system

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a news article and parsing its content; means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content based on the parsed news content; means for obtaining user device information and choosing an optimal experience format; means for delivering the generated experience content to the user's device; and means for displaying the experience content and enabling interaction on the user's device.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional news articles are provided in the form of text and video, but there are limitations to how much the recipient can truly grasp the content. This can lead to a lack of understanding of the news or a waning of interest. In particular, when the content of the news is difficult to grasp, the information lacks reality and is difficult to link to action. Therefore, there is a need for technology that can increase recipients' interest and lead to action by providing a deeper understanding and realization of the news content. [Means for solving the problem]

[0005] The present invention provides a means for receiving news articles and analyzing their content, and a means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content. The present invention also provides a system that includes a means for acquiring user device information and selecting an optimal experiential format, a means for delivering the generated experiential content to the user's device, and a means for displaying the experiential content on the user's device and enabling interaction. This allows the news content to become "personal" to the recipient, leading to a deeper understanding and interest. By using natural language processing to extract information about the subject, location, events, and characters of the news article, the news content is accurately reproduced, and device information is acquired from the user's registered profile information, and the optimal experiential format is selected based on that information. As a result, the news content is more immersive, providing an experience that blends with reality and inspires deeper understanding and interest.

[0006] 1. A "news article" is a written or visual piece containing events or information provided by a news organization or individual.

[0007] 2. "Receiving" is the process of obtaining data from the outside.

[0008] 3. "Analysis" is the process of breaking down and analyzing received data to make it easier to understand.

[0009] 4. "Virtual reality (VR)" is a technology that allows you to experience a three-dimensional virtual space generated using computer technology.

[0010] 5. "Augmented reality (AR)" is a technology that overlays digital information and virtual objects onto real-world scenery.

[0011] 6. "Mixed reality (MR)" is a technology that seamlessly integrates virtual reality and the real world, allowing users to experience both simultaneously.

[0012] 7. "Experiential content" refers to a collection of digital information and scenarios provided to users to allow them to experience and understand the content of the news.

[0013] 8. "Device Information" means information about the type, performance, and functions of the device used by the User.

[0014] 9. "Selection" is the process of choosing the best option from multiple options.

[0015] 10. "Distribution" is the process of delivering generated digital content to users.

[0016] 11. "Preparing for display" is the process of configuring received digital content for proper display on a user's device.

[0017] 12. "Interaction" is the process by which a user interacts with content provided on a device.

[0018] 13. "Natural Language Processing (NLP)" is a technology that enables computers to understand and analyze human language.

[0019] 14. A "subject" is the main topic or theme in a news story.

[0020] 15. "Location" is the specific geographic location where the event described in the news article occurred.

[0021] 16. An "incident" is a specific event or action reported in a news article.

[0022] 17. "Characters" are individuals or entities mentioned in a news story. [Brief explanation of the drawings]

[0023] [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

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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."

[0044] This invention is a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies to help users experience the content of news articles. The program for this system performs processing in the following steps.

[0045] Program processing

[0046] 1. Receiving and analyzing news articles

[0047] server

[0048] Receive news articles from external news providers via API or RSS feed.

[0049] It uses natural language processing (NLP) algorithms on incoming news articles to extract key information such as subject, location, events, and characters.

[0050] For example, if an article is about the progression of a typhoon, extract terms such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[0051] 2. Obtaining user information and selecting the experience format

[0052] server

[0053] Get device information from the user's profile information.

[0054] Example: Checking if the user owns a VR device or has an AR-enabled smartphone.

[0055] The optimal experience format (VR, AR, MR) is selected based on the news content and the user's device information.

[0056] Example: If you have a VR device, simulate the progression of a typhoon in a virtual space.

[0057] 3. Creating experience content

[0058] server

[0059] Based on the news content, it generates content for users to experience, including 3D models, scenarios, audio, and video.

[0060] Example: To simulate the progression of a typhoon, generate a 3D model and audio that expresses the strength of wind and rain.

[0061] Retrieve external resources (e.g., 3D model databases, weather data) as needed and integrate them into your content.

[0062] 4. Content Delivery

[0063] server

[0064] The generated experience content is streamed to the user's device.

[0065] Example: Compressing typhoon simulation data and delivering it with low latency.

[0066] 5. Preparation for the experience

[0067] Terminal

[0068] Processes the received content and prepares it for display.

[0069] For VR headsets, set up the 360-degree environment and enable user eye tracking.

[0070] In the case of AR devices, the camera is activated to overlay virtual content onto the real world.

[0071] 6. Experience Delivery and User Interaction

[0072] User

[0073] Use your device to experience news content.

[0074] In VR, users can observe the progress of the typhoon while exploring the virtual space.

[0075] With AR, predicted rainfall and wind speed information is overlaid on the scenery around your home using your smartphone.

[0076] Display additional information or provide interaction as needed.

[0077] Example: Displaying detailed information to confirm safe evacuation routes and countermeasures.

[0078] Specific examples

[0079] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[0080] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[0081] 2. The server checks the user's device information, and if the user has a VR device, generates content to be experienced in VR format.

[0082] 3. The server generates a 3D model and audio simulating the typhoon's progression and streams it to the user's VR headset.

[0083] 4. The device processes the received content and prepares it so that the user can wear the VR headset and experience the 3D model.

[0084] 5. Users put on a VR headset and observe the progress of the typhoon in a virtual space, checking safe evacuation routes, etc.

[0085] This allows users to gain a deeper understanding of the content of news articles and experience them in a realistic way. Through this experience, users perceive the information as something that concerns them personally, making it easier for them to take actual action.

[0086] The processing flow will be explained below.

[0087] Step 1:

[0088] The server receives news articles from external news providers via API or RSS feeds, and stores them on the server.

[0089] Step 2:

[0090] The server applies natural language processing (NLP) algorithms to the received news articles to extract key information such as themes, locations, events, and characters. As a result, the elements of the news article are classified as follows:

[0091] Subject: Typhoon

[0092] Location: Japan

[0093] Incident: Heavy rain

[0094] Characters: Citizens, safety officials

[0095] Step 3:

[0096] The server retrieves the user's device information from the user profile database. The profile data includes which device the user is using, the type of device, and its capabilities.

[0097] Step 4:

[0098] The server selects the optimal experience format (VR, AR, or MR) based on the news content and the user's device information. For example, if the user owns a VR device, it selects the experience content in VR format.

[0099] Step 5:

[0100] The server generates content for users to experience based on the news content. The content includes 3D models, scenarios, audio, and video. Data to represent the progress of the typhoon and the strength of the wind and rain is generated as a 3D model.

[0101] Step 6:

[0102] The server references external resources (e.g., weather data or 3D model databases) to obtain additional data that matches the news content and integrates it into the generated content.

[0103] Step 7:

[0104] The server streams the generated experience content to the user's device, appropriately compressed and configured for low latency delivery.

[0105] Step 8:

[0106] The device unpacks and processes the received content and prepares it for display. For VR headsets, this involves configuring the 360-degree environment and enabling the user's eye-tracking. For AR devices, this involves activating the camera and overlaying virtual content onto the real-world scene.

[0107] Step 9:

[0108] Users experience the news content using a device. In the case of VR, users wear a VR headset and observe the progress of the typhoon in a virtual space. In the case of AR, users use their smartphone to view forecasted rainfall and wind speed information overlaid on the real world.

[0109] Step 10:

[0110] The interface allows users to obtain additional information and interact as needed, for example by displaying detailed information to check evacuation routes or check countermeasures.

[0111] This allows users to experience the content of news articles in detail and in a realistic way, which is expected to lead to a deeper understanding of the news content and make it easier for users to perceive it as something that concerns them personally.

[0112] Example 1

[0113] 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."

[0114] Conventional news article delivery methods have had issues with insufficient information transmission, especially for disaster and incident information, as it is difficult for users to grasp the reality of the information. Furthermore, they are unable to fully support the diverse devices used by users, making it difficult to experience the news in the most optimal way. Furthermore, there was a lack of a mechanism for integrating appropriate external resources based on extracted news content, making it difficult to create a realistic experience.

[0115] 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.

[0116] In this invention, the server includes means for receiving news articles and analyzing their contents, means for extracting information on themes, locations, events, and characters contained in the news articles using natural language processing, means for acquiring user profile information and selecting an optimal experience format, means for delivering the generated experience content to the user's device with low latency, means for displaying the experience content on the user's device and enabling interaction, and means for integrating external resources based on the news articles. This allows users to easily visually experience the news content in an experience format such as virtual reality (VR), augmented reality (AR), or mixed reality (MR), improving the effectiveness of information transmission and facilitating linking it to actual actions.

[0117] "News Article" means content received from a news provider via API or RSS feed that contains information about a particular event, occurrence, or topic.

[0118] "Analysis" involves using natural language processing (NLP) algorithms on incoming news articles to extract key information from the article, such as themes, locations, events, and characters.

[0119] "Natural Language Processing (NLP)" is a technology that enables computers to understand, analyze, and generate human language, and is used to extract useful information from text.

[0120] "Profile information" is information that indicates a user's attributes and tendencies, such as device information registered by the user, areas of interest, and past usage history.

[0121] "Experience format" refers to the way in which users experience news content, and includes virtual reality (VR), augmented reality (AR), and mixed reality (MR).

[0122] "Generation" refers to the creation of experiential content such as 3D models, scenarios, audio, and video based on the news content and the selected experience format.

[0123] "Low latency" refers to data transmission and reception with minimal delay, and is an important technology for achieving a real-time experience.

[0124] "Interaction" refers to a user's direct interaction with experiential content through a device, with the content dynamically changing in response to the user's operations and actions.

[0125] "External resources" are data or information obtained from external sources to complement news content, such as 3D model databases or weather data APIs.

[0126] This system generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies to help users experience the content of news articles more realistically. Below, we list each processing step and explain how to implement it.

[0127] Receiving and analyzing news articles

[0128] The server receives news articles from news providers via APIs or RSS feeds, then uses natural language processing (NLP) algorithms to extract key information from the articles, such as themes, locations, events, and characters. The software used is an NLP library (e.g., SpaCy or NLTK).

[0129] Example: A server receives news articles about typhoons from "News Provider A" via API, and uses SpaCy to extract information about "typhoons," "Japan," "heavy rain," and "citizens."

[0130] Obtaining user information and selecting experience format

[0131] The server obtains the user's profile information (device information, areas of interest, past usage history, etc.) and selects the optimal experience format (VR, AR, MR) for the news content based on the device information.

[0132] Example: The server checks the user's profile information from a database, detects that the user has a VR device, and determines that if the news item is about a typhoon progressing, it would be best experienced in VR format.

[0133] Creating experience content

[0134] The server generates experience content such as 3D models, scenarios, audio, and video based on the news content and the selected experience format. External resources (e.g., 3D model databases, weather data APIs, etc.) are integrated and reflected in the content. 3D models are generated using 3D engines such as Unity and Unreal Engine.

[0135] Example: A server uses a weather data API to obtain forecast data for a typhoon's progress, and uses Unity to generate a 3D model that visualizes the strength of the wind and rain.

[0136] Content Delivery

[0137] The server generates the experience content and delivers it to the user's device with low latency using low-latency technologies (e.g., WebRTC or RTMP).

[0138] Example: Server-generated typhoon simulation data is compressed and delivered in real time to the user's VR device using WebRTC.

[0139] Preparing for the experience

[0140] The device processes the received content and prepares the experience, setting up the 360-degree environment for VR devices, and activating the camera for AR devices to overlay virtual content onto the real world.

[0141] Example: A user's VR device analyzes typhoon simulation data received from a server, sets up a 360-degree view, and enables eye tracking. The AR device activates the camera and displays a virtual typhoon progression simulation overlaid on the real landscape.

[0142] Experience delivery and user interaction

[0143] Users experience the news content using a device. In the case of VR, users can freely explore the virtual space and observe the progress of the typhoon. In the case of AR, forecasted rainfall and wind speed information is superimposed on the area around their home.

[0144] Example: A user wears a VR device and observes a typhoon in progress in a virtual space, checking changes in wind and rain and safe evacuation routes. Using an AR device, a user can check real-time wind speed information and forecasted rainfall around their home via their smartphone, and consider countermeasures at home.

[0145] Prompt Sentence Examples

[0146] "I want to experience a news article about a typhoon approaching Japan in virtual reality. Please generate simulation content including the typhoon's progress, rainfall, wind speed, evacuation routes, etc."

[0147] By using this system, users can experience the contents of news articles in a realistic way, deepening their understanding of the information and making it easier to link it to actual actions.

[0148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0149] Step 1:

[0150] Receiving and analyzing news articles

[0151] The server receives news articles from news providers via API or RSS feed.

[0152] Input: A news article feed from a news provider.

[0153] Output: Received news article data.

[0154] How it works: The server sends an API request and receives news article data in JSON format. It then uses natural language processing (NLP) algorithms to parse the article and extract key information such as the subject, location, events, and characters. The NLP libraries used are SpaCy and NLTK.

[0155] Step 2:

[0156] Obtaining user information and selecting experience format

[0157] The server retrieves the user's profile information from a database.

[0158] Input: User's registered profile information.

[0159] Output: User's device information.

[0160] Specific operation: The server searches the database for profile information using the user ID as a key and obtains information about the device owned by the user. Based on the user's device information, it checks whether the user has a VR device, an AR-compatible smartphone, or other device. It then selects the optimal experience format (VR, AR, or MR) based on the news content.

[0161] Step 3:

[0162] Creating experience content

[0163] The server generates experience content based on the news content and the selected experience format.

[0164] Input: Parsed news information, user device information.

[0165] Output: The generated experience content (3D models, scenarios, audio, video, etc.).

[0166] Specific operation: The server obtains additional information from external resources such as weather data APIs and generates content using a 3D engine such as Unity or Unreal Engine. For example, in a typhoon progression simulation, a 3D model visualizing the strength of wind and rain and audio are generated.

[0167] Step 4:

[0168] Content Delivery

[0169] The server delivers the generated experience content to the user's device with low latency.

[0170] Input: Experience content data.

[0171] Output: Streaming data to user devices.

[0172] How it works: The server compresses the generated experience content and streams it to the user's device using low-latency technologies such as WebRTC or RTMP. For example, it sends typhoon simulation data to the user's VR device in real time.

[0173] Step 5:

[0174] Preparing for the experience

[0175] The terminal processes the received content and prepares it for display.

[0176] Input: Experience content data received from the server.

[0177] Output: The experience content ready to be displayed.

[0178] What happens: For VR devices, the device sets up a 360-degree view and enables eye tracking. For AR devices, the device activates the camera and prepares to overlay virtual content onto the real world.

[0179] Step 6:

[0180] Experience delivery and user interaction

[0181] A user uses the device to experience the news content.

[0182] Input: Experience content on the user device.

[0183] Output: User experience data and interaction logs.

[0184] Specific operation: Using a VR device or an AR-enabled smartphone, users visually experience the typhoon's progress, rainfall, wind speed, evacuation routes, and more. VR allows users to explore the virtual space, while AR displays real-time information. Interactions include eye tracking, touch input, and voice input.

[0185] (Application example 1)

[0186] 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."

[0187] Conventional news articles are often presented in the form of text or still images, limiting the user's ability to deeply understand the content. Furthermore, there is little experiential content that makes it easier to understand the news content, making it difficult for users to experience the actual situation, especially when it comes to natural disasters or major incidents. As a result, users may lack the understanding and preparation necessary to take appropriate action. There is a need to solve these problems.

[0188] 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.

[0189] In this invention, the server includes means for receiving news articles and analyzing their contents, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for acquiring camera footage and overlaying and displaying augmented reality content based on the analyzed news content, means for delivering the generated experiential content to the user's device, and means for displaying the experiential content on the user's device and enabling interaction. This allows the content of the news article to be intuitively understood, providing a more realistic experience compared to the real world.

[0190] "News article" refers to information about an event or occurrence distributed via the internet or other media.

[0191] "Analysis" refers to analyzing information such as text data using specific algorithms and techniques to understand its meaning and structure.

[0192] "Virtual reality (VR)" is a technology that uses computer graphics and sensor technology to create a virtual environment that users perceive as real.

[0193] Augmented reality (AR) is a technology that displays virtual objects and information overlaid on real-world scenery.

[0194] "Mixed reality (MR)" is a technology that allows real and virtual objects to work together and interact, and is an integration of virtual reality and augmented reality.

[0195] "Experiential content" is multimedia content designed to allow users to virtually experience specific situations or settings.

[0196] "Device Information" refers to information about the type and capabilities of the device owned by the User.

[0197] "User's device" refers to electronic devices used by a user, such as a smartphone, tablet, computer, or head-mounted display.

[0198] "Interaction" refers to the ability of a user to interact with, manipulate, or obtain information about experiential content through a device.

[0199] "Camera Footage" refers to current real-world video data captured by a camera device.

[0200] "Delivery" refers to the transmission of data or content from a server to a user's device.

[0201] "Overlay display" refers to the display of virtual objects and information over real-world images.

[0202] "Natural language processing (NLP)" refers to the techniques and algorithms that enable computers to understand and process human language.

[0203] This invention is a system that converts news articles into experiential content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies and provides them to users. This system consists of a server, a user's device (e.g., a smartphone, smart glasses, or head-mounted display), and an application installed on the device.

[0204] System configuration

[0205] 1. Receiving and analyzing news articles

[0206] The server receives news articles from external news providers via APIs or RSS feeds, which are then parsed using natural language processing (NLP) algorithms to extract information such as subject, location, events, and characters.

[0207] 2. Obtaining user information and selecting the experience format

[0208] The server obtains device information from the user's profile information, and based on this information, selects the experience format (VR, AR, or MR) that best suits the news content and device information.

[0209] 3. Creating experience content

[0210] The server generates experiential content based on the analyzed news content, specifically 3D models, scenarios, audio, and video related to the news content, allowing users to experience it.

[0211] 4. Content Delivery

[0212] The generated experience content is streamed from the server to the user's device, with data compression and low latency ensured during delivery.

[0213] 5. Preparing and delivering the experience

[0214] The user's device (e.g., smartphone, smart glasses, etc.) analyzes the received content and prepares it for display. For example, in the case of an AR device, it activates the camera and overlays virtual content on the real world.

[0215] 6. User Interaction

[0216] Users can interact with the generated content using their devices to experience the content of news articles. For example, an app for AR devices displays information related to news articles in real-time on the smartphone camera screen.

[0217] Hardware and software used

[0218] Hardware: User devices such as smartphones, smart glasses, and head-mounted displays

[0219] Software: Natural Language Processing (NLP) algorithms, device drivers (cameras, sensors, etc.), streaming software

[0220] As a concrete example, we use Python libraries (e.g., SpaCy, NLTK) for natural language processing and OpenCV for image processing.

[0221] Specific examples

[0222] As a concrete example, let's consider a news article reporting an approaching typhoon in Japan. After the news article is received and parsed by the server, the following process takes place:

[0223] Analysis of news articles: The server extracts information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[0224] Get user information: Verify that the user has an AR-enabled smartphone.

[0225] Content generation: To simulate the progression of a typhoon, 3D models and audio are generated to express the strength of wind and rain.

[0226] Content delivery: The generated AR content is delivered to the user's smartphone.

[0227] Display preparation: The user activates the smartphone camera and displays the 3D model and typhoon information superimposed on the real landscape.

[0228] Interaction: Users can visually understand the progress of the typhoon and evacuation routes through their smartphone screen.

[0229] Prompt Sentence Examples

[0230] "Extract key information about a news article (subject, location, events, characters, etc.)."

[0231] This allows users to more intuitively understand the content of news articles and link it to actual actions.

[0232] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0233] Step 1:

[0234] The server receives news articles from external news providers via API or RSS feed. The input of the received news article is the JSON data of the news article. Based on this input, the server starts parsing the text data.

[0235] Step 2:

[0236] The server uses natural language processing (NLP) algorithms on the received news articles to extract key information such as themes, locations, events, and characters. The input is the text data of the news articles. Specifically, it uses NLP algorithms (e.g., SpaCy, NLTK) to extract keywords and phrases from the articles and outputs the results in JSON format.

[0237] Step 3:

[0238] The server obtains device information from the user's profile information and selects the optimal experience format. The input is the user's profile information and device information. Based on the extracted news content and device information, the server selects one of the experience formats (VR, AR, or MR) and records the result.

[0239] Step 4:

[0240] The server generates experience content based on the analyzed news content. Specifically, it generates 3D models, scenarios, audio, video, etc. related to the news content. The input is the main information of the news and the selected experience format. The resulting 3D models, audio files, etc. are output.

[0241] Step 5:

[0242] The server streams the generated experiential content to the user's device. The input is the generated experiential content. The server compresses the content and delivers it with low latency. The output is the stream data sent to the user's device.

[0243] Step 6:

[0244] The user's device processes the received experience content and prepares it for display. This input is the experience content streamed from the server. The device decodes the received data and converts it into a displayable format. In the case of a VR headset, it sets up a 360-degree virtual environment. In the case of an AR device, it activates the camera and overlays the virtual content onto the real world.

[0245] Step 7:

[0246] The user experiences news content using the device. This input is the experience content ready for display. For example, the user uses a smartphone to display forecasted rainfall and wind speed information overlaid on the scenery around their home. The user operates the device and interacts with the displayed content.

[0247] Through these steps, users can intuitively understand the content of the news article and get a realistic experience.

[0248] 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.

[0249] This invention combines a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, with an emotion engine that recognizes the user's emotions, in order to make the content of news articles more realistic for users. The program for this system performs processing in the following steps:

[0250] Program processing

[0251] 1. Receiving and analyzing news articles

[0252] server

[0253] News articles are received from external news providers via API or RSS feeds, and are stored on the server.

