the data

[0503] The server allocates the received data to each dedicated analysis module for analysis.

[0504] Input: Text, audio, image, and video data sent from your device

[0505] Operation: The server analyzes text using the text analysis module, converts audio data into acoustic features using the audio analysis module, extracts image features using the image analysis module, and analyzes video scenes using the video analysis module.

[0506] Output: Analysis result data from each analysis module

[0507] Step 4: Integrate the data

[0508] The server integrates the data obtained from each analysis module.

[0509] Input: Analysis result data from the analysis module

[0510] How it works: The analysis results are compiled into a single data structure, adjusted into a unified scenario and character configuration, and passed to a generative AI model.

[0511] Output: The aggregated data passed to the generative AI model

[0512] Step 5: Generate VR content

[0513] The generative AI generates VR content based on the integrated data.

[0514] Input: Integrated data

[0515] How it works: Generative AI generates scenarios, characters, and environments, combining content such as pirate adventures and the sound of waves to build an overall VR story.

[0516] Output: Generated VR content

[0517] Step 6: Providing VR content

[0518] The server packages the generated VR content and converts it into a format that can be delivered to the user.

[0519] Input: Generated VR content

[0520] How it works: The server packages the VR content and sends it to the device. The device displays the received content on the VR device. The user puts on the VR device and experiences the content.

[0521] Output: VR content that users can experience

[0522] Through these steps, users can create and enjoy personalized virtual reality experiences using data in a variety of formats.

[0523] (Application example 1)

[0524] 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."

[0525] In recent years, the demand for personalized content based on user interests and preferences has been growing rapidly. However, traditional content delivery services are limited to static text, images, and standard video streaming, making it difficult for users to achieve a more immersive experience. Furthermore, technologies for analyzing and integrating diverse inputs from multiple media formats to generate high-quality virtual reality (VR) content are limited. This calls for innovation to improve user satisfaction.

[0526] 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.

[0527] In this invention, the server includes means for receiving input in multiple forms such as text, audio, images, and videos from the user, data analysis means for analyzing the input in multiple forms and understanding its content, generation means for generating virtual reality content based on the analyzed data, and provision means for providing the generated virtual reality content to the user. This makes it possible to generate a personalized and immersive virtual reality experience based on the various data provided by the user and quickly provide it to the user.

[0528] 1. "Multiple forms of input" refers to different types of data provided by users, such as text, audio, images, and video.

[0529] 2. "Data Analysis Tools" are modules and algorithms used to analyze and understand multiple forms of input.

[0530] 3. "Generation means" means modules or algorithms for generating virtual reality content based on analyzed data.

[0531] 4. "Provision means" refers to the interface and communication means used to provide the generated virtual reality content to the user.

[0532] 5. "Data for customizing news content" refers to input data used to identify news and information that the user is interested in and reflect that in the VR footage.

[0533] 6. "Analysis module" refers to a program or algorithm for performing specialized analysis for each format, such as text, audio, image, or video.

[0534] 7. "Interface" means the operating screen or input device through which a user uploads text, audio, images, or video.

[0535] 8. "VR Video" means visual content created to provide users with a virtual reality experience.

[0536] 9. "Server" means a computer system that receives input data from users, analyzes it, and provides generated VR content.

[0537] The system of this invention generates virtual reality (VR) content based on input data in various formats and provides it to users. The system mainly consists of the following elements.

[0538] 1. Getting User Input

[0539] The terminal provides a means to receive multiple forms of input from the user, including text, audio, images, video, etc. Through this interface, the user can upload data in various forms.

[0540] 2. Data Analysis

[0541] The server receives the data sent from the device and analyzes it using a dedicated analysis module for each format. Different modules, such as text analysis, audio analysis, image analysis, and video analysis, are combined to gain a detailed understanding of the data's content. Specifically, natural language processing (NLP) models are used for text analysis, speech recognition APIs for audio analysis, image recognition algorithms (e.g., TensorFlow) for image analysis, and frame analysis tools (e.g., OpenCV) for video analysis.

[0542] 3. VR content generation

[0543] The analyzed data is integrated and input into a generative AI model, which generates scenarios, characters, and environments based on the integrated data to construct the overall VR content, which is then packaged on a server and converted into a tangible form.

[0544] 4. Provision of VR content

[0545] The server sends the generated VR content to the terminal, which then displays it on the VR device. The user experiences the generated content through the VR device. For example, they can immerse themselves in the virtual reality world using a VR headset (e.g., Oculus Quest).

[0546] Specific examples

[0547] Let's say a user wants to create a "pirate treasure hunting story" and provides the text "pirate treasure hunting adventure," the audio "sound of waves," the image "ship," and the video "treasure hunting scene." This input data is sent to the server and analyzed appropriately by each analysis module. Based on the analysis results, the generation AI generates an active pirate scenario and environment, adding the sound of waves as a sound effect. The server integrates this and packages it into a single VR content, which is then sent to the device. The user can then experience this customized adventure through their VR device.

[0548] Prompt Sentence Examples

[0549] The prompt text that the user enters will be in the following format:

[0550] "Text": "Pirate Treasure Adventure",

[0551] "Audio file": "wave_sound.mp3",

[0552] "Image file": "pirate_ship.png",

[0553] "video file": "treasure_hunt.mp4"

[0554] In this way, a personalized virtual reality experience tailored to individual preferences is generated based on the data provided by the user.

[0555] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0556] Step 1:

[0557] User data entry and upload

[0558] The user provides input data in multiple formats, including text, audio, images, and video, through the device interface. This data is temporarily stored on the device. Specifically, the user uploads the text "Pirate's Treasure Hunt Adventure," the audio "Sound of Waves," the image "Ship," and the video "Treasure Hunt Scene." The input data at this point is in the form of files or strings of various formats, and the output is a temporary file or memory storage.

[0559] Step 2:

[0560] Sending data to the server

[0561] The device sends the temporarily stored user data to the server. The server receives the data sent from the device and prepares it for analysis. At this time, each piece of data is assigned to the appropriate analysis module. The input is the user's data file, and the output is the transfer of data to the analysis module on the server.

[0562] Step 3:

[0563] Data analysis

[0564] Each analysis module in the server analyzes the received data. Specifically, the text analysis module uses natural language processing (NLP) to analyze text based on context, the audio analysis module converts audio content into text using a speech recognition API, the image analysis module extracts image features using an image recognition algorithm, and the video analysis module analyzes video scenes using a frame analysis tool. The input data are files of various formats and their content information, and the output is the analysis results (e.g., text, metadata, feature vectors, etc.).

[0565] Step 4:

[0566] Input to generative AI models

[0567] The analysis results of each data obtained from the analysis module are integrated and input into the generative AI model. The generative AI model generates scenarios, characters, and environments based on the integrated data to construct the overall VR content. The input of this step is the integrated analysis results, and the output is the constituent data of the generated VR content.

[0568] Step 5:

[0569] Packaging VR content and converting it on the server

[0570] The server packages the generated VR content and converts it into a format that can be displayed on the user's device, such as packaging scenario text, audio files, 3D models, scene data, etc. The input of this step is the configuration data of the generated VR content, and the output is a packaged VR content file.

[0571] Step 6:

[0572] Content provision

[0573] The server sends the packaged VR content to the terminal. The terminal displays the received VR content on a VR device (e.g., a VR headset) and provides it to the user. At this point, the user can enjoy the generated virtual reality experience. The input is the packaged VR content file, and the output is a display of the content.

[0574] Through these steps, a personalized and immersive virtual reality experience is generated based on the data provided by the user. For example, a virtual reality experience of a pirate's treasure hunt can be created.

[0575] 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.

[0576] The system of the present invention analyzes and integrates user inputs such as text, voice, images, and video to generate and provide personalized virtual reality (VR) content. Furthermore, by incorporating an emotion engine, the system is equipped with the ability to recognize user emotions and adjust content accordingly. The system primarily consists of three main components: a terminal, a server, and a user.

[0577] System Configuration

[0578] 1. Terminal functions

[0579] The device provides an interface that receives input from the user. Through this interface, the user can upload data such as text, audio, images, and video. The device temporarily stores the received data and transmits it to the server.

[0580] 2. Server-side functionality

[0581] The server receives the data sent from the device and distributes it to the analysis module corresponding to each format. It also has a built-in emotion engine that analyzes emotions based on the user's input data.

[0582] Data Analysis Modules: The text analysis module understands the context and keywords of a sentence, the audio analysis module analyzes sound features, the image analysis module recognizes image features, and the video analysis module analyzes movie sequences.

[0583] Emotion Engine: Analyzes emotions from text and voice to determine the user's state. The emotion engine can understand whether the user is amused, surprised, or in any other emotional state.

[0584] The analysis results are then integrated and fed into a generative AI model, which generates VR content such as scenarios, characters, and environments based on the analysis results, adjusting the content to suit the user's emotional state as needed.

[0585] 3. Providing a user experience

[0586] The user experiences the generated content through a VR device. The server sends the generated VR content to the terminal, which then displays it on the VR device. The user's emotional feedback is also taken into account, and the content is adjusted in real time as needed.

[0587] Program processing explanation

[0588] The specific process flow for a user to customize their VR experience is as follows:

[0589] Getting User Input

[0590] The device receives text, audio, image, and video input through a user interface. The user uploads these materials, which the device temporarily stores.

[0591] Data analysis and emotion recognition

[0592] The server receives the data sent from the terminal and assigns the data to an analysis module corresponding to each format: text analysis module, audio analysis module, image analysis module, and video analysis module.

[0593] The emotion engine performs emotional analysis based on user input data (especially text and voice) to identify emotional states. For example, it analyzes the tone and pitch of a user's voice to determine whether they are excited or relaxed.

[0594] Data integration and VR content generation

[0595] The server integrates the data obtained from the analysis module and emotion engine and passes it to the generative AI model. The generative AI generates virtual reality content based on this data. Based on the results of the emotion engine, a scenario and environment adapted to the user's emotional state are set up.

[0596] Providing VR content

[0597] The generative AI generates a personalized VR experience based on the user's emotional state, and this generated content is packaged on the server and sent to the device.

[0598] The terminal prepares the received VR content for display on the VR device. The user experiences the generated content through the VR device, and emotional changes are monitored in real time.

[0599] Specific examples

[0600] For example, if a user wants to create a "story about pirates searching for treasure," and provides "pirate's treasure-hunting adventure" in text, "sound of waves" in audio, "ship" in images, and "treasure hunting scene" in video, this input data is sent to the server.

[0601] The server analyzes this data through each analysis module, and the emotion engine analyzes the user's expectations and excitement. The analysis results are integrated and a personalized VR experience is generated by the generative AI. This generated content is sent to the terminal and displayed on the VR device.

[0602] As the user experiences this customized adventure through the VR device, their emotional state is continuously monitored and the content is adjusted accordingly. For example, if the system determines that the user is bored, it will add new, interesting scenarios or surprise elements. In this way, the system provides a personalized VR experience that dynamically changes based on the user's emotions.

[0603] The processing flow will be explained below.

[0604] Step 1:

[0605] The device displays a screen for uploading text, audio, images, and videos to the user, allowing them to select and upload the materials for their desired VR experience.

[0606] Step 2:

[0607] Users select the material they want and upload it to their device in the form of text, audio, images, or video. For example, text can be used to provide a story, audio can be used to provide an ambient sound, images can be used to provide a scene, and video can be used to provide a moving sequence.

[0608] Step 3:

[0609] The device temporarily stores the text, audio, images, and video provided by the user and prepares them for transmission. During this step, the data format of each material is checked for any errors.

[0610] Step 4:

[0611] The terminal transmits the saved data to the server, along with the data format information.

[0612] Step 5:

[0613] The server receives the data sent from the device, classifies it by type, and assigns it to the appropriate analysis module.

[0614] Step 6:

[0615] The server sends the text data to the text analysis module, which then extracts the context and keywords from the text and creates the outline of the scenario.

[0616] Step 7:

[0617] The server sends the audio data to the audio analysis module, which then extracts the audio characteristics and recognizes them as environmental sounds or sound effects.

[0618] Step 8:

[0619] The server sends the image data to the image analysis module, which analyzes the image for features and components and uses them to design scenes and characters.

[0620] Step 9:

[0621] The server sends the video data to the video analysis module, which then extracts movie sequences and uses them as material for storyboards and animations.

[0622] Step 10:

[0623] The analysis results sent from the analysis modules are integrated into the server, which then aggregates them and passes the unified data set to the generative AI model.

[0624] Step 11:

[0625] The server sends the text and voice data to the emotion engine, which then analyzes the user's emotional state from the text and voice data to determine emotions such as joy, surprise, and sadness.

[0626] Step 12:

[0627] The generative AI model generates VR content such as scenarios, characters, and environments based on the results of the integrated dataset and emotion engine, and can also adjust the content based on the user's emotional state.

[0628] Step 13:

[0629] The server packages the generated VR content in real time and converts it into a format that can be experienced by the user, and the packaged content is saved in the optimal format.

[0630] Step 14:

[0631] The server transmits the packaged VR content to the device, which receives the data.

