system

Abstract

We provide the system. [Solution] A means for collecting data on user desires, attributes, preferences, and operational behavior, A means of analyzing the elements of current trends, A means for generating a customized film plan based on the above user data and trending elements, Based on the generated film project, means for producing a film, A means of making the generated movie viewable by users and followers, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Movie production requires many resources such as budget, connections, talent, know-how, equipment, etc., and it is difficult for many individual users to create their own movies. To solve this problem, there is a need to provide a platform that can generate original movies optimized according to individual preferences and attributes using AI technology and can easily view and share them. In addition, it is necessary to enable customization and additional input according to user requests for the generated movies.

Means for Solving the Problems

[0005] The present invention includes means for collecting data on user preferences, attributes, tastes, and operational behavior, and means for analyzing current trends. It also includes means for generating a customized film plan based on the user data and trends. Furthermore, the invention provides a system that includes means for generating a film based on the generated film plan, and means for making the generated film viewable by users and followers.

[0006] Furthermore, this system includes means for users to request movie content and direction, and also includes means for regenerating movies based on those requests. In addition, by including means for sharing the viewing history and revenue of the generated movies between the user and the operator, it makes it easy for individual users to create, view, and share their own original movies.

[0007] "User data" refers to information about a user's wishes, attributes, preferences, and operational behavior.

[0008] "Trendy elements" refer to elements such as themes, genres, and characters that are currently popular in society.

[0009] "Film project" refers to a plan for a film's setting, storyline, main characters, etc., created based on user data and trending elements.

[0010] "Generative AI" refers to artificial intelligence that creates films using live-action, animation, and other methods based on film concepts.

[0011] A "viewing link" refers to an internet link that allows users to access and watch a generated movie.

[0012] "Followers" refer to other users who can view and share content created by the user.

[0013] "Revenue sharing" refers to a function that divides revenue between users and site operators based on the number of views and advertising revenue generated for the movies produced.

[0014] "Prompt billing" refers to a system where users pay a fee when they request changes to the content or presentation of a movie.

[0015] A "database" refers to a system for storing collected user data, trending topics, generated film projects, and so on. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0019] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a RAM (Random Access Memory) with a reference number is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a storage with a reference number is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention provides a system that creates original films incorporating popular trends based on user preferences, attributes, tastes, app operation behavior, and survey results, and allows users and their followers to watch these films. The program processing of this system is described below in natural language.

[0038] Basic System Configuration

[0039] User data entry

[0040] 1. Terminal: When a user launches the application, an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[0041] 2. User: Enter the specified information.

[0042] Data collection and storage

[0043] 3. Device: Continuously records user activity logs and collects them as application operation behavior. For example, it records which movies the user watched, which trailers they viewed, etc.

[0044] 4. Server: Stores collected user data in a database.

[0045] Analysis of popular trends

[0046] 5. Server: Collects the latest movie trend data from the internet. This includes popular movies, notable actors, trending themes, etc.

[0047] 6. Server: Analyzes collected trend data and identifies trending elements.

[0048] Creating a film project

[0049] 7. Server: An analytical AI combines user data with current trends to generate original movie concepts. These concepts include genre, story setting, and main characters.

[0050] 8. Server: Saves the generated film proposals to the database and sends them to the generation AI.

[0051] The creation of a film

[0052] 9. Generating AI: Automatically generates detailed scenarios based on film proposals. This includes scriptwriting, casting, location scouting, and music selection.

[0053] 10. Generative AI: Creates films in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[0054] Movie preservation and distribution

[0055] 11. Server: Stores the generated movie data and prepares it for streaming.

[0056] 12. Server: Generates and displays a viewing link on the user's My Page.

[0057] Watching and sharing movies

[0058] 13. Device: User A can click the provided viewing link and watch the movie.

[0059] 14. Terminal: Displays options for User A to share a movie with their followers.

[0060] 15. User: Share the viewing link with your followers.

[0061] Profit calculation and distribution

[0062] 16. Server: Records the viewing history and advertising revenue of generated movies.

[0063] 17. Server: Revenue is distributed 1:1 between User A and the site operator and reflected in the user's account.

[0064] Movie customization

[0065] 18. Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[0066] 19. User: Enter a movie change request and pay the corresponding fee.

[0067] 20. Server: Notifies the generation AI of the request content and regenerates the movie script and direction.

[0068] 21. Server: Upload the regenerated movie to the streaming server so that users and followers can watch it again.

[0069] Specific example

[0070] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates a movie concept that includes popular heroes and magical elements. The generating AI creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. If user A watches the movie and wants to add new scenes, they can submit a change request via prompt payment and enjoy the regenerated movie.

[0071] The above describes the embodiments for carrying out the present invention. The present invention enables users to easily create, view, and share original movies optimized for themselves.

[0072] The following describes the processing flow.

[0073] Step 1:

[0074] Device: After launching the app, an input form will be displayed regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[0075] Step 2:

[0076] User: Enter the specified information and press the submit button.

[0077] Step 3:

[0078] Terminal: Sends the entered user information to the server.

[0079] Step 4:

[0080] Server: Stores the received user information in the database.

[0081] Step 5:

[0082] Device: Records user actions within the app (which movies were watched, which trailers were viewed) and collects this data as app operation behavior.

[0083] Step 6:

[0084] Server: Receives application operation behavior and saves it to the database.

[0085] Step 7:

[0086] Terminal: Displays a survey to the user and collects responses.

[0087] Step 8:

[0088] User: Answers the survey and presses the submit button.

[0089] Step 9:

[0090] Terminal: Sends survey responses to the server.