[0254] It uses natural language processing (NLP) algorithms on incoming news articles to extract key information such as subject, location, events, and characters.

[0255] For example, if an article is about the progression of a typhoon, extract terms such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[0256] 2. Obtaining user information and selecting the experience format

[0257] server

[0258] Retrieve the user's device information from the user's profile database. Profile data includes which device the user is using, the device type, and its capabilities.

[0259] The optimal experience format (VR, AR, MR) is selected based on the news content and the user's device information.

[0260] Example: If the user has a VR device, select experience content in VR format.

[0261] 3. Creating experience content

[0262] server

[0263] Based on the news content, content is generated for users to experience. The content includes 3D models, scenarios, audio, and video. Data is generated as a 3D model to represent the progress of the typhoon and the strength of the wind and rain.

[0264] If necessary, external resources (e.g., weather data or 3D model databases) are referenced to obtain additional data that matches the news content and are integrated into the generated content.

[0265] 4. Emotion engine integration

[0266] server

[0267] The emotion engine recognizes the user's emotional state by analyzing the user's facial expressions, voice, and behavioral patterns.

[0268] Example: If the user has a surprised expression, the emotion engine will recognize it.

[0269] It provides feedback on experience content based on the user's emotional state and dynamically adjusts the scenario as needed.

[0270] Example: If the user is feeling scared, adjust the scenario by making it a little less strenuous.

[0271] 5. Content Delivery

[0272] server

[0273] The resulting experience content is streamed to the user's device, appropriately compressed and configured for low latency delivery.

[0274] 6. Preparation for the experience

[0275] Terminal

[0276] It unpacks and processes the received content and prepares it for display. For VR headsets, it configures the 360-degree environment and enables eye tracking for the user. For AR devices, it activates the camera and overlays virtual content onto the real-world scene.

[0277] 7. Experience Delivery and User Interaction

[0278] User

[0279] Users can experience the news using a device. In the case of VR, users wear a VR headset and observe the progress of the typhoon in a virtual space. In the case of AR, users use their smartphone to view forecasted rainfall and wind speed information overlaid on the real world.

[0280] An emotion engine monitors the user's emotions in real time and provides feedback: for example, if the user expresses curiosity, additional relevant information will be displayed.

[0281] Specific examples

[0282] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[0283] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[0284] 2. The server checks the user's device information, and if the user has a VR device, generates content to be experienced in VR format.

[0285] 3. The server generates a 3D model and audio simulating the typhoon's progress and streams it to the user's VR headset.

[0286] 4. The device processes the received content and prepares it so that the user can wear the VR headset and experience the 3D model.

[0287] 5. Users put on a VR headset and observe the progress of the typhoon in a virtual space, checking safe evacuation routes, etc.

[0288] 6. The emotion engine monitors the user's emotions, and if the user feels surprised, for example, it reflects that information in the content and adjusts the scenario.

[0289] This allows users to experience the content of news articles in detail and realistically, while dynamically adjusting the experience based on the user's emotional state, allowing them to gain a deeper understanding of the news content and more easily recognize it as an issue close to home.

[0290] The processing flow will be explained below.

[0291] Step 1:

[0292] The server receives news articles from external news providers via API or RSS feeds, and stores them on the server.

[0293] Step 2:

[0294] The server applies natural language processing (NLP) algorithms to the received news articles to extract key information such as subject, location, events, and characters.

[0295] For example, if an article is about the progression of a typhoon, information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials" will be extracted.

[0296] Step 3:

[0297] The server retrieves the user's device information from the user's profile database.

[0298] Example: Checking if the user owns a VR device (e.g., a headset) or is using an AR-enabled smartphone.

[0299] Step 4:

[0300] The server selects the optimal experience format (VR, AR, MR) based on the news content and the user's device information.

[0301] Example: If the user has a VR device, select VR experience content.

[0302] Step 5:

[0303] The server generates content for users to experience based on the news content, including 3D models, scenarios, audio, and video.

[0304] Example: Generating 3D models and sounds to represent the progress of a typhoon and the strength of wind and rain.

[0305] Step 6:

[0306] The server references external resources (e.g., weather data or 3D model databases) to obtain additional data that matches the news content and integrates it into the generated content.

[0307] Example: Accurately simulate the movement of typhoons by referencing actual weather data.

[0308] Step 7:

[0309] The server streams the generated experience content to the user's device, appropriately compressed and configured for low latency delivery.

[0310] Example: Delivering typhoon simulation data in real time to a user's VR headset.

[0311] Step 8:

[0312] The device unpacks and processes the received content and prepares it for display. For VR headsets, this involves configuring the 360-degree environment and enabling the user's eye-tracking. For AR devices, this involves activating the camera and overlaying virtual content onto the real-world scene.

[0313] For example, a VR headset allows users to freely move their viewpoint, and an AR device displays the predicted path of a typhoon through the camera.

[0314] Step 9:

[0315] Users experience the news content using a device. In the case of VR, users wear a VR headset to observe the progress of the typhoon in a virtual space and check safe evacuation routes. In the case of AR, users can see forecasted rainfall and wind speed information overlaid on the real world.

[0316] Example: A user observes the direction of a typhoon in a VR space and checks evacuation routes.

[0317] Step 10:

[0318] The emotion engine recognizes the user's emotional state and obtains emotional data by analyzing the user's facial expressions, voice, and behavioral patterns.

[0319] For example, if a user shows signs of surprise or fear, that information is collected.

[0320] Step 11:

[0321] The server uses the emotion engine data to provide feedback to the experience content based on the user's emotional state, dynamically adjusting the scenario as needed.

[0322] Example: If the user is feeling scared, adjust the scenario to make it more nuanced and reassuring.

[0323] Information presentation: If the user shows interest, more detailed news information or additional content is provided.

[0324] This allows users to not only experience the content of news articles in detail and realistically, but also to get an optimal experience tailored to their emotional state. By deepening their understanding of the news content and providing a customized experience tailored to the recipient's emotions, this system makes it easier for them to recognize news information as something that concerns them personally.

[0325] Example 2

[0326] 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."

[0327] In modern society, news articles cover a wide range of topics, and it takes time and effort to gain a deep understanding of their content. However, simply reading news content as text can be difficult to grasp, especially when it comes to complex events. Furthermore, users may lose interest if the content of the news article does not feel familiar to them. In particular, when it comes to news that has a strong emotional impact, such as natural disasters or social incidents, it is difficult for users to actually experience the situation, making it difficult for them to truly appreciate the importance of the information. Therefore, a method is needed to provide news content that is more realistic and responds to the individual emotions of each user.

[0328] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0329] In this invention, the server includes means for receiving a news article and analyzing its content, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for delivering the generated experiential content to the user's device, means for using an emotion engine that analyzes the user's facial expressions, voice, and behavioral patterns to recognize the user's emotional state, means for dynamically providing feedback on the experiential content and adjusting the scenario based on the user's emotional state, and means for displaying the experiential content on the user's device and enabling interaction. This allows the user to experience the content of the news article more realistically and enables the provision of dynamic content according to emotions.

[0330] A "news article" is a document containing information distributed by a news organization or information provider.

[0331] "Means of analysis" refers to a system for analyzing the content of news articles and extracting key information and keywords.

[0332] "Virtual reality (VR)" is a technology that allows users to immerse themselves in a virtual environment using a dedicated device.

[0333] Augmented reality (AR) is a technology that displays virtual information overlaid on real-world scenery.

[0334] "Mixed reality (MR)" is a technology that combines virtual reality and augmented reality to integrate and display virtual information with real-world information.

[0335] "Experiential content" is digital content that transforms the content of a news article into a format that can be experienced in virtual reality, augmented reality, or mixed reality.

[0336] "User device information" is data related to the type and performance of the device used by the user.

[0337] An "emotion engine" is software that analyzes a user's facial expressions, voice, and behavioral patterns to recognize their emotional state.

[0338] "Feedback" is a response that adjusts the content or scenario of the experience content based on the user's emotional state.

[0339] A "scenario" is a set of events or situations that a user experiences within experiential content.

[0340] "Interaction" is the process by which a user interacts with experiential content through a device.

[0341] A "user device" is an electronic device that a user uses to view experiential content.

[0342] The "means of delivery" is the mechanism by which the generated experience content is sent to the user's device.

[0343] "Natural language processing (NLP)" is a technology for analyzing and understanding natural language such as text and speech.

[0344] This invention combines a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, with an emotion engine that recognizes the user's emotions, in order to make the content of news articles more realistic for users.

[0345] Receiving and analyzing news articles

[0346] server

[0347] The server receives news articles from external news providers via APIs or RSS feeds. This process uses the news delivery service's API or RSS feed reader software. The received news articles are stored in a database on the server. Natural language processing (NLP) algorithms are then used on the stored news articles to extract key information such as themes, locations, events, and characters. Specifically, natural language processing libraries and frameworks (e.g., NLTK, SpaCy) can be used.

[0348] Obtaining user information and selecting experience format

[0349] server

[0350] The server accesses the user's profile database to obtain the user's device information and personal settings. It identifies the type of device the user is using (VR device, AR device, smartphone, etc.) and its capabilities (resolution, memory, processing power, etc.). Based on the news content and the user's device information, the server selects the optimal experience format (VR, AR, MR) for the user.

[0351] Creating experience content

[0352] server

[0353] The server generates content for users to experience based on the news content. This content includes 3D models, scenarios, audio, and video. For example, a 3D model showing the progression of a typhoon is created using Autodesk Maya, and audio narration and sound effects are edited using Adobe Audition. Furthermore, if necessary, external resources (e.g., weather data, 3D model databases) are referenced to obtain and integrate additional data that matches the news content.

[0354] Emotion engine integration

[0355] server

[0356] The server recognizes the user's emotional state through an emotion engine. This is done by analyzing the user's facial expressions, voice, and behavioral patterns. Specifically, it analyzes facial and voice data using Microsoft Azure's Face API and Speech API. It then provides feedback on the experience content based on the user's emotional state and dynamically adjusts the scenario. For example, if the user is startled, it changes the music or visual effects to ease parts of the scenario and provides additional safety information.

[0357] Content Delivery

[0358] server

[0359] The server streams the generated experience content to the user's device using the H.265 video codec and the HTTP / 2.0 protocol for low latency. Data is compressed on the server side to maximize network bandwidth efficiency.

[0360] Preparing for the experience

[0361] Terminal

[0362] The device unpacks the received content and processes it for display. For example, for VR devices (e.g., Oculus Quest 2), it uses the Oculus SDK to set up the 360-degree environment and enable eye tracking. For AR devices (e.g., an ARKit-enabled iPhone), it activates the camera and uses ARKit to overlay virtual content on the real-world landscape.

[0363] Experience delivery and user interaction

[0364] User

[0365] Users experience news content using a VR headset or an AR smartphone app. For example, a user wearing an Oculus Quest 2 can observe the progress of a typhoon in real time in a 3D simulation. An interactive scenario is also provided in which users can choose different evacuation routes. An emotion engine monitors the user's emotions in real time. If the user expresses curiosity, for example, relevant additional information or interactive questions are displayed on the screen.

[0366] Specific examples

[0367] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[0368] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[0369] 2. The server checks the user's device information and, if the user has an Oculus Quest 2, generates content to be experienced in VR format.

[0370] 3. The server generates a 3D model and audio simulating the progression of the typhoon and streams it to the user's VR headset. Specifically, the 3D model was created in Autodesk Maya and the audio was edited in Adobe Audition.

[0371] 4. The device processes the received content and sets up the VR environment using the Oculus SDK.

[0372] 5. Users wear a VR headset and experience the typhoon's progress in a realistic way. They are also provided with an interactive scenario where they can choose different evacuation routes.

[0373] 6. The emotion engine monitors the user's emotions and, if surprised, mitigates the scenario and provides additional safety information.

[0374] Example prompts for generative AI models

[0375] "Describe a system that generates VR experiences based on news articles, including a process for recognizing the user's emotions in real time and dynamically adjusting the experience accordingly."

[0376] This allows users to experience the content of news articles in detail and realistically, while dynamically adjusting the experience based on the user's emotional state, allowing them to gain a deeper understanding of the news content and more easily recognize it as an issue close to home.

[0377] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0378] Step 1: Receiving and parsing news articles

[0379] server

[0380] Input: News article data provided by external news providers (API or RSS feed).

[0381] What it does: The server periodically receives news articles via API or RSS feeds and stores them in a database.

[0382] Data processing: Analyzing text data from news articles using natural language processing (NLP) algorithms.

[0383] Output: Analyzed data including key information such as subjects, places, events, and characters (e.g., "typhoon," "Japan," "heavy rain," "citizens," "safety officials").

[0384] Step 2: Obtain user information and select experience format

[0385] server

[0386] Input: Device information (device type and capabilities) retrieved from the user's profile database.

[0387] What happens: The server accesses the user's profile database to see which device the user is using.

[0388] Data calculation: Executes logic to select the experience format based on the news content and user device information.

[0389] Output: The optimal experience format (VR, AR, MR) selected.

[0390] Step 3: Generate experience content

[0391] server

[0392] Input: Analysis data (key news information), user experience format (VR, AR, MR).

[0393] What it does: The server creates 3D models in Autodesk Maya and edits voice narration and sound effects in Adobe Audition, and optionally references external resources such as weather data and 3D model databases.

[0394] Data processing: Integrating key news information with external data to generate content for the user experience.

[0395] Output: Generated experience content (3D model, scenario, audio, video).

[0396] Step 4: Integrating the Emotion Engine

[0397] server

[0398] Input: User's facial expression data, voice data, and behavioral pattern data.

[0399] Specific operation: The server performs facial expression analysis and voice analysis using Microsoft Azure's Face API and Speech API.

[0400] Data computation: Running algorithms to recognize the user's emotional state in real time.

[0401] Output: The user's emotional state (e.g., surprise, fear, curiosity).

[0402] Step 5: Content feedback and scenario adjustments

[0403] server

[0404] Input: User experience content, user emotional state.

[0405] Specific behavior: Based on the user's emotional state, the server generates feedback on the experience content and dynamically adjusts the scenario, changing music and visual effects and providing additional safety information.

[0406] Data processing: Generate customized content based on the user's emotional state.

[0407] Output: Tailored experience content.

[0408] Step 6: Deliver your content

[0409] server

[0410] Input: Tailored experience content.

[0411] What it does: The server compresses the content using the H.265 video codec and streams it to the user's device using the HTTP / 2.0 protocol.

[0412] Output: The experience content that is streamed to the user's device.

[0413] Step 7: Prepare for the experience

[0414] Terminal

[0415] Input: The received experience content.

[0416] What it does: The device unpacks the received content and uses the Oculus SDK to set up a 360-degree VR environment, enable eye tracking, and, in the case of AR devices, uses ARKit to overlay virtual content onto the camera image.

[0417] Data operations: Converting content into a format that can be displayed on the device.

[0418] Output: The experience content ready to be displayed.

[0419] Step 8: Experience Delivery and User Interaction

[0420] User

[0421] Input: Optimized VR or AR content.

[0422] What happens: Users use a VR headset or AR device to experience the news in a realistic way.

[0423] Output: User experience and interaction data (user responses and choices).

[0424] These are the specific steps involved in generating and providing experiential content based on news articles. This process allows users to gain a deeper understanding of the news article and experience it in a way that is realistic and emotionally relevant.

[0425] (Application example 2)

[0426] 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."

[0427] Conventional news delivery systems have the problem that users have difficulty grasping the content of the news and have a shallow understanding of the information. In addition, they are unable to take into account users' emotional reactions to news articles, making it difficult to provide an optimal experience for each individual user.

[0428] The identification processing by identification processing unit 290 of data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving news articles and analyzing their contents, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for recognizing the user's emotions and providing feedback, means for delivering the generated experiential content to the user's device, and means for displaying the experiential content on the user's device and enabling interaction. This allows the user to experience the news content in real time and receive optimal feedback based on their emotional response.

[0429] "News Article" means a news article containing information distributed over the Internet.

[0430] "Analysis" is the process of breaking down the content of a news article and extracting information such as themes, characters, locations, and events.

[0431] "Virtual reality (VR)" is a technology that allows users to experience a three-dimensional virtual environment generated using computer technology through a dedicated device.

[0432] Augmented reality (AR) is a technology that displays computer-generated information overlaid on real-world scenery.

[0433] "Mixed reality (MR)" is a technology that provides an experience that combines virtual reality (VR) and augmented reality (AR).

[0434] "Experiential content" refers to content in the form of virtual reality (VR), augmented reality (AR), or mixed reality (MR) generated from the content of a news article.

[0435] "Device" means the hardware that enables a user to experience virtual reality (VR), augmented reality (AR), or mixed reality (MR).

[0436] "Emotion recognition" means judging the user's emotional state by analyzing the user's facial expressions, voice, behavioral patterns, etc.

[0437] "Feedback" refers to information or responses returned to the user that adjust the scenario based on the user's emotional state.

[0438] "Interaction" refers to the ability for users to interact with experiential content through a device.

[0439] The present invention relates to a system for providing news articles to users as virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content. The system includes means for receiving news articles, analyzing them, generating experience content, recognizing emotions, delivering them, and interacting with them.

[0440] Server Processing

[0441] The server first receives news articles from external news providers via APIs or RSS feeds. While we will not specify the names of specific news providers, we will assume that they are publicly available news distribution services.

[0442] Next, the received news article is analyzed using natural language processing (NLP) algorithms. An NLP engine like Spacy is used to extract key information such as subject, location, incident, and characters. For example, in an article about a typhoon's progress, information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials" are extracted.

[0443] The system then retrieves device information from the user's profile information and selects the optimal experience format. The system retrieves the device type and capabilities of the user from the profile database. Based on this information, if the user has a VR device, the system selects the VR experience content.

[0444] In the generation of experience content, 3D models, scenarios, audio, and video are generated based on the news content. Additional data from simulation data and external resources (e.g., weather data and 3D model databases) is integrated to complete the content for the user to experience.

[0445] In addition, the emotion engine recognizes the user's emotional state in real time and provides feedback. The emotion engine analyzes facial expressions, voice, and behavioral patterns, and adjusts the scenario if the user feels surprised or scared.

[0446] The generated experience content is delivered to the user's device with low latency, using streaming technology to compress and appropriately transfer the content.

[0447] User's Device

[0448] The user's device receives, decompresses, and processes the delivered content: in the case of a VR headset, a 360-degree visual environment is created and eye tracking is enabled, while in the case of an AR device, virtual content is overlaid on the real-world landscape.

[0449] Users experience the news through a device. For example, by wearing a VR headset, they can observe the progress of a typhoon in a virtual space and check safe evacuation routes. An emotion engine monitors the user's emotions in real time and provides feedback. If the user expresses curiosity, additional relevant information will be displayed.

[0450] Examples of concrete examples and prompts

[0451] As an example, suppose you receive a news article about a large typhoon approaching Japan. The server analyzes the news article and extracts information such as "typhoon," "Japan," "heavy rain," and "Tokyo." It then verifies that the user owns a VR device and generates a 3D model of the typhoon simulation. The generative AI model uses the following prompt:

[0452] News article: A powerful typhoon is approaching Japan, with heavy rain expected in Tokyo.

[0453] Keywords: typhoon, Japan, heavy rain, Tokyo

[0454] Generated VR content: 3D model simulating the typhoon's progress, rainfall, wind speed, and safety advice

[0455] This allows users to experience the progression of the typhoon in real time based on actual news articles and receive optimal feedback based on their emotional response.

[0456] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0457] Step 1: Receiving and parsing news articles

[0458] The server receives news articles from external news providers using APIs or RSS feeds. The received news articles are stored on the server. Natural language processing (NLP) algorithms (e.g., Spacy) are then used to analyze the news content and extract key information such as themes, locations, events, and characters. The input is the news article, and the output is the extracted information (e.g., "typhoon," "Japan," "heavy rain," "citizens," "safety officials").

[0459] Step 2: Obtain user information and select experience format

[0460] The server retrieves the user's device information from the user profile database. The profile data includes the device the user is using, as well as the device's type and performance. The input is the user ID, and the output is the device information. The server then selects the optimal experience format (VR, AR, or MR) based on the news content and the user's device information. For example, if the user owns a VR device, experience content in VR format is selected.

[0461] Step 3: Generate experience content

[0462] The server generates 3D models, scenarios, audio, and video based on the news content. For example, it generates a 3D model using data to represent the progress of a typhoon and the strength of wind and rain. If necessary, it obtains additional data from external resources (e.g., weather data or a 3D model database) and integrates it into the generated content. The input is the analyzed news information and the user's device information, and the output is the generated VR content.

[0463] Step 4: Integrating the Emotion Engine

[0464] The server uses an emotion engine to recognize the user's emotional state in real time. This is done by analyzing the user's facial expressions, voice, and behavioral patterns. For example, if the user shows a surprised expression, the emotion engine recognizes this. The input is the user's behavioral data, and the output is the user's emotional state. Based on the user's emotional state, the server provides feedback on the experience content and dynamically adjusts the scenario.

[0465] Step 5: Deliver your content

[0466] The server streams the generated experience content to the user's device. The data is appropriately compressed and configured for low latency delivery. The input is the generated VR content, and the output is the content delivered to the user's device.

[0467] Step 6: Prepare for the experience

[0468] The device unpacks and processes the received content and prepares it for display. In the case of a VR headset, this involves configuring the 360-degree environment and enabling the user's eye-tracking. In the case of an AR device, it activates the camera and overlays virtual content onto the real-world scene. The input is the streamed VR content, and the output is the content ready to be displayed.