[0632] Step 15:

[0633] The terminal transfers the received VR content to the VR device and prepares it for display, at which point the user interface is updated to display the option to start the experience.

[0634] Step 16:

[0635] The user experiences the generated content using a VR device, and the emotion engine monitors the user's emotional state during the experience and adjusts the content accordingly.

[0636] Step 17:

[0637] Users can provide feedback after their experience, which is sent to the server via their device and used to improve the experience and generate new content.

[0638] Example 2

[0639] 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."

[0640] In modern virtual reality (VR) technology, it is important to provide users with personalized content. However, there are still many shortcomings in the technology for receiving and analyzing user input data in multiple formats, and then generating and adjusting content based on the user's emotional state. In particular, implementing a system that adapts to the user's emotional feedback in real time is challenging. Therefore, more advanced and flexible analysis and generation mechanisms are needed to improve the quality of the user experience.

[0641] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving input in multiple forms, such as text, audio, images, and videos, from the user; data analysis and emotion analysis means for analyzing the input in multiple forms, understanding its content, and determining the user's emotional state; generation means for generating virtual reality content using a generative AI model based on the analyzed data and the emotion analysis results; and provision means for providing the generated virtual reality content to the user. This makes it possible to analyze the user's input data in multiple forms in detail and generate and provide personalized VR content based on the results and the user's emotional state.

[0642] "User Input" refers to information provided by users in multiple formats, including text, audio, images, and video.

[0643] "Data analysis and emotion analysis means" refers to technology that analyzes multiple forms of input from users, understands their content, and determines their emotional state.

[0644] A "generative AI model" is an artificial intelligence technology that automatically generates virtual reality content based on analyzed data and emotion analysis results.

[0645] "Virtual reality content" refers to digital content, including scenarios, characters, environments, etc., that users experience through VR devices.

[0646] "Providing means" refers to the technology used to transmit the generated virtual reality content to the user's terminal and display it on the VR device.

[0647] "Emotional feedback" refers to the emotional changes and reactions that users display while experiencing virtual reality content.

[0648] The system of the present invention analyzes and integrates user inputs such as text, voice, images, and video to generate and provide personalized virtual reality (VR) content. Furthermore, by incorporating an emotion engine, the system is equipped with the ability to recognize user emotions and adjust content accordingly.

[0649] System Configuration

[0650] This system mainly consists of three main elements: terminals, servers, and users.

[0651] 1. Terminal functions

[0652] The device provides an interface that receives input from the user. Through this interface, the user can upload data such as text, audio, images, and video. The device temporarily stores the received data and transmits it to the server.

[0653] 2. Server-side functionality

[0654] The server receives the data sent from the device and distributes it to the analysis module corresponding to each format. It also has a built-in emotion engine that analyzes emotions based on the user's input data.

[0655] Data Analysis Module

[0656] The text analysis module understands the context and keywords of the text.

[0657] The audio analysis module analyzes the characteristics of the sound.

[0658] The image analysis module recognizes features in the image.

[0659] The video analysis module analyzes movie sequences.

[0660] Emotion Engine

[0661] Emotions are analyzed from text and voice to determine the user's state. The emotion engine can determine whether the user is amused, surprised, or in some other emotional state. The analysis results are integrated and passed to a generative AI model. This generative AI generates VR content such as scenarios, characters, and environments based on the analysis results, and adjusts the content to match the user's emotional state as needed.

[0662] 3. Providing a user experience

[0663] The user experiences the generated content through a VR device. The server sends the generated VR content to the terminal, which then displays it on the VR device. The user's emotional feedback is also taken into account, and the content is adjusted in real time as needed.

[0664] Specific examples

[0665] For example, if a user wants to create a "pirate treasure hunting story" and provides the following input:

[0666] Text: "A pirate's treasure hunting adventure"

[0667] Audio: "Sound of waves"

[0668] Image: "Ship"

[0669] Video: "Treasure Hunt Scene"

[0670] These input data are sent to the server, where each analysis module analyzes the data, and the emotion engine analyzes the user's expectations and excitement. The analysis results are integrated, and a personalized VR experience is generated by the generative AI. This generated content is sent to the terminal, where it is displayed on the VR device.

[0671] As the user experiences this customized adventure through the VR device, their emotional state is continuously monitored and the content is adjusted accordingly. For example, if the system determines that the user is bored, it will add new, interesting scenarios or surprise elements. In this way, the system provides a personalized VR experience that dynamically changes based on the user's emotions.

[0672] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0673] Step 1:

[0674] The terminal receives text, audio, image, and video input through a user interface. The user provides these materials to the terminal by entering text in a text field and uploading audio files, image files, and video files. For example, the user enters "A pirate's treasure hunting adventure" in a text field and uploads an audio file of the sound of waves, an image file of a ship, and a video file of a treasure hunting scene. The terminal temporarily stores them and compiles them to be sent to the server as a transaction.

[0675] Step 2:

[0676] The device sends the temporarily stored data to the server. Communication is performed using a secure protocol (e.g., HTTPS). For example, the device compresses text, audio, image, and video files and sends them to the server. The input is various media files obtained from the user, and the output is a data package sent to the server.

[0677] Step 3:

[0678] The server receives data packages sent from the terminal. The data packages include text, audio, image, and video files. The server then assigns these different types of data to the respective analysis modules. The input is the data package received from the terminal, and the output is the data of each type assigned to the analysis module.

[0679] Step 4:

[0680] The text analysis module analyzes the received text data. For example, it analyzes the text "A pirate's treasure-hunting adventure" and extracts key keywords such as "pirate," "treasure," and "adventure." Based on this, it identifies the basic elements for generating a scenario. The input is text data, and the output is the extracted keywords and contextual information.

[0681] Step 5:

[0682] The audio analysis module analyzes the received audio data. For example, it analyzes the sound of waves, identifies their rhythm and pitch, and extracts elements that recreate a seaside environment. The input is audio data, and the output is sound feature information.

[0683] Step 6:

[0684] The image analysis module analyzes the received image data. For example, it analyzes an image of a ship to identify its shape, color, and background information, which are then used to create a 3D model. The input is image data, and the output is image feature information.

[0685] Step 7:

[0686] The video analysis module analyzes the received video data. For example, it analyzes a video of a treasure hunt scene frame by frame to identify sequences and important actions. The input is the video data, and the output is sequence information and information identifying important actions.

[0687] Step 8:

[0688] The emotion engine analyzes the user's emotional state based on the received text and voice data. For example, if the user speaks in an excited tone, it determines that the user is excited. The input is text and voice data, and the output is information about the user's emotional state.

[0689] Step 9:

[0690] The server integrates the data obtained from the analysis modules and emotion engine and passes it to the generative AI model. For example, it combines the analysis results of text, audio, images, and video, along with emotional state information, into a single data package. The input is the output from each analysis module and emotion engine, and the output is the integrated data package.

[0691] Step 10:

[0692] The generative AI model generates virtual reality content based on a provided data package. For example, it creates a 3D model, scenario, and environment setting based on a "pirate treasure hunting adventure" scenario. The input is the integrated data package, and the output is the generated virtual reality content.

[0693] Step 11:

[0694] The server packages the generated virtual reality content and transmits it to the terminal, for example, by encoding the generated content into an appropriate format and compressing it for transmission to the terminal, where the input is the generated virtual reality content and the output is the data package transmitted to the terminal.

[0695] Step 12:

[0696] The terminal provides the received virtual reality content to the VR device. The terminal unpacks the received content and streams it to the VR device for display. The input is the data package received from the server, and the output is the virtual reality content experienced by the user.

[0697] Step 13:

[0698] The server monitors emotional changes during the user experience and adjusts the content in real time as needed. For example, if it determines that the user is bored, it adds new, interesting scenarios or surprise elements. It issues commands to the generative AI to do so. The input is the user's emotional feedback, and the output is the adjusted virtual reality content.

[0699] (Application example 2)

[0700] 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."

[0701] Conventional virtual reality (VR) content generation systems have the ability to analyze user input data and generate content, but it is difficult to dynamically adjust the content according to the user's emotions. Furthermore, to improve the shopping experience in brick-and-mortar stores, personalized information provision that takes into account the user's emotional state is required. Therefore, a system that recognizes the user's emotions and dynamically adjusts VR content based on those emotions is needed.

[0702] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input in multiple forms from the user, such as text, audio, images, and videos; data analysis means for analyzing the input in multiple forms and understanding its content; generation means for generating virtual reality content based on the analyzed data; and emotion recognition means for analyzing the user's emotions and dynamically adjusting the virtual reality content based on the analysis results. This makes it possible to provide seamless and personalized VR content according to the user's emotional state.

[0703] "Text input" is data in the form of text from the user.

[0704] "Voice input" refers to sound data from a user, particularly data that refers to spoken words.

[0705] "Image input" is still image data from the user.

[0706] "Video input" is video data from the user.

[0707] "Data analysis means" is a function for analyzing input data in multiple formats and understanding its contents.

[0708] "Generation means" is a function for generating virtual reality content based on analyzed data.

[0709] "Providing means" is a function for providing the generated virtual reality content to the user.

[0710] The "emotion recognition means" is a function for analyzing the user's emotions and dynamically adjusting the virtual reality content based on the analysis results.

[0711] "Interface" means the means by which a User can upload text, audio, image, or video data.

[0712] An "analysis module" is a dedicated function for analyzing data in a specific format (text, audio, image, video).

[0713] The system of the present invention is designed to enhance the user's shopping experience in a physical store. Specifically, smart glasses can be used to provide detailed product information and related content in real time when the user views the product. The system consists of the following main components: a user, a terminal (smart glasses), and a server.

[0714] System Configuration

[0715] 1. Terminal features:

[0716] The smart glasses, which are the terminal, provide an interface that receives text, voice, image, and video input from the user. When a user sees a product, they can ask questions by voice or input text to get more information about it. The smart glasses are equipped with a camera and microphone, which capture video and audio data.

[0717] 2. Server-side functionality:

[0718] The server receives and analyzes data sent from the device. Specifically, it has the following functions:

[0719] - Data Analysis Modules: Data is analyzed using dedicated analysis modules for text, audio, image, and video formats. The text analysis module understands the context and keywords of the text, the audio analysis module analyzes sound features, the image analysis module recognizes image features, and the video analysis module analyzes movie sequences.

[0720] - Emotion recognition means: The device incorporates an emotion engine to analyze emotions from user input data, for example, analyzing the tone and pitch of a user's voice from audio data to identify the user's emotional state.

[0721] - Generation method: Based on the analysis results, a generative AI model is used to generate personalized virtual reality content for the user, dynamically adjusting the scenario, characters, environment, etc. based on the user's emotional state.

[0722] Specific examples

[0723] As a user looks at clothes in a store, detailed information about the clothes is displayed through the smart glasses. For example, they can input text such as "What are the characteristics of this clothing?" and ask by voice, "Is this color trendy?". Furthermore, the glasses provide data such as "This is my favorite color" through images and "This is the latest trend in styles" through videos.

[0724] The server receives this data and analyzes it using the data analysis module. The emotion engine analyzes the user's excitement and interest, and the generative AI model generates appropriate VR content based on the analysis results. The generated content is instantly sent to the smart glasses and displayed in the user's field of view. The user's emotional state is monitored in real time, and if they are excited, new promotional information or interesting products are recommended.

[0725] Prompt Sentence Examples

[0726] "Generate a program for a system that inputs and analyzes detailed text information, related audio descriptions, and related images and videos about the clothes a user is looking at through smart glasses, and provides personalized information in real time according to the user's level of excitement and interest."

[0727] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0728] Step 1:

[0729] Users input text, voice, image, and video data through the smart glasses, which are then captured by the user interface and temporarily stored on the device. For example, a user might enter text such as "What are the characteristics of this clothing item?" and ask a voice question such as "Is this color trendy?"

[0730] Step 2:

[0731] The device sends the captured data to the server. Specifically, audio data, text data, image data, and video data are transferred to the server. At this stage, the input data arrives at the server.

[0732] Step 3:

[0733] The server distributes the received data to the data analysis modules. The text analysis module understands the context and keywords of the text, the audio analysis module analyzes the sound characteristics, the image analysis module recognizes the image characteristics, and the video analysis module analyzes the movie sequence. This analyzes the input data and provides the analysis results corresponding to each type of data. The output is the analyzed text, audio, image, and video information.

[0734] Step 4:

[0735] The server's emotion recognition means identifies the user's emotional state from the analyzed data. It analyzes the user's emotions, such as excitement or relaxation, based on the tone and pitch of the voice data and the content of the text data. The user's emotional state is identified as the output.

[0736] Step 5:

[0737] The server passes the analysis results and emotional state data to a generative AI model to generate personalized VR content for the user. The generative AI model then configures a scenario, characters, and environment that adapts to the user's emotional state. This generates personalized VR content. The output is VR content that matches the user's emotional state.

[0738] Step 6:

[0739] The server sends the generated VR content to the device, which then prepares the received VR content for display on the smart glasses. As an output, the displayable VR content is prepared.