[0091] Step 10:

[0092] Server: Saves survey results to the database.

[0093] Step 11:

[0094] Server: Automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet.

[0095] Step 12:

[0096] Server: Analyzes collected trend data and identifies trending elements.

[0097] Step 13:

[0098] Server: An analytical AI combines user data with current trends to generate original movie concepts.

[0099] Step 14:

[0100] Server: Saves the generated film proposals to a database and sends them to the generation AI.

[0101] Step 15:

[0102] Generating AI: Automatically generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection.

[0103] Step 16:

[0104] Generative AI: Generates movies in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[0105] Step 17:

[0106] Server: Uploads the generated movie data to the streaming server.

[0107] Step 18:

[0108] Server: Generates and displays a viewing link on the user's My Page.

[0109] Step 19:

[0110] Device: User A clicks on the provided viewing link and watches the movie.

[0111] Step 20:

[0112] Terminal: Displays options for User A to share a movie with their followers.

[0113] Step 21:

[0114] User: Share the viewing link with your followers.

[0115] Step 22:

[0116] Server: Records the viewing history of shared movies and collects revenue data.

[0117] Step 23:

[0118] Server: Revenue is distributed 1:1 between User A and the site operator and reflected in the user's account.

[0119] Step 24:

[0120] Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[0121] Step 25:

[0122] User: Enter a movie change request and pay the corresponding fee.

[0123] Step 26:

[0124] Terminal: Sends a request to the server.

[0125] Step 27:

[0126] Server: Notifies the generating AI of the request details.

[0127] Step 28:

[0128] Generative AI: Updates the movie by generating additional scenes and different endings.

[0129] Step 29:

[0130] Server: Uploads the updated movie to the streaming server and prepares it for distribution again.

[0131] Step 30:

[0132] Terminal: Allows User A and their followers to watch the regenerated movie.

[0133] (Example 1)

[0134] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0135] In the current film production process, it is difficult to create original films that reflect the individual preferences and attributes of users, making it challenging for films to fully meet user expectations. Furthermore, customizing the content and direction of films, as well as efficiently distributing revenue from the resulting films, is also difficult. Therefore, there is a need for a system that efficiently and easily creates, customizes, and distributes revenue from original films that reflect user wishes and preferences.

[0136] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0137] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for recording user operation logs; means for storing the collected user data in a database; means for collecting the latest movie trend data from the internet; means for analyzing the collected trend data to identify trend elements; means for generating customized movie plans based on user data and trend elements; means for storing the generated movie plans in a database and transmitting them to a generating AI model; means for generating detailed scenarios based on the generating AI model; means for creating movies in formats such as live-action, animation, special effects, and CG using the generating AI model and saving them as video data; means for saving the generated movie data and preparing it for streaming distribution; and means for generating and displaying viewing links on the user's My Page. This makes it possible to create, customize, and distribute revenue from movies that reflect the individual preferences and wishes of the user.

[0138] "User preferences, attributes, and tastes" refer to the specific demands and preferences that users have regarding movies, including genre, theme, and favorite actors.

[0139] "Operational behavior" refers to the actions and patterns a user exhibits when interacting with an application, including operational information such as which movies were watched or which trailers were viewed.

[0140] A "database" is a system for efficiently storing, managing, searching, and using collected user data and trend data.

[0141] "Methods for collecting the latest movie trend data from the internet" refers to the process of automatically obtaining the latest movie information from online resources such as movie review sites and social media.

[0142] "Trend elements" refer to characteristics such as themes, actors, and genres of movies that are generally popular with the public today.

[0143] A "generative AI model" is a program and algorithm that uses artificial intelligence to automatically generate movie plans and scripts.

[0144] A "detailed scenario" refers to a plan that includes specific elements such as the film's script, casting, filming locations, and music.

[0145] "Live-action, animation, special effects, and CG" are different formats and types of techniques used to produce films, each possessing its own unique visual expression.

[0146] "Preparing for streaming distribution" refers to the process of converting file formats and uploading to servers in order to make the generated movie viewable online.

[0147] A "viewing link" refers to a URL or access method that allows a user to watch a generated movie online.

[0148] A "customized film project" refers to a basic plan or proposal for a film that is specially designed to reflect user preferences and current trends.

[0149] "Regeneration" refers to the process of regenerating a movie that has already been created, based on a new request from the user.

[0150] This invention is a system that automatically generates original movies based on user preferences, attributes, tastes, app operation behavior, and current trends. A specific embodiment of this system is described below.

[0151] When a user launches the application, the device displays an input form for their preferences, attributes, and tastes. This includes their name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The device collects this information as the user enters it.

[0152] The collected data is recorded by the terminal along with the user's operation log. This includes information such as which movies the user watched and which trailers they viewed. This data is then stored in a database by the server. Relational databases such as MySQL or PostgreSQL are used for this database.

[0153] The server collects the latest movie trend data from the internet. This data is obtained from movie review sites and social media. The collected data is analyzed by analytical algorithms on the server to identify trending elements. This utilizes techniques such as natural language processing and data mining.

[0154] Next, the server uses analytical AI to combine user data and trending elements to generate a customized movie proposal. This proposal includes genre, story setting, main characters, and other elements. The generated movie proposal is stored in a database and sent to the generating AI model.

[0155] The generative AI model automatically generates a detailed scenario based on the received film proposal. This includes scriptwriting, casting, location scouting, and music selection. The AI ​​model then uses the model to create the film in various formats, such as live-action, animation, special effects, or CGI. The film, saved as video data, is then prepared for streaming distribution by a server.