[0469] Step 7: Experience Delivery and User Interaction

[0470] Users use devices to experience news content. In the case of VR, users wear a VR headset to observe the progress of the typhoon in a virtual space and check safe evacuation routes. In the case of AR, users use their smartphones to check predicted rainfall and wind speed information overlaid on the real world. An emotion engine monitors the user's emotions in real time and provides feedback. The input is the displayed content and the user's real-time behavioral data, and the output is the user experience and feedback.

[0471] 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.

[0472] 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.

[0473] 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.

[0474] [Second embodiment]

[0475] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0476] 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.

[0477] 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).

[0478] 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.

[0479] 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.

[0480] 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).

[0481] 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.

[0482] 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.

[0483] 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.

[0484] 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.

[0485] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0486] 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."

[0487] This invention is a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies to help users experience the content of news articles. The program for this system performs processing in the following steps.

[0488] Program processing

[0489] 1. Receiving and analyzing news articles

[0490] server

[0491] Receive news articles from external news providers via API or RSS feed.

[0492] It uses natural language processing (NLP) algorithms on incoming news articles to extract key information such as subject, location, events, and characters.

[0493] For example, if an article is about the progression of a typhoon, extract terms such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[0494] 2. Obtaining user information and selecting the experience format

[0495] server

[0496] Get device information from the user's profile information.

[0497] Example: Checking if the user owns a VR device or has an AR-enabled smartphone.

[0498] The optimal experience format (VR, AR, MR) is selected based on the news content and the user's device information.

[0499] Example: If you have a VR device, simulate the progression of a typhoon in a virtual space.

[0500] 3. Creating experience content

[0501] server

[0502] Based on the news content, it generates content for users to experience, including 3D models, scenarios, audio, and video.

[0503] Example: To simulate the progression of a typhoon, generate a 3D model and audio that expresses the strength of wind and rain.

[0504] Retrieve external resources (e.g., 3D model databases, weather data) as needed and integrate them into your content.

[0505] 4. Content Delivery

[0506] server

[0507] The generated experience content is streamed to the user's device.

[0508] Example: Compressing typhoon simulation data and delivering it with low latency.

[0509] 5. Preparation for the experience

[0510] Terminal

[0511] Processes the received content and prepares it for display.

[0512] For VR headsets, set up the 360-degree environment and enable user eye tracking.

[0513] In the case of AR devices, the camera is activated to overlay virtual content onto the real world.

[0514] 6. Experience Delivery and User Interaction

[0515] User

[0516] Use your device to experience news content.

[0517] In VR, users can observe the progress of the typhoon while exploring the virtual space.

[0518] With AR, predicted rainfall and wind speed information is overlaid on the scenery around your home using your smartphone.

[0519] Display additional information or provide interaction as needed.

[0520] Example: Displaying detailed information to confirm safe evacuation routes and countermeasures.

[0521] Specific examples

[0522] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[0523] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[0524] 2. The server checks the user's device information, and if the user has a VR device, generates content to be experienced in VR format.

[0525] 3. The server generates a 3D model and audio simulating the typhoon's progression and streams it to the user's VR headset.

[0526] 4. The device processes the received content and prepares it so that the user can wear the VR headset and experience the 3D model.

[0527] 5. Users put on a VR headset and observe the progress of the typhoon in a virtual space, checking safe evacuation routes, etc.

[0528] This allows users to gain a deeper understanding of the content of news articles and experience them in a realistic way. Through this experience, users perceive the information as something that concerns them personally, making it easier for them to take actual action.

[0529] The processing flow will be explained below.

[0530] Step 1:

[0531] The server receives news articles from external news providers via API or RSS feeds, and stores them on the server.

[0532] Step 2:

[0533] The server applies natural language processing (NLP) algorithms to the received news articles to extract key information such as themes, locations, events, and characters. As a result, the elements of the news article are classified as follows:

[0534] Subject: Typhoon

[0535] Location: Japan

[0536] Incident: Heavy rain

[0537] Characters: Citizens, safety officials

[0538] Step 3:

[0539] The server retrieves the user's device information from the user profile database. The profile data includes which device the user is using, the type of device, and its capabilities.

[0540] Step 4:

[0541] The server selects the optimal experience format (VR, AR, or MR) based on the news content and the user's device information. For example, if the user owns a VR device, it selects the experience content in VR format.

[0542] Step 5:

[0543] The server generates content for users to experience based on the news content. The content includes 3D models, scenarios, audio, and video. Data to represent the progress of the typhoon and the strength of the wind and rain is generated as a 3D model.

[0544] Step 6:

[0545] The server references external resources (e.g., weather data or 3D model databases) to obtain additional data that matches the news content and integrates it into the generated content.

[0546] Step 7:

[0547] The server streams the generated experience content to the user's device, appropriately compressed and configured for low latency delivery.

[0548] Step 8:

[0549] The device unpacks and processes the received content and prepares it for display. For VR headsets, this involves configuring the 360-degree environment and enabling the user's eye-tracking. For AR devices, this involves activating the camera and overlaying virtual content onto the real-world scene.

[0550] Step 9:

[0551] Users experience the news content using a device. In the case of VR, users wear a VR headset and observe the progress of the typhoon in a virtual space. In the case of AR, users use their smartphone to view forecasted rainfall and wind speed information overlaid on the real world.

[0552] Step 10:

[0553] The interface allows users to obtain additional information and interact as needed, for example by displaying detailed information to check evacuation routes or check countermeasures.

[0554] This allows users to experience the content of news articles in detail and in a realistic way, which is expected to lead to a deeper understanding of the news content and make it easier for users to perceive it as something that concerns them personally.

[0555] Example 1

[0556] 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."

[0557] Conventional news article delivery methods have had issues with insufficient information transmission, especially for disaster and incident information, as it is difficult for users to grasp the reality of the information. Furthermore, they are unable to fully support the diverse devices used by users, making it difficult to experience the news in the most optimal way. Furthermore, there was a lack of a mechanism for integrating appropriate external resources based on extracted news content, making it difficult to create a realistic experience.

[0558] 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.

[0559] In this invention, the server includes means for receiving news articles and analyzing their contents, means for extracting information on themes, locations, events, and characters contained in the news articles using natural language processing, means for acquiring user profile information and selecting an optimal experience format, means for delivering the generated experience content to the user's device with low latency, means for displaying the experience content on the user's device and enabling interaction, and means for integrating external resources based on the news articles. This allows users to easily visually experience the news content in an experience format such as virtual reality (VR), augmented reality (AR), or mixed reality (MR), improving the effectiveness of information transmission and facilitating linking it to actual actions.

[0560] "News Article" means content received from a news provider via API or RSS feed that contains information about a particular event, occurrence, or topic.

[0561] "Analysis" involves using natural language processing (NLP) algorithms on incoming news articles to extract key information from the article, such as themes, locations, events, and characters.

[0562] "Natural Language Processing (NLP)" is a technology that enables computers to understand, analyze, and generate human language, and is used to extract useful information from text.

[0563] "Profile information" is information that indicates a user's attributes and tendencies, such as device information registered by the user, areas of interest, and past usage history.

[0564] "Experience format" refers to the way in which users experience news content, and includes virtual reality (VR), augmented reality (AR), and mixed reality (MR).

[0565] "Generation" refers to the creation of experiential content such as 3D models, scenarios, audio, and video based on the news content and the selected experience format.

[0566] "Low latency" refers to data transmission and reception with minimal delay, and is an important technology for achieving a real-time experience.

[0567] "Interaction" refers to a user's direct interaction with experiential content through a device, with the content dynamically changing in response to the user's operations and actions.

[0568] "External resources" are data or information obtained from external sources to complement news content, such as 3D model databases or weather data APIs.

[0569] This system generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies to help users experience the content of news articles more realistically. Below, we list each processing step and explain how to implement it.

[0570] Receiving and analyzing news articles

[0571] The server receives news articles from news providers via APIs or RSS feeds, then uses natural language processing (NLP) algorithms to extract key information from the articles, such as themes, locations, events, and characters. The software used is an NLP library (e.g., SpaCy or NLTK).

[0572] Example: A server receives news articles about typhoons from "News Provider A" via API, and uses SpaCy to extract information about "typhoons," "Japan," "heavy rain," and "citizens."

[0573] Obtaining user information and selecting experience format

[0574] The server obtains the user's profile information (device information, areas of interest, past usage history, etc.) and selects the optimal experience format (VR, AR, MR) for the news content based on the device information.

[0575] Example: The server checks the user's profile information from a database, detects that the user has a VR device, and determines that if the news item is about a typhoon progressing, it would be best experienced in VR format.

[0576] Creating experience content

[0577] The server generates experience content such as 3D models, scenarios, audio, and video based on the news content and the selected experience format. External resources (e.g., 3D model databases, weather data APIs, etc.) are integrated and reflected in the content. 3D models are generated using 3D engines such as Unity and Unreal Engine.

[0578] Example: A server uses a weather data API to obtain forecast data for a typhoon's progress, and uses Unity to generate a 3D model that visualizes the strength of the wind and rain.

[0579] Content Delivery

[0580] The server generates the experience content and delivers it to the user's device with low latency using low-latency technologies (e.g., WebRTC or RTMP).

[0581] Example: Server-generated typhoon simulation data is compressed and delivered in real time to the user's VR device using WebRTC.

[0582] Preparing for the experience

[0583] The device processes the received content and prepares the experience, setting up the 360-degree environment for VR devices, and activating the camera for AR devices to overlay virtual content onto the real world.

[0584] Example: A user's VR device analyzes typhoon simulation data received from a server, sets up a 360-degree view, and enables eye tracking. The AR device activates the camera and displays a virtual typhoon progression simulation overlaid on the real landscape.

[0585] Experience delivery and user interaction

[0586] Users experience the news content using a device. In the case of VR, users can freely explore the virtual space and observe the progress of the typhoon. In the case of AR, forecasted rainfall and wind speed information is superimposed on the area around their home.

[0587] Example: A user wears a VR device and observes a typhoon in progress in a virtual space, checking changes in wind and rain and safe evacuation routes. Using an AR device, a user can check real-time wind speed information and forecasted rainfall around their home via their smartphone, and consider countermeasures at home.

[0588] Prompt Sentence Examples

[0589] "I want to experience a news article about a typhoon approaching Japan in virtual reality. Please generate simulation content including the typhoon's progress, rainfall, wind speed, evacuation routes, etc."

[0590] By using this system, users can experience the contents of news articles in a realistic way, deepening their understanding of the information and making it easier to link it to actual actions.

[0591] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0592] Step 1:

[0593] Receiving and analyzing news articles

[0594] The server receives news articles from news providers via API or RSS feed.

[0595] Input: A news article feed from a news provider.

[0596] Output: Received news article data.

[0597] How it works: The server sends an API request and receives news article data in JSON format. It then uses natural language processing (NLP) algorithms to parse the article and extract key information such as the subject, location, events, and characters. The NLP libraries used are SpaCy and NLTK.

[0598] Step 2:

[0599] Obtaining user information and selecting experience format

[0600] The server retrieves the user's profile information from a database.

[0601] Input: User's registered profile information.

[0602] Output: User's device information.

[0603] Specific operation: The server searches the database for profile information using the user ID as a key and obtains information about the device owned by the user. Based on the user's device information, it checks whether the user has a VR device, an AR-compatible smartphone, or other device. It then selects the optimal experience format (VR, AR, or MR) based on the news content.

[0604] Step 3:

[0605] Creating experience content

[0606] The server generates experience content based on the news content and the selected experience format.

[0607] Input: Parsed news information, user device information.

[0608] Output: The generated experience content (3D models, scenarios, audio, video, etc.).

[0609] Specific operation: The server obtains additional information from external resources such as weather data APIs and generates content using a 3D engine such as Unity or Unreal Engine. For example, in a typhoon progression simulation, a 3D model visualizing the strength of wind and rain and audio are generated.

[0610] Step 4:

[0611] Content Delivery

[0612] The server delivers the generated experience content to the user's device with low latency.

[0613] Input: Experience content data.

[0614] Output: Streaming data to user devices.

[0615] How it works: The server compresses the generated experience content and streams it to the user's device using low-latency technologies such as WebRTC or RTMP. For example, it sends typhoon simulation data to the user's VR device in real time.

[0616] Step 5:

[0617] Preparing for the experience

[0618] The terminal processes the received content and prepares it for display.

[0619] Input: Experience content data received from the server.

[0620] Output: The experience content ready to be displayed.

[0621] What happens: For VR devices, the device sets up a 360-degree view and enables eye tracking. For AR devices, the device activates the camera and prepares to overlay virtual content onto the real world.

[0622] Step 6:

[0623] Experience delivery and user interaction

[0624] A user uses the device to experience the news content.

[0625] Input: Experience content on the user device.

[0626] Output: User experience data and interaction logs.

[0627] Specific operation: Using a VR device or an AR-enabled smartphone, users visually experience the typhoon's progress, rainfall, wind speed, evacuation routes, and more. VR allows users to explore the virtual space, while AR displays real-time information. Interactions include eye tracking, touch input, and voice input.

[0628] (Application example 1)

[0629] 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."

[0630] Conventional news articles are often presented in the form of text or still images, limiting the user's ability to deeply understand the content. Furthermore, there is little experiential content that makes it easier to understand the news content, making it difficult for users to experience the actual situation, especially when it comes to natural disasters or major incidents. As a result, users may lack the understanding and preparation necessary to take appropriate action. There is a need to solve these problems.

[0631] 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.

[0632] In this invention, the server includes means for receiving news articles and analyzing their contents, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for acquiring camera footage and overlaying and displaying augmented reality content based on the analyzed news content, means for delivering the generated experiential content to the user's device, and means for displaying the experiential content on the user's device and enabling interaction. This allows the content of the news article to be intuitively understood, providing a more realistic experience compared to the real world.

[0633] "News article" refers to information about an event or occurrence distributed via the internet or other media.

[0634] "Analysis" refers to analyzing information such as text data using specific algorithms and techniques to understand its meaning and structure.

[0635] "Virtual reality (VR)" is a technology that uses computer graphics and sensor technology to create a virtual environment that users perceive as real.

[0636] Augmented reality (AR) is a technology that displays virtual objects and information overlaid on real-world scenery.

[0637] "Mixed reality (MR)" is a technology that allows real and virtual objects to work together and interact, and is an integration of virtual reality and augmented reality.

[0638] "Experiential content" is multimedia content designed to allow users to virtually experience specific situations or settings.

[0639] "Device Information" refers to information about the type and capabilities of the device owned by the User.

[0640] "User's device" refers to electronic devices used by a user, such as a smartphone, tablet, computer, or head-mounted display.

[0641] "Interaction" refers to the ability of a user to interact with, manipulate, or obtain information about experiential content through a device.

[0642] "Camera Footage" refers to current real-world video data captured by a camera device.

[0643] "Delivery" refers to the transmission of data or content from a server to a user's device.

[0644] "Overlay display" refers to the display of virtual objects and information over real-world images.

[0645] "Natural language processing (NLP)" refers to the techniques and algorithms that enable computers to understand and process human language.

[0646] This invention is a system that converts news articles into experiential content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies and provides them to users. This system consists of a server, a user's device (e.g., a smartphone, smart glasses, or head-mounted display), and an application installed on the device.

[0647] System configuration

[0648] 1. Receiving and analyzing news articles

[0649] The server receives news articles from external news providers via APIs or RSS feeds, which are then parsed using natural language processing (NLP) algorithms to extract information such as subject, location, events, and characters.

[0650] 2. Obtaining user information and selecting the experience format

[0651] The server obtains device information from the user's profile information, and based on this information, selects the experience format (VR, AR, or MR) that best suits the news content and device information.

[0652] 3. Creating experience content

[0653] The server generates experiential content based on the analyzed news content, specifically 3D models, scenarios, audio, and video related to the news content, allowing users to experience it.

[0654] 4. Content Delivery

[0655] The generated experience content is streamed from the server to the user's device, with data compression and low latency ensured during delivery.

[0656] 5. Preparing and delivering the experience

[0657] The user's device (e.g., smartphone, smart glasses, etc.) analyzes the received content and prepares it for display. For example, in the case of an AR device, it activates the camera and overlays virtual content on the real world.

[0658] 6. User Interaction

[0659] Users can interact with the generated content using their devices to experience the content of news articles. For example, an app for AR devices displays information related to news articles in real-time on the smartphone camera screen.

[0660] Hardware and software used

[0661] Hardware: User devices such as smartphones, smart glasses, and head-mounted displays

[0662] Software: Natural Language Processing (NLP) algorithms, device drivers (cameras, sensors, etc.), streaming software

[0663] As a concrete example, we use Python libraries (e.g., SpaCy, NLTK) for natural language processing and OpenCV for image processing.

[0664] Specific examples

[0665] As a concrete example, let's consider a news article reporting an approaching typhoon in Japan. After the news article is received and parsed by the server, the following process takes place:

[0666] Analysis of news articles: The server extracts information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[0667] Get user information: Verify that the user has an AR-enabled smartphone.

[0668] Content generation: To simulate the progression of a typhoon, 3D models and audio are generated to express the strength of wind and rain.

[0669] Content delivery: The generated AR content is delivered to the user's smartphone.

[0670] Display preparation: The user activates the smartphone camera and displays the 3D model and typhoon information superimposed on the real landscape.

[0671] Interaction: Users can visually understand the progress of the typhoon and evacuation routes through their smartphone screen.

[0672] Prompt Sentence Examples

[0673] "Extract key information about a news article (subject, location, events, characters, etc.)."

[0674] This allows users to more intuitively understand the content of news articles and link it to actual actions.

[0675] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0676] Step 1:

[0677] The server receives news articles from external news providers via API or RSS feed. The input of the received news article is the JSON data of the news article. Based on this input, the server starts parsing the text data.

[0678] Step 2:

[0679] The server uses natural language processing (NLP) algorithms on the received news articles to extract key information such as themes, locations, events, and characters. The input is the text data of the news articles. Specifically, it uses NLP algorithms (e.g., SpaCy, NLTK) to extract keywords and phrases from the articles and outputs the results in JSON format.

[0680] Step 3:

[0681] The server obtains device information from the user's profile information and selects the optimal experience format. The input is the user's profile information and device information. Based on the extracted news content and device information, the server selects one of the experience formats (VR, AR, or MR) and records the result.

[0682] Step 4:

[0683] The server generates experience content based on the analyzed news content. Specifically, it generates 3D models, scenarios, audio, video, etc. related to the news content. The input is the main information of the news and the selected experience format. The resulting 3D models, audio files, etc. are output.

[0684] Step 5:

[0685] The server streams the generated experiential content to the user's device. The input is the generated experiential content. The server compresses the content and delivers it with low latency. The output is the stream data sent to the user's device.

[0686] Step 6:

[0687] The user's device processes the received experience content and prepares it for display. This input is the experience content streamed from the server. The device decodes the received data and converts it into a displayable format. In the case of a VR headset, it sets up a 360-degree virtual environment. In the case of an AR device, it activates the camera and overlays the virtual content onto the real world.

[0688] Step 7:

[0689] The user experiences news content using the device. This input is the experience content ready for display. For example, the user uses a smartphone to display forecasted rainfall and wind speed information overlaid on the scenery around their home. The user operates the device and interacts with the displayed content.

[0690] Through these steps, users can intuitively understand the content of the news article and get a realistic experience.

[0691] 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.

[0692] This invention combines a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, with an emotion engine that recognizes the user's emotions, in order to make the content of news articles more realistic for users. The program for this system performs processing in the following steps:

[0693] Program processing

[0694] 1. Receiving and analyzing news articles

[0695] server

[0696] News articles are received from external news providers via API or RSS feeds, and are stored on the server.

[0697] It uses natural language processing (NLP) algorithms on incoming news articles to extract key information such as subject, location, events, and characters.

[0698] For example, if an article is about the progression of a typhoon, extract terms such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[0699] 2. Obtaining user information and selecting the experience format

[0700] server

[0701] Retrieve the user's device information from the user's profile database. Profile data includes which device the user is using, the device type, and its capabilities.

[0702] The optimal experience format (VR, AR, MR) is selected based on the news content and the user's device information.

[0703] Example: If the user has a VR device, select experience content in VR format.

[0704] 3. Creating experience content

[0705] server

[0706] Based on the news content, content is generated for users to experience. The content includes 3D models, scenarios, audio, and video. Data is generated as a 3D model to represent the progress of the typhoon and the strength of the wind and rain.

[0707] If necessary, external resources (e.g., weather data or 3D model databases) are referenced to obtain additional data that matches the news content and are integrated into the generated content.

[0708] 4. Emotion engine integration

[0709] server

[0710] The emotion engine recognizes the user's emotional state by analyzing the user's facial expressions, voice, and behavioral patterns.

[0711] Example: If the user has a surprised expression, the emotion engine will recognize it.

[0712] It provides feedback on experience content based on the user's emotional state and dynamically adjusts the scenario as needed.

[0713] Example: If the user is feeling scared, adjust the scenario by making it a little less strenuous.

[0714] 5. Content Delivery

[0715] server

[0716] The resulting experience content is streamed to the user's device, appropriately compressed and configured for low latency delivery.

[0717] 6. Preparation for the experience

[0718] Terminal

[0719] It unpacks and processes the received content and prepares it for display. For VR headsets, it configures the 360-degree environment and enables eye tracking for the user. For AR devices, it activates the camera and overlays virtual content onto the real-world scene.