[0740] Step 7:

[0741] The device displays the user-generated VR content through smart glasses. As the user experiences the VR content, their emotional state is monitored in real time based on their experience. If the user's excitement level is high, new information or interesting promotions will be displayed. In this way, the user receives a dynamically generated personalized shopping experience.

[0742] This processing step allows users to enjoy a personalized shopping experience in physical stores that is tailored to their emotional state.

[0743] 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.

[0744] 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.

[0745] 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.

[0746] [Third embodiment]

[0747] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0748] 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.

[0749] 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).

[0750] 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.

[0751] 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.

[0752] 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).

[0753] 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.

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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."

[0759] The system of the present invention receives inputs such as text, voice, images, and videos provided by users, analyzes and integrates them to generate virtual reality (VR) content, and provides it to users. This system mainly consists of three main components: a terminal, a server, and a user.

[0760] System Configuration

[0761] 1. Terminal functions

[0762] The terminal provides an interface for receiving input from the user. Through this interface, the user can send data such as text, audio, images, and video to the system. The terminal also temporarily stores the received data and sends it to the server.

[0763] 2. Server-side functionality

[0764] The server has many analysis modules that receive and analyze data sent from the device. The server uses text analysis, voice analysis, image analysis, and video analysis modules to perform detailed analysis of user input, making it easier to understand the user's intent and the context of the data.

[0765] The analyzed data is then passed to the generation AI, which generates scenarios, characters, and environments based on the analysis results to create virtual reality content. The generated content is then packaged on the server and converted into a format that can be provided to users.

[0766] 3. Providing a user experience

[0767] Users experience the generated content through a VR device. The server sends the completed VR content to the terminal, which then displays it on the VR device. Users can then use the VR device to enjoy the virtual experience.

[0768] Program processing explanation

[0769] The specific process is as follows:

[0770] Getting User Input

[0771] The device receives text, audio, images, and video through the user interface. When the user uploads this data, the device temporarily stores it and sends it to the server.

[0772] Data analysis and integration

[0773] The server receives data sent from the device and assigns it to an analysis module according to the data format. The text analysis module analyzes the input text and understands the context. The audio analysis module analyzes the provided audio data and understands the sound content. The image analysis module extracts image features, and the video analysis module analyzes video scenes.

[0774] The data obtained from the analysis module is integrated on the server and passed to a generative AI model, which uses the integrated data to generate scenarios, characters, and environments, building the overall VR content.

[0775] VR content generation and provision

[0776] Generative AI creates a personalized VR experience based on the user's intent, including a pirate treasure hunt story, realistic ocean sounds, ship images, and a treasure hunt movie.

[0777] The server packages the generated VR content and converts it into a format that can be experienced by the user. The packaged VR content is then sent to the terminal, which displays it on the VR device.

[0778] Specific examples

[0779] For example, suppose a user wants to create a "pirate treasure hunting story" and provides the text "pirate treasure hunting adventure," the audio "sound of waves," the image "ship," and the video "treasure hunting scene." This input data is sent to the server and analyzed appropriately by each analysis module. Based on the analysis results, the generation AI generates an active pirate scenario and environment, adding the sound of waves as a sound effect. The server integrates this and packages it into a single VR content, which is then sent to the device. The user can then experience this customized adventure through their VR device.

[0780] As described above, the system of the present invention allows users to easily create and enjoy personalized VR experiences.

[0781] The processing flow will be explained below.

[0782] Step 1:

[0783] The device displays a screen for uploading text, audio, images, and videos to the user, allowing them to select and upload the materials for the VR experience they want to create.

[0784] Step 2:

[0785] Users select the desired material and upload it to their device in the form of text, audio, images, or video. For example, text can be used to provide a story, audio can be used to provide an ambient sound, images can be used to provide a scene, and video can be used to provide a moving sequence.

[0786] Step 3:

[0787] The device temporarily stores the text, audio, images, and video provided by the user and prepares them for transmission. In this step, the data format of each material is checked for any errors.

[0788] Step 4:

[0789] The device sends the saved data to the server, along with the classification information of the data.

[0790] Step 5:

[0791] The server receives the data sent from the device, classifies it by type, and assigns it to the appropriate analysis module.

[0792] Step 6:

[0793] The server sends the text data to the text analysis module, which then extracts the context and keywords from the text and creates the outline of the scenario.

[0794] Step 7:

[0795] The server sends the audio data to the audio analysis module, which then extracts the audio characteristics and recognizes them as environmental sounds or sound effects.

[0796] Step 8:

[0797] The server sends the image data to the image analysis module, which analyzes the image for features and components and uses them as scene and character designs.

[0798] Step 9:

[0799] The server sends the video data to the video analysis module, which then extracts movie sequences and uses them as material for storyboards and animations.

[0800] Step 10:

[0801] The analysis results sent from the analysis modules are integrated into the server, which then aggregates them and passes the unified data set to the generative AI model.

[0802] Step 11:

[0803] The generative AI model generates VR content such as scenarios, characters, and environments based on the integrated dataset, and interactive elements are also created during this step.

[0804] Step 12:

[0805] The server packages the generated VR content and converts it into a format that can be experienced by the user, and saves the packaged content in the optimal format.

[0806] Step 13:

[0807] The server transmits the packaged VR content to the device, which receives the data.

[0808] Step 14:

[0809] The terminal transfers the received VR content to the VR device and prepares it for display, at which point the user interface is updated to display the option to start the experience.

[0810] Step 15:

[0811] Users use VR devices to experience the generated content, and their movements and reactions are collected and reflected in the interactive elements.

[0812] Step 16:

[0813] Users can provide feedback after their experience, which is sent to the server via their device and used to improve the experience and generate new content.

[0814] Example 1

[0815] 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."

[0816] Conventional virtual reality content generation systems have difficulty effectively analyzing and integrating diverse forms of data from users to provide personalized virtual reality experiences tailored to their individual needs. Furthermore, the content generation process is complex, making it difficult to generate consistent scenarios and characters.

[0817] 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.

[0818] In this invention, the server includes a means for receiving input in multiple forms from a user, such as text, audio, images, and videos, a data analysis means for analyzing the input in multiple forms and understanding its content, a means for integrating the analyzed data and generating virtual reality content based on a generative AI model, and a means for packaging the generated virtual reality content and providing it to the user, thereby enabling the user to easily generate and enjoy a personalized virtual reality experience using data in various forms.

[0819] A "means for receiving multiple forms of input from a user, such as text, audio, images, and video" is a device or method that provides an interface for receiving different forms of data, such as text, audio, images, and video, input from a user.

[0820] "Data analysis means" refers to a device or method for analyzing received data in multiple formats, such as text, audio, images, and video, and understanding its content.

[0821] A "generative AI model" is an artificial intelligence model that generates scenarios, characters, and environments based on analyzed data, and builds overall virtual reality content.

[0822] A "means for generating virtual reality content" is a device or method for generating a virtual reality experience based on the analyzed and synthesized data.

[0823] A "means for packaging and providing virtual reality content to a user" is a device or method for converting the generated virtual reality content into a format that can be experienced by a user and providing it to a user.

[0824] A "dedicated analysis module" is a separate piece of software or equipment that is specialized for analyzing each data format, such as text, audio, images, and video.

[0825] "Virtual reality experience" refers to interactive content that allows users to immerse themselves in a virtual environment and experience it as if it were real through their senses, such as sight and hearing.

[0826] The system of the present invention receives input data such as text, audio, images, and videos provided by users, analyzes and integrates them to generate virtual reality (VR) content, and provides it to users. This system mainly consists of three main components: a terminal, a server, and a user.

[0827] System Configuration

[0828] Terminal functions

[0829] The terminal provides an interface for receiving input from the user. Through the user interface, the user can send data such as text, audio, images, and videos to the system. The terminal temporarily stores the received data and sends it to the server. Specifically, the user can enter text such as "A pirate's treasure-hunting adventure" through the application, record the "sound of waves" using the voice recording function, and upload images and videos using the file selection dialog.

[0830] Server-side features

[0831] The server receives data sent from the terminal and has many analysis modules for analyzing it. The server uses the following analysis modules to analyze the data in detail.

[0832] The text analysis module uses natural language processing technology to analyze the input text and understand the meaning and context of the text.

[0833] The speech analysis module converts the provided speech data into acoustic features and understands the content.

[0834] The image analysis module extracts object and scene features from images.

[0835] The video analysis module analyzes the video frame by frame to understand the content of the scene.

[0836] The analyzed data is integrated on the server and passed to a generative AI model. The generative AI model generates scenarios, characters, and environments based on the integrated data to build the overall VR content. For example, a pirate adventure may unfold based on the generated scenario, with sound effects like the sound of waves playing in real time. Images of ships may also be set as backgrounds, and treasure hunt videos may be incorporated as part of the scenario.

[0837] Providing VR content

[0838] The server packages the generated VR content and converts it into a format that can be experienced by the user. This packaged VR content is sent to the terminal, which displays it on the VR device. The user can then experience a customized pirate adventure using the VR device. For example, when the user puts on the VR goggles, they can immerse themselves in the pirate world and enjoy the adventure through realistic sights and sounds.

[0839] Prompt Sentence Examples

[0840] Examples of prompts to input into a generative AI model include:

[0841] example:

[0842] "Generate virtual reality content for a story about pirates searching for treasure. Use 'A pirate's treasure-hunting adventure' for the text, 'The sound of waves' for the audio, 'A ship' for the image, and 'A treasure-hunting scene' for the video."

[0843] In this way, users can easily create and enjoy personalized VR experiences using data in a variety of formats.

[0844] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0845] Program processing flow

[0846] Step 1: Getting User Input

[0847] Step 2: Sending data

[0848] Step 3: Analyze the data

[0849] Step 4: Integrate the data

[0850] Step 5: Generate VR content

[0851] Step 6: Providing VR content

[0852] Detailed explanation of the processing steps

[0853] Step 1: Getting User Input

[0854] The terminal receives input data such as text, audio, images, and video through a user interface.

[0855] Input: User input of text, audio, images, and video

[0856] How it works: A user interacts with the application, enters "A pirate's treasure hunting adventure" into the text field, records the sound of "waves" using the voice recorder, and uploads image and video files.

[0857] Output: Text, audio, image, and video data temporarily stored on the device

[0858] Step 2: Sending data

[0859] The terminal transmits the temporarily stored data to the server.

[0860] Input: Stored text, audio, image, and video data

[0861] How it works: When the user presses the "upload" button, the device makes an HTTP request and sends the data to the server.

[0862] Output: Text, audio, image, and video data sent to the server

[0863] Step 3: Analyze the data

[0864] The server allocates the received data to each dedicated analysis module for analysis.

[0865] Input: Text, audio, image, and video data sent from your device

[0866] Operation: The server analyzes text using the text analysis module, converts audio data into acoustic features using the audio analysis module, extracts image features using the image analysis module, and analyzes video scenes using the video analysis module.

[0867] Output: Analysis result data from each analysis module

[0868] Step 4: Integrate the data

[0869] The server integrates the data obtained from each analysis module.

[0870] Input: Analysis result data from the analysis module

[0871] How it works: The analysis results are compiled into a single data structure, adjusted into a unified scenario and character configuration, and passed to a generative AI model.

[0872] Output: The aggregated data passed to the generative AI model

[0873] Step 5: Generate VR content

[0874] The generative AI generates VR content based on the integrated data.

[0875] Input: Integrated data

[0876] How it works: Generative AI generates scenarios, characters, and environments, combining content such as pirate adventures and the sound of waves to build an overall VR story.

[0877] Output: Generated VR content

[0878] Step 6: Providing VR content

[0879] The server packages the generated VR content and converts it into a format that can be delivered to the user.

[0880] Input: Generated VR content

[0881] How it works: The server packages the VR content and sends it to the device. The device displays the received content on the VR device. The user puts on the VR device and experiences the content.

[0882] Output: VR content that users can experience

[0883] Through these steps, users can create and enjoy personalized virtual reality experiences using data in a variety of formats.

[0884] (Application example 1)

[0885] 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."

[0886] In recent years, the demand for personalized content based on user interests and preferences has been growing rapidly. However, traditional content delivery services are limited to static text, images, and standard video streaming, making it difficult for users to achieve a more immersive experience. Furthermore, technologies for analyzing and integrating diverse inputs from multiple media formats to generate high-quality virtual reality (VR) content are limited. This calls for innovation to improve user satisfaction.

[0887] 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.

[0888] In this invention, the server includes means for receiving input in multiple forms such as text, audio, images, and videos from the user, data analysis means for analyzing the input in multiple forms and understanding its content, generation means for generating virtual reality content based on the analyzed data, and provision means for providing the generated virtual reality content to the user. This makes it possible to generate a personalized and immersive virtual reality experience based on the various data provided by the user and quickly provide it to the user.

[0889] 1. "Multiple forms of input" refers to different types of data provided by users, such as text, audio, images, and video.

[0890] 2. "Data Analysis Tools" are modules and algorithms used to analyze and understand multiple forms of input.

[0891] 3. "Generation means" means modules or algorithms for generating virtual reality content based on analyzed data.

[0892] 4. "Provision means" refers to the interface and communication means used to provide the generated virtual reality content to the user.