[0156] Users can watch movies by accessing their personal page and clicking on a viewing link. The viewing page also has a sharing option, allowing users to share movies with their followers. Viewing history and advertising revenue for shared movies are recorded by the server, and these revenues are shared between the user and the site operator.

[0157] Additionally, users can request changes to the movie's content and direction using a prompt billing feature. Once a user enters a change request and pays the corresponding fee, the server notifies the generation AI model of the request, and the movie's script and direction are regenerated. The regenerated movie is uploaded to the streaming server and becomes available for viewing again by the user and their followers.

[0158] Specific example

[0159] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates a movie concept that includes popular heroes and magical elements. The generating AI model creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. If user A watches the movie and wants to add new scenes, they can submit a change request via prompt billing and enjoy the regenerated movie.

[0160] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0161] Step 1:

[0162] Launching the app and entering user information

[0163] Terminal: When a user launches the application, a form is displayed for them to enter their preferences, attributes, and tastes.

[0164] Input: User's name, age, gender, movie preferences (genre, theme, favorite actor, etc.).

[0165] Output: User-entered data on preferences, attributes, and tastes.

[0166] Specific operation: The terminal stores data in each field according to the user's input.

[0167] Step 2:

[0168] Recording user behavior

[0169] Terminal: Continuously records logs of user actions within the application.

[0170] Input: User actions (movies watched, trailers viewed, etc.).

[0171] Output: Operation log data.

[0172] Specific operation: The device saves user actions such as taps, clicks, and scrolls to a log file.

[0173] Step 3:

[0174] Data storage

[0175] Server: Stores collected user data and operation logs in a database.

[0176] Input: Data on preferences, attributes, and actions.

[0177] Output: User information and operation logs stored in the database.

[0178] Specific operation: The server issues an INSERT statement to the database and persists the data.

[0179] Step 4:

[0180] Collection and analysis of trending elements

[0181] Server: Collects and analyzes the latest movie trend data from the internet.

[0182] Input: Trend data obtained from movie review sites and social media.

[0183] Output: Analyzed trend elements.

[0184] Specific operation: A crawler periodically collects data from websites, and an analysis algorithm on the server processes that data using natural language processing.

[0185] Step 5:

[0186] Creating a film project

[0187] Server: Combines user data and trending elements to generate customized movie concepts.

[0188] Input: User data, operation logs, analyzed trending factors.

[0189] Output: Film project data (genre, story setting, main characters, etc.).

[0190] Specific operation: An analytical AI on the server creates a movie plot based on the user's preferences and the latest trends.

[0191] Step 6:

[0192] Scenario and film generation

[0193] Generative AI Model: Automatically generates detailed scenarios based on generated film plans and creates films.

[0194] Input: Film project data.

[0195] Output: Video data of the completed film.

[0196] Specific operation: The generation AI model automatically handles scriptwriting, casting, location selection, music selection, etc., and generates the film in CG, animation, and live-action formats.

[0197] Step 7:

[0198] Saving movie data and preparing for streaming

[0199] Server: Stores the generated movie data and prepares it for streaming.

[0200] Input: Video data of the completed film.

[0201] Output: Movie data prepared for streaming.

[0202] Specific operation: Convert movie data to the appropriate format and upload it to the streaming server.

[0203] Step 8:

[0204] Generating and displaying viewing links

[0205] Server: Generates and displays a viewing link on the user's My Page.

[0206] Input: Movie data prepared for streaming, user account information.

[0207] Output: The viewing link displayed on your My Page.

[0208] Specific operation: The server generates a unique viewing link for the user and displays it on the user's My Page.

[0209] Step 9:

[0210] Watch and share movies

[0211] Device: Users can watch generated movies and share them with their followers if desired.

[0212] Input: The viewing link displayed on your My Page.

[0213] Output: Viewing history, sharing information.

[0214] Specific actions: The user clicks the link to play the movie and uses the sharing option to send the link to their followers.

[0215] Step 10:

[0216] Profit calculation and distribution

[0217] Server: Records viewing history and advertising revenue, and distributes it to users and operators.

[0218] Input: Viewing history data, advertising revenue data.

[0219] Output: Distributed revenue information.

[0220] Specific operation: The server uses revenue data to reflect the revenue in the user and operator accounts.

[0221] Step 11:

[0222] Movie customization

[0223] Terminal: Accepts requests for changes to movie content and presentation via prompt payment.

[0224] Input: User request details, billing information.

[0225] Output: Regenerated movie data based on the request.

[0226] Specific operation: The user fills out a change request and submits billing information. The request is sent to the server, and the generation AI model generates the movie again.

[0227] (Application Example 1)

[0228] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0229] Traditional content distribution services struggle to provide original films tailored to individual user preferences, and it's also difficult for users to request and modify the content or direction of films themselves. Furthermore, easily creating and making available original films compatible with virtual reality viewing environments is another challenge.

[0230] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0231] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for analyzing current trends; means for generating customized movie plans based on the user data and trends; means for generating a movie based on the generated movie plan; means for making the generated movie viewable by the user and their followers; and means for making the generated movie viewable in a virtual reality environment. This makes it possible to easily generate original movies optimized for the user's individual preferences and enjoy them in a virtual reality environment.

[0232] "User data" refers to information about a user's wishes, attributes, preferences, and operational behavior.

[0233] "Trend elements" refer to data on the latest trends collected from the internet and other sources.

[0234] A "customized film project" is a film project proposal that is individually designed based on user data and trending elements.