[0720] 7. Experience Delivery and User Interaction

[0721] User

[0722] Users can experience the news using a device. In the case of VR, users wear a VR headset and observe the progress of the typhoon in a virtual space. In the case of AR, users use their smartphone to view forecasted rainfall and wind speed information overlaid on the real world.

[0723] An emotion engine monitors the user's emotions in real time and provides feedback: for example, if the user expresses curiosity, additional relevant information will be displayed.

[0724] Specific examples

[0725] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[0726] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[0727] 2. The server checks the user's device information, and if the user has a VR device, generates content to be experienced in VR format.

[0728] 3. The server generates a 3D model and audio simulating the typhoon's progress and streams it to the user's VR headset.

[0729] 4. The device processes the received content and prepares it so that the user can wear the VR headset and experience the 3D model.

[0730] 5. Users put on a VR headset and observe the progress of the typhoon in a virtual space, checking safe evacuation routes, etc.

[0731] 6. The emotion engine monitors the user's emotions, and if the user feels surprised, for example, it reflects that information in the content and adjusts the scenario.

[0732] This allows users to experience the content of news articles in detail and realistically, while dynamically adjusting the experience based on the user's emotional state, allowing them to gain a deeper understanding of the news content and more easily recognize it as an issue close to home.

[0733] The processing flow will be explained below.

[0734] Step 1:

[0735] The server receives news articles from external news providers via API or RSS feeds, and stores them on the server.

[0736] Step 2:

[0737] The server applies natural language processing (NLP) algorithms to the received news articles to extract key information such as subject, location, events, and characters.

[0738] For example, if an article is about the progression of a typhoon, information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials" will be extracted.

[0739] Step 3:

[0740] The server retrieves the user's device information from the user's profile database.

[0741] Example: Checking if the user owns a VR device (e.g., a headset) or is using an AR-enabled smartphone.

[0742] Step 4:

[0743] The server selects the optimal experience format (VR, AR, MR) based on the news content and the user's device information.

[0744] Example: If the user has a VR device, select VR experience content.

[0745] Step 5:

[0746] The server generates content for users to experience based on the news content, including 3D models, scenarios, audio, and video.

[0747] Example: Generating 3D models and sounds to represent the progress of a typhoon and the strength of wind and rain.

[0748] Step 6:

[0749] The server references external resources (e.g., weather data or 3D model databases) to obtain additional data that matches the news content and integrates it into the generated content.

[0750] Example: Accurately simulate the movement of typhoons by referencing actual weather data.

[0751] Step 7:

[0752] The server streams the generated experience content to the user's device, appropriately compressed and configured for low latency delivery.

[0753] Example: Delivering typhoon simulation data in real time to a user's VR headset.

[0754] Step 8:

[0755] The device unpacks and processes the received content and prepares it for display. For VR headsets, this involves configuring the 360-degree environment and enabling the user's eye-tracking. For AR devices, this involves activating the camera and overlaying virtual content onto the real-world scene.

[0756] For example, a VR headset allows users to freely move their viewpoint, and an AR device displays the predicted path of a typhoon through the camera.

[0757] Step 9:

[0758] Users experience the news content using a device. In the case of VR, users wear a VR headset to observe the progress of the typhoon in a virtual space and check safe evacuation routes. In the case of AR, users can see forecasted rainfall and wind speed information overlaid on the real world.

[0759] Example: A user observes the direction of a typhoon in a VR space and checks evacuation routes.

[0760] Step 10:

[0761] The emotion engine recognizes the user's emotional state and obtains emotional data by analyzing the user's facial expressions, voice, and behavioral patterns.

[0762] For example, if a user shows signs of surprise or fear, that information is collected.

[0763] Step 11:

[0764] The server uses the emotion engine data to provide feedback to the experience content based on the user's emotional state, dynamically adjusting the scenario as needed.

[0765] Example: If the user is feeling scared, adjust the scenario to make it more nuanced and reassuring.

[0766] Information presentation: If the user shows interest, more detailed news information or additional content is provided.

[0767] This allows users to not only experience the content of news articles in detail and realistically, but also to get an optimal experience tailored to their emotional state. By deepening their understanding of the news content and providing a customized experience tailored to the recipient's emotions, this system makes it easier for them to recognize news information as something that concerns them personally.

[0768] Example 2

[0769] 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."

[0770] In modern society, news articles cover a wide range of topics, and it takes time and effort to gain a deep understanding of their content. However, simply reading news content as text can be difficult to grasp, especially when it comes to complex events. Furthermore, users may lose interest if the content of the news article does not feel familiar to them. In particular, when it comes to news that has a strong emotional impact, such as natural disasters or social incidents, it is difficult for users to actually experience the situation, making it difficult for them to truly appreciate the importance of the information. Therefore, a method is needed to provide news content that is more realistic and responds to the individual emotions of each user.

[0771] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0772] In this invention, the server includes means for receiving a news article and analyzing its content, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for delivering the generated experiential content to the user's device, means for using an emotion engine that analyzes the user's facial expressions, voice, and behavioral patterns to recognize the user's emotional state, means for dynamically providing feedback on the experiential content and adjusting the scenario based on the user's emotional state, and means for displaying the experiential content on the user's device and enabling interaction. This allows the user to experience the content of the news article more realistically and enables the provision of dynamic content according to emotions.

[0773] A "news article" is a document containing information distributed by a news organization or information provider.

[0774] "Means of analysis" refers to a system for analyzing the content of news articles and extracting key information and keywords.

[0775] "Virtual reality (VR)" is a technology that allows users to immerse themselves in a virtual environment using a dedicated device.

[0776] Augmented reality (AR) is a technology that displays virtual information overlaid on real-world scenery.

[0777] "Mixed reality (MR)" is a technology that combines virtual reality and augmented reality to integrate and display virtual information with real-world information.

[0778] "Experiential content" is digital content that transforms the content of a news article into a format that can be experienced in virtual reality, augmented reality, or mixed reality.

[0779] "User device information" is data related to the type and performance of the device used by the user.

[0780] An "emotion engine" is software that analyzes a user's facial expressions, voice, and behavioral patterns to recognize their emotional state.

[0781] "Feedback" is a response that adjusts the content or scenario of the experience content based on the user's emotional state.

[0782] A "scenario" is a set of events or situations that a user experiences within experiential content.

[0783] "Interaction" is the process by which a user interacts with experiential content through a device.

[0784] A "user device" is an electronic device that a user uses to view experiential content.

[0785] The "means of delivery" is the mechanism by which the generated experience content is sent to the user's device.

[0786] "Natural language processing (NLP)" is a technology for analyzing and understanding natural language such as text and speech.

[0787] This invention combines a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, with an emotion engine that recognizes the user's emotions, in order to make the content of news articles more realistic for users.

[0788] Receiving and analyzing news articles

[0789] server

[0790] The server receives news articles from external news providers via APIs or RSS feeds. This process uses the news delivery service's API or RSS feed reader software. The received news articles are stored in a database on the server. Natural language processing (NLP) algorithms are then used on the stored news articles to extract key information such as themes, locations, events, and characters. Specifically, natural language processing libraries and frameworks (e.g., NLTK, SpaCy) can be used.

[0791] Obtaining user information and selecting experience format

[0792] server

[0793] The server accesses the user's profile database to obtain the user's device information and personal settings. It identifies the type of device the user is using (VR device, AR device, smartphone, etc.) and its capabilities (resolution, memory, processing power, etc.). Based on the news content and the user's device information, the server selects the optimal experience format (VR, AR, MR) for the user.

[0794] Creating experience content

[0795] server

[0796] The server generates content for users to experience based on the news content. This content includes 3D models, scenarios, audio, and video. For example, a 3D model showing the progression of a typhoon is created using Autodesk Maya, and audio narration and sound effects are edited using Adobe Audition. Furthermore, if necessary, external resources (e.g., weather data, 3D model databases) are referenced to obtain and integrate additional data that matches the news content.

[0797] Emotion engine integration

[0798] server

[0799] The server recognizes the user's emotional state through an emotion engine. This is done by analyzing the user's facial expressions, voice, and behavioral patterns. Specifically, it analyzes facial and voice data using Microsoft Azure's Face API and Speech API. It then provides feedback on the experience content based on the user's emotional state and dynamically adjusts the scenario. For example, if the user is startled, it changes the music or visual effects to ease parts of the scenario and provides additional safety information.

[0800] Content Delivery

[0801] server

[0802] The server streams the generated experience content to the user's device using the H.265 video codec and the HTTP / 2.0 protocol for low latency. Data is compressed on the server side to maximize network bandwidth efficiency.

[0803] Preparing for the experience

[0804] Terminal

[0805] The device unpacks the received content and processes it for display. For example, for VR devices (e.g., Oculus Quest 2), it uses the Oculus SDK to set up the 360-degree environment and enable eye tracking. For AR devices (e.g., an ARKit-enabled iPhone), it activates the camera and uses ARKit to overlay virtual content on the real-world landscape.

[0806] Experience delivery and user interaction

[0807] User

[0808] Users experience news content using a VR headset or an AR smartphone app. For example, a user wearing an Oculus Quest 2 can observe the progress of a typhoon in real time in a 3D simulation. An interactive scenario is also provided in which users can choose different evacuation routes. An emotion engine monitors the user's emotions in real time. If the user expresses curiosity, for example, relevant additional information or interactive questions are displayed on the screen.

[0809] Specific examples

[0810] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[0811] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[0812] 2. The server checks the user's device information and, if the user has an Oculus Quest 2, generates content to be experienced in VR format.

[0813] 3. The server generates a 3D model and audio simulating the progression of the typhoon and streams it to the user's VR headset. Specifically, the 3D model was created in Autodesk Maya and the audio was edited in Adobe Audition.

[0814] 4. The device processes the received content and sets up the VR environment using the Oculus SDK.

[0815] 5. Users wear a VR headset and experience the typhoon's progress in a realistic way. They are also provided with an interactive scenario where they can choose different evacuation routes.

[0816] 6. The emotion engine monitors the user's emotions and, if surprised, mitigates the scenario and provides additional safety information.

[0817] Example prompts for generative AI models

[0818] "Describe a system that generates VR experiences based on news articles, including a process for recognizing the user's emotions in real time and dynamically adjusting the experience accordingly."

[0819] This allows users to experience the content of news articles in detail and realistically, while dynamically adjusting the experience based on the user's emotional state, allowing them to gain a deeper understanding of the news content and more easily recognize it as an issue close to home.

[0820] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0821] Step 1: Receiving and parsing news articles

[0822] server

[0823] Input: News article data provided by external news providers (API or RSS feed).

[0824] What it does: The server periodically receives news articles via API or RSS feeds and stores them in a database.

[0825] Data processing: Analyzing text data from news articles using natural language processing (NLP) algorithms.

[0826] Output: Analyzed data including key information such as subjects, places, events, and characters (e.g., "typhoon," "Japan," "heavy rain," "citizens," "safety officials").

[0827] Step 2: Obtain user information and select experience format

[0828] server

[0829] Input: Device information (device type and capabilities) retrieved from the user's profile database.

[0830] What happens: The server accesses the user's profile database to see which device the user is using.

[0831] Data calculation: Executes logic to select the experience format based on the news content and user device information.

[0832] Output: The optimal experience format (VR, AR, MR) selected.

[0833] Step 3: Generate experience content

[0834] server

[0835] Input: Analysis data (key news information), user experience format (VR, AR, MR).

[0836] What it does: The server creates 3D models in Autodesk Maya and edits voice narration and sound effects in Adobe Audition, and optionally references external resources such as weather data and 3D model databases.

[0837] Data processing: Integrating key news information with external data to generate content for the user experience.

[0838] Output: Generated experience content (3D model, scenario, audio, video).

[0839] Step 4: Integrating the Emotion Engine

[0840] server

[0841] Input: User's facial expression data, voice data, and behavioral pattern data.

[0842] Specific operation: The server performs facial expression analysis and voice analysis using Microsoft Azure's Face API and Speech API.

[0843] Data computation: Running algorithms to recognize the user's emotional state in real time.

[0844] Output: The user's emotional state (e.g., surprise, fear, curiosity).

[0845] Step 5: Content feedback and scenario adjustments

[0846] server

[0847] Input: User experience content, user emotional state.

[0848] Specific behavior: Based on the user's emotional state, the server generates feedback on the experience content and dynamically adjusts the scenario, changing music and visual effects and providing additional safety information.

[0849] Data processing: Generate customized content based on the user's emotional state.

[0850] Output: Tailored experience content.

[0851] Step 6: Deliver your content

[0852] server

[0853] Input: Tailored experience content.

[0854] What it does: The server compresses the content using the H.265 video codec and streams it to the user's device using the HTTP / 2.0 protocol.

[0855] Output: The experience content that is streamed to the user's device.

[0856] Step 7: Prepare for the experience

[0857] Terminal

[0858] Input: The received experience content.

[0859] What it does: The device unpacks the received content and uses the Oculus SDK to set up a 360-degree VR environment, enable eye tracking, and, in the case of AR devices, uses ARKit to overlay virtual content onto the camera image.

[0860] Data operations: Converting content into a format that can be displayed on the device.

[0861] Output: The experience content ready to be displayed.

[0862] Step 8: Experience Delivery and User Interaction

[0863] User

[0864] Input: Optimized VR or AR content.

[0865] What happens: Users use a VR headset or AR device to experience the news in a realistic way.

[0866] Output: User experience and interaction data (user responses and choices).

[0867] These are the specific steps involved in generating and providing experiential content based on news articles. This process allows users to gain a deeper understanding of the news article and experience it in a way that is realistic and emotionally relevant.

[0868] (Application example 2)

[0869] 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."

[0870] Conventional news delivery systems have the problem that users have difficulty grasping the content of the news and have a shallow understanding of the information. In addition, they are unable to take into account users' emotional reactions to news articles, making it difficult to provide an optimal experience for each individual user.

[0871] The identification processing by identification processing unit 290 of data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving news articles and analyzing their contents, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for recognizing the user's emotions and providing feedback, means for delivering the generated experiential content to the user's device, and means for displaying the experiential content on the user's device and enabling interaction. This allows the user to experience the news content in real time and receive optimal feedback based on their emotional response.

[0872] "News Article" means a news article containing information distributed over the Internet.

[0873] "Analysis" is the process of breaking down the content of a news article and extracting information such as themes, characters, locations, and events.

[0874] "Virtual reality (VR)" is a technology that allows users to experience a three-dimensional virtual environment generated using computer technology through a dedicated device.

[0875] Augmented reality (AR) is a technology that displays computer-generated information overlaid on real-world scenery.

[0876] "Mixed reality (MR)" is a technology that provides an experience that combines virtual reality (VR) and augmented reality (AR).

[0877] "Experiential content" refers to content in the form of virtual reality (VR), augmented reality (AR), or mixed reality (MR) generated from the content of a news article.

[0878] "Device" means the hardware that enables a user to experience virtual reality (VR), augmented reality (AR), or mixed reality (MR).

[0879] "Emotion recognition" means judging the user's emotional state by analyzing the user's facial expressions, voice, behavioral patterns, etc.

[0880] "Feedback" refers to information or responses returned to the user that adjust the scenario based on the user's emotional state.

[0881] "Interaction" refers to the ability for users to interact with experiential content through a device.

[0882] The present invention relates to a system for providing news articles to users as virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content. The system includes means for receiving news articles, analyzing them, generating experience content, recognizing emotions, delivering them, and interacting with them.

[0883] Server Processing

[0884] The server first receives news articles from external news providers via APIs or RSS feeds. While we will not specify the names of specific news providers, we will assume that they are publicly available news distribution services.

[0885] Next, the received news article is analyzed using natural language processing (NLP) algorithms. An NLP engine like Spacy is used to extract key information such as subject, location, incident, and characters. For example, in an article about a typhoon's progress, information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials" are extracted.

[0886] The system then retrieves device information from the user's profile information and selects the optimal experience format. The system retrieves the device type and capabilities of the user from the profile database. Based on this information, if the user has a VR device, the system selects the VR experience content.

[0887] In the generation of experience content, 3D models, scenarios, audio, and video are generated based on the news content. Additional data from simulation data and external resources (e.g., weather data and 3D model databases) is integrated to complete the content for the user to experience.

[0888] In addition, the emotion engine recognizes the user's emotional state in real time and provides feedback. The emotion engine analyzes facial expressions, voice, and behavioral patterns, and adjusts the scenario if the user feels surprised or scared.

[0889] The generated experience content is delivered to the user's device with low latency, using streaming technology to compress and appropriately transfer the content.

[0890] User's Device

[0891] The user's device receives, decompresses, and processes the delivered content: in the case of a VR headset, a 360-degree visual environment is created and eye tracking is enabled, while in the case of an AR device, virtual content is overlaid on the real-world landscape.

[0892] Users experience the news through a device. For example, by wearing a VR headset, they can observe the progress of a typhoon in a virtual space and check safe evacuation routes. An emotion engine monitors the user's emotions in real time and provides feedback. If the user expresses curiosity, additional relevant information will be displayed.

[0893] Examples of concrete examples and prompts

[0894] As an example, suppose you receive a news article about a large typhoon approaching Japan. The server analyzes the news article and extracts information such as "typhoon," "Japan," "heavy rain," and "Tokyo." It then verifies that the user owns a VR device and generates a 3D model of the typhoon simulation. The generative AI model uses the following prompt:

[0895] News article: A powerful typhoon is approaching Japan, with heavy rain expected in Tokyo.

[0896] Keywords: typhoon, Japan, heavy rain, Tokyo

[0897] Generated VR content: 3D model simulating the typhoon's progress, rainfall, wind speed, and safety advice

[0898] This allows users to experience the progression of the typhoon in real time based on actual news articles and receive optimal feedback based on their emotional response.

[0899] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0900] Step 1: Receiving and parsing news articles

[0901] The server receives news articles from external news providers using APIs or RSS feeds. The received news articles are stored on the server. Natural language processing (NLP) algorithms (e.g., Spacy) are then used to analyze the news content and extract key information such as themes, locations, events, and characters. The input is the news article, and the output is the extracted information (e.g., "typhoon," "Japan," "heavy rain," "citizens," "safety officials").

[0902] Step 2: Obtain user information and select experience format

[0903] The server retrieves the user's device information from the user profile database. The profile data includes the device the user is using, as well as the device's type and performance. The input is the user ID, and the output is the device information. The server then selects the optimal experience format (VR, AR, or MR) based on the news content and the user's device information. For example, if the user owns a VR device, experience content in VR format is selected.

[0904] Step 3: Generate experience content

[0905] The server generates 3D models, scenarios, audio, and video based on the news content. For example, it generates a 3D model using data to represent the progress of a typhoon and the strength of wind and rain. If necessary, it obtains additional data from external resources (e.g., weather data or a 3D model database) and integrates it into the generated content. The input is the analyzed news information and the user's device information, and the output is the generated VR content.

[0906] Step 4: Integrating the Emotion Engine

[0907] The server uses an emotion engine to recognize the user's emotional state in real time. This is done by analyzing the user's facial expressions, voice, and behavioral patterns. For example, if the user shows a surprised expression, the emotion engine recognizes this. The input is the user's behavioral data, and the output is the user's emotional state. Based on the user's emotional state, the server provides feedback on the experience content and dynamically adjusts the scenario.

[0908] Step 5: Deliver your content

[0909] The server streams the generated experience content to the user's device. The data is appropriately compressed and configured for low latency delivery. The input is the generated VR content, and the output is the content delivered to the user's device.

[0910] Step 6: Prepare for the experience

[0911] The device unpacks and processes the received content and prepares it for display. In the case of a VR headset, this involves configuring the 360-degree environment and enabling the user's eye-tracking. In the case of an AR device, it activates the camera and overlays virtual content onto the real-world scene. The input is the streamed VR content, and the output is the content ready to be displayed.

[0912] Step 7: Experience Delivery and User Interaction

[0913] Users use devices to experience news content. In the case of VR, users wear a VR headset to observe the progress of the typhoon in a virtual space and check safe evacuation routes. In the case of AR, users use their smartphones to check predicted rainfall and wind speed information overlaid on the real world. An emotion engine monitors the user's emotions in real time and provides feedback. The input is the displayed content and the user's real-time behavioral data, and the output is the user experience and feedback.

[0914] 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.

[0915] 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.

[0916] 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.

[0917] [Third embodiment]

[0918] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0919] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0920] 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).

[0921] 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.

[0922] 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.

[0923] 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).

[0924] 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.

[0925] 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.

[0926] 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.

[0927] 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.

[0928] 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.

[0929] 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."

[0930] This invention is a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies to help users experience the content of news articles. The program for this system performs processing in the following steps.

[0931] Program processing

[0932] 1. Receiving and analyzing news articles

[0933] server

[0934] Receive news articles from external news providers via API or RSS feed.

[0935] It uses natural language processing (NLP) algorithms on incoming news articles to extract key information such as subject, location, events, and characters.

[0936] For example, if an article is about the progression of a typhoon, extract terms such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[0937] 2. Obtaining user information and selecting the experience format

[0938] server

[0939] Get device information from the user's profile information.

[0940] Example: Checking if the user owns a VR device or has an AR-enabled smartphone.

[0941] The optimal experience format (VR, AR, MR) is selected based on the news content and the user's device information.

[0942] Example: If you have a VR device, simulate the progression of a typhoon in a virtual space.

[0943] 3. Creating experience content

[0944] server

[0945] Based on the news content, it generates content for users to experience, including 3D models, scenarios, audio, and video.

[0946] Example: To simulate the progression of a typhoon, generate a 3D model and audio that expresses the strength of wind and rain.

[0947] Retrieve external resources (e.g., 3D model databases, weather data) as needed and integrate them into your content.