[0893] 5. "Data for customizing news content" refers to input data used to identify news and information that the user is interested in and reflect that in the VR footage.

[0894] 6. "Analysis module" refers to a program or algorithm for performing specialized analysis for each format, such as text, audio, image, or video.

[0895] 7. "Interface" means the operating screen or input device through which a user uploads text, audio, images, or video.

[0896] 8. "VR Video" means visual content created to provide users with a virtual reality experience.

[0897] 9. "Server" means a computer system that receives input data from users, analyzes it, and provides generated VR content.

[0898] The system of this invention generates virtual reality (VR) content based on input data in various formats and provides it to users. The system mainly consists of the following elements.

[0899] 1. Getting User Input

[0900] The terminal provides a means to receive multiple forms of input from the user, including text, audio, images, video, etc. Through this interface, the user can upload data in various forms.

[0901] 2. Data Analysis

[0902] The server receives the data sent from the device and analyzes it using a dedicated analysis module for each format. Different modules, such as text analysis, audio analysis, image analysis, and video analysis, are combined to gain a detailed understanding of the data's content. Specifically, natural language processing (NLP) models are used for text analysis, speech recognition APIs for audio analysis, image recognition algorithms (e.g., TensorFlow) for image analysis, and frame analysis tools (e.g., OpenCV) for video analysis.

[0903] 3. VR content generation

[0904] The analyzed data is integrated and input into a generative AI model, which generates scenarios, characters, and environments based on the integrated data to construct the overall VR content, which is then packaged on a server and converted into a tangible form.

[0905] 4. Provision of VR content

[0906] The server sends the generated VR content to the terminal, which then displays it on the VR device. The user experiences the generated content through the VR device. For example, they can immerse themselves in the virtual reality world using a VR headset (e.g., Oculus Quest).

[0907] Specific examples

[0908] Let's say a user wants to create a "pirate treasure hunting story" and provides the text "pirate treasure hunting adventure," the audio "sound of waves," the image "ship," and the video "treasure hunting scene." This input data is sent to the server and analyzed appropriately by each analysis module. Based on the analysis results, the generation AI generates an active pirate scenario and environment, adding the sound of waves as a sound effect. The server integrates this and packages it into a single VR content, which is then sent to the device. The user can then experience this customized adventure through their VR device.

[0909] Prompt Sentence Examples

[0910] The prompt text that the user enters will be in the following format:

[0911] "Text": "Pirate Treasure Adventure",

[0912] "Audio file": "wave_sound.mp3",

[0913] "Image file": "pirate_ship.png",

[0914] "video file": "treasure_hunt.mp4"

[0915] In this way, a personalized virtual reality experience tailored to individual preferences is generated based on the data provided by the user.

[0916] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0917] Step 1:

[0918] User data entry and upload

[0919] The user provides input data in multiple formats, including text, audio, images, and video, through the device interface. This data is temporarily stored on the device. Specifically, the user uploads the text "Pirate's Treasure Hunt Adventure," the audio "Sound of Waves," the image "Ship," and the video "Treasure Hunt Scene." The input data at this point is in the form of files or strings of various formats, and the output is a temporary file or memory storage.

[0920] Step 2:

[0921] Sending data to the server

[0922] The device sends the temporarily stored user data to the server. The server receives the data sent from the device and prepares it for analysis. At this time, each piece of data is assigned to the appropriate analysis module. The input is the user's data file, and the output is the transfer of data to the analysis module on the server.

[0923] Step 3:

[0924] Data analysis

[0925] Each analysis module in the server analyzes the received data. Specifically, the text analysis module uses natural language processing (NLP) to analyze text based on context, the audio analysis module converts audio content into text using a speech recognition API, the image analysis module extracts image features using an image recognition algorithm, and the video analysis module analyzes video scenes using a frame analysis tool. The input data are files of various formats and their content information, and the output is the analysis results (e.g., text, metadata, feature vectors, etc.).

[0926] Step 4:

[0927] Input to generative AI models

[0928] The analysis results of each data obtained from the analysis module are integrated and input into the generative AI model. The generative AI model generates scenarios, characters, and environments based on the integrated data to construct the overall VR content. The input of this step is the integrated analysis results, and the output is the constituent data of the generated VR content.

[0929] Step 5:

[0930] Packaging VR content and converting it on the server

[0931] The server packages the generated VR content and converts it into a format that can be displayed on the user's device, such as packaging scenario text, audio files, 3D models, scene data, etc. The input of this step is the configuration data of the generated VR content, and the output is a packaged VR content file.

[0932] Step 6:

[0933] Content provision

[0934] The server sends the packaged VR content to the terminal. The terminal displays the received VR content on a VR device (e.g., a VR headset) and provides it to the user. At this point, the user can enjoy the generated virtual reality experience. The input is the packaged VR content file, and the output is a display of the content.

[0935] Through these steps, a personalized and immersive virtual reality experience is generated based on the data provided by the user. For example, a virtual reality experience of a pirate's treasure hunt can be created.

[0936] 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.

[0937] The system of the present invention analyzes and integrates user inputs such as text, voice, images, and video to generate and provide personalized virtual reality (VR) content. Furthermore, by incorporating an emotion engine, the system is equipped with the ability to recognize user emotions and adjust content accordingly. The system primarily consists of three main components: a terminal, a server, and a user.

[0938] System Configuration

[0939] 1. Terminal functions

[0940] The device provides an interface that receives input from the user. Through this interface, the user can upload data such as text, audio, images, and video. The device temporarily stores the received data and transmits it to the server.

[0941] 2. Server-side functionality

[0942] The server receives the data sent from the device and distributes it to the analysis module corresponding to each format. It also has a built-in emotion engine that analyzes emotions based on the user's input data.

[0943] Data Analysis Modules: The text analysis module understands the context and keywords of a sentence, the audio analysis module analyzes sound features, the image analysis module recognizes image features, and the video analysis module analyzes movie sequences.

[0944] Emotion Engine: Analyzes emotions from text and voice to determine the user's state. The emotion engine can understand whether the user is amused, surprised, or in any other emotional state.

[0945] The analysis results are then integrated and fed into a generative AI model, which generates VR content such as scenarios, characters, and environments based on the analysis results, adjusting the content to suit the user's emotional state as needed.

[0946] 3. Providing a user experience

[0947] The user experiences the generated content through a VR device. The server sends the generated VR content to the terminal, which then displays it on the VR device. The user's emotional feedback is also taken into account, and the content is adjusted in real time as needed.

[0948] Program processing explanation

[0949] The specific process flow for a user to customize their VR experience is as follows:

[0950] Getting User Input

[0951] The device receives text, audio, image, and video input through a user interface. The user uploads these materials, which the device temporarily stores.

[0952] Data analysis and emotion recognition

[0953] The server receives the data sent from the terminal and assigns the data to an analysis module corresponding to each format: text analysis module, audio analysis module, image analysis module, and video analysis module.

[0954] The emotion engine performs emotional analysis based on user input data (especially text and voice) to identify emotional states. For example, it analyzes the tone and pitch of a user's voice to determine whether they are excited or relaxed.

[0955] Data integration and VR content generation

[0956] The server integrates the data obtained from the analysis module and emotion engine and passes it to the generative AI model. The generative AI generates virtual reality content based on this data. Based on the results of the emotion engine, a scenario and environment adapted to the user's emotional state are set up.

[0957] Providing VR content

[0958] The generative AI generates a personalized VR experience based on the user's emotional state, and this generated content is packaged on the server and sent to the device.

[0959] The terminal prepares the received VR content for display on the VR device. The user experiences the generated content through the VR device, and emotional changes are monitored in real time.

[0960] Specific examples

[0961] For example, if a user wants to create a "story about pirates searching for treasure," and provides "pirate's treasure-hunting adventure" in text, "sound of waves" in audio, "ship" in images, and "treasure hunting scene" in video, this input data is sent to the server.

[0962] The server analyzes this data through each analysis module, and the emotion engine analyzes the user's expectations and excitement. The analysis results are integrated and a personalized VR experience is generated by the generative AI. This generated content is sent to the terminal and displayed on the VR device.

[0963] As the user experiences this customized adventure through the VR device, their emotional state is continuously monitored and the content is adjusted accordingly. For example, if the system determines that the user is bored, it will add new, interesting scenarios or surprise elements. In this way, the system provides a personalized VR experience that dynamically changes based on the user's emotions.

[0964] The processing flow will be explained below.

[0965] Step 1:

[0966] The device displays a screen for uploading text, audio, images, and videos to the user, allowing them to select and upload the materials for their desired VR experience.

[0967] Step 2:

[0968] Users select the material they want and upload it to their device in the form of text, audio, images, or video. For example, text can be used to provide a story, audio can be used to provide an ambient sound, images can be used to provide a scene, and video can be used to provide a moving sequence.

[0969] Step 3:

[0970] The device temporarily stores the text, audio, images, and video provided by the user and prepares them for transmission. During this step, the data format of each material is checked for any errors.

[0971] Step 4:

[0972] The terminal transmits the saved data to the server, along with the data format information.

[0973] Step 5:

[0974] The server receives the data sent from the device, classifies it by type, and assigns it to the appropriate analysis module.

[0975] Step 6:

[0976] The server sends the text data to the text analysis module, which then extracts the context and keywords from the text and creates the outline of the scenario.

[0977] Step 7:

[0978] The server sends the audio data to the audio analysis module, which then extracts the audio characteristics and recognizes them as environmental sounds or sound effects.

[0979] Step 8:

[0980] The server sends the image data to the image analysis module, which analyzes the image for features and components and uses them to design scenes and characters.

[0981] Step 9:

[0982] The server sends the video data to the video analysis module, which then extracts movie sequences and uses them as material for storyboards and animations.

[0983] Step 10:

[0984] The analysis results sent from the analysis modules are integrated into the server, which then aggregates them and passes the unified data set to the generative AI model.

[0985] Step 11:

[0986] The server sends the text and voice data to the emotion engine, which then analyzes the user's emotional state from the text and voice data to determine emotions such as joy, surprise, and sadness.

[0987] Step 12:

[0988] The generative AI model generates VR content such as scenarios, characters, and environments based on the results of the integrated dataset and emotion engine, and can also adjust the content based on the user's emotional state.

[0989] Step 13:

[0990] The server packages the generated VR content in real time and converts it into a format that can be experienced by the user, and the packaged content is saved in the optimal format.

[0991] Step 14:

[0992] The server transmits the packaged VR content to the device, which receives the data.

[0993] Step 15:

[0994] The terminal transfers the received VR content to the VR device and prepares it for display, at which point the user interface is updated to display the option to start the experience.

[0995] Step 16:

[0996] The user experiences the generated content using a VR device, and the emotion engine monitors the user's emotional state during the experience and adjusts the content accordingly.

[0997] Step 17:

[0998] Users can provide feedback after their experience, which is sent to the server via their device and used to improve the experience and generate new content.

[0999] Example 2

[1000] 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."

[1001] In modern virtual reality (VR) technology, it is important to provide users with personalized content. However, there are still many shortcomings in the technology for receiving and analyzing user input data in multiple formats, and then generating and adjusting content based on the user's emotional state. In particular, implementing a system that adapts to the user's emotional feedback in real time is challenging. Therefore, more advanced and flexible analysis and generation mechanisms are needed to improve the quality of the user experience.

[1002] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving input in multiple forms, such as text, audio, images, and videos, from the user; data analysis and emotion analysis means for analyzing the input in multiple forms, understanding its content, and determining the user's emotional state; generation means for generating virtual reality content using a generative AI model based on the analyzed data and the emotion analysis results; and provision means for providing the generated virtual reality content to the user. This makes it possible to analyze the user's input data in multiple forms in detail and generate and provide personalized VR content based on the results and the user's emotional state.

[1003] "User Input" refers to information provided by users in multiple formats, including text, audio, images, and video.

[1004] "Data analysis and emotion analysis means" refers to technology that analyzes multiple forms of input from users, understands their content, and determines their emotional state.

[1005] A "generative AI model" is an artificial intelligence technology that automatically generates virtual reality content based on analyzed data and emotion analysis results.

[1006] "Virtual reality content" refers to digital content, including scenarios, characters, environments, etc., that users experience through VR devices.

[1007] "Providing means" refers to the technology used to transmit the generated virtual reality content to the user's terminal and display it on the VR device.

[1008] "Emotional feedback" refers to the emotional changes and reactions that users display while experiencing virtual reality content.

[1009] The system of the present invention analyzes and integrates user inputs such as text, voice, images, and video to generate and provide personalized virtual reality (VR) content. Furthermore, by incorporating an emotion engine, the system is equipped with the ability to recognize user emotions and adjust content accordingly.

[1010] System Configuration

[1011] This system mainly consists of three main elements: terminals, servers, and users.

[1012] 1. Terminal functions

[1013] The device provides an interface that receives input from the user. Through this interface, the user can upload data such as text, audio, images, and video. The device temporarily stores the received data and transmits it to the server.