[0235] "Means of creating films" refers to the technology of creating visuals in various formats such as live-action, animation, special effects, and computer graphics based on a customized film project.

[0236] A "virtual reality environment" is a virtual visual world that users can experience using VR head-mounted displays or other VR devices.

[0237] "Available for viewing" means that the generated film is provided to users and followers in a form that is accessible online.

[0238] "Request details" refer to specific changes that the user would like to see made to the content or direction of the film.

[0239] "Method of regeneration" refers to a technology that regenerates already created movies based on user requests.

[0240] The "means of revenue distribution" refer to a system that distributes the revenue generated between users and operators based on the viewing history of the movies that have been produced.

[0241] System Overview

[0242] This invention is a system that collects user wishes, attributes, preferences, and operational behaviors, combines them with current trends to generate customized movies, and makes them viewable in a virtual reality environment.

[0243] Hardware and software to be used

[0244] Hardware: Smartphones, VR head-mounted displays (e.g., Oculus Quest 2)

[0245] Software: Flask (web framework), Python (programming language), generative AI model

[0246] Data collection and storage

[0247] 1. Device (smartphone or VR device):

[0248] When a user launches the application, an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor).

[0249] 2. User:

[0250] Enter the specified information.

[0251] 3. Server:

[0252] The system continuously records user activity logs and collects them as application operation behavior. For example, it records which movies a user watched, which trailers they viewed, and so on.

[0253] Analysis of popular trends

[0254] 4. Server:

[0255] We collect the latest movie trend data from the internet. This includes popular movies, notable actors, and trending themes.

[0256] 5. Server:

[0257] We analyze collected trend data to identify trending elements.

[0258] Film planning and creation

[0259] 6. Server:

[0260] An analytical AI combines user data with current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[0261] 7. Server:

[0262] Using a generative AI model, detailed scenarios are automatically generated based on the plan.

[0263] 8. Server:

[0264] We create films in various formats such as live-action, animation, special effects, and CGI, and save them as video data.

[0265] Watch and customize movies

[0266] 9. Server:

[0267] The generated movie data is saved and prepared for streaming distribution.

[0268] 10. Terminal:

[0269] Users can watch the movie by clicking on the provided viewing link.

[0270] 11. Server:

[0271] It provides an interface for users to request specific content and direction for the film.

[0272] 12. Generative AI Models:

[0273] Based on the requested content, we will regenerate the movie's script and direction.

[0274] 13. Server:

[0275] The regenerated movie data is uploaded to a streaming server, allowing users and followers to watch it again.

[0276] Specific example

[0277] For example, if the user prefers "Actions" and "Magic," enter the following prompt:

[0278] "User ID: user123"

[0279] Genre: Action

[0280] "Theme: Magic"

[0281] Based on this prompt, the server generates movie recommendations tailored to the user's preferences and creates movie data using a generation AI model. The generated movies are provided to the user via a link, and the user can watch them using a smartphone or VR head-mounted display.

[0282] In this way, the system can easily generate original movies optimized for the individual preferences of users and allow them to be enjoyed in a viewing and virtual reality environment. This provides a personalized experience that was difficult to achieve with conventional content delivery services.

[0283] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0284] Step 1:

[0285] Terminal:

[0286] The user launches the application and displays an input form for information regarding their wishes, attributes, and preferences. This includes name, age, gender, movie preferences (genre, theme, favorite actors).

[0287] )]]Input: Name, age, gender, movie preferences

[0288] Output: User input data

[0289] Step 2:

[0290] User:

[0291] The user enters the desired information and submits the input form. <000921>

[0292] Input: Input form

[0293] Output: User data (name, age, gender, movie preferences)

[0294] Step 3:

[0295] Server:

[0296] The server constantly records the user's operation logs (which movies were watched, which trailers were viewed) and saves them in the database as application operation behavior.

[0297] Input: User data and operation logs

[0298] Output: Operation history data

[0299] Step 4:

[0300] Server:

[0301] Collect the latest movie trend data from the Internet (popular movies, notable actors, trendy themes, etc.).

[0302] Input: Trend information on the Internet

[0303] Output: Popularity data

[0304] Step 5:

[0305] Server:

[0306] Analyze the collected popularity data to identify popularity factors.

[0307] Input: Popularity data

[0308] Output: Identified popularity factors

[0309] Step 6:

[0310] Server:

[0311] The analysis AI combines user data and popularity factors to generate original movie concepts (genre, story setting, main characters).

[0312] Input: User data, popularity factors

[0313] Output: Movie concept data

[0314] Step 7:

[0315] Server:

[0316] The generative AI model automatically generates detailed scenarios based on film project data.

[0317] Input: Film project data

[0318] Output: Detailed Scenario

[0319] Step 8:

[0320] Generative AI models:

[0321] We create films in various formats such as live-action, animation, special effects, and CGI, and save them as video data.

[0322] Input: Detailed Scenario

[0323] Output: Video data

[0324] Step 9:

[0325] server:

[0326] The generated movie data is saved, and a link for streaming is generated.

[0327] Input: Video data

[0328] Output: Viewing link

[0329] Step 10:

[0330] Terminal:

[0331] Users click on the provided viewing link and watch the movie using their smartphone or VR head-mounted display.

[0332] Input: Viewing link

[0333] Output: Movie playback

[0334] Step 11:

[0335] server:

[0336] It provides an interface for users to request specific content and direction for the film.

[0337] Input: User Request

[0338] Output: Request details

[0339] Step 12:

[0340] Generative AI models:

[0341] Based on user requests, the system regenerates movie scripts and direction.