[0948] 4. Content Delivery

[0949] server

[0950] The generated experience content is streamed to the user's device.

[0951] Example: Compressing typhoon simulation data and delivering it with low latency.

[0952] 5. Preparation for the experience

[0953] Terminal

[0954] Processes the received content and prepares it for display.

[0955] For VR headsets, set up the 360-degree environment and enable user eye tracking.

[0956] In the case of AR devices, the camera is activated to overlay virtual content onto the real world.

[0957] 6. Experience Delivery and User Interaction

[0958] User

[0959] Use your device to experience news content.

[0960] In VR, users can observe the progress of the typhoon while exploring the virtual space.

[0961] With AR, predicted rainfall and wind speed information is overlaid on the scenery around your home using your smartphone.

[0962] Display additional information or provide interaction as needed.

[0963] Example: Displaying detailed information to confirm safe evacuation routes and countermeasures.

[0964] Specific examples

[0965] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[0966] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[0967] 2. The server checks the user's device information, and if the user has a VR device, generates content to be experienced in VR format.

[0968] 3. The server generates a 3D model and audio simulating the typhoon's progression and streams it to the user's VR headset.

[0969] 4. The device processes the received content and prepares it so that the user can wear the VR headset and experience the 3D model.

[0970] 5. Users put on a VR headset and observe the progress of the typhoon in a virtual space, checking safe evacuation routes, etc.

[0971] This allows users to gain a deeper understanding of the content of news articles and experience them in a realistic way. Through this experience, users perceive the information as something that concerns them personally, making it easier for them to take actual action.

[0972] The processing flow will be explained below.

[0973] Step 1:

[0974] The server receives news articles from external news providers via API or RSS feeds, and stores them on the server.

[0975] Step 2:

[0976] The server applies natural language processing (NLP) algorithms to the received news articles to extract key information such as themes, locations, events, and characters. As a result, the elements of the news article are classified as follows:

[0977] Subject: Typhoon

[0978] Location: Japan

[0979] Incident: Heavy rain

[0980] Characters: Citizens, safety officials

[0981] Step 3:

[0982] The server retrieves the user's device information from the user profile database. The profile data includes which device the user is using, the type of device, and its capabilities.

[0983] Step 4:

[0984] The server selects the optimal experience format (VR, AR, or MR) based on the news content and the user's device information. For example, if the user owns a VR device, it selects the experience content in VR format.

[0985] Step 5:

[0986] The server generates content for users to experience based on the news content. The content includes 3D models, scenarios, audio, and video. Data to represent the progress of the typhoon and the strength of the wind and rain is generated as a 3D model.

[0987] Step 6:

[0988] The server references external resources (e.g., weather data or 3D model databases) to obtain additional data that matches the news content and integrates it into the generated content.

[0989] Step 7:

[0990] The server streams the generated experience content to the user's device, appropriately compressed and configured for low latency delivery.

[0991] Step 8:

[0992] The device unpacks and processes the received content and prepares it for display. For VR headsets, this involves configuring the 360-degree environment and enabling the user's eye-tracking. For AR devices, this involves activating the camera and overlaying virtual content onto the real-world scene.

[0993] Step 9:

[0994] Users experience the news content using a device. In the case of VR, users wear a VR headset and observe the progress of the typhoon in a virtual space. In the case of AR, users use their smartphone to view forecasted rainfall and wind speed information overlaid on the real world.

[0995] Step 10:

[0996] The interface allows users to obtain additional information and interact as needed, for example by displaying detailed information to check evacuation routes or check countermeasures.

[0997] This allows users to experience the content of news articles in detail and in a realistic way, which is expected to lead to a deeper understanding of the news content and make it easier for users to perceive it as something that concerns them personally.

[0998] Example 1

[0999] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1000] Conventional news article delivery methods have had issues with insufficient information transmission, especially for disaster and incident information, as it is difficult for users to grasp the reality of the information. Furthermore, they are unable to fully support the diverse devices used by users, making it difficult to experience the news in the most optimal way. Furthermore, there was a lack of a mechanism for integrating appropriate external resources based on extracted news content, making it difficult to create a realistic experience.

[1001] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1002] In this invention, the server includes means for receiving news articles and analyzing their contents, means for extracting information on themes, locations, events, and characters contained in the news articles using natural language processing, means for acquiring user profile information and selecting an optimal experience format, means for delivering the generated experience content to the user's device with low latency, means for displaying the experience content on the user's device and enabling interaction, and means for integrating external resources based on the news articles. This allows users to easily visually experience the news content in an experience format such as virtual reality (VR), augmented reality (AR), or mixed reality (MR), improving the effectiveness of information transmission and facilitating linking it to actual actions.

[1003] "News Article" means content received from a news provider via API or RSS feed that contains information about a particular event, occurrence, or topic.

[1004] "Analysis" involves using natural language processing (NLP) algorithms on incoming news articles to extract key information from the article, such as themes, locations, events, and characters.

[1005] "Natural Language Processing (NLP)" is a technology that enables computers to understand, analyze, and generate human language, and is used to extract useful information from text.

[1006] "Profile information" is information that indicates a user's attributes and tendencies, such as device information registered by the user, areas of interest, and past usage history.

[1007] "Experience format" refers to the way in which users experience news content, and includes virtual reality (VR), augmented reality (AR), and mixed reality (MR).

[1008] "Generation" refers to the creation of experiential content such as 3D models, scenarios, audio, and video based on the news content and the selected experience format.

[1009] "Low latency" refers to data transmission and reception with minimal delay, and is an important technology for achieving a real-time experience.

[1010] "Interaction" refers to a user's direct interaction with experiential content through a device, with the content dynamically changing in response to the user's operations and actions.

[1011] "External resources" are data or information obtained from external sources to complement news content, such as 3D model databases or weather data APIs.

[1012] This system generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies to help users experience the content of news articles more realistically. Below, we list each processing step and explain how to implement it.

[1013] Receiving and analyzing news articles

[1014] The server receives news articles from news providers via APIs or RSS feeds, then uses natural language processing (NLP) algorithms to extract key information from the articles, such as themes, locations, events, and characters. The software used is an NLP library (e.g., SpaCy or NLTK).

[1015] Example: A server receives news articles about typhoons from "News Provider A" via API, and uses SpaCy to extract information about "typhoons," "Japan," "heavy rain," and "citizens."

[1016] Obtaining user information and selecting experience format

[1017] The server obtains the user's profile information (device information, areas of interest, past usage history, etc.) and selects the optimal experience format (VR, AR, MR) for the news content based on the device information.

[1018] Example: The server checks the user's profile information from a database, detects that the user has a VR device, and determines that if the news item is about a typhoon progressing, it would be best experienced in VR format.

[1019] Creating experience content

[1020] The server generates experience content such as 3D models, scenarios, audio, and video based on the news content and the selected experience format. External resources (e.g., 3D model databases, weather data APIs, etc.) are integrated and reflected in the content. 3D models are generated using 3D engines such as Unity and Unreal Engine.

[1021] Example: A server uses a weather data API to obtain forecast data for a typhoon's progress, and uses Unity to generate a 3D model that visualizes the strength of the wind and rain.

[1022] Content Delivery

[1023] The server generates the experience content and delivers it to the user's device with low latency using low-latency technologies (e.g., WebRTC or RTMP).

[1024] Example: Server-generated typhoon simulation data is compressed and delivered in real time to the user's VR device using WebRTC.

[1025] Preparing for the experience

[1026] The device processes the received content and prepares the experience, setting up the 360-degree environment for VR devices, and activating the camera for AR devices to overlay virtual content onto the real world.

[1027] Example: A user's VR device analyzes typhoon simulation data received from a server, sets up a 360-degree view, and enables eye tracking. The AR device activates the camera and displays a virtual typhoon progression simulation overlaid on the real landscape.

[1028] Experience delivery and user interaction

[1029] Users experience the news content using a device. In the case of VR, users can freely explore the virtual space and observe the progress of the typhoon. In the case of AR, forecasted rainfall and wind speed information is superimposed on the area around their home.

[1030] Example: A user wears a VR device and observes a typhoon in progress in a virtual space, checking changes in wind and rain and safe evacuation routes. Using an AR device, a user can check real-time wind speed information and forecasted rainfall around their home via their smartphone, and consider countermeasures at home.

[1031] Prompt Sentence Examples

[1032] "I want to experience a news article about a typhoon approaching Japan in virtual reality. Please generate simulation content including the typhoon's progress, rainfall, wind speed, evacuation routes, etc."

[1033] By using this system, users can experience the contents of news articles in a realistic way, deepening their understanding of the information and making it easier to link it to actual actions.

[1034] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1035] Step 1:

[1036] Receiving and analyzing news articles

[1037] The server receives news articles from news providers via API or RSS feed.

[1038] Input: A news article feed from a news provider.

[1039] Output: Received news article data.

[1040] How it works: The server sends an API request and receives news article data in JSON format. It then uses natural language processing (NLP) algorithms to parse the article and extract key information such as the subject, location, events, and characters. The NLP libraries used are SpaCy and NLTK.

[1041] Step 2:

[1042] Obtaining user information and selecting experience format

[1043] The server retrieves the user's profile information from a database.

[1044] Input: User's registered profile information.

[1045] Output: User's device information.

[1046] Specific operation: The server searches the database for profile information using the user ID as a key and obtains information about the device owned by the user. Based on the user's device information, it checks whether the user has a VR device, an AR-compatible smartphone, or other device. It then selects the optimal experience format (VR, AR, or MR) based on the news content.

[1047] Step 3:

[1048] Creating experience content

[1049] The server generates experience content based on the news content and the selected experience format.

[1050] Input: Parsed news information, user device information.

[1051] Output: The generated experience content (3D models, scenarios, audio, video, etc.).

[1052] Specific operation: The server obtains additional information from external resources such as weather data APIs and generates content using a 3D engine such as Unity or Unreal Engine. For example, in a typhoon progression simulation, a 3D model visualizing the strength of wind and rain and audio are generated.

[1053] Step 4:

[1054] Content Delivery

[1055] The server delivers the generated experience content to the user's device with low latency.

[1056] Input: Experience content data.

[1057] Output: Streaming data to user devices.

[1058] How it works: The server compresses the generated experience content and streams it to the user's device using low-latency technologies such as WebRTC or RTMP. For example, it sends typhoon simulation data to the user's VR device in real time.

[1059] Step 5:

[1060] Preparing for the experience

[1061] The terminal processes the received content and prepares it for display.

[1062] Input: Experience content data received from the server.

[1063] Output: The experience content ready to be displayed.

[1064] What happens: For VR devices, the device sets up a 360-degree view and enables eye tracking. For AR devices, the device activates the camera and prepares to overlay virtual content onto the real world.

[1065] Step 6:

[1066] Experience delivery and user interaction

[1067] A user uses the device to experience the news content.

[1068] Input: Experience content on the user device.

[1069] Output: User experience data and interaction logs.

[1070] Specific operation: Using a VR device or an AR-enabled smartphone, users visually experience the typhoon's progress, rainfall, wind speed, evacuation routes, and more. VR allows users to explore the virtual space, while AR displays real-time information. Interactions include eye tracking, touch input, and voice input.

[1071] (Application example 1)

[1072] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1073] Conventional news articles are often presented in the form of text or still images, limiting the user's ability to deeply understand the content. Furthermore, there is little experiential content that makes it easier to understand the news content, making it difficult for users to experience the actual situation, especially when it comes to natural disasters or major incidents. As a result, users may lack the understanding and preparation necessary to take appropriate action. There is a need to solve these problems.

[1074] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1075] In this invention, the server includes means for receiving news articles and analyzing their contents, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for acquiring camera footage and overlaying and displaying augmented reality content based on the analyzed news content, means for delivering the generated experiential content to the user's device, and means for displaying the experiential content on the user's device and enabling interaction. This allows the content of the news article to be intuitively understood, providing a more realistic experience compared to the real world.

[1076] "News article" refers to information about an event or occurrence distributed via the internet or other media.

[1077] "Analysis" refers to analyzing information such as text data using specific algorithms and techniques to understand its meaning and structure.

[1078] "Virtual reality (VR)" is a technology that uses computer graphics and sensor technology to create a virtual environment that users perceive as real.

[1079] Augmented reality (AR) is a technology that displays virtual objects and information overlaid on real-world scenery.

[1080] "Mixed reality (MR)" is a technology that allows real and virtual objects to work together and interact, and is an integration of virtual reality and augmented reality.

[1081] "Experiential content" is multimedia content designed to allow users to virtually experience specific situations or settings.

[1082] "Device Information" refers to information about the type and capabilities of the device owned by the User.

[1083] "User's device" refers to electronic devices used by a user, such as a smartphone, tablet, computer, or head-mounted display.

[1084] "Interaction" refers to the ability of a user to interact with, manipulate, or obtain information about experiential content through a device.

[1085] "Camera Footage" refers to current real-world video data captured by a camera device.

[1086] "Delivery" refers to the transmission of data or content from a server to a user's device.

[1087] "Overlay display" refers to the display of virtual objects and information over real-world images.

[1088] "Natural language processing (NLP)" refers to the techniques and algorithms that enable computers to understand and process human language.

[1089] This invention is a system that converts news articles into experiential content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies and provides them to users. This system consists of a server, a user's device (e.g., a smartphone, smart glasses, or head-mounted display), and an application installed on the device.

[1090] System configuration

[1091] 1. Receiving and analyzing news articles

[1092] The server receives news articles from external news providers via APIs or RSS feeds, which are then parsed using natural language processing (NLP) algorithms to extract information such as subject, location, events, and characters.

[1093] 2. Obtaining user information and selecting the experience format

[1094] The server obtains device information from the user's profile information, and based on this information, selects the experience format (VR, AR, or MR) that best suits the news content and device information.

[1095] 3. Creating experience content

[1096] The server generates experiential content based on the analyzed news content, specifically 3D models, scenarios, audio, and video related to the news content, allowing users to experience it.

[1097] 4. Content Delivery

[1098] The generated experience content is streamed from the server to the user's device, with data compression and low latency ensured during delivery.

[1099] 5. Preparing and delivering the experience

[1100] The user's device (e.g., smartphone, smart glasses, etc.) analyzes the received content and prepares it for display. For example, in the case of an AR device, it activates the camera and overlays virtual content on the real world.

[1101] 6. User Interaction

[1102] Users can interact with the generated content using their devices to experience the content of news articles. For example, an app for AR devices displays information related to news articles in real-time on the smartphone camera screen.

[1103] Hardware and software used

[1104] Hardware: User devices such as smartphones, smart glasses, and head-mounted displays

[1105] Software: Natural Language Processing (NLP) algorithms, device drivers (cameras, sensors, etc.), streaming software

[1106] As a concrete example, we use Python libraries (e.g., SpaCy, NLTK) for natural language processing and OpenCV for image processing.

[1107] Specific examples

[1108] As a concrete example, let's consider a news article reporting an approaching typhoon in Japan. After the news article is received and parsed by the server, the following process takes place:

[1109] Analysis of news articles: The server extracts information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[1110] Get user information: Verify that the user has an AR-enabled smartphone.

[1111] Content generation: To simulate the progression of a typhoon, 3D models and audio are generated to express the strength of wind and rain.

[1112] Content delivery: The generated AR content is delivered to the user's smartphone.

[1113] Display preparation: The user activates the smartphone camera and displays the 3D model and typhoon information superimposed on the real landscape.

[1114] Interaction: Users can visually understand the progress of the typhoon and evacuation routes through their smartphone screen.

[1115] Prompt Sentence Examples

[1116] "Extract key information about a news article (subject, location, events, characters, etc.)."

[1117] This allows users to more intuitively understand the content of news articles and link it to actual actions.

[1118] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1119] Step 1:

[1120] The server receives news articles from external news providers via API or RSS feed. The input of the received news article is the JSON data of the news article. Based on this input, the server starts parsing the text data.

[1121] Step 2:

[1122] The server uses natural language processing (NLP) algorithms on the received news articles to extract key information such as themes, locations, events, and characters. The input is the text data of the news articles. Specifically, it uses NLP algorithms (e.g., SpaCy, NLTK) to extract keywords and phrases from the articles and outputs the results in JSON format.

[1123] Step 3:

[1124] The server obtains device information from the user's profile information and selects the optimal experience format. The input is the user's profile information and device information. Based on the extracted news content and device information, the server selects one of the experience formats (VR, AR, or MR) and records the result.

[1125] Step 4:

[1126] The server generates experience content based on the analyzed news content. Specifically, it generates 3D models, scenarios, audio, video, etc. related to the news content. The input is the main information of the news and the selected experience format. The resulting 3D models, audio files, etc. are output.

[1127] Step 5:

[1128] The server streams the generated experiential content to the user's device. The input is the generated experiential content. The server compresses the content and delivers it with low latency. The output is the stream data sent to the user's device.

[1129] Step 6:

[1130] The user's device processes the received experience content and prepares it for display. This input is the experience content streamed from the server. The device decodes the received data and converts it into a displayable format. In the case of a VR headset, it sets up a 360-degree virtual environment. In the case of an AR device, it activates the camera and overlays the virtual content onto the real world.

[1131] Step 7:

[1132] The user experiences news content using the device. This input is the experience content ready for display. For example, the user uses a smartphone to display forecasted rainfall and wind speed information overlaid on the scenery around their home. The user operates the device and interacts with the displayed content.

[1133] Through these steps, users can intuitively understand the content of the news article and get a realistic experience.

[1134] 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.

[1135] This invention combines a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, with an emotion engine that recognizes the user's emotions, in order to make the content of news articles more realistic for users. The program for this system performs processing in the following steps:

[1136] Program processing

[1137] 1. Receiving and analyzing news articles

[1138] server

[1139] News articles are received from external news providers via API or RSS feeds, and are stored on the server.

[1140] It uses natural language processing (NLP) algorithms on incoming news articles to extract key information such as subject, location, events, and characters.

[1141] For example, if an article is about the progression of a typhoon, extract terms such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[1142] 2. Obtaining user information and selecting the experience format

[1143] server

[1144] Retrieve the user's device information from the user's profile database. Profile data includes which device the user is using, the device type, and its capabilities.

[1145] The optimal experience format (VR, AR, MR) is selected based on the news content and the user's device information.

[1146] Example: If the user has a VR device, select experience content in VR format.

[1147] 3. Creating experience content

[1148] server

[1149] Based on the news content, content is generated for users to experience. The content includes 3D models, scenarios, audio, and video. Data is generated as a 3D model to represent the progress of the typhoon and the strength of the wind and rain.

[1150] If necessary, external resources (e.g., weather data or 3D model databases) are referenced to obtain additional data that matches the news content and are integrated into the generated content.

[1151] 4. Emotion engine integration

[1152] server

[1153] The emotion engine recognizes the user's emotional state by analyzing the user's facial expressions, voice, and behavioral patterns.

[1154] Example: If the user has a surprised expression, the emotion engine will recognize it.

[1155] It provides feedback on experience content based on the user's emotional state and dynamically adjusts the scenario as needed.

[1156] Example: If the user is feeling scared, adjust the scenario by making it a little less strenuous.

[1157] 5. Content Delivery

[1158] server

[1159] The resulting experience content is streamed to the user's device, appropriately compressed and configured for low latency delivery.

[1160] 6. Preparation for the experience

[1161] Terminal

[1162] It unpacks and processes the received content and prepares it for display. For VR headsets, it configures the 360-degree environment and enables eye tracking for the user. For AR devices, it activates the camera and overlays virtual content onto the real-world scene.

[1163] 7. Experience Delivery and User Interaction

[1164] User

[1165] Users can experience the news using a device. In the case of VR, users wear a VR headset and observe the progress of the typhoon in a virtual space. In the case of AR, users use their smartphone to view forecasted rainfall and wind speed information overlaid on the real world.

[1166] An emotion engine monitors the user's emotions in real time and provides feedback: for example, if the user expresses curiosity, additional relevant information will be displayed.

[1167] Specific examples

[1168] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[1169] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[1170] 2. The server checks the user's device information, and if the user has a VR device, generates content to be experienced in VR format.

[1171] 3. The server generates a 3D model and audio simulating the typhoon's progress and streams it to the user's VR headset.

[1172] 4. The device processes the received content and prepares it so that the user can wear the VR headset and experience the 3D model.

[1173] 5. Users put on a VR headset and observe the progress of the typhoon in a virtual space, checking safe evacuation routes, etc.

[1174] 6. The emotion engine monitors the user's emotions, and if the user feels surprised, for example, it reflects that information in the content and adjusts the scenario.

[1175] This allows users to experience the content of news articles in detail and realistically, while dynamically adjusting the experience based on the user's emotional state, allowing them to gain a deeper understanding of the news content and more easily recognize it as an issue close to home.

[1176] The processing flow will be explained below.

[1177] Step 1:

[1178] The server receives news articles from external news providers via API or RSS feeds, and stores them on the server.

[1179] Step 2:

[1180] The server applies natural language processing (NLP) algorithms to the received news articles to extract key information such as subject, location, events, and characters.

[1181] For example, if an article is about the progression of a typhoon, information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials" will be extracted.

[1182] Step 3:

[1183] The server retrieves the user's device information from the user's profile database.

[1184] Example: Checking if the user owns a VR device (e.g., a headset) or is using an AR-enabled smartphone.

[1185] Step 4:

[1186] The server selects the optimal experience format (VR, AR, MR) based on the news content and the user's device information.

[1187] Example: If the user has a VR device, select VR experience content.

[1188] Step 5:

[1189] The server generates content for users to experience based on the news content, including 3D models, scenarios, audio, and video.

[1190] Example: Generating 3D models and sounds to represent the progress of a typhoon and the strength of wind and rain.