[1014] 2. Server-side functionality

[1015] The server receives the data sent from the device and distributes it to the analysis module corresponding to each format. It also has a built-in emotion engine that analyzes emotions based on the user's input data.

[1016] Data Analysis Module

[1017] The text analysis module understands the context and keywords of the text.

[1018] The audio analysis module analyzes the characteristics of the sound.

[1019] The image analysis module recognizes features in the image.

[1020] The video analysis module analyzes movie sequences.

[1021] Emotion Engine

[1022] Emotions are analyzed from text and voice to determine the user's state. The emotion engine can determine whether the user is amused, surprised, or in some other emotional state. The analysis results are integrated and passed to a generative AI model. This generative AI generates VR content such as scenarios, characters, and environments based on the analysis results, and adjusts the content to match the user's emotional state as needed.

[1023] 3. Providing a user experience

[1024] The user experiences the generated content through a VR device. The server sends the generated VR content to the terminal, which then displays it on the VR device. The user's emotional feedback is also taken into account, and the content is adjusted in real time as needed.

[1025] Specific examples

[1026] For example, if a user wants to create a "pirate treasure hunting story" and provides the following input:

[1027] Text: "A pirate's treasure hunting adventure"

[1028] Audio: "Sound of waves"

[1029] Image: "Ship"

[1030] Video: "Treasure Hunt Scene"

[1031] These input data are sent to the server, where each analysis module analyzes the data, and the emotion engine analyzes the user's expectations and excitement. The analysis results are integrated, and a personalized VR experience is generated by the generative AI. This generated content is sent to the terminal, where it is displayed on the VR device.

[1032] As the user experiences this customized adventure through the VR device, their emotional state is continuously monitored and the content is adjusted accordingly. For example, if the system determines that the user is bored, it will add new, interesting scenarios or surprise elements. In this way, the system provides a personalized VR experience that dynamically changes based on the user's emotions.

[1033] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1034] Step 1:

[1035] The terminal receives text, audio, image, and video input through a user interface. The user provides these materials to the terminal by entering text in a text field and uploading audio files, image files, and video files. For example, the user enters "A pirate's treasure hunting adventure" in a text field and uploads an audio file of the sound of waves, an image file of a ship, and a video file of a treasure hunting scene. The terminal temporarily stores them and compiles them to be sent to the server as a transaction.

[1036] Step 2:

[1037] The device sends the temporarily stored data to the server. Communication is performed using a secure protocol (e.g., HTTPS). For example, the device compresses text, audio, image, and video files and sends them to the server. The input is various media files obtained from the user, and the output is a data package sent to the server.

[1038] Step 3:

[1039] The server receives data packages sent from the terminal. The data packages include text, audio, image, and video files. The server then assigns these different types of data to the respective analysis modules. The input is the data package received from the terminal, and the output is the data of each type assigned to the analysis module.

[1040] Step 4:

[1041] The text analysis module analyzes the received text data. For example, it analyzes the text "A pirate's treasure-hunting adventure" and extracts key keywords such as "pirate," "treasure," and "adventure." Based on this, it identifies the basic elements for generating a scenario. The input is text data, and the output is the extracted keywords and contextual information.

[1042] Step 5:

[1043] The audio analysis module analyzes the received audio data. For example, it analyzes the sound of waves, identifies their rhythm and pitch, and extracts elements that recreate a seaside environment. The input is audio data, and the output is sound feature information.

[1044] Step 6:

[1045] The image analysis module analyzes the received image data. For example, it analyzes an image of a ship to identify its shape, color, and background information, which are then used to create a 3D model. The input is image data, and the output is image feature information.

[1046] Step 7:

[1047] The video analysis module analyzes the received video data. For example, it analyzes a video of a treasure hunt scene frame by frame to identify sequences and important actions. The input is the video data, and the output is sequence information and information identifying important actions.

[1048] Step 8:

[1049] The emotion engine analyzes the user's emotional state based on the received text and voice data. For example, if the user speaks in an excited tone, it determines that the user is excited. The input is text and voice data, and the output is information about the user's emotional state.

[1050] Step 9:

[1051] The server integrates the data obtained from the analysis modules and emotion engine and passes it to the generative AI model. For example, it combines the analysis results of text, audio, images, and video, along with emotional state information, into a single data package. The input is the output from each analysis module and emotion engine, and the output is the integrated data package.

[1052] Step 10:

[1053] The generative AI model generates virtual reality content based on a provided data package. For example, it creates a 3D model, scenario, and environment setting based on a "pirate treasure hunting adventure" scenario. The input is the integrated data package, and the output is the generated virtual reality content.

[1054] Step 11:

[1055] The server packages the generated virtual reality content and transmits it to the terminal, for example, by encoding the generated content into an appropriate format and compressing it for transmission to the terminal, where the input is the generated virtual reality content and the output is the data package transmitted to the terminal.

[1056] Step 12:

[1057] The terminal provides the received virtual reality content to the VR device. The terminal unpacks the received content and streams it to the VR device for display. The input is the data package received from the server, and the output is the virtual reality content experienced by the user.

[1058] Step 13:

[1059] The server monitors emotional changes during the user experience and adjusts the content in real time as needed. For example, if it determines that the user is bored, it adds new, interesting scenarios or surprise elements. It issues commands to the generative AI to do so. The input is the user's emotional feedback, and the output is the adjusted virtual reality content.

[1060] (Application example 2)

[1061] 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."

[1062] Conventional virtual reality (VR) content generation systems have the ability to analyze user input data and generate content, but it is difficult to dynamically adjust the content according to the user's emotions. Furthermore, to improve the shopping experience in brick-and-mortar stores, personalized information provision that takes into account the user's emotional state is required. Therefore, a system that recognizes the user's emotions and dynamically adjusts VR content based on those emotions is needed.

[1063] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input in multiple forms from the user, such as text, audio, images, and videos; data analysis means for analyzing the input in multiple forms and understanding its content; generation means for generating virtual reality content based on the analyzed data; and emotion recognition means for analyzing the user's emotions and dynamically adjusting the virtual reality content based on the analysis results. This makes it possible to provide seamless and personalized VR content according to the user's emotional state.

[1064] "Text input" is data in the form of text from the user.

[1065] "Voice input" refers to sound data from a user, particularly data that refers to spoken words.

[1066] "Image input" is still image data from the user.

[1067] "Video input" is video data from the user.

[1068] "Data analysis means" is a function for analyzing input data in multiple formats and understanding its contents.

[1069] "Generation means" is a function for generating virtual reality content based on analyzed data.

[1070] "Providing means" is a function for providing the generated virtual reality content to the user.

[1071] The "emotion recognition means" is a function for analyzing the user's emotions and dynamically adjusting the virtual reality content based on the analysis results.

[1072] "Interface" means the means by which a User can upload text, audio, image, or video data.

[1073] An "analysis module" is a dedicated function for analyzing data in a specific format (text, audio, image, video).

[1074] The system of the present invention is designed to enhance the user's shopping experience in a physical store. Specifically, smart glasses can be used to provide detailed product information and related content in real time when the user views the product. The system consists of the following main components: a user, a terminal (smart glasses), and a server.

[1075] System Configuration

[1076] 1. Terminal features:

[1077] The smart glasses, which are the terminal, provide an interface that receives text, voice, image, and video input from the user. When a user sees a product, they can ask questions by voice or input text to get more information about it. The smart glasses are equipped with a camera and microphone, which capture video and audio data.

[1078] 2. Server-side functionality:

[1079] The server receives and analyzes data sent from the device. Specifically, it has the following functions:

[1080] - Data Analysis Modules: Data is analyzed using dedicated analysis modules for text, audio, image, and video formats. The text analysis module understands the context and keywords of the text, the audio analysis module analyzes sound features, the image analysis module recognizes image features, and the video analysis module analyzes movie sequences.

[1081] - Emotion recognition means: The device incorporates an emotion engine to analyze emotions from user input data, for example, analyzing the tone and pitch of a user's voice from audio data to identify the user's emotional state.

[1082] - Generation method: Based on the analysis results, a generative AI model is used to generate personalized virtual reality content for the user, dynamically adjusting the scenario, characters, environment, etc. based on the user's emotional state.

[1083] Specific examples

[1084] As a user looks at clothes in a store, detailed information about the clothes is displayed through the smart glasses. For example, they can input text such as "What are the characteristics of this clothing?" and ask by voice, "Is this color trendy?". Furthermore, the glasses provide data such as "This is my favorite color" through images and "This is the latest trend in styles" through videos.

[1085] The server receives this data and analyzes it using the data analysis module. The emotion engine analyzes the user's excitement and interest, and the generative AI model generates appropriate VR content based on the analysis results. The generated content is instantly sent to the smart glasses and displayed in the user's field of view. The user's emotional state is monitored in real time, and if they are excited, new promotional information or interesting products are recommended.

[1086] Prompt Sentence Examples

[1087] "Generate a program for a system that inputs and analyzes detailed text information, related audio descriptions, and related images and videos about the clothes a user is looking at through smart glasses, and provides personalized information in real time according to the user's level of excitement and interest."

[1088] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1089] Step 1:

[1090] Users input text, voice, image, and video data through the smart glasses, which are then captured by the user interface and temporarily stored on the device. For example, a user might enter text such as "What are the characteristics of this clothing item?" and ask a voice question such as "Is this color trendy?"

[1091] Step 2:

[1092] The device sends the captured data to the server. Specifically, audio data, text data, image data, and video data are transferred to the server. At this stage, the input data arrives at the server.

[1093] Step 3:

[1094] The server distributes the received data to the data analysis modules. The text analysis module understands the context and keywords of the text, the audio analysis module analyzes the sound characteristics, the image analysis module recognizes the image characteristics, and the video analysis module analyzes the movie sequence. This analyzes the input data and provides the analysis results corresponding to each type of data. The output is the analyzed text, audio, image, and video information.

[1095] Step 4:

[1096] The server's emotion recognition means identifies the user's emotional state from the analyzed data. It analyzes the user's emotions, such as excitement or relaxation, based on the tone and pitch of the voice data and the content of the text data. The user's emotional state is identified as the output.

[1097] Step 5:

[1098] The server passes the analysis results and emotional state data to a generative AI model to generate personalized VR content for the user. The generative AI model then configures a scenario, characters, and environment that adapts to the user's emotional state. This generates personalized VR content. The output is VR content that matches the user's emotional state.

[1099] Step 6:

[1100] The server sends the generated VR content to the device, which then prepares the received VR content for display on the smart glasses. As an output, the displayable VR content is prepared.

[1101] Step 7:

[1102] The device displays the user-generated VR content through smart glasses. As the user experiences the VR content, their emotional state is monitored in real time based on their experience. If the user's excitement level is high, new information or interesting promotions will be displayed. In this way, the user receives a dynamically generated personalized shopping experience.

[1103] This processing step allows users to enjoy a personalized shopping experience in physical stores that is tailored to their emotional state.

[1104] 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.

[1105] 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.

[1106] 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.

[1107] [Fourth embodiment]

[1108] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1109] 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.

[1110] 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).

[1111] 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.

[1112] 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.

[1113] 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).

[1114] 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.

[1115] 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.

[1116] 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.

[1117] 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.

[1118] 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.

[1119] 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.

[1120] 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."

[1121] The system of the present invention receives inputs such as text, voice, images, and videos provided by users, analyzes and integrates them to generate virtual reality (VR) content, and provides it to users. This system mainly consists of three main components: a terminal, a server, and a user.

[1122] System Configuration

[1123] 1. Terminal functions

[1124] The terminal provides an interface for receiving input from the user. Through this interface, the user can send data such as text, audio, images, and video to the system. The terminal also temporarily stores the received data and sends it to the server.

[1125] 2. Server-side functionality

[1126] The server has many analysis modules that receive and analyze data sent from the device. The server uses text analysis, voice analysis, image analysis, and video analysis modules to perform detailed analysis of user input, making it easier to understand the user's intent and the context of the data.

[1127] The analyzed data is then passed to the generation AI, which generates scenarios, characters, and environments based on the analysis results to create virtual reality content. The generated content is then packaged on the server and converted into a format that can be provided to users.

[1128] 3. Providing a user experience

[1129] Users experience the generated content through a VR device. The server sends the completed VR content to the terminal, which then displays it on the VR device. Users can then use the VR device to enjoy the virtual experience.

[1130] Program processing explanation

[1131] The specific process is as follows:

[1132] Getting User Input

[1133] The device receives text, audio, images, and video through the user interface. When the user uploads this data, the device temporarily stores it and sends it to the server.

[1134] Data analysis and integration

[1135] The server receives data sent from the device and assigns it to an analysis module according to the data format. The text analysis module analyzes the input text and understands the context. The audio analysis module analyzes the provided audio data and understands the sound content. The image analysis module extracts image features, and the video analysis module analyzes video scenes.

[1136] The data obtained from the analysis module is integrated on the server and passed to a generative AI model, which uses the integrated data to generate scenarios, characters, and environments, building the overall VR content.

[1137] VR content generation and provision

[1138] Generative AI creates a personalized VR experience based on the user's intent, including a pirate treasure hunt story, realistic ocean sounds, ship images, and a treasure hunt movie.