[0342] Input: Request details

[0343] Output: Regenerated movie script

[0344] Step 13:

[0345] server:

[0346] The regenerated movie data is uploaded to a streaming server, allowing users and followers to watch it again.

[0347] Input: Regenerated movie script, video data

[0348] Output: Regenerated movie viewing link

[0349] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0350] This invention is a system that creates original films incorporating popular trends based on users' wishes, attributes, preferences, app operation behavior, survey results, and emotions, and allows users and their followers to watch these films. Furthermore, it regenerates films according to user requests regarding content and direction, and distributes the revenue. The program processing of this system is described below in natural language.

[0351] Basic System Configuration

[0352] User data entry

[0353] 1. Terminal: When the application is launched, an input form will be displayed regarding the user's wishes, attributes, and preferences. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[0354] 2. User: Enter the specified information and press the submit button.

[0355] Data collection and storage

[0356] 3. Device: Collects data including user operation logs and app operation behavior. This includes things like which movies the user watched and which trailers they viewed.

[0357] 4. Server: Stores collected user data in a database.

[0358] emotion recognition

[0359] 5. Device: Captures the user's facial expressions and voice through the camera and microphone and sends them to the emotion engine.

[0360] 6. Emotion Engine: Analyzes the user's facial expressions and voice to generate emotion data.

[0361] 7. Server: Stores the emotion data sent from the emotion engine in the database.

[0362] Analysis of popular trends

[0363] 8. Server: Automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet.

[0364] 9. Server: Analyzes collected trend data and identifies trending elements.

[0365] Creating a film project

[0366] 10. Server: An analytical AI combines user data, sentiment data, and current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[0367] 11. Server: Saves the generated film proposals to the database and sends them to the generation AI.

[0368] The creation of a film

[0369] 12. Generating AI: Automatically generates a detailed scenario based on the content of the film project. This includes scriptwriting, casting, location selection, and music selection.

[0370] 13. Generative AI: Generates films in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[0371] Preservation and distribution of movies

[0372] 14. Server: Stores the generated movie data and prepares it for streaming.

[0373] 15. Server: Generates and displays a viewing link on the user's My Page.

[0374] Watching and sharing movies

[0375] 16. Device: The user clicks the provided viewing link to watch the movie.

[0376] 17. Device: Displays options for users to share movies with their followers.

[0377] 18. User: Share the viewing link with your followers.

[0378] Profit calculation and distribution

[0379] 19. Server: Records the viewing history and advertising revenue of generated movies.

[0380] 20. Server: Distributes revenue 1:1 between users and site operators and reflects it in the user's account.

[0381] Movie customization

[0382] 21. Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[0383] 22. User: Enter a movie change request and pay the corresponding fee.

[0384] 23. Terminal: Sends the request to the server.

[0385] 24. Server: Notifies the generating AI of the request details.

[0386] 25. Generating AI: Updates the movie by generating additional scenes and different endings.

[0387] 26. Server: Upload the updated movie to the streaming server and prepare it for distribution again.

[0388] 27. Device: Allow users and followers to watch the regenerated movie.

[0389] Specific example

[0390] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates movie proposals that include popular hero and magical elements. The generating AI creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. Furthermore, an emotion engine analyzes the user's emotions while they are watching, and this data is used when generating future movie proposals, resulting in a more personalized movie.

[0391] This invention enables users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie-watching experience.

[0392] The following describes the processing flow.

[0393] Step 1:

[0394] Terminal: When the application is launched, it displays an input form regarding the user's wishes, attributes, and preferences. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[0395] Step 2:

[0396] User: Enter the specified information and press the submit button.

[0397] Step 3:

[0398] Terminal: Sends the entered user information to the server.

[0399] Step 4:

[0400] Server: Stores the received user information in the database.

[0401] Step 5:

[0402] Device: Records user activity logs and app operation behavior, collecting information such as which movies were watched and which trailers were viewed.

[0403] Step 6:

[0404] Server: Stores collected application operation behaviors in a database.

[0405] Step 7:

[0406] Terminal: Displays a survey to the user and collects responses.

[0407] Step 8:

[0408] User: Answers the survey and presses the submit button.

[0409] Step 9:

[0410] Terminal: Sends survey responses to the server.

[0411] Step 10:

[0412] Server: Saves survey results to the database.

[0413] Step 11:

[0414] Device: Captures the user's facial expressions and voice through the camera and microphone, and sends them to the emotion engine.

[0415] Step 12:

[0416] Emotion Engine: Analyzes the user's facial expressions and voice to generate emotion data.

[0417] Step 13:

[0418] Server: Stores emotion data sent from the emotion engine in the database.

[0419] Step 14:

[0420] Server: Automatically collects the latest movie trend data from the internet. This includes popular movies, featured actors, trending themes, and more.

[0421] Step 15:

[0422] Server: Analyzes collected trend data and identifies trending elements.

[0423] Step 16:

[0424] Server: An analytical AI combines user data, sentiment data, and current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[0425] Step 17:

[0426] Server: Saves the generated film proposals to the database and sends them to the generation AI.

[0427] Step 18:

[0428] Generating AI: Automatically generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location selection, and music selection.

[0429] Step 19:

[0430] Generative AI: Generates movies in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[0431] Step 20:

[0432] Server: Stores the generated movie data and prepares it for streaming.

[0433] Step 21:

[0434] Server: Generates and displays a viewing link on the user's My Page.

[0435] Step 22:

[0436] Device: The user clicks the provided viewing link to watch the movie.

[0437] Step 23:

[0438] Device: Displays options for users to share movies with their followers.