[1191] Step 6:

[1192] The server references external resources (e.g., weather data or 3D model databases) to obtain additional data that matches the news content and integrates it into the generated content.

[1193] Example: Accurately simulate the movement of typhoons by referencing actual weather data.

[1194] Step 7:

[1195] The server streams the generated experience content to the user's device, appropriately compressed and configured for low latency delivery.

[1196] Example: Delivering typhoon simulation data in real time to a user's VR headset.

[1197] Step 8:

[1198] The device unpacks and processes the received content and prepares it for display. For VR headsets, this involves configuring the 360-degree environment and enabling the user's eye-tracking. For AR devices, this involves activating the camera and overlaying virtual content onto the real-world scene.

[1199] For example, a VR headset allows users to freely move their viewpoint, and an AR device displays the predicted path of a typhoon through the camera.

[1200] Step 9:

[1201] Users experience the news content using a device. In the case of VR, users wear a VR headset to observe the progress of the typhoon in a virtual space and check safe evacuation routes. In the case of AR, users can see forecasted rainfall and wind speed information overlaid on the real world.

[1202] Example: A user observes the direction of a typhoon in a VR space and checks evacuation routes.

[1203] Step 10:

[1204] The emotion engine recognizes the user's emotional state and obtains emotional data by analyzing the user's facial expressions, voice, and behavioral patterns.

[1205] For example, if a user shows signs of surprise or fear, that information is collected.

[1206] Step 11:

[1207] The server uses the emotion engine data to provide feedback to the experience content based on the user's emotional state, dynamically adjusting the scenario as needed.

[1208] Example: If the user is feeling scared, adjust the scenario to make it more nuanced and reassuring.

[1209] Information presentation: If the user shows interest, more detailed news information or additional content is provided.

[1210] This allows users to not only experience the content of news articles in detail and realistically, but also to get an optimal experience tailored to their emotional state. By deepening their understanding of the news content and providing a customized experience tailored to the recipient's emotions, this system makes it easier for them to recognize news information as something that concerns them personally.

[1211] Example 2

[1212] 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."

[1213] In modern society, news articles cover a wide range of topics, and it takes time and effort to gain a deep understanding of their content. However, simply reading news content as text can be difficult to grasp, especially when it comes to complex events. Furthermore, users may lose interest if the content of the news article does not feel familiar to them. In particular, when it comes to news that has a strong emotional impact, such as natural disasters or social incidents, it is difficult for users to actually experience the situation, making it difficult for them to truly appreciate the importance of the information. Therefore, a method is needed to provide news content that is more realistic and responds to the individual emotions of each user.

[1214] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1215] In this invention, the server includes means for receiving a news article and analyzing its content, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for delivering the generated experiential content to the user's device, means for using an emotion engine that analyzes the user's facial expressions, voice, and behavioral patterns to recognize the user's emotional state, means for dynamically providing feedback on the experiential content and adjusting the scenario based on the user's emotional state, and means for displaying the experiential content on the user's device and enabling interaction. This allows the user to experience the content of the news article more realistically and enables the provision of dynamic content according to emotions.

[1216] A "news article" is a document containing information distributed by a news organization or information provider.

[1217] "Means of analysis" refers to a system for analyzing the content of news articles and extracting key information and keywords.

[1218] "Virtual reality (VR)" is a technology that allows users to immerse themselves in a virtual environment using a dedicated device.

[1219] Augmented reality (AR) is a technology that displays virtual information overlaid on real-world scenery.

[1220] "Mixed reality (MR)" is a technology that combines virtual reality and augmented reality to integrate and display virtual information with real-world information.

[1221] "Experiential content" is digital content that transforms the content of a news article into a format that can be experienced in virtual reality, augmented reality, or mixed reality.

[1222] "User device information" is data related to the type and performance of the device used by the user.

[1223] An "emotion engine" is software that analyzes a user's facial expressions, voice, and behavioral patterns to recognize their emotional state.

[1224] "Feedback" is a response that adjusts the content or scenario of the experience content based on the user's emotional state.

[1225] A "scenario" is a set of events or situations that a user experiences within experiential content.

[1226] "Interaction" is the process by which a user interacts with experiential content through a device.

[1227] A "user device" is an electronic device that a user uses to view experiential content.

[1228] The "means of delivery" is the mechanism by which the generated experience content is sent to the user's device.

[1229] "Natural language processing (NLP)" is a technology for analyzing and understanding natural language such as text and speech.

[1230] This invention combines a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, with an emotion engine that recognizes the user's emotions, in order to make the content of news articles more realistic for users.

[1231] Receiving and analyzing news articles

[1232] server

[1233] The server receives news articles from external news providers via APIs or RSS feeds. This process uses the news delivery service's API or RSS feed reader software. The received news articles are stored in a database on the server. Natural language processing (NLP) algorithms are then used on the stored news articles to extract key information such as themes, locations, events, and characters. Specifically, natural language processing libraries and frameworks (e.g., NLTK, SpaCy) can be used.

[1234] Obtaining user information and selecting experience format

[1235] server

[1236] The server accesses the user's profile database to obtain the user's device information and personal settings. It identifies the type of device the user is using (VR device, AR device, smartphone, etc.) and its capabilities (resolution, memory, processing power, etc.). Based on the news content and the user's device information, the server selects the optimal experience format (VR, AR, MR) for the user.

[1237] Creating experience content

[1238] server

[1239] The server generates content for users to experience based on the news content. This content includes 3D models, scenarios, audio, and video. For example, a 3D model showing the progression of a typhoon is created using Autodesk Maya, and audio narration and sound effects are edited using Adobe Audition. Furthermore, if necessary, external resources (e.g., weather data, 3D model databases) are referenced to obtain and integrate additional data that matches the news content.

[1240] Emotion engine integration

[1241] server

[1242] The server recognizes the user's emotional state through an emotion engine. This is done by analyzing the user's facial expressions, voice, and behavioral patterns. Specifically, it analyzes facial and voice data using Microsoft Azure's Face API and Speech API. It then provides feedback on the experience content based on the user's emotional state and dynamically adjusts the scenario. For example, if the user is startled, it changes the music or visual effects to ease parts of the scenario and provides additional safety information.

[1243] Content Delivery

[1244] server

[1245] The server streams the generated experience content to the user's device using the H.265 video codec and the HTTP / 2.0 protocol for low latency. Data is compressed on the server side to maximize network bandwidth efficiency.

[1246] Preparing for the experience

[1247] Terminal

[1248] The device unpacks the received content and processes it for display. For example, for VR devices (e.g., Oculus Quest 2), it uses the Oculus SDK to set up the 360-degree environment and enable eye tracking. For AR devices (e.g., an ARKit-enabled iPhone), it activates the camera and uses ARKit to overlay virtual content on the real-world landscape.

[1249] Experience delivery and user interaction

[1250] User

[1251] Users experience news content using a VR headset or an AR smartphone app. For example, a user wearing an Oculus Quest 2 can observe the progress of a typhoon in real time in a 3D simulation. An interactive scenario is also provided in which users can choose different evacuation routes. An emotion engine monitors the user's emotions in real time. If the user expresses curiosity, for example, relevant additional information or interactive questions are displayed on the screen.

[1252] Specific examples

[1253] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[1254] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[1255] 2. The server checks the user's device information and, if the user has an Oculus Quest 2, generates content to be experienced in VR format.

[1256] 3. The server generates a 3D model and audio simulating the progression of the typhoon and streams it to the user's VR headset. Specifically, the 3D model was created in Autodesk Maya and the audio was edited in Adobe Audition.

[1257] 4. The device processes the received content and sets up the VR environment using the Oculus SDK.

[1258] 5. Users wear a VR headset and experience the typhoon's progress in a realistic way. They are also provided with an interactive scenario where they can choose different evacuation routes.

[1259] 6. The emotion engine monitors the user's emotions and, if surprised, mitigates the scenario and provides additional safety information.

[1260] Example prompts for generative AI models

[1261] "Describe a system that generates VR experiences based on news articles, including a process for recognizing the user's emotions in real time and dynamically adjusting the experience accordingly."

[1262] This allows users to experience the content of news articles in detail and realistically, while dynamically adjusting the experience based on the user's emotional state, allowing them to gain a deeper understanding of the news content and more easily recognize it as an issue close to home.

[1263] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1264] Step 1: Receiving and parsing news articles

[1265] server

[1266] Input: News article data provided by external news providers (API or RSS feed).

[1267] What it does: The server periodically receives news articles via API or RSS feeds and stores them in a database.

[1268] Data processing: Analyzing text data from news articles using natural language processing (NLP) algorithms.

[1269] Output: Analyzed data including key information such as subjects, places, events, and characters (e.g., "typhoon," "Japan," "heavy rain," "citizens," "safety officials").

[1270] Step 2: Obtain user information and select experience format

[1271] server

[1272] Input: Device information (device type and capabilities) retrieved from the user's profile database.

[1273] What happens: The server accesses the user's profile database to see which device the user is using.

[1274] Data calculation: Executes logic to select the experience format based on the news content and user device information.

[1275] Output: The optimal experience format (VR, AR, MR) selected.

[1276] Step 3: Generate experience content

[1277] server

[1278] Input: Analysis data (key news information), user experience format (VR, AR, MR).

[1279] What it does: The server creates 3D models in Autodesk Maya and edits voice narration and sound effects in Adobe Audition, and optionally references external resources such as weather data and 3D model databases.

[1280] Data processing: Integrating key news information with external data to generate content for the user experience.

[1281] Output: Generated experience content (3D model, scenario, audio, video).

[1282] Step 4: Integrating the Emotion Engine

[1283] server

[1284] Input: User's facial expression data, voice data, and behavioral pattern data.

[1285] Specific operation: The server performs facial expression analysis and voice analysis using Microsoft Azure's Face API and Speech API.

[1286] Data computation: Running algorithms to recognize the user's emotional state in real time.

[1287] Output: The user's emotional state (e.g., surprise, fear, curiosity).

[1288] Step 5: Content feedback and scenario adjustments

[1289] server

[1290] Input: User experience content, user emotional state.

[1291] Specific behavior: Based on the user's emotional state, the server generates feedback on the experience content and dynamically adjusts the scenario, changing music and visual effects and providing additional safety information.

[1292] Data processing: Generate customized content based on the user's emotional state.

[1293] Output: Tailored experience content.

[1294] Step 6: Deliver your content

[1295] server

[1296] Input: Tailored experience content.

[1297] What it does: The server compresses the content using the H.265 video codec and streams it to the user's device using the HTTP / 2.0 protocol.

[1298] Output: The experience content that is streamed to the user's device.

[1299] Step 7: Prepare for the experience

[1300] Terminal

[1301] Input: The received experience content.

[1302] What it does: The device unpacks the received content and uses the Oculus SDK to set up a 360-degree VR environment, enable eye tracking, and, in the case of AR devices, uses ARKit to overlay virtual content onto the camera image.

[1303] Data operations: Converting content into a format that can be displayed on the device.

[1304] Output: The experience content ready to be displayed.

[1305] Step 8: Experience Delivery and User Interaction

[1306] User

[1307] Input: Optimized VR or AR content.

[1308] What happens: Users use a VR headset or AR device to experience the news in a realistic way.

[1309] Output: User experience and interaction data (user responses and choices).

[1310] These are the specific steps involved in generating and providing experiential content based on news articles. This process allows users to gain a deeper understanding of the news article and experience it in a way that is realistic and emotionally relevant.

[1311] (Application example 2)

[1312] 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."

[1313] Conventional news delivery systems have the problem that users have difficulty grasping the content of the news and have a shallow understanding of the information. In addition, they are unable to take into account users' emotional reactions to news articles, making it difficult to provide an optimal experience for each individual user.

[1314] The identification processing by identification processing unit 290 of data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving news articles and analyzing their contents, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for recognizing the user's emotions and providing feedback, means for delivering the generated experiential content to the user's device, and means for displaying the experiential content on the user's device and enabling interaction. This allows the user to experience the news content in real time and receive optimal feedback based on their emotional response.

[1315] "News Article" means a news article containing information distributed over the Internet.

[1316] "Analysis" is the process of breaking down the content of a news article and extracting information such as themes, characters, locations, and events.

[1317] "Virtual reality (VR)" is a technology that allows users to experience a three-dimensional virtual environment generated using computer technology through a dedicated device.

[1318] Augmented reality (AR) is a technology that displays computer-generated information overlaid on real-world scenery.

[1319] "Mixed reality (MR)" is a technology that provides an experience that combines virtual reality (VR) and augmented reality (AR).

[1320] "Experiential content" refers to content in the form of virtual reality (VR), augmented reality (AR), or mixed reality (MR) generated from the content of a news article.

[1321] "Device" means the hardware that enables a user to experience virtual reality (VR), augmented reality (AR), or mixed reality (MR).

[1322] "Emotion recognition" means judging the user's emotional state by analyzing the user's facial expressions, voice, behavioral patterns, etc.

[1323] "Feedback" refers to information or responses returned to the user that adjust the scenario based on the user's emotional state.

[1324] "Interaction" refers to the ability for users to interact with experiential content through a device.

[1325] The present invention relates to a system for providing news articles to users as virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content. The system includes means for receiving news articles, analyzing them, generating experience content, recognizing emotions, delivering them, and interacting with them.

[1326] Server Processing

[1327] The server first receives news articles from external news providers via APIs or RSS feeds. While we will not specify the names of specific news providers, we will assume that they are publicly available news distribution services.

[1328] Next, the received news article is analyzed using natural language processing (NLP) algorithms. An NLP engine like Spacy is used to extract key information such as subject, location, incident, and characters. For example, in an article about a typhoon's progress, information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials" are extracted.

[1329] The system then retrieves device information from the user's profile information and selects the optimal experience format. The system retrieves the device type and capabilities of the user from the profile database. Based on this information, if the user has a VR device, the system selects the VR experience content.

[1330] In the generation of experience content, 3D models, scenarios, audio, and video are generated based on the news content. Additional data from simulation data and external resources (e.g., weather data and 3D model databases) is integrated to complete the content for the user to experience.

[1331] In addition, the emotion engine recognizes the user's emotional state in real time and provides feedback. The emotion engine analyzes facial expressions, voice, and behavioral patterns, and adjusts the scenario if the user feels surprised or scared.

[1332] The generated experience content is delivered to the user's device with low latency, using streaming technology to compress and appropriately transfer the content.

[1333] User's Device

[1334] The user's device receives, decompresses, and processes the delivered content: in the case of a VR headset, a 360-degree visual environment is created and eye tracking is enabled, while in the case of an AR device, virtual content is overlaid on the real-world landscape.

[1335] Users experience the news through a device. For example, by wearing a VR headset, they can observe the progress of a typhoon in a virtual space and check safe evacuation routes. An emotion engine monitors the user's emotions in real time and provides feedback. If the user expresses curiosity, additional relevant information will be displayed.

[1336] Examples of concrete examples and prompts

[1337] As an example, suppose you receive a news article about a large typhoon approaching Japan. The server analyzes the news article and extracts information such as "typhoon," "Japan," "heavy rain," and "Tokyo." It then verifies that the user owns a VR device and generates a 3D model of the typhoon simulation. The generative AI model uses the following prompt:

[1338] News article: A powerful typhoon is approaching Japan, with heavy rain expected in Tokyo.

[1339] Keywords: typhoon, Japan, heavy rain, Tokyo

[1340] Generated VR content: 3D model simulating the typhoon's progress, rainfall, wind speed, and safety advice

[1341] This allows users to experience the progression of the typhoon in real time based on actual news articles and receive optimal feedback based on their emotional response.

[1342] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1343] Step 1: Receiving and parsing news articles

[1344] The server receives news articles from external news providers using APIs or RSS feeds. The received news articles are stored on the server. Natural language processing (NLP) algorithms (e.g., Spacy) are then used to analyze the news content and extract key information such as themes, locations, events, and characters. The input is the news article, and the output is the extracted information (e.g., "typhoon," "Japan," "heavy rain," "citizens," "safety officials").

[1345] Step 2: Obtain user information and select experience format

[1346] The server retrieves the user's device information from the user profile database. The profile data includes the device the user is using, as well as the device's type and performance. The input is the user ID, and the output is the device information. The server then selects the optimal experience format (VR, AR, or MR) based on the news content and the user's device information. For example, if the user owns a VR device, experience content in VR format is selected.

[1347] Step 3: Generate experience content

[1348] The server generates 3D models, scenarios, audio, and video based on the news content. For example, it generates a 3D model using data to represent the progress of a typhoon and the strength of wind and rain. If necessary, it obtains additional data from external resources (e.g., weather data or a 3D model database) and integrates it into the generated content. The input is the analyzed news information and the user's device information, and the output is the generated VR content.

[1349] Step 4: Integrating the Emotion Engine

[1350] The server uses an emotion engine to recognize the user's emotional state in real time. This is done by analyzing the user's facial expressions, voice, and behavioral patterns. For example, if the user shows a surprised expression, the emotion engine recognizes this. The input is the user's behavioral data, and the output is the user's emotional state. Based on the user's emotional state, the server provides feedback on the experience content and dynamically adjusts the scenario.

[1351] Step 5: Deliver your content

[1352] The server streams the generated experience content to the user's device. The data is appropriately compressed and configured for low latency delivery. The input is the generated VR content, and the output is the content delivered to the user's device.

[1353] Step 6: Prepare for the experience

[1354] The device unpacks and processes the received content and prepares it for display. In the case of a VR headset, this involves configuring the 360-degree environment and enabling the user's eye-tracking. In the case of an AR device, it activates the camera and overlays virtual content onto the real-world scene. The input is the streamed VR content, and the output is the content ready to be displayed.

[1355] Step 7: Experience Delivery and User Interaction

[1356] Users use devices to experience news content. In the case of VR, users wear a VR headset to observe the progress of the typhoon in a virtual space and check safe evacuation routes. In the case of AR, users use their smartphones to check predicted rainfall and wind speed information overlaid on the real world. An emotion engine monitors the user's emotions in real time and provides feedback. The input is the displayed content and the user's real-time behavioral data, and the output is the user experience and feedback.

[1357] 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.

[1358] 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.

[1359] 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.

[1360] [Fourth embodiment]

[1361] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1362] 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.

[1363] 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).

[1364] 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.

[1365] 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.

[1366] 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).

[1367] 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.

[1368] 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.

[1369] 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.

[1370] 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.

[1371] 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.

[1372] 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.

[1373] 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."

[1374] This invention is a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies to help users experience the content of news articles. The program for this system performs processing in the following steps.

[1375] Program processing

[1376] 1. Receiving and analyzing news articles

[1377] server

[1378] Receive news articles from external news providers via API or RSS feed.

[1379] It uses natural language processing (NLP) algorithms on incoming news articles to extract key information such as subject, location, events, and characters.

[1380] For example, if an article is about the progression of a typhoon, extract terms such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[1381] 2. Obtaining user information and selecting the experience format

[1382] server

[1383] Get device information from the user's profile information.

[1384] Example: Checking if the user owns a VR device or has an AR-enabled smartphone.

[1385] The optimal experience format (VR, AR, MR) is selected based on the news content and the user's device information.

[1386] Example: If you have a VR device, simulate the progression of a typhoon in a virtual space.

[1387] 3. Creating experience content

[1388] server

[1389] Based on the news content, it generates content for users to experience, including 3D models, scenarios, audio, and video.

[1390] Example: To simulate the progression of a typhoon, generate a 3D model and audio that expresses the strength of wind and rain.

[1391] Retrieve external resources (e.g., 3D model databases, weather data) as needed and integrate them into your content.

[1392] 4. Content Delivery

[1393] server

[1394] The generated experience content is streamed to the user's device.

[1395] Example: Compressing typhoon simulation data and delivering it with low latency.

[1396] 5. Preparation for the experience

[1397] Terminal

[1398] Processes the received content and prepares it for display.

[1399] For VR headsets, set up the 360-degree environment and enable user eye tracking.

[1400] In the case of AR devices, the camera is activated to overlay virtual content onto the real world.

[1401] 6. Experience Delivery and User Interaction

[1402] User

[1403] Use your device to experience news content.

[1404] In VR, users can observe the progress of the typhoon while exploring the virtual space.

[1405] With AR, predicted rainfall and wind speed information is overlaid on the scenery around your home using your smartphone.

[1406] Display additional information or provide interaction as needed.

[1407] Example: Displaying detailed information to confirm safe evacuation routes and countermeasures.

[1408] Specific examples

[1409] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[1410] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[1411] 2. The server checks the user's device information, and if the user has a VR device, generates content to be experienced in VR format.

[1412] 3. The server generates a 3D model and audio simulating the typhoon's progression and streams it to the user's VR headset.

[1413] 4. The device processes the received content and prepares it so that the user can wear the VR headset and experience the 3D model.

[1414] 5. Users put on a VR headset and observe the progress of the typhoon in a virtual space, checking safe evacuation routes, etc.

[1415] This allows users to gain a deeper understanding of the content of news articles and experience them in a realistic way. Through this experience, users perceive the information as something that concerns them personally, making it easier for them to take actual action.

[1416] The processing flow will be explained below.

[1417] Step 1:

[1418] The server receives news articles from external news providers via API or RSS feeds, and stores them on the server.

[1419] Step 2:

[1420] The server applies natural language processing (NLP) algorithms to the received news articles to extract key information such as themes, locations, events, and characters. As a result, the elements of the news article are classified as follows:

[1421] Subject: Typhoon

[1422] Location: Japan

[1423] Incident: Heavy rain

[1424] Characters: Citizens, safety officials

[1425] Step 3:

[1426] The server retrieves the user's device information from the user profile database. The profile data includes which device the user is using, the type of device, and its capabilities.