[1139] The server packages the generated VR content and converts it into a format that can be experienced by the user. The packaged VR content is then sent to the terminal, which displays it on the VR device.

[1140] Specific examples

[1141] For example, suppose a user wants to create a "pirate treasure hunting story" and provides the text "pirate treasure hunting adventure," the audio "sound of waves," the image "ship," and the video "treasure hunting scene." This input data is sent to the server and analyzed appropriately by each analysis module. Based on the analysis results, the generation AI generates an active pirate scenario and environment, adding the sound of waves as a sound effect. The server integrates this and packages it into a single VR content, which is then sent to the device. The user can then experience this customized adventure through their VR device.

[1142] As described above, the system of the present invention allows users to easily create and enjoy personalized VR experiences.

[1143] The processing flow will be explained below.

[1144] Step 1:

[1145] The device displays a screen for uploading text, audio, images, and videos to the user, allowing them to select and upload the materials for the VR experience they want to create.

[1146] Step 2:

[1147] Users select the desired material and upload it to their device in the form of text, audio, images, or video. For example, text can be used to provide a story, audio can be used to provide an ambient sound, images can be used to provide a scene, and video can be used to provide a moving sequence.

[1148] Step 3:

[1149] The device temporarily stores the text, audio, images, and video provided by the user and prepares them for transmission. In this step, the data format of each material is checked for any errors.

[1150] Step 4:

[1151] The device sends the saved data to the server, along with the classification information of the data.

[1152] Step 5:

[1153] The server receives the data sent from the device, classifies it by type, and assigns it to the appropriate analysis module.

[1154] Step 6:

[1155] The server sends the text data to the text analysis module, which then extracts the context and keywords from the text and creates the outline of the scenario.

[1156] Step 7:

[1157] The server sends the audio data to the audio analysis module, which then extracts the audio characteristics and recognizes them as environmental sounds or sound effects.

[1158] Step 8:

[1159] The server sends the image data to the image analysis module, which analyzes the image for features and components and uses them as scene and character designs.

[1160] Step 9:

[1161] The server sends the video data to the video analysis module, which then extracts movie sequences and uses them as material for storyboards and animations.

[1162] Step 10:

[1163] The analysis results sent from the analysis modules are integrated into the server, which then aggregates them and passes the unified data set to the generative AI model.

[1164] Step 11:

[1165] The generative AI model generates VR content such as scenarios, characters, and environments based on the integrated dataset, and interactive elements are also created during this step.

[1166] Step 12:

[1167] The server packages the generated VR content and converts it into a format that can be experienced by the user, and saves the packaged content in the optimal format.

[1168] Step 13:

[1169] The server transmits the packaged VR content to the device, which receives the data.

[1170] Step 14:

[1171] The terminal transfers the received VR content to the VR device and prepares it for display, at which point the user interface is updated to display the option to start the experience.

[1172] Step 15:

[1173] Users use VR devices to experience the generated content, and their movements and reactions are collected and reflected in the interactive elements.

[1174] Step 16:

[1175] Users can provide feedback after their experience, which is sent to the server via their device and used to improve the experience and generate new content.

[1176] Example 1

[1177] 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."

[1178] Conventional virtual reality content generation systems have difficulty effectively analyzing and integrating diverse forms of data from users to provide personalized virtual reality experiences tailored to their individual needs. Furthermore, the content generation process is complex, making it difficult to generate consistent scenarios and characters.

[1179] 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.

[1180] In this invention, the server includes a means for receiving input in multiple forms from a user, such as text, audio, images, and videos, a data analysis means for analyzing the input in multiple forms and understanding its content, a means for integrating the analyzed data and generating virtual reality content based on a generative AI model, and a means for packaging the generated virtual reality content and providing it to the user, thereby enabling the user to easily generate and enjoy a personalized virtual reality experience using data in various forms.

[1181] A "means for receiving multiple forms of input from a user, such as text, audio, images, and video" is a device or method that provides an interface for receiving different forms of data, such as text, audio, images, and video, input from a user.

[1182] "Data analysis means" refers to a device or method for analyzing received data in multiple formats, such as text, audio, images, and video, and understanding its content.

[1183] A "generative AI model" is an artificial intelligence model that generates scenarios, characters, and environments based on analyzed data, and builds overall virtual reality content.

[1184] A "means for generating virtual reality content" is a device or method for generating a virtual reality experience based on the analyzed and synthesized data.

[1185] A "means for packaging and providing virtual reality content to a user" is a device or method for converting the generated virtual reality content into a format that can be experienced by a user and providing it to a user.

[1186] A "dedicated analysis module" is a separate piece of software or equipment that is specialized for analyzing each data format, such as text, audio, images, and video.

[1187] "Virtual reality experience" refers to interactive content that allows users to immerse themselves in a virtual environment and experience it as if it were real through their senses, such as sight and hearing.

[1188] The system of the present invention receives input data such as text, audio, images, and videos provided by users, analyzes and integrates them to generate virtual reality (VR) content, and provides it to users. This system mainly consists of three main components: a terminal, a server, and a user.

[1189] System Configuration

[1190] Terminal functions

[1191] The terminal provides an interface for receiving input from the user. Through the user interface, the user can send data such as text, audio, images, and videos to the system. The terminal temporarily stores the received data and sends it to the server. Specifically, the user can enter text such as "A pirate's treasure-hunting adventure" through the application, record the "sound of waves" using the voice recording function, and upload images and videos using the file selection dialog.

[1192] Server-side features

[1193] The server receives data sent from the terminal and has many analysis modules for analyzing it. The server uses the following analysis modules to analyze the data in detail.

[1194] The text analysis module uses natural language processing technology to analyze the input text and understand the meaning and context of the text.

[1195] The speech analysis module converts the provided speech data into acoustic features and understands the content.

[1196] The image analysis module extracts object and scene features from images.

[1197] The video analysis module analyzes the video frame by frame to understand the content of the scene.

[1198] The analyzed data is integrated on the server and passed to a generative AI model. The generative AI model generates scenarios, characters, and environments based on the integrated data to build the overall VR content. For example, a pirate adventure may unfold based on the generated scenario, with sound effects like the sound of waves playing in real time. Images of ships may also be set as backgrounds, and treasure hunt videos may be incorporated as part of the scenario.

[1199] Providing VR content

[1200] The server packages the generated VR content and converts it into a format that can be experienced by the user. This packaged VR content is sent to the terminal, which displays it on the VR device. The user can then experience a customized pirate adventure using the VR device. For example, when the user puts on the VR goggles, they can immerse themselves in the pirate world and enjoy the adventure through realistic sights and sounds.

[1201] Prompt Sentence Examples

[1202] Examples of prompts to input into a generative AI model include:

[1203] example:

[1204] "Generate virtual reality content for a story about pirates searching for treasure. Use 'A pirate's treasure-hunting adventure' for the text, 'The sound of waves' for the audio, 'A ship' for the image, and 'A treasure-hunting scene' for the video."

[1205] In this way, users can easily create and enjoy personalized VR experiences using data in a variety of formats.

[1206] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1207] Program processing flow

[1208] Step 1: Getting User Input

[1209] Step 2: Sending data

[1210] Step 3: Analyze the data

[1211] Step 4: Integrate the data

[1212] Step 5: Generate VR content

[1213] Step 6: Providing VR content

[1214] Detailed explanation of the processing steps

[1215] Step 1: Getting User Input

[1216] The terminal receives input data such as text, audio, images, and video through a user interface.

[1217] Input: User input of text, audio, images, and video

[1218] How it works: A user interacts with the application, enters "A pirate's treasure hunting adventure" into the text field, records the sound of "waves" using the voice recorder, and uploads image and video files.

[1219] Output: Text, audio, image, and video data temporarily stored on the device

[1220] Step 2: Sending data

[1221] The terminal transmits the temporarily stored data to the server.

[1222] Input: Stored text, audio, image, and video data

[1223] How it works: When the user presses the "upload" button, the device makes an HTTP request and sends the data to the server.

[1224] Output: Text, audio, image, and video data sent to the server

[1225] Step 3: Analyze the data

[1226] The server allocates the received data to each dedicated analysis module for analysis.

[1227] Input: Text, audio, image, and video data sent from your device

[1228] Operation: The server analyzes text using the text analysis module, converts audio data into acoustic features using the audio analysis module, extracts image features using the image analysis module, and analyzes video scenes using the video analysis module.

[1229] Output: Analysis result data from each analysis module

[1230] Step 4: Integrate the data

[1231] The server integrates the data obtained from each analysis module.

[1232] Input: Analysis result data from the analysis module

[1233] How it works: The analysis results are compiled into a single data structure, adjusted into a unified scenario and character configuration, and passed to a generative AI model.

[1234] Output: The aggregated data passed to the generative AI model

[1235] Step 5: Generate VR content

[1236] The generative AI generates VR content based on the integrated data.

[1237] Input: Integrated data

[1238] How it works: Generative AI generates scenarios, characters, and environments, combining content such as pirate adventures and the sound of waves to build an overall VR story.

[1239] Output: Generated VR content

[1240] Step 6: Providing VR content

[1241] The server packages the generated VR content and converts it into a format that can be delivered to the user.

[1242] Input: Generated VR content

[1243] How it works: The server packages the VR content and sends it to the device. The device displays the received content on the VR device. The user puts on the VR device and experiences the content.

[1244] Output: VR content that users can experience

[1245] Through these steps, users can create and enjoy personalized virtual reality experiences using data in a variety of formats.

[1246] (Application example 1)

[1247] 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."

[1248] In recent years, the demand for personalized content based on user interests and preferences has been growing rapidly. However, traditional content delivery services are limited to static text, images, and standard video streaming, making it difficult for users to achieve a more immersive experience. Furthermore, technologies for analyzing and integrating diverse inputs from multiple media formats to generate high-quality virtual reality (VR) content are limited. This calls for innovation to improve user satisfaction.

[1249] 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.

[1250] In this invention, the server includes means for receiving input in multiple forms such as text, audio, images, and videos from the user, data analysis means for analyzing the input in multiple forms and understanding its content, generation means for generating virtual reality content based on the analyzed data, and provision means for providing the generated virtual reality content to the user. This makes it possible to generate a personalized and immersive virtual reality experience based on the various data provided by the user and quickly provide it to the user.

[1251] 1. "Multiple forms of input" refers to different types of data provided by users, such as text, audio, images, and video.

[1252] 2. "Data Analysis Tools" are modules and algorithms used to analyze and understand multiple forms of input.

[1253] 3. "Generation means" means modules or algorithms for generating virtual reality content based on analyzed data.

[1254] 4. "Provision means" refers to the interface and communication means used to provide the generated virtual reality content to the user.

[1255] 5. "Data for customizing news content" refers to input data used to identify news and information that the user is interested in and reflect that in the VR footage.

[1256] 6. "Analysis module" refers to a program or algorithm for performing specialized analysis for each format, such as text, audio, image, or video.

[1257] 7. "Interface" means the operating screen or input device through which a user uploads text, audio, images, or video.

[1258] 8. "VR Video" means visual content created to provide users with a virtual reality experience.

[1259] 9. "Server" means a computer system that receives input data from users, analyzes it, and provides generated VR content.

[1260] The system of this invention generates virtual reality (VR) content based on input data in various formats and provides it to users. The system mainly consists of the following elements.

[1261] 1. Getting User Input

[1262] The terminal provides a means to receive multiple forms of input from the user, including text, audio, images, video, etc. Through this interface, the user can upload data in various forms.

[1263] 2. Data Analysis

[1264] The server receives the data sent from the device and analyzes it using a dedicated analysis module for each format. Different modules, such as text analysis, audio analysis, image analysis, and video analysis, are combined to gain a detailed understanding of the data's content. Specifically, natural language processing (NLP) models are used for text analysis, speech recognition APIs for audio analysis, image recognition algorithms (e.g., TensorFlow) for image analysis, and frame analysis tools (e.g., OpenCV) for video analysis.

[1265] 3. VR content generation

[1266] The analyzed data is integrated and input into a generative AI model, which generates scenarios, characters, and environments based on the integrated data to construct the overall VR content, which is then packaged on a server and converted into a tangible form.

[1267] 4. Provision of VR content

[1268] The server sends the generated VR content to the terminal, which then displays it on the VR device. The user experiences the generated content through the VR device. For example, they can immerse themselves in the virtual reality world using a VR headset (e.g., Oculus Quest).

[1269] Specific examples

[1270] Let's say a user wants to create a "pirate treasure hunting story" and provides the text "pirate treasure hunting adventure," the audio "sound of waves," the image "ship," and the video "treasure hunting scene." This input data is sent to the server and analyzed appropriately by each analysis module. Based on the analysis results, the generation AI generates an active pirate scenario and environment, adding the sound of waves as a sound effect. The server integrates this and packages it into a single VR content, which is then sent to the device. The user can then experience this customized adventure through their VR device.

[1271] Prompt Sentence Examples

[1272] The prompt text that the user enters will be in the following format:

[1273] "Text": "Pirate Treasure Adventure",

[1274] "Audio file": "wave_sound.mp3",

[1275] "Image file": "pirate_ship.png",

[1276] "video file": "treasure_hunt.mp4"

[1277] In this way, a personalized virtual reality experience tailored to individual preferences is generated based on the data provided by the user.