[0439] Step 24:

[0440] User: Share the viewing link with your followers.

[0441] Step 25:

[0442] Server: Records the viewing history of shared movies and collects revenue data.

[0443] Step 26:

[0444] Server: Revenue is distributed 1:1 between users and site operators and reflected in the user's account.

[0445] Step 27:

[0446] Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[0447] Step 28:

[0448] User: Enter a movie change request and pay the corresponding fee.

[0449] Step 29:

[0450] Terminal: Sends a request to the server.

[0451] Step 30:

[0452] Server: Notifies the generating AI of the request details.

[0453] Step 31:

[0454] Generative AI: Updates the movie by generating additional scenes and different endings.

[0455] Step 32:

[0456] Server: Uploads the updated movie to the streaming server and prepares it for distribution again.

[0457] Step 33:

[0458] Device: Allows users and followers to watch the regenerated movie.

[0459] (Example 2)

[0460] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0461] Traditional film creation systems have struggled to automatically generate films that fully reflect the individual preferences and emotions of users. Furthermore, customizing films according to user requests and ensuring a fair distribution of revenue from generated films have been difficult. As a result, improving the user experience and optimizing revenue have been insufficient.

[0462] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0463] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for emotion recognition that captures the user's facial expressions and voice using a camera and microphone and analyzes their emotions; and means for collecting and analyzing movie trend data from the internet. This enables the automatic generation of more personalized movies that reflect the user's individual preferences, emotions, and the latest trending elements. The server also includes means for distributing the viewing history and revenue of the generated movies between the user and the operator, and means for providing a prompt billing function. This enables the customization of movies according to the user's requests and fair revenue distribution.

[0464] "Data relating to user preferences, attributes, tastes, and operational behavior" refers to information entered by the user into the system, such as name, age, gender, preferences for movie genres and themes, and viewing history of movies and trailers.

[0465] "Emotion recognition means" refers to technology that uses cameras and microphones to capture the user's facial expressions and voice, analyzes them, and generates emotional data such as positive, negative, and neutral.

[0466] "Movie trend data" refers to information collected from the internet about the latest popular movies, notable actors, trending themes, and more.

[0467] "Film planning" refers to the initial design of a film, including its genre, story setting, and main characters, which is generated based on user data and trend data.

[0468] "Generative AI" refers to artificial intelligence that automatically generates detailed scenarios based on film concepts and then produces films in various formats such as live-action, animation, special effects, and CGI.

[0469] "Means of making the content viewable by users and followers" refers to technologies that save the generated movie data, create a viewing link to display on the user's profile page, and enable streaming playback of the movie.

[0470] "Means for recording viewing history and advertising revenue" refers to technology that records in a database the history of movies a user has watched and the revenue generated from advertisements displayed during movie viewing.

[0471] A "payment gateway" refers to an online payment system that securely processes the payment a user makes for their movie request.

[0472] "Prompt billing" refers to a billing technology that allows users to pay a fee when they request changes to the content or presentation of a movie.

[0473] This invention is a system that creates original films incorporating popular trends based on users' wishes, attributes, preferences, operational behavior, survey results, and emotions, and allows users and their followers to watch these films. Furthermore, it is possible to regenerate films according to user requests regarding content and direction, and distribute the revenue. The following describes specific embodiments of this system.

[0474] Basic System Configuration

[0475] This system consists of a user terminal, a server that processes and stores data, and a generative AI that generates movies.

[0476] User data entry

[0477] 1. When the device launches the application, an input form will appear regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the information and clicks the submit button. For example, they might enter, "I like action movies, especially those with sci-fi elements."

[0478] Data collection and storage

[0479] 2. The device collects real-time activity logs, such as which movies the user watched and which trailers they viewed. This data is sent to a server and stored in a database.

[0480] emotion recognition

[0481] 3. The device uses its camera and microphone to capture the user's facial expressions and voice, and sends them to the emotion analysis engine. The emotion engine uses OpenCV and Deep Learning models to analyze the user's emotions and generates emotion data such as positive, negative, and neutral. This emotion data is sent to a server and stored in a database.

[0482] Analysis of popular trends

[0483] 4. The server uses web crawling technologies (e.g., BeautifulSoup or Scrapy) to collect the latest movie trend data from the internet. This data is analyzed using natural language processing technologies (e.g., NLTK or SpaCy) to identify trending elements.

[0484] Creating a film project

[0485] 5. An analysis AI on the server (using, for example, TensorFlow or PyTorch) combines user data, sentiment data, and trending elements to generate a movie concept. This movie concept includes genre, story setting, main characters, etc.

[0486] The creation of a film

[0487] 6. The generative AI generates a detailed scenario based on the film project. This scenario includes the script, casting, location selection, and music selection. The generative AI uses frameworks such as Unreal Engine and Unity to produce the film in various formats including live-action, animation, special effects, and CG, and the video data is stored in cloud storage.

[0488] Preservation and distribution of movies

[0489] 7. The server stores the generated movie data in high-performance storage (e.g., AWS S3) and generates metadata for streaming. A viewing link is generated and displayed on the user's My Page.

[0490] Watching and sharing movies

[0491] 8. The device prompts the user to click a viewing link and streams the movie. Streaming technologies such as HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) are used. Users can share the viewing link with their followers by clicking the share button, and share the movie via social media and messaging apps.

[0492] Profit calculation and distribution

[0493] 9. The server records movie viewing history and advertising revenue. Revenue data is obtained from external advertising APIs (e.g., Google AdSense). The server distributes the revenue to users and site operators in a 1:1 ratio and reflects it in the user's account. Specifically, payments are made using payment gateways (e.g., Stripe or PayPal).