[1427] Step 4:

[1428] The server selects the optimal experience format (VR, AR, or MR) based on the news content and the user's device information. For example, if the user owns a VR device, it selects the experience content in VR format.

[1429] Step 5:

[1430] The server generates content for users to experience based on the news content. The content includes 3D models, scenarios, audio, and video. Data to represent the progress of the typhoon and the strength of the wind and rain is generated as a 3D model.

[1431] Step 6:

[1432] The server references external resources (e.g., weather data or 3D model databases) to obtain additional data that matches the news content and integrates it into the generated content.

[1433] Step 7:

[1434] The server streams the generated experience content to the user's device, appropriately compressed and configured for low latency delivery.

[1435] Step 8:

[1436] The device unpacks and processes the received content and prepares it for display. For VR headsets, this involves configuring the 360-degree environment and enabling the user's eye-tracking. For AR devices, this involves activating the camera and overlaying virtual content onto the real-world scene.

[1437] Step 9:

[1438] Users experience the news content using a device. In the case of VR, users wear a VR headset and observe the progress of the typhoon in a virtual space. In the case of AR, users use their smartphone to view forecasted rainfall and wind speed information overlaid on the real world.

[1439] Step 10:

[1440] The interface allows users to obtain additional information and interact as needed, for example by displaying detailed information to check evacuation routes or check countermeasures.

[1441] This allows users to experience the content of news articles in detail and in a realistic way, which is expected to lead to a deeper understanding of the news content and make it easier for users to perceive it as something that concerns them personally.

[1442] Example 1

[1443] 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."

[1444] Conventional news article delivery methods have had issues with insufficient information transmission, especially for disaster and incident information, as it is difficult for users to grasp the reality of the information. Furthermore, they are unable to fully support the diverse devices used by users, making it difficult to experience the news in the most optimal way. Furthermore, there was a lack of a mechanism for integrating appropriate external resources based on extracted news content, making it difficult to create a realistic experience.

[1445] 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.

[1446] In this invention, the server includes means for receiving news articles and analyzing their contents, means for extracting information on themes, locations, events, and characters contained in the news articles using natural language processing, means for acquiring user profile information and selecting an optimal experience format, means for delivering the generated experience content to the user's device with low latency, means for displaying the experience content on the user's device and enabling interaction, and means for integrating external resources based on the news articles. This allows users to easily visually experience the news content in an experience format such as virtual reality (VR), augmented reality (AR), or mixed reality (MR), improving the effectiveness of information transmission and facilitating linking it to actual actions.

[1447] "News Article" means content received from a news provider via API or RSS feed that contains information about a particular event, occurrence, or topic.

[1448] "Analysis" involves using natural language processing (NLP) algorithms on incoming news articles to extract key information from the article, such as themes, locations, events, and characters.

[1449] "Natural Language Processing (NLP)" is a technology that enables computers to understand, analyze, and generate human language, and is used to extract useful information from text.

[1450] "Profile information" is information that indicates a user's attributes and tendencies, such as device information registered by the user, areas of interest, and past usage history.

[1451] "Experience format" refers to the way in which users experience news content, and includes virtual reality (VR), augmented reality (AR), and mixed reality (MR).

[1452] "Generation" refers to the creation of experiential content such as 3D models, scenarios, audio, and video based on the news content and the selected experience format.

[1453] "Low latency" refers to data transmission and reception with minimal delay, and is an important technology for achieving a real-time experience.

[1454] "Interaction" refers to a user's direct interaction with experiential content through a device, with the content dynamically changing in response to the user's operations and actions.

[1455] "External resources" are data or information obtained from external sources to complement news content, such as 3D model databases or weather data APIs.

[1456] This system generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies to help users experience the content of news articles more realistically. Below, we list each processing step and explain how to implement it.

[1457] Receiving and analyzing news articles

[1458] The server receives news articles from news providers via APIs or RSS feeds, then uses natural language processing (NLP) algorithms to extract key information from the articles, such as themes, locations, events, and characters. The software used is an NLP library (e.g., SpaCy or NLTK).

[1459] Example: A server receives news articles about typhoons from "News Provider A" via API, and uses SpaCy to extract information about "typhoons," "Japan," "heavy rain," and "citizens."

[1460] Obtaining user information and selecting experience format

[1461] The server obtains the user's profile information (device information, areas of interest, past usage history, etc.) and selects the optimal experience format (VR, AR, MR) for the news content based on the device information.

[1462] Example: The server checks the user's profile information from a database, detects that the user has a VR device, and determines that if the news item is about a typhoon progressing, it would be best experienced in VR format.

[1463] Creating experience content

[1464] The server generates experience content such as 3D models, scenarios, audio, and video based on the news content and the selected experience format. External resources (e.g., 3D model databases, weather data APIs, etc.) are integrated and reflected in the content. 3D models are generated using 3D engines such as Unity and Unreal Engine.

[1465] Example: A server uses a weather data API to obtain forecast data for a typhoon's progress, and uses Unity to generate a 3D model that visualizes the strength of the wind and rain.

[1466] Content Delivery

[1467] The server generates the experience content and delivers it to the user's device with low latency using low-latency technologies (e.g., WebRTC or RTMP).

[1468] Example: Server-generated typhoon simulation data is compressed and delivered in real time to the user's VR device using WebRTC.

[1469] Preparing for the experience

[1470] The device processes the received content and prepares the experience, setting up the 360-degree environment for VR devices, and activating the camera for AR devices to overlay virtual content onto the real world.

[1471] Example: A user's VR device analyzes typhoon simulation data received from a server, sets up a 360-degree view, and enables eye tracking. The AR device activates the camera and displays a virtual typhoon progression simulation overlaid on the real landscape.

[1472] Experience delivery and user interaction

[1473] Users experience the news content using a device. In the case of VR, users can freely explore the virtual space and observe the progress of the typhoon. In the case of AR, forecasted rainfall and wind speed information is superimposed on the area around their home.

[1474] Example: A user wears a VR device and observes a typhoon in progress in a virtual space, checking changes in wind and rain and safe evacuation routes. Using an AR device, a user can check real-time wind speed information and forecasted rainfall around their home via their smartphone, and consider countermeasures at home.

[1475] Prompt Sentence Examples

[1476] "I want to experience a news article about a typhoon approaching Japan in virtual reality. Please generate simulation content including the typhoon's progress, rainfall, wind speed, evacuation routes, etc."

[1477] By using this system, users can experience the contents of news articles in a realistic way, deepening their understanding of the information and making it easier to link it to actual actions.

[1478] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1479] Step 1:

[1480] Receiving and analyzing news articles

[1481] The server receives news articles from news providers via API or RSS feed.

[1482] Input: A news article feed from a news provider.

[1483] Output: Received news article data.

[1484] How it works: The server sends an API request and receives news article data in JSON format. It then uses natural language processing (NLP) algorithms to parse the article and extract key information such as the subject, location, events, and characters. The NLP libraries used are SpaCy and NLTK.

[1485] Step 2:

[1486] Obtaining user information and selecting experience format

[1487] The server retrieves the user's profile information from a database.

[1488] Input: User's registered profile information.

[1489] Output: User's device information.

[1490] Specific operation: The server searches the database for profile information using the user ID as a key and obtains information about the device owned by the user. Based on the user's device information, it checks whether the user has a VR device, an AR-compatible smartphone, or other device. It then selects the optimal experience format (VR, AR, or MR) based on the news content.

[1491] Step 3:

[1492] Creating experience content

[1493] The server generates experience content based on the news content and the selected experience format.

[1494] Input: Parsed news information, user device information.

[1495] Output: The generated experience content (3D models, scenarios, audio, video, etc.).

[1496] Specific operation: The server obtains additional information from external resources such as weather data APIs and generates content using a 3D engine such as Unity or Unreal Engine. For example, in a typhoon progression simulation, a 3D model visualizing the strength of wind and rain and audio are generated.

[1497] Step 4:

[1498] Content Delivery

[1499] The server delivers the generated experience content to the user's device with low latency.

[1500] Input: Experience content data.

[1501] Output: Streaming data to user devices.

[1502] How it works: The server compresses the generated experience content and streams it to the user's device using low-latency technologies such as WebRTC or RTMP. For example, it sends typhoon simulation data to the user's VR device in real time.

[1503] Step 5:

[1504] Preparing for the experience

[1505] The terminal processes the received content and prepares it for display.

[1506] Input: Experience content data received from the server.

[1507] Output: The experience content ready to be displayed.

[1508] What happens: For VR devices, the device sets up a 360-degree view and enables eye tracking. For AR devices, the device activates the camera and prepares to overlay virtual content onto the real world.

[1509] Step 6:

[1510] Experience delivery and user interaction

[1511] A user uses the device to experience the news content.

[1512] Input: Experience content on the user device.

[1513] Output: User experience data and interaction logs.

[1514] Specific operation: Using a VR device or an AR-enabled smartphone, users visually experience the typhoon's progress, rainfall, wind speed, evacuation routes, and more. VR allows users to explore the virtual space, while AR displays real-time information. Interactions include eye tracking, touch input, and voice input.

[1515] (Application example 1)

[1516] 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."

[1517] Conventional news articles are often presented in the form of text or still images, limiting the user's ability to deeply understand the content. Furthermore, there is little experiential content that makes it easier to understand the news content, making it difficult for users to experience the actual situation, especially when it comes to natural disasters or major incidents. As a result, users may lack the understanding and preparation necessary to take appropriate action. There is a need to solve these problems.

[1518] 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.

[1519] In this invention, the server includes means for receiving news articles and analyzing their contents, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for acquiring camera footage and overlaying and displaying augmented reality content based on the analyzed news content, means for delivering the generated experiential content to the user's device, and means for displaying the experiential content on the user's device and enabling interaction. This allows the content of the news article to be intuitively understood, providing a more realistic experience compared to the real world.

[1520] "News article" refers to information about an event or occurrence distributed via the internet or other media.

[1521] "Analysis" refers to analyzing information such as text data using specific algorithms and techniques to understand its meaning and structure.

[1522] "Virtual reality (VR)" is a technology that uses computer graphics and sensor technology to create a virtual environment that users perceive as real.

[1523] Augmented reality (AR) is a technology that displays virtual objects and information overlaid on real-world scenery.

[1524] "Mixed reality (MR)" is a technology that allows real and virtual objects to work together and interact, and is an integration of virtual reality and augmented reality.

[1525] "Experiential content" is multimedia content designed to allow users to virtually experience specific situations or settings.

[1526] "Device Information" refers to information about the type and capabilities of the device owned by the User.

[1527] "User's device" refers to electronic devices used by a user, such as a smartphone, tablet, computer, or head-mounted display.

[1528] "Interaction" refers to the ability of a user to interact with, manipulate, or obtain information about experiential content through a device.

[1529] "Camera Footage" refers to current real-world video data captured by a camera device.

[1530] "Delivery" refers to the transmission of data or content from a server to a user's device.

[1531] "Overlay display" refers to the display of virtual objects and information over real-world images.

[1532] "Natural language processing (NLP)" refers to the techniques and algorithms that enable computers to understand and process human language.

[1533] This invention is a system that converts news articles into experiential content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies and provides them to users. This system consists of a server, a user's device (e.g., a smartphone, smart glasses, or head-mounted display), and an application installed on the device.

[1534] System configuration

[1535] 1. Receiving and analyzing news articles

[1536] The server receives news articles from external news providers via APIs or RSS feeds, which are then parsed using natural language processing (NLP) algorithms to extract information such as subject, location, events, and characters.

[1537] 2. Obtaining user information and selecting the experience format

[1538] The server obtains device information from the user's profile information, and based on this information, selects the experience format (VR, AR, or MR) that best suits the news content and device information.

[1539] 3. Creating experience content

[1540] The server generates experiential content based on the analyzed news content, specifically 3D models, scenarios, audio, and video related to the news content, allowing users to experience it.

[1541] 4. Content Delivery

[1542] The generated experience content is streamed from the server to the user's device, with data compression and low latency ensured during delivery.

[1543] 5. Preparing and delivering the experience

[1544] The user's device (e.g., smartphone, smart glasses, etc.) analyzes the received content and prepares it for display. For example, in the case of an AR device, it activates the camera and overlays virtual content on the real world.

[1545] 6. User Interaction

[1546] Users can interact with the generated content using their devices to experience the content of news articles. For example, an app for AR devices displays information related to news articles in real-time on the smartphone camera screen.

[1547] Hardware and software used

[1548] Hardware: User devices such as smartphones, smart glasses, and head-mounted displays

[1549] Software: Natural Language Processing (NLP) algorithms, device drivers (cameras, sensors, etc.), streaming software

[1550] As a concrete example, we use Python libraries (e.g., SpaCy, NLTK) for natural language processing and OpenCV for image processing.

[1551] Specific examples

[1552] As a concrete example, let's consider a news article reporting an approaching typhoon in Japan. After the news article is received and parsed by the server, the following process takes place:

[1553] Analysis of news articles: The server extracts information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[1554] Get user information: Verify that the user has an AR-enabled smartphone.

[1555] Content generation: To simulate the progression of a typhoon, 3D models and audio are generated to express the strength of wind and rain.

[1556] Content delivery: The generated AR content is delivered to the user's smartphone.

[1557] Display preparation: The user activates the smartphone camera and displays the 3D model and typhoon information superimposed on the real landscape.

[1558] Interaction: Users can visually understand the progress of the typhoon and evacuation routes through their smartphone screen.

[1559] Prompt Sentence Examples

[1560] "Extract key information about a news article (subject, location, events, characters, etc.)."

[1561] This allows users to more intuitively understand the content of news articles and link it to actual actions.

[1562] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1563] Step 1:

[1564] The server receives news articles from external news providers via API or RSS feed. The input of the received news article is the JSON data of the news article. Based on this input, the server starts parsing the text data.

[1565] Step 2:

[1566] The server uses natural language processing (NLP) algorithms on the received news articles to extract key information such as themes, locations, events, and characters. The input is the text data of the news articles. Specifically, it uses NLP algorithms (e.g., SpaCy, NLTK) to extract keywords and phrases from the articles and outputs the results in JSON format.

[1567] Step 3:

[1568] The server obtains device information from the user's profile information and selects the optimal experience format. The input is the user's profile information and device information. Based on the extracted news content and device information, the server selects one of the experience formats (VR, AR, or MR) and records the result.

[1569] Step 4:

[1570] The server generates experience content based on the analyzed news content. Specifically, it generates 3D models, scenarios, audio, video, etc. related to the news content. The input is the main information of the news and the selected experience format. The resulting 3D models, audio files, etc. are output.

[1571] Step 5:

[1572] The server streams the generated experiential content to the user's device. The input is the generated experiential content. The server compresses the content and delivers it with low latency. The output is the stream data sent to the user's device.

[1573] Step 6:

[1574] The user's device processes the received experience content and prepares it for display. This input is the experience content streamed from the server. The device decodes the received data and converts it into a displayable format. In the case of a VR headset, it sets up a 360-degree virtual environment. In the case of an AR device, it activates the camera and overlays the virtual content onto the real world.

[1575] Step 7:

[1576] The user experiences news content using the device. This input is the experience content ready for display. For example, the user uses a smartphone to display forecasted rainfall and wind speed information overlaid on the scenery around their home. The user operates the device and interacts with the displayed content.

[1577] Through these steps, users can intuitively understand the content of the news article and get a realistic experience.

[1578] 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.

[1579] This invention combines a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, with an emotion engine that recognizes the user's emotions, in order to make the content of news articles more realistic for users. The program for this system performs processing in the following steps:

[1580] Program processing

[1581] 1. Receiving and analyzing news articles

[1582] server

[1583] News articles are received from external news providers via API or RSS feeds, and are stored on the server.

[1584] It uses natural language processing (NLP) algorithms on incoming news articles to extract key information such as subject, location, events, and characters.

[1585] For example, if an article is about the progression of a typhoon, extract terms such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials."

[1586] 2. Obtaining user information and selecting the experience format

[1587] server

[1588] Retrieve the user's device information from the user's profile database. Profile data includes which device the user is using, the device type, and its capabilities.

[1589] The optimal experience format (VR, AR, MR) is selected based on the news content and the user's device information.

[1590] Example: If the user has a VR device, select experience content in VR format.

[1591] 3. Creating experience content

[1592] server

[1593] Based on the news content, content is generated for users to experience. The content includes 3D models, scenarios, audio, and video. Data is generated as a 3D model to represent the progress of the typhoon and the strength of the wind and rain.

[1594] If necessary, external resources (e.g., weather data or 3D model databases) are referenced to obtain additional data that matches the news content and are integrated into the generated content.

[1595] 4. Emotion engine integration

[1596] server

[1597] The emotion engine recognizes the user's emotional state by analyzing the user's facial expressions, voice, and behavioral patterns.

[1598] Example: If the user has a surprised expression, the emotion engine will recognize it.

[1599] It provides feedback on experience content based on the user's emotional state and dynamically adjusts the scenario as needed.

[1600] Example: If the user is feeling scared, adjust the scenario by making it a little less strenuous.

[1601] 5. Content Delivery

[1602] server

[1603] The resulting experience content is streamed to the user's device, appropriately compressed and configured for low latency delivery.

[1604] 6. Preparation for the experience

[1605] Terminal

[1606] It unpacks and processes the received content and prepares it for display. For VR headsets, it configures the 360-degree environment and enables eye tracking for the user. For AR devices, it activates the camera and overlays virtual content onto the real-world scene.

[1607] 7. Experience Delivery and User Interaction

[1608] User

[1609] Users can experience the news using a device. In the case of VR, users wear a VR headset and observe the progress of the typhoon in a virtual space. In the case of AR, users use their smartphone to view forecasted rainfall and wind speed information overlaid on the real world.

[1610] An emotion engine monitors the user's emotions in real time and provides feedback: for example, if the user expresses curiosity, additional relevant information will be displayed.

[1611] Specific examples

[1612] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[1613] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[1614] 2. The server checks the user's device information, and if the user has a VR device, generates content to be experienced in VR format.

[1615] 3. The server generates a 3D model and audio simulating the typhoon's progress and streams it to the user's VR headset.

[1616] 4. The device processes the received content and prepares it so that the user can wear the VR headset and experience the 3D model.

[1617] 5. Users put on a VR headset and observe the progress of the typhoon in a virtual space, checking safe evacuation routes, etc.

[1618] 6. The emotion engine monitors the user's emotions, and if the user feels surprised, for example, it reflects that information in the content and adjusts the scenario.

[1619] This allows users to experience the content of news articles in detail and realistically, while dynamically adjusting the experience based on the user's emotional state, allowing them to gain a deeper understanding of the news content and more easily recognize it as an issue close to home.

[1620] The processing flow will be explained below.

[1621] Step 1:

[1622] The server receives news articles from external news providers via API or RSS feeds, and stores them on the server.

[1623] Step 2:

[1624] The server applies natural language processing (NLP) algorithms to the received news articles to extract key information such as subject, location, events, and characters.

[1625] For example, if an article is about the progression of a typhoon, information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials" will be extracted.

[1626] Step 3:

[1627] The server retrieves the user's device information from the user's profile database.

[1628] Example: Checking if the user owns a VR device (e.g., a headset) or is using an AR-enabled smartphone.

[1629] Step 4:

[1630] The server selects the optimal experience format (VR, AR, MR) based on the news content and the user's device information.

[1631] Example: If the user has a VR device, select VR experience content.

[1632] Step 5:

[1633] The server generates content for users to experience based on the news content, including 3D models, scenarios, audio, and video.

[1634] Example: Generating 3D models and sounds to represent the progress of a typhoon and the strength of wind and rain.

[1635] Step 6:

[1636] The server references external resources (e.g., weather data or 3D model databases) to obtain additional data that matches the news content and integrates it into the generated content.

[1637] Example: Accurately simulate the movement of typhoons by referencing actual weather data.

[1638] Step 7:

[1639] The server streams the generated experience content to the user's device, appropriately compressed and configured for low latency delivery.

[1640] Example: Delivering typhoon simulation data in real time to a user's VR headset.

[1641] Step 8:

[1642] The device unpacks and processes the received content and prepares it for display. For VR headsets, this involves configuring the 360-degree environment and enabling the user's eye-tracking. For AR devices, this involves activating the camera and overlaying virtual content onto the real-world scene.

[1643] For example, a VR headset allows users to freely move their viewpoint, and an AR device displays the predicted path of a typhoon through the camera.

[1644] Step 9:

[1645] Users experience the news content using a device. In the case of VR, users wear a VR headset to observe the progress of the typhoon in a virtual space and check safe evacuation routes. In the case of AR, users can see forecasted rainfall and wind speed information overlaid on the real world.

[1646] Example: A user observes the direction of a typhoon in a VR space and checks evacuation routes.

[1647] Step 10:

[1648] The emotion engine recognizes the user's emotional state and obtains emotional data by analyzing the user's facial expressions, voice, and behavioral patterns.

[1649] For example, if a user shows signs of surprise or fear, that information is collected.

[1650] Step 11:

[1651] The server uses the emotion engine data to provide feedback to the experience content based on the user's emotional state, dynamically adjusting the scenario as needed.

[1652] Example: If the user is feeling scared, adjust the scenario to make it more nuanced and reassuring.

[1653] Information presentation: If the user shows interest, more detailed news information or additional content is provided.

[1654] This allows users to not only experience the content of news articles in detail and realistically, but also to get an optimal experience tailored to their emotional state. By deepening their understanding of the news content and providing a customized experience tailored to the recipient's emotions, this system makes it easier for them to recognize news information as something that concerns them personally.