[1278] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1279] Step 1:

[1280] User data entry and upload

[1281] The user provides input data in multiple formats, including text, audio, images, and video, through the device interface. This data is temporarily stored on the device. Specifically, the user uploads the text "Pirate's Treasure Hunt Adventure," the audio "Sound of Waves," the image "Ship," and the video "Treasure Hunt Scene." The input data at this point is in the form of files or strings of various formats, and the output is a temporary file or memory storage.

[1282] Step 2:

[1283] Sending data to the server

[1284] The device sends the temporarily stored user data to the server. The server receives the data sent from the device and prepares it for analysis. At this time, each piece of data is assigned to the appropriate analysis module. The input is the user's data file, and the output is the transfer of data to the analysis module on the server.

[1285] Step 3:

[1286] Data analysis

[1287] Each analysis module in the server analyzes the received data. Specifically, the text analysis module uses natural language processing (NLP) to analyze text based on context, the audio analysis module converts audio content into text using a speech recognition API, the image analysis module extracts image features using an image recognition algorithm, and the video analysis module analyzes video scenes using a frame analysis tool. The input data are files of various formats and their content information, and the output is the analysis results (e.g., text, metadata, feature vectors, etc.).

[1288] Step 4:

[1289] Input to generative AI models

[1290] The analysis results of each data obtained from the analysis module are integrated and input into the generative AI model. The generative AI model generates scenarios, characters, and environments based on the integrated data to construct the overall VR content. The input of this step is the integrated analysis results, and the output is the constituent data of the generated VR content.

[1291] Step 5:

[1292] Packaging VR content and converting it on the server

[1293] The server packages the generated VR content and converts it into a format that can be displayed on the user's device, such as packaging scenario text, audio files, 3D models, scene data, etc. The input of this step is the configuration data of the generated VR content, and the output is a packaged VR content file.

[1294] Step 6:

[1295] Content provision

[1296] The server sends the packaged VR content to the terminal. The terminal displays the received VR content on a VR device (e.g., a VR headset) and provides it to the user. At this point, the user can enjoy the generated virtual reality experience. The input is the packaged VR content file, and the output is a display of the content.

[1297] Through these steps, a personalized and immersive virtual reality experience is generated based on the data provided by the user. For example, a virtual reality experience of a pirate's treasure hunt can be created.

[1298] 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.

[1299] The system of the present invention analyzes and integrates user inputs such as text, voice, images, and video to generate and provide personalized virtual reality (VR) content. Furthermore, by incorporating an emotion engine, the system is equipped with the ability to recognize user emotions and adjust content accordingly. The system primarily consists of three main components: a terminal, a server, and a user.

[1300] System Configuration

[1301] 1. Terminal functions

[1302] The device provides an interface that receives input from the user. Through this interface, the user can upload data such as text, audio, images, and video. The device temporarily stores the received data and transmits it to the server.

[1303] 2. Server-side functionality

[1304] The server receives the data sent from the device and distributes it to the analysis module corresponding to each format. It also has a built-in emotion engine that analyzes emotions based on the user's input data.

[1305] Data Analysis Modules: The text analysis module understands the context and keywords of a sentence, the audio analysis module analyzes sound features, the image analysis module recognizes image features, and the video analysis module analyzes movie sequences.

[1306] Emotion Engine: Analyzes emotions from text and voice to determine the user's state. The emotion engine can understand whether the user is amused, surprised, or in any other emotional state.

[1307] The analysis results are then integrated and fed into a generative AI model, which generates VR content such as scenarios, characters, and environments based on the analysis results, adjusting the content to suit the user's emotional state as needed.

[1308] 3. Providing a user experience

[1309] The user experiences the generated content through a VR device. The server sends the generated VR content to the terminal, which then displays it on the VR device. The user's emotional feedback is also taken into account, and the content is adjusted in real time as needed.

[1310] Program processing explanation

[1311] The specific process flow for a user to customize their VR experience is as follows:

[1312] Getting User Input

[1313] The device receives text, audio, image, and video input through a user interface. The user uploads these materials, which the device temporarily stores.

[1314] Data analysis and emotion recognition

[1315] The server receives the data sent from the terminal and assigns the data to an analysis module corresponding to each format: text analysis module, audio analysis module, image analysis module, and video analysis module.

[1316] The emotion engine performs emotional analysis based on user input data (especially text and voice) to identify emotional states. For example, it analyzes the tone and pitch of a user's voice to determine whether they are excited or relaxed.

[1317] Data integration and VR content generation

[1318] The server integrates the data obtained from the analysis module and emotion engine and passes it to the generative AI model. The generative AI generates virtual reality content based on this data. Based on the results of the emotion engine, a scenario and environment adapted to the user's emotional state are set up.

[1319] Providing VR content

[1320] The generative AI generates a personalized VR experience based on the user's emotional state, and this generated content is packaged on the server and sent to the device.

[1321] The terminal prepares the received VR content for display on the VR device. The user experiences the generated content through the VR device, and emotional changes are monitored in real time.

[1322] Specific examples

[1323] For example, if a user wants to create a "story about pirates searching for treasure," and provides "pirate's treasure-hunting adventure" in text, "sound of waves" in audio, "ship" in images, and "treasure hunting scene" in video, this input data is sent to the server.

[1324] The server analyzes this data through each analysis module, and the emotion engine analyzes the user's expectations and excitement. The analysis results are integrated and a personalized VR experience is generated by the generative AI. This generated content is sent to the terminal and displayed on the VR device.

[1325] As the user experiences this customized adventure through the VR device, their emotional state is continuously monitored and the content is adjusted accordingly. For example, if the system determines that the user is bored, it will add new, interesting scenarios or surprise elements. In this way, the system provides a personalized VR experience that dynamically changes based on the user's emotions.

[1326] The processing flow will be explained below.

[1327] Step 1:

[1328] The device displays a screen for uploading text, audio, images, and videos to the user, allowing them to select and upload the materials for their desired VR experience.

[1329] Step 2:

[1330] Users select the material they want and upload it to their device in the form of text, audio, images, or video. For example, text can be used to provide a story, audio can be used to provide an ambient sound, images can be used to provide a scene, and video can be used to provide a moving sequence.

[1331] Step 3:

[1332] The device temporarily stores the text, audio, images, and video provided by the user and prepares them for transmission. During this step, the data format of each material is checked for any errors.

[1333] Step 4:

[1334] The terminal transmits the saved data to the server, along with the data format information.

[1335] Step 5:

[1336] The server receives the data sent from the device, classifies it by type, and assigns it to the appropriate analysis module.

[1337] Step 6:

[1338] The server sends the text data to the text analysis module, which then extracts the context and keywords from the text and creates the outline of the scenario.

[1339] Step 7:

[1340] The server sends the audio data to the audio analysis module, which then extracts the audio characteristics and recognizes them as environmental sounds or sound effects.

[1341] Step 8:

[1342] The server sends the image data to the image analysis module, which analyzes the image for features and components and uses them to design scenes and characters.

[1343] Step 9:

[1344] The server sends the video data to the video analysis module, which then extracts movie sequences and uses them as material for storyboards and animations.

[1345] Step 10:

[1346] The analysis results sent from the analysis modules are integrated into the server, which then aggregates them and passes the unified data set to the generative AI model.

[1347] Step 11:

[1348] The server sends the text and voice data to the emotion engine, which then analyzes the user's emotional state from the text and voice data to determine emotions such as joy, surprise, and sadness.

[1349] Step 12:

[1350] The generative AI model generates VR content such as scenarios, characters, and environments based on the results of the integrated dataset and emotion engine, and can also adjust the content based on the user's emotional state.

[1351] Step 13:

[1352] The server packages the generated VR content in real time and converts it into a format that can be experienced by the user, and the packaged content is saved in the optimal format.

[1353] Step 14:

[1354] The server transmits the packaged VR content to the device, which receives the data.

[1355] Step 15:

[1356] The terminal transfers the received VR content to the VR device and prepares it for display, at which point the user interface is updated to display the option to start the experience.

[1357] Step 16:

[1358] The user experiences the generated content using a VR device, and the emotion engine monitors the user's emotional state during the experience and adjusts the content accordingly.

[1359] Step 17:

[1360] Users can provide feedback after their experience, which is sent to the server via their device and used to improve the experience and generate new content.

[1361] Example 2

[1362] 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."

[1363] In modern virtual reality (VR) technology, it is important to provide users with personalized content. However, there are still many shortcomings in the technology for receiving and analyzing user input data in multiple formats, and then generating and adjusting content based on the user's emotional state. In particular, implementing a system that adapts to the user's emotional feedback in real time is challenging. Therefore, more advanced and flexible analysis and generation mechanisms are needed to improve the quality of the user experience.

[1364] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving input in multiple forms, such as text, audio, images, and videos, from the user; data analysis and emotion analysis means for analyzing the input in multiple forms, understanding its content, and determining the user's emotional state; generation means for generating virtual reality content using a generative AI model based on the analyzed data and the emotion analysis results; and provision means for providing the generated virtual reality content to the user. This makes it possible to analyze the user's input data in multiple forms in detail and generate and provide personalized VR content based on the results and the user's emotional state.

[1365] "User Input" refers to information provided by users in multiple formats, including text, audio, images, and video.

[1366] "Data analysis and emotion analysis means" refers to technology that analyzes multiple forms of input from users, understands their content, and determines their emotional state.

[1367] A "generative AI model" is an artificial intelligence technology that automatically generates virtual reality content based on analyzed data and emotion analysis results.

[1368] "Virtual reality content" refers to digital content, including scenarios, characters, environments, etc., that users experience through VR devices.

[1369] "Providing means" refers to the technology used to transmit the generated virtual reality content to the user's terminal and display it on the VR device.

[1370] "Emotional feedback" refers to the emotional changes and reactions that users display while experiencing virtual reality content.

[1371] The system of the present invention analyzes and integrates user inputs such as text, voice, images, and video to generate and provide personalized virtual reality (VR) content. Furthermore, by incorporating an emotion engine, the system is equipped with the ability to recognize user emotions and adjust content accordingly.

[1372] System Configuration

[1373] This system mainly consists of three main elements: terminals, servers, and users.

[1374] 1. Terminal functions

[1375] The device provides an interface that receives input from the user. Through this interface, the user can upload data such as text, audio, images, and video. The device temporarily stores the received data and transmits it to the server.

[1376] 2. Server-side functionality

[1377] The server receives the data sent from the device and distributes it to the analysis module corresponding to each format. It also has a built-in emotion engine that analyzes emotions based on the user's input data.

[1378] Data Analysis Module

[1379] The text analysis module understands the context and keywords of the text.

[1380] The audio analysis module analyzes the characteristics of the sound.

[1381] The image analysis module recognizes features in the image.

[1382] The video analysis module analyzes movie sequences.

[1383] Emotion Engine

[1384] Emotions are analyzed from text and voice to determine the user's state. The emotion engine can determine whether the user is amused, surprised, or in some other emotional state. The analysis results are integrated and passed to a generative AI model. This generative AI generates VR content such as scenarios, characters, and environments based on the analysis results, and adjusts the content to match the user's emotional state as needed.

[1385] 3. Providing a user experience

[1386] The user experiences the generated content through a VR device. The server sends the generated VR content to the terminal, which then displays it on the VR device. The user's emotional feedback is also taken into account, and the content is adjusted in real time as needed.

[1387] Specific examples

[1388] For example, if a user wants to create a "pirate treasure hunting story" and provides the following input:

[1389] Text: "A pirate's treasure hunting adventure"

[1390] Audio: "Sound of waves"

[1391] Image: "Ship"

[1392] Video: "Treasure Hunt Scene"

[1393] These input data are sent to the server, where each analysis module analyzes the data, and the emotion engine analyzes the user's expectations and excitement. The analysis results are integrated, and a personalized VR experience is generated by the generative AI. This generated content is sent to the terminal, where it is displayed on the VR device.

[1394] As the user experiences this customized adventure through the VR device, their emotional state is continuously monitored and the content is adjusted accordingly. For example, if the system determines that the user is bored, it will add new, interesting scenarios or surprise elements. In this way, the system provides a personalized VR experience that dynamically changes based on the user's emotions.

[1395] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1396] Step 1:

[1397] The terminal receives text, audio, image, and video input through a user interface. The user provides these materials to the terminal by entering text in a text field and uploading audio files, image files, and video files. For example, the user enters "A pirate's treasure hunting adventure" in a text field and uploads an audio file of the sound of waves, an image file of a ship, and a video file of a treasure hunting scene. The terminal temporarily stores them and compiles them to be sent to the server as a transaction.

[1398] Step 2:

[1399] The device sends the temporarily stored data to the server. Communication is performed using a secure protocol (e.g., HTTPS). For example, the device compresses text, audio, image, and video files and sends them to the server. The input is various media files obtained from the user, and the output is a data package sent to the server.