[0494] Movie customization

[0495] 10. The device provides a prompt billing function and displays a page where users can request changes to the movie's content or presentation. Users enter their requests and pay the corresponding fees through a payment gateway. The requests are notified to the generation AI via the server. The generation AI regenerates the movie based on the requested changes (e.g., additional scenes or a different ending) and updates the movie data. The updated movie data is uploaded back to the streaming server and made available for viewing by the user and their followers.

[0496] Specific example

[0497] For example, if a user requests a "moving ending," the AI ​​will generate a new scene that replaces the current movie's ending. This modified movie will then reappear on the user's profile page and become available for viewing. Based on the user's emotional data and viewing history, this modified movie will be reused when generating future movie projects.

[0498] As described above, the present invention allows users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie viewing experience.

[0499] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0500] Step 1:

[0501] When the device launches the application, an input form is displayed that asks about the user's preferences, attributes, and tastes. The input form includes fields such as name, age, gender, movie genre, theme, and favorite actor. The user enters information into these fields and clicks the submit button. The entered data is sent from the device to the server in JSON format. The sent data becomes a JSON object containing the user's personal information and preference information.

[0502] Step 2:

[0503] The terminal collects user activity logs. This includes activity data such as which movies the user watched and which trailers they viewed. The terminal saves this activity data to a log file in real time and sends it to the server as a batch process at regular intervals. The server analyzes the received log data and stores it in a database as user-specific data. Here, the input is the activity log, and the output is user-specific activity data.

[0504] Step 3:

[0505] The device uses its camera and microphone to capture the user's facial expressions and voice. The resulting video and audio data is sent to the server. The input data consists of the user's facial expressions and voice, which the emotion engine analyzes to generate emotion data (positive, negative, neutral, etc.). The generated emotion data is stored on the server. The output is the analyzed emotion data.

[0506] Step 4:

[0507] The server uses web crawling technology to collect the latest movie trend data from the internet. This includes popular movies, notable actors, and trending themes. The server analyzes the collected trend data using natural language processing technology to identify current trend elements. The data input is trend information collected from the web, and the output is the analyzed trend elements.

[0508] Step 5:

[0509] An analytical AI on the server generates a movie concept by combining user data, sentiment data, and trend data. This movie concept includes genre, story setting, main characters, and other elements. The input is user data and trend data, and the output is a specific movie concept. The server stores this concept data in a database and sends it to the generating AI.

[0510] Step 6:

[0511] The generative AI automatically generates a detailed scenario based on a film project proposal. This scenario includes the script, casting, location selection, and music selection. The input is a film project proposal, and the output is a detailed scenario. Based on the generated scenario, the generative AI uses tools such as Unreal Engine or Unity to create the film, and saves the final video data to cloud storage.

[0512] Step 7:

[0513] The server saves the generated movie data to high-performance storage (e.g., AWS S3) and generates metadata for streaming. The output is a viewing link, which is displayed on the user's My Page on their device. The input here is the completed video data.

[0514] Step 8:

[0515] The device prompts the user to click a viewing link, and the movie is streamed. Streaming technologies such as HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) are used. The input is the viewing link, and the output is the movie being played. The user clicks a share button to share the viewing link with their followers, spreading the movie through social media and messaging apps.

[0516] Step 9:

[0517] The server records movie viewing history and advertising revenue. Revenue data is obtained from an external advertising API. Based on the aggregated information, the server distributes the revenue to the user and the site operator in a 1:1 ratio and reflects it in the user's account. The input is viewing history and advertising revenue data, and the output is the distributed revenue.

[0518] Step 10:

[0519] The device provides a prompt billing function and displays a page where the user can request changes to the movie's content or presentation. The user enters their request and pays the fee through a payment gateway. The device sends the request and payment information to the server. The server notifies the generation AI of the request, and the generation AI regenerates the movie reflecting the requested changes. The regenerated movie is saved to cloud storage, and the viewing link is displayed again on the device's My Page. The input is the user's request and payment information, and the output is the updated movie data and viewing link.

[0520] (Application Example 2)

[0521] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0522] In recent years, the diversification of entertainment has led to a growing demand for customized films tailored to individual preferences and emotions. However, a system that efficiently generates films that reflect user preferences, emotions, and operational behavior in real time, and distributes revenue based on these films, still does not exist. This invention aims to solve these problems and provide a system that enables the generation, viewing, and sharing of films optimized for individual users.

[0523] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data relating to the user's wishes, attributes, preferences, and operational behavior; means for analyzing popular trends; means for generating a customized movie plan based on the user data and popular trends; means for generating a movie based on the generated movie plan; means for making the generated movie viewable by the user and followers; means for recognizing the user's emotions and generating and storing emotion data; and means for providing the user with a viewing link to the generated movie. This enables the generation of customized movies based on the user's preferences and emotions, as well as efficient viewing and sharing.

[0524] "User preferences" refer to specific requirements that users have for movies, such as genres, themes, and favorite actors.

[0525] "Attributes" refer to personal background information of the user, such as age, gender, occupation, and hobbies.

[0526] "Preferences" refer to the genres and themes of movies that a user enjoys, as well as their preferences and interests in the types of movies that have been produced.

[0527] "Operational behavior" refers to the actions and patterns of operation that a user exhibits while using an application.

[0528] "Trendy elements" refer to the latest movie trends, popular actors, and trending themes and storylines, gathered from the internet and other sources.

[0529] A "customized film project" refers to a film story and setting that is specially designed based on individual user data and trending elements.