[1655] Example 2

[1656] 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."

[1657] In modern society, news articles cover a wide range of topics, and it takes time and effort to gain a deep understanding of their content. However, simply reading news content as text can be difficult to grasp, especially when it comes to complex events. Furthermore, users may lose interest if the content of the news article does not feel familiar to them. In particular, when it comes to news that has a strong emotional impact, such as natural disasters or social incidents, it is difficult for users to actually experience the situation, making it difficult for them to truly appreciate the importance of the information. Therefore, a method is needed to provide news content that is more realistic and responds to the individual emotions of each user.

[1658] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1659] In this invention, the server includes means for receiving a news article and analyzing its content, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for delivering the generated experiential content to the user's device, means for using an emotion engine that analyzes the user's facial expressions, voice, and behavioral patterns to recognize the user's emotional state, means for dynamically providing feedback on the experiential content and adjusting the scenario based on the user's emotional state, and means for displaying the experiential content on the user's device and enabling interaction. This allows the user to experience the content of the news article more realistically and enables the provision of dynamic content according to emotions.

[1660] A "news article" is a document containing information distributed by a news organization or information provider.

[1661] "Means of analysis" refers to a system for analyzing the content of news articles and extracting key information and keywords.

[1662] "Virtual reality (VR)" is a technology that allows users to immerse themselves in a virtual environment using a dedicated device.

[1663] Augmented reality (AR) is a technology that displays virtual information overlaid on real-world scenery.

[1664] "Mixed reality (MR)" is a technology that combines virtual reality and augmented reality to integrate and display virtual information with real-world information.

[1665] "Experiential content" is digital content that transforms the content of a news article into a format that can be experienced in virtual reality, augmented reality, or mixed reality.

[1666] "User device information" is data related to the type and performance of the device used by the user.

[1667] An "emotion engine" is software that analyzes a user's facial expressions, voice, and behavioral patterns to recognize their emotional state.

[1668] "Feedback" is a response that adjusts the content or scenario of the experience content based on the user's emotional state.

[1669] A "scenario" is a set of events or situations that a user experiences within experiential content.

[1670] "Interaction" is the process by which a user interacts with experiential content through a device.

[1671] A "user device" is an electronic device that a user uses to view experiential content.

[1672] The "means of delivery" is the mechanism by which the generated experience content is sent to the user's device.

[1673] "Natural language processing (NLP)" is a technology for analyzing and understanding natural language such as text and speech.

[1674] This invention combines a system that generates and provides experiential news content using virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, with an emotion engine that recognizes the user's emotions, in order to make the content of news articles more realistic for users.

[1675] Receiving and analyzing news articles

[1676] server

[1677] The server receives news articles from external news providers via APIs or RSS feeds. This process uses the news delivery service's API or RSS feed reader software. The received news articles are stored in a database on the server. Natural language processing (NLP) algorithms are then used on the stored news articles to extract key information such as themes, locations, events, and characters. Specifically, natural language processing libraries and frameworks (e.g., NLTK, SpaCy) can be used.

[1678] Obtaining user information and selecting experience format

[1679] server

[1680] The server accesses the user's profile database to obtain the user's device information and personal settings. It identifies the type of device the user is using (VR device, AR device, smartphone, etc.) and its capabilities (resolution, memory, processing power, etc.). Based on the news content and the user's device information, the server selects the optimal experience format (VR, AR, MR) for the user.

[1681] Creating experience content

[1682] server

[1683] The server generates content for users to experience based on the news content. This content includes 3D models, scenarios, audio, and video. For example, a 3D model showing the progression of a typhoon is created using Autodesk Maya, and audio narration and sound effects are edited using Adobe Audition. Furthermore, if necessary, external resources (e.g., weather data, 3D model databases) are referenced to obtain and integrate additional data that matches the news content.

[1684] Emotion engine integration

[1685] server

[1686] The server recognizes the user's emotional state through an emotion engine. This is done by analyzing the user's facial expressions, voice, and behavioral patterns. Specifically, it analyzes facial and voice data using Microsoft Azure's Face API and Speech API. It then provides feedback on the experience content based on the user's emotional state and dynamically adjusts the scenario. For example, if the user is startled, it changes the music or visual effects to ease parts of the scenario and provides additional safety information.

[1687] Content Delivery

[1688] server

[1689] The server streams the generated experience content to the user's device using the H.265 video codec and the HTTP / 2.0 protocol for low latency. Data is compressed on the server side to maximize network bandwidth efficiency.

[1690] Preparing for the experience

[1691] Terminal

[1692] The device unpacks the received content and processes it for display. For example, for VR devices (e.g., Oculus Quest 2), it uses the Oculus SDK to set up the 360-degree environment and enable eye tracking. For AR devices (e.g., an ARKit-enabled iPhone), it activates the camera and uses ARKit to overlay virtual content on the real-world landscape.

[1693] Experience delivery and user interaction

[1694] User

[1695] Users experience news content using a VR headset or an AR smartphone app. For example, a user wearing an Oculus Quest 2 can observe the progress of a typhoon in real time in a 3D simulation. An interactive scenario is also provided in which users can choose different evacuation routes. An emotion engine monitors the user's emotions in real time. If the user expresses curiosity, for example, relevant additional information or interactive questions are displayed on the screen.

[1696] Specific examples

[1697] As a concrete example, let's consider a news article reporting that a typhoon is approaching Japan. The server receives this news article, analyzes it, and does the following:

[1698] 1. The server receives the news article and extracts the subject (typhoon), location (Japan), incident (heavy rain), and characters (citizens, safety officials).

[1699] 2. The server checks the user's device information and, if the user has an Oculus Quest 2, generates content to be experienced in VR format.

[1700] 3. The server generates a 3D model and audio simulating the progression of the typhoon and streams it to the user's VR headset. Specifically, the 3D model was created in Autodesk Maya and the audio was edited in Adobe Audition.

[1701] 4. The device processes the received content and sets up the VR environment using the Oculus SDK.

[1702] 5. Users wear a VR headset and experience the typhoon's progress in a realistic way. They are also provided with an interactive scenario where they can choose different evacuation routes.

[1703] 6. The emotion engine monitors the user's emotions and, if surprised, mitigates the scenario and provides additional safety information.

[1704] Example prompts for generative AI models

[1705] "Describe a system that generates VR experiences based on news articles, including a process for recognizing the user's emotions in real time and dynamically adjusting the experience accordingly."

[1706] This allows users to experience the content of news articles in detail and realistically, while dynamically adjusting the experience based on the user's emotional state, allowing them to gain a deeper understanding of the news content and more easily recognize it as an issue close to home.

[1707] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1708] Step 1: Receiving and parsing news articles

[1709] server

[1710] Input: News article data provided by external news providers (API or RSS feed).

[1711] What it does: The server periodically receives news articles via API or RSS feeds and stores them in a database.

[1712] Data processing: Analyzing text data from news articles using natural language processing (NLP) algorithms.

[1713] Output: Analyzed data including key information such as subjects, places, events, and characters (e.g., "typhoon," "Japan," "heavy rain," "citizens," "safety officials").

[1714] Step 2: Obtain user information and select experience format

[1715] server

[1716] Input: Device information (device type and capabilities) retrieved from the user's profile database.

[1717] What happens: The server accesses the user's profile database to see which device the user is using.

[1718] Data calculation: Executes logic to select the experience format based on the news content and user device information.

[1719] Output: The optimal experience format (VR, AR, MR) selected.

[1720] Step 3: Generate experience content

[1721] server

[1722] Input: Analysis data (key news information), user experience format (VR, AR, MR).

[1723] What it does: The server creates 3D models in Autodesk Maya and edits voice narration and sound effects in Adobe Audition, and optionally references external resources such as weather data and 3D model databases.

[1724] Data processing: Integrating key news information with external data to generate content for the user experience.

[1725] Output: Generated experience content (3D model, scenario, audio, video).

[1726] Step 4: Integrating the Emotion Engine

[1727] server

[1728] Input: User's facial expression data, voice data, and behavioral pattern data.

[1729] Specific operation: The server performs facial expression analysis and voice analysis using Microsoft Azure's Face API and Speech API.

[1730] Data computation: Running algorithms to recognize the user's emotional state in real time.

[1731] Output: The user's emotional state (e.g., surprise, fear, curiosity).

[1732] Step 5: Content feedback and scenario adjustments

[1733] server

[1734] Input: User experience content, user emotional state.

[1735] Specific behavior: Based on the user's emotional state, the server generates feedback on the experience content and dynamically adjusts the scenario, changing music and visual effects and providing additional safety information.

[1736] Data processing: Generate customized content based on the user's emotional state.

[1737] Output: Tailored experience content.

[1738] Step 6: Deliver your content

[1739] server

[1740] Input: Tailored experience content.

[1741] What it does: The server compresses the content using the H.265 video codec and streams it to the user's device using the HTTP / 2.0 protocol.

[1742] Output: The experience content that is streamed to the user's device.

[1743] Step 7: Prepare for the experience

[1744] Terminal

[1745] Input: The received experience content.

[1746] What it does: The device unpacks the received content and uses the Oculus SDK to set up a 360-degree VR environment, enable eye tracking, and, in the case of AR devices, uses ARKit to overlay virtual content onto the camera image.

[1747] Data operations: Converting content into a format that can be displayed on the device.

[1748] Output: The experience content ready to be displayed.

[1749] Step 8: Experience Delivery and User Interaction

[1750] User

[1751] Input: Optimized VR or AR content.

[1752] What happens: Users use a VR headset or AR device to experience the news in a realistic way.

[1753] Output: User experience and interaction data (user responses and choices).

[1754] These are the specific steps involved in generating and providing experiential content based on news articles. This process allows users to gain a deeper understanding of the news article and experience it in a way that is realistic and emotionally relevant.

[1755] (Application example 2)

[1756] 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."

[1757] Conventional news delivery systems have the problem that users have difficulty grasping the content of the news and have a shallow understanding of the information. In addition, they are unable to take into account users' emotional reactions to news articles, making it difficult to provide an optimal experience for each individual user.

[1758] The identification processing by identification processing unit 290 of data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving news articles and analyzing their contents, means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experiential content based on the analyzed news content, means for acquiring user device information and selecting an optimal experiential format, means for recognizing the user's emotions and providing feedback, means for delivering the generated experiential content to the user's device, and means for displaying the experiential content on the user's device and enabling interaction. This allows the user to experience the news content in real time and receive optimal feedback based on their emotional response.

[1759] "News Article" means a news article containing information distributed over the Internet.

[1760] "Analysis" is the process of breaking down the content of a news article and extracting information such as themes, characters, locations, and events.

[1761] "Virtual reality (VR)" is a technology that allows users to experience a three-dimensional virtual environment generated using computer technology through a dedicated device.

[1762] Augmented reality (AR) is a technology that displays computer-generated information overlaid on real-world scenery.

[1763] "Mixed reality (MR)" is a technology that provides an experience that combines virtual reality (VR) and augmented reality (AR).

[1764] "Experiential content" refers to content in the form of virtual reality (VR), augmented reality (AR), or mixed reality (MR) generated from the content of a news article.

[1765] "Device" means the hardware that enables a user to experience virtual reality (VR), augmented reality (AR), or mixed reality (MR).

[1766] "Emotion recognition" means judging the user's emotional state by analyzing the user's facial expressions, voice, behavioral patterns, etc.

[1767] "Feedback" refers to information or responses returned to the user that adjust the scenario based on the user's emotional state.

[1768] "Interaction" refers to the ability for users to interact with experiential content through a device.

[1769] The present invention relates to a system for providing news articles to users as virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content. The system includes means for receiving news articles, analyzing them, generating experience content, recognizing emotions, delivering them, and interacting with them.

[1770] Server Processing

[1771] The server first receives news articles from external news providers via APIs or RSS feeds. While we will not specify the names of specific news providers, we will assume that they are publicly available news distribution services.

[1772] Next, the received news article is analyzed using natural language processing (NLP) algorithms. An NLP engine like Spacy is used to extract key information such as subject, location, incident, and characters. For example, in an article about a typhoon's progress, information such as "typhoon," "Japan," "heavy rain," "citizens," and "safety officials" are extracted.

[1773] The system then retrieves device information from the user's profile information and selects the optimal experience format. The system retrieves the device type and capabilities of the user from the profile database. Based on this information, if the user has a VR device, the system selects the VR experience content.

[1774] In the generation of experience content, 3D models, scenarios, audio, and video are generated based on the news content. Additional data from simulation data and external resources (e.g., weather data and 3D model databases) is integrated to complete the content for the user to experience.

[1775] In addition, the emotion engine recognizes the user's emotional state in real time and provides feedback. The emotion engine analyzes facial expressions, voice, and behavioral patterns, and adjusts the scenario if the user feels surprised or scared.

[1776] The generated experience content is delivered to the user's device with low latency, using streaming technology to compress and appropriately transfer the content.

[1777] User's Device

[1778] The user's device receives, decompresses, and processes the delivered content: in the case of a VR headset, a 360-degree visual environment is created and eye tracking is enabled, while in the case of an AR device, virtual content is overlaid on the real-world landscape.

[1779] Users experience the news through a device. For example, by wearing a VR headset, they can observe the progress of a typhoon in a virtual space and check safe evacuation routes. An emotion engine monitors the user's emotions in real time and provides feedback. If the user expresses curiosity, additional relevant information will be displayed.

[1780] Examples of concrete examples and prompts

[1781] As an example, suppose you receive a news article about a large typhoon approaching Japan. The server analyzes the news article and extracts information such as "typhoon," "Japan," "heavy rain," and "Tokyo." It then verifies that the user owns a VR device and generates a 3D model of the typhoon simulation. The generative AI model uses the following prompt:

[1782] News article: A powerful typhoon is approaching Japan, with heavy rain expected in Tokyo.

[1783] Keywords: typhoon, Japan, heavy rain, Tokyo

[1784] Generated VR content: 3D model simulating the typhoon's progress, rainfall, wind speed, and safety advice

[1785] This allows users to experience the progression of the typhoon in real time based on actual news articles and receive optimal feedback based on their emotional response.

[1786] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1787] Step 1: Receiving and parsing news articles

[1788] The server receives news articles from external news providers using APIs or RSS feeds. The received news articles are stored on the server. Natural language processing (NLP) algorithms (e.g., Spacy) are then used to analyze the news content and extract key information such as themes, locations, events, and characters. The input is the news article, and the output is the extracted information (e.g., "typhoon," "Japan," "heavy rain," "citizens," "safety officials").

[1789] Step 2: Obtain user information and select experience format

[1790] The server retrieves the user's device information from the user profile database. The profile data includes the device the user is using, as well as the device's type and performance. The input is the user ID, and the output is the device information. The server then selects the optimal experience format (VR, AR, or MR) based on the news content and the user's device information. For example, if the user owns a VR device, experience content in VR format is selected.

[1791] Step 3: Generate experience content

[1792] The server generates 3D models, scenarios, audio, and video based on the news content. For example, it generates a 3D model using data to represent the progress of a typhoon and the strength of wind and rain. If necessary, it obtains additional data from external resources (e.g., weather data or a 3D model database) and integrates it into the generated content. The input is the analyzed news information and the user's device information, and the output is the generated VR content.

[1793] Step 4: Integrating the Emotion Engine

[1794] The server uses an emotion engine to recognize the user's emotional state in real time. This is done by analyzing the user's facial expressions, voice, and behavioral patterns. For example, if the user shows a surprised expression, the emotion engine recognizes this. The input is the user's behavioral data, and the output is the user's emotional state. Based on the user's emotional state, the server provides feedback on the experience content and dynamically adjusts the scenario.

[1795] Step 5: Deliver your content

[1796] The server streams the generated experience content to the user's device. The data is appropriately compressed and configured for low latency delivery. The input is the generated VR content, and the output is the content delivered to the user's device.

[1797] Step 6: Prepare for the experience

[1798] The device unpacks and processes the received content and prepares it for display. In the case of a VR headset, this involves configuring the 360-degree environment and enabling the user's eye-tracking. In the case of an AR device, it activates the camera and overlays virtual content onto the real-world scene. The input is the streamed VR content, and the output is the content ready to be displayed.

[1799] Step 7: Experience Delivery and User Interaction

[1800] Users use devices to experience news content. In the case of VR, users wear a VR headset to observe the progress of the typhoon in a virtual space and check safe evacuation routes. In the case of AR, users use their smartphones to check predicted rainfall and wind speed information overlaid on the real world. An emotion engine monitors the user's emotions in real time and provides feedback. The input is the displayed content and the user's real-time behavioral data, and the output is the user experience and feedback.

[1801] 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.

[1802] 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.

[1803] 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.

[1804] 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.

[1805] 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.

[1806] 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.

[1807] 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).

[1808] 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.

[1809] 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."

[1810] 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.

[1811] 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).

[1812] 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.

[1813] 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.

[1814] 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.

[1815] 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.

[1816] 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.

[1817] 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.

[1818] 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.

[1819] 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.

[1820] 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.

[1821] 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.

[1822] The following is further disclosed regarding the above embodiment.

[1823] (Claim 1)

[1824] means for receiving news articles and analyzing their content;

[1825] A means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content based on the analyzed news content;

[1826] A means for acquiring user device information and selecting the optimal experience format;

[1827] means for delivering the generated experiential content to a user's device;

[1828] A system including means for displaying and enabling interaction with experiential content on a user's device.

[1829] (Claim 2)

[1830] 10. The system of claim 1, wherein natural language processing is used to extract information about topics, places, events, and characters contained in news articles.

[1831] (Claim 3)

[1832] 2. The system according to claim 1, wherein device information is obtained from profile information registered by the user, and the experience format is selected based on the device information.

[1833] (Claim 4)

[1834] 10. The system of claim 1, wherein the generated experience content includes a 3D model, a scenario, audio, and video.

[1835] (Claim 5)

[1836] 10. The system of claim 1, wherein the experiential content is compressed and delivered with low latency.

[1837] (Claim 6)

[1838] 10. The system of claim 1, wherein the system displays virtual content superimposed on a real-world scene on a user's device.

[1839] (Claim 7)

[1840] 10. The system of claim 1, wherein the system allows a user to obtain additional information and interact while the experiential content is being displayed.

[1841] "Example 1"

[1842] (Claim 1)

[1843] means for receiving news articles and analyzing their content;

[1844] A means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content based on the analyzed news content;

[1845] A means for obtaining user profile information and selecting the most suitable experience format;

[1846] means for delivering the generated experiential content to a user's device with low latency;

[1847] a means for displaying and enabling interaction with the experiential content on the user's device;

[1848] a means of integrating external resources based on news articles;

[1849] A system including:

[1850] (Claim 2)

[1851] 10. The system of claim 1, wherein natural language processing is used to extract information about topics, places, events, and characters contained in news articles.

[1852] (Claim 3)

[1853] 2. The system according to claim 1, wherein device information is obtained from profile information registered by the user, and the experience format is selected based on the device information.

[1854] "Application Example 1"

[1855] (Claim 1)

[1856] means for receiving news articles and analyzing their content;

[1857] A means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content based on the analyzed news content;

[1858] A means for acquiring user device information and selecting the optimal experience format;

[1859] means for delivering the generated experiential content to a user's device;

[1860] a means for acquiring camera footage and overlaying augmented reality content based on analyzed news content to display the footage;

[1861] A system including means for displaying and enabling interaction with experiential content on a user's device.

[1862] (Claim 2)

[1863] 10. The system of claim 1, wherein natural language processing is used to extract information about topics, places, events, and characters contained in news articles.

[1864] (Claim 3)

[1865] 2. The system according to claim 1, wherein device information is obtained from profile information registered by the user, and the experience format is selected based on the device information.

[1866] "Example 2: Combining Emotion Engines"

[1867] (Claim 1)

[1868] means for receiving news articles and analyzing their content;

[1869] A means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content based on the analyzed news content;

[1870] A means for acquiring user device information and selecting the optimal experience format;

[1871] means for delivering the generated experiential content to a user's device;

[1872] a means for using an emotion engine that analyzes the user's facial expressions, voice, and behavioral patterns to recognize the user's emotional state;

[1873] means for dynamically providing feedback of experiential content and adjusting the scenario based on the user's emotional state;

[1874] A system including means for displaying and enabling interaction with experiential content on a user's device.

[1875] (Claim 2)

[1876] 10. The system of claim 1, wherein information contained in news articles is extracted using natural language processing.

[1877] (Claim 3)

[1878] 2. The system according to claim 1, wherein device information is obtained from profile information registered by the user, and the experience format is selected based on the device information.

[1879] "Application example 2 when combining emotion engines"

[1880] (Claim...

Claims

1. means for receiving news articles and analyzing their content; A means for generating virtual reality (VR), augmented reality (AR), or mixed reality (MR) experience content based on the analyzed news content; A means for acquiring user device information and selecting the optimal experience format; means for delivering the generated experiential content to a user's device; A system including means for displaying and enabling interaction with experiential content on a user's device.

2. 10. The system of claim 1, wherein the information about topics, places, events, and characters contained in news articles is extracted using natural language processing.

3. 2. The system according to claim 1, wherein device information is acquired from profile information registered by the user, and the experience format is selected based on the device information.

4. The system of claim 1 , wherein the generated experience content includes a 3D model, a scenario, audio, and video.

5. 10. The system of claim 1, wherein the experiential content is compressed and delivered with low latency.

6. The system of claim 1 , wherein the system displays virtual content superimposed on a real-world scene on a user's device.

7. The system of claim 1 , wherein the system allows a user to obtain additional information and interact while the experiential content is being displayed.

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