[1400] Step 3:

[1401] The server receives data packages sent from the terminal. The data packages include text, audio, image, and video files. The server then assigns these different types of data to the respective analysis modules. The input is the data package received from the terminal, and the output is the data of each type assigned to the analysis module.

[1402] Step 4:

[1403] The text analysis module analyzes the received text data. For example, it analyzes the text "A pirate's treasure-hunting adventure" and extracts key keywords such as "pirate," "treasure," and "adventure." Based on this, it identifies the basic elements for generating a scenario. The input is text data, and the output is the extracted keywords and contextual information.

[1404] Step 5:

[1405] The audio analysis module analyzes the received audio data. For example, it analyzes the sound of waves, identifies their rhythm and pitch, and extracts elements that recreate a seaside environment. The input is audio data, and the output is sound feature information.

[1406] Step 6:

[1407] The image analysis module analyzes the received image data. For example, it analyzes an image of a ship to identify its shape, color, and background information, which are then used to create a 3D model. The input is image data, and the output is image feature information.

[1408] Step 7:

[1409] The video analysis module analyzes the received video data. For example, it analyzes a video of a treasure hunt scene frame by frame to identify sequences and important actions. The input is the video data, and the output is sequence information and information identifying important actions.

[1410] Step 8:

[1411] The emotion engine analyzes the user's emotional state based on the received text and voice data. For example, if the user speaks in an excited tone, it determines that the user is excited. The input is text and voice data, and the output is information about the user's emotional state.

[1412] Step 9:

[1413] The server integrates the data obtained from the analysis modules and emotion engine and passes it to the generative AI model. For example, it combines the analysis results of text, audio, images, and video, along with emotional state information, into a single data package. The input is the output from each analysis module and emotion engine, and the output is the integrated data package.

[1414] Step 10:

[1415] The generative AI model generates virtual reality content based on a provided data package. For example, it creates a 3D model, scenario, and environment setting based on a "pirate treasure hunting adventure" scenario. The input is the integrated data package, and the output is the generated virtual reality content.

[1416] Step 11:

[1417] The server packages the generated virtual reality content and transmits it to the terminal, for example, by encoding the generated content into an appropriate format and compressing it for transmission to the terminal, where the input is the generated virtual reality content and the output is the data package transmitted to the terminal.

[1418] Step 12:

[1419] The terminal provides the received virtual reality content to the VR device. The terminal unpacks the received content and streams it to the VR device for display. The input is the data package received from the server, and the output is the virtual reality content experienced by the user.

[1420] Step 13:

[1421] The server monitors emotional changes during the user experience and adjusts the content in real time as needed. For example, if it determines that the user is bored, it adds new, interesting scenarios or surprise elements. It issues commands to the generative AI to do so. The input is the user's emotional feedback, and the output is the adjusted virtual reality content.

[1422] (Application example 2)

[1423] 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."

[1424] Conventional virtual reality (VR) content generation systems have the ability to analyze user input data and generate content, but it is difficult to dynamically adjust the content according to the user's emotions. Furthermore, to improve the shopping experience in brick-and-mortar stores, personalized information provision that takes into account the user's emotional state is required. Therefore, a system that recognizes the user's emotions and dynamically adjusts VR content based on those emotions is needed.

[1425] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input in multiple forms from the user, such as text, audio, images, and videos; data analysis means for analyzing the input in multiple forms and understanding its content; generation means for generating virtual reality content based on the analyzed data; and emotion recognition means for analyzing the user's emotions and dynamically adjusting the virtual reality content based on the analysis results. This makes it possible to provide seamless and personalized VR content according to the user's emotional state.

[1426] "Text input" is data in the form of text from the user.

[1427] "Voice input" refers to sound data from a user, particularly data that refers to spoken words.

[1428] "Image input" is still image data from the user.

[1429] "Video input" is video data from the user.

[1430] "Data analysis means" is a function for analyzing input data in multiple formats and understanding its contents.

[1431] "Generation means" is a function for generating virtual reality content based on analyzed data.

[1432] "Providing means" is a function for providing the generated virtual reality content to the user.

[1433] The "emotion recognition means" is a function for analyzing the user's emotions and dynamically adjusting the virtual reality content based on the analysis results.

[1434] "Interface" means the means by which a User can upload text, audio, image, or video data.

[1435] An "analysis module" is a dedicated function for analyzing data in a specific format (text, audio, image, video).

[1436] The system of the present invention is designed to enhance the user's shopping experience in a physical store. Specifically, smart glasses can be used to provide detailed product information and related content in real time when the user views the product. The system consists of the following main components: a user, a terminal (smart glasses), and a server.

[1437] System Configuration

[1438] 1. Terminal features:

[1439] The smart glasses, which are the terminal, provide an interface that receives text, voice, image, and video input from the user. When a user sees a product, they can ask questions by voice or input text to get more information about it. The smart glasses are equipped with a camera and microphone, which capture video and audio data.

[1440] 2. Server-side functionality:

[1441] The server receives and analyzes data sent from the device. Specifically, it has the following functions:

[1442] - Data Analysis Modules: Data is analyzed using dedicated analysis modules for text, audio, image, and video formats. The text analysis module understands the context and keywords of the text, the audio analysis module analyzes sound features, the image analysis module recognizes image features, and the video analysis module analyzes movie sequences.

[1443] - Emotion recognition means: The device incorporates an emotion engine to analyze emotions from user input data, for example, analyzing the tone and pitch of a user's voice from audio data to identify the user's emotional state.

[1444] - Generation method: Based on the analysis results, a generative AI model is used to generate personalized virtual reality content for the user, dynamically adjusting the scenario, characters, environment, etc. based on the user's emotional state.

[1445] Specific examples

[1446] As a user looks at clothes in a store, detailed information about the clothes is displayed through the smart glasses. For example, they can input text such as "What are the characteristics of this clothing?" and ask by voice, "Is this color trendy?". Furthermore, the glasses provide data such as "This is my favorite color" through images and "This is the latest trend in styles" through videos.

[1447] The server receives this data and analyzes it using the data analysis module. The emotion engine analyzes the user's excitement and interest, and the generative AI model generates appropriate VR content based on the analysis results. The generated content is instantly sent to the smart glasses and displayed in the user's field of view. The user's emotional state is monitored in real time, and if they are excited, new promotional information or interesting products are recommended.

[1448] Prompt Sentence Examples

[1449] "Generate a program for a system that inputs and analyzes detailed text information, related audio descriptions, and related images and videos about the clothes a user is looking at through smart glasses, and provides personalized information in real time according to the user's level of excitement and interest."

[1450] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1451] Step 1:

[1452] Users input text, voice, image, and video data through the smart glasses, which are then captured by the user interface and temporarily stored on the device. For example, a user might enter text such as "What are the characteristics of this clothing item?" and ask a voice question such as "Is this color trendy?"

[1453] Step 2:

[1454] The device sends the captured data to the server. Specifically, audio data, text data, image data, and video data are transferred to the server. At this stage, the input data arrives at the server.

[1455] Step 3:

[1456] The server distributes the received data to the data analysis modules. The text analysis module understands the context and keywords of the text, the audio analysis module analyzes the sound characteristics, the image analysis module recognizes the image characteristics, and the video analysis module analyzes the movie sequence. This analyzes the input data and provides the analysis results corresponding to each type of data. The output is the analyzed text, audio, image, and video information.

[1457] Step 4:

[1458] The server's emotion recognition means identifies the user's emotional state from the analyzed data. It analyzes the user's emotions, such as excitement or relaxation, based on the tone and pitch of the voice data and the content of the text data. The user's emotional state is identified as the output.

[1459] Step 5:

[1460] The server passes the analysis results and emotional state data to a generative AI model to generate personalized VR content for the user. The generative AI model then configures a scenario, characters, and environment that adapts to the user's emotional state. This generates personalized VR content. The output is VR content that matches the user's emotional state.

[1461] Step 6:

[1462] The server sends the generated VR content to the device, which then prepares the received VR content for display on the smart glasses. As an output, the displayable VR content is prepared.

[1463] Step 7:

[1464] The device displays the user-generated VR content through smart glasses. As the user experiences the VR content, their emotional state is monitored in real time based on their experience. If the user's excitement level is high, new information or interesting promotions will be displayed. In this way, the user receives a dynamically generated personalized shopping experience.

[1465] This processing step allows users to enjoy a personalized shopping experience in physical stores that is tailored to their emotional state.

[1466] 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.

[1467] 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.

[1468] 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.

[1469] 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.

[1470] 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.

[1471] 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.

[1472] 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).

[1473] 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.

[1474] 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."

[1475] 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.

[1476] 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).

[1477] 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.

[1478] 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.

[1479] 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.

[1480] 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.

[1481] 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.

[1482] 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.

[1483] 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.

[1484] 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.

[1485] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1486] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1487] The following is further disclosed regarding the above embodiment.

[1488] (Claim 1)

[1489] A means of receiving multiple forms of input from users, including text, audio, images, and video;

[1490] data analysis means for analyzing the input in the multiple formats and understanding the content thereof;

[1491] a generating means for generating virtual reality content based on the analyzed data;

[1492] a providing means for providing the generated virtual reality content to a user;

[1493] A system including:

[1494] (Claim 2)

[1495] 2. The system according to claim 1, wherein when parsing the input of the multiple formats, a dedicated parsing module for each format is used.

[1496] (Claim 3)

[1497] 2. The system of claim 1, wherein the means for receiving input from the user provides an interface that allows uploading of text, audio, images, and video.

[1498] "Example 1"

[1499] (Claim 1)

[1500] A means of receiving multiple forms of input from users, including text, audio, images, and video;

[1501] data analysis means for analyzing the input in the multiple formats and understanding the content thereof;

[1502] means for integrating the analyzed data and generating virtual reality content based on a generative AI model;

[1503] a means for packaging and providing the generated virtual reality content to a user;

[1504] A system including:

[1505] (Claim 2)

[1506] 2. The system according to claim 1, wherein when parsing the input of the multiple formats, a dedicated parsing module for each format is used.

[1507] (Claim 3)

[1508] 2. The system of claim 1, wherein the means for receiving input from the user provides an interface that allows uploading of text, audio, images, and video.

[1509] "Application Example 1"

[1510] New Claims

[1511] (Claim 1)

[1512] A means of receiving multiple forms of input from users, including text, audio, images, and video;

[1513] data analysis means for analyzing the input in the multiple formats and understanding the content thereof;

[1514] a generating means for generating virtual reality content based on the analyzed data;

[1515] a providing means for providing the generated virtual reality content to a user;

[1516] A method for analyzing data to customize news content and generating VR images based on the results.

[1517] A system including:

[1518] (Claim 2)

[1519] 2. The system according to claim 1, wherein when parsing the input of the multiple formats, a dedicated parsing module for each format is used.

[1520] (Claim 3)

[1521] 2. The system of claim 1, wherein the means for receiving input from the user provides an interface that allows uploading of text, audio, images, and video.

[1522] "Example 2: Combining Emotion Engines"

[1523] (Claim 1)

[1524] A means of receiving multiple forms of input from users, including text, audio, images, and video;

[1525] data analysis and emotion analysis means for analyzing the multiple forms of input to understand its content and determine the user's emotional state;

[1526] A generating means for generating virtual reality content using a generative AI model based on the analyzed data and the emotion analysis results;

[1527] a providing means for providing the generated virtual reality content to a user;

[1528] A system including:

[1529] (Claim 2)

[1530] 2. The system according to claim 1, wherein when analyzing the input in multiple formats, a dedicated analysis module and a sentiment analysis module are used for each format.

[1531] (Claim 3)

[1532] 10. The system of claim 1, wherein the means for receiving input from the user provides an interface that allows uploading of text, audio, images, and video, and the generated virtual reality content is adjusted in real time based on the user's emotional feedback.

[1533] "Application example 2 when combining emotion engines"

[1534] (Claim 1)

[1535] A means of receiving multiple forms of input from users, including text, audio, images, and video;

[1536] data analysis means for analyzing the input in the multiple formats and understanding the content thereof;

[1537] a generating means for generating virtual reality content based on the analyzed data;

[1538] a providing means for providing the generated virtual reality content to a user;

[1539] an emotion recognition means for analyzing the emotion of a user and dynamically adjusting the virtual reality content based on the analysis result;

[1540] A system including:

[1541] (Claim 2)

[1542] 2. The system according to claim 1, wherein when parsing the input of the multiple formats, a dedicated parsing module for each format is used.

[1543] (Claim 3)

[1544] 2. The system of claim 1, wherein the means for receiving input from the user provides an interface that allows uploading of text, audio, images, and video. [Explanation of symbols]

[1545] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving multiple forms of input from users, including text, audio, images, and video; data analysis means for analyzing the input in the multiple formats and understanding the content thereof; a generating means for generating virtual reality content based on the analyzed data; a providing means for providing the generated virtual reality content to a user; A system including:

2. 2. The system of claim 1, wherein said inputs of multiple formats are parsed using a dedicated parsing module for each format.

3. 2. The system of claim 1, wherein the means for receiving input from the user provides an interface that allows uploading of text, audio, images, and video.

Images