[0530] "Means of producing a film" refers to the processes and systems used to create films in various formats, such as live-action, animation, special effects, and computer graphics, based on a generated film project.

[0531] "Emotional data" refers to emotional information analyzed from the user's facial expressions and voice.

[0532] A "viewing link" refers to a URL or access method provided for viewing a generated movie online.

[0533] "Followers" refer to other users who track a specific user online and view their activities and shared content.

[0534] This invention relates to a system that creates an original film incorporating popular trends based on the user's wishes, attributes, preferences, operational behavior, survey results, and emotions, and allows the user and their followers to watch this film. Specific embodiments are described below.

[0535] Basic System Configuration

[0536] User data entry

[0537] When the application is launched, the device displays an input form regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the requested information and presses the submit button.

[0538] Data collection and storage

[0539] The device collects data including user activity logs and app operation behavior. This includes information such as which movies the user watched and which trailers they viewed. The server stores the collected user data in a database.

[0540] emotion recognition

[0541] The device captures the user's facial expressions and voice through its camera and microphone and sends this data to the emotion engine. The emotion engine analyzes the user's emotions from their facial expressions and voice and generates emotion data. The server stores this emotion data in a database.

[0542] Analysis of popular trends

[0543] The server automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet and analyzes it to identify trending elements.

[0544] Creating a film project

[0545] The server uses a generative AI to combine user data, emotional data, and current trends to generate original movie concepts. These concepts include genre, story setting, and main characters. The generated movie concepts are stored in a database and sent back to the generative AI.

[0546] The creation of a film

[0547] The AI ​​generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection. It also generates films in various formats such as live-action, animation, special effects, and CGI, and saves them as video data.

[0548] Preservation and distribution of movies

[0549] The server stores the generated movie data and prepares it for streaming. It generates and displays a viewing link on the user's My Page.

[0550] Watching and sharing movies

[0551] The device allows the user to click the provided viewing link and watch the movie. It then displays an option for the user to share the movie with their followers. The user can then share the viewing link with their followers.

[0552] Specific example

[0553] For example, if user B inputs that they like movies in the "comedy" and "romance" genres, the system will generate an original movie incorporating the latest trends in comedy romance films. User B can watch the generated movie on their smartphone and, if necessary, send scene change requests to customize specific scenes to their liking. The following example prompts can also be used to input data into the generation AI model.

[0554] "User movie preferences: Comedy and Romance"

[0555] User's favorite actor: A specific actor

[0556] Latest trends: Romantic happenings and funny events

[0557] User sentiment data: Mostly smiles

[0558] Based on this data, please create a hilarious romantic comedy film.

[0559] This invention enables users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie-watching experience.

[0560] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0561] Step 1:

[0562] When the application is launched, the device displays an input form regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the requested information and presses the submit button. The input in this step is the user's personal information and preferences, and the device sends this data to the server as output.

[0563] Step 2:

[0564] The device collects data including user operation logs and application operation behavior. Information such as which movies the user watched and which trailers they viewed is collected. This data is temporarily stored on the device and then sent to the server. The input is user operation data, and this is sent to the server as output.

[0565] Step 3:

[0566] The server stores the collected user data in a database. This stored data is used for subsequent processing. The input is user data sent from the terminal, and the output is stored in the database.

[0567] Step 4:

[0568] The device captures the user's facial expressions and voice through its camera and microphone, and sends this data to the emotion engine. The input is the user's face and voice data, and the output is sent to the emotion engine.

[0569] Step 5:

[0570] The emotion engine analyzes the user's facial expressions and voice to generate emotion data. This analysis is performed using machine learning algorithms. The input is the user's face and voice data, and the output is generated emotion data.

[0571] Step 6:

[0572] The server stores this emotion data in a database. The input is emotion data sent from the emotion engine, and the output is stored in the database.

[0573] Step 7:

[0574] The server automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet and analyzes it to identify trending elements. This process uses web scraping and data analysis techniques. The input is trend data from the internet, and the output is the analyzed trending elements.

[0575] Step 8:

[0576] The server uses a generative AI to combine user data, sentiment data, and current trends to generate original film proposals. These proposals include genre, story setting, and main characters. The input is user data, sentiment data, and current trends, and the output is a film proposal.

[0577] Step 9:

[0578] The AI ​​generator automatically produces a detailed scenario based on the content of a film project. This includes the script, casting, location selection, and music selection. It also generates the film in various formats such as live-action, animation, special effects, and CG, and saves it as video data. The input is film project data, and the output is the scenario and video data.

[0579] Step 10:

[0580] The server stores the generated movie data and prepares it for streaming. The input is the generated movie data, and the output is a viewing link.

[0581] Step 11:

[0582] The device plays the movie when the user clicks on the provided viewing link. The input is the viewing link, and the output is the movie being played.

[0583] Step 12:

[0584] The device displays options for the user to share a movie with their followers. The user can share a viewing link with their followers. The input is the viewing link, and the output is sharing with followers.

[0585] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0586] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0587] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0588] [Second Embodiment]

[0589] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0590] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0591] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0592] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0593] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0594] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0595] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0596] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0597] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0598] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0599] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0600] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0601] This invention provides a system that creates original films incorporating popular trends based on user preferences, attributes, tastes, app operation behavior, and survey results, and allows users and their followers to watch these films. The program processing of this system is described below in natural language.

[0602] Basic System Configuration

[0603] User data entry

[0604] 1. Terminal: When a user launches the application, an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[0605] 2. User: Enter the specified information.

[0606] Data collection and storage

[0607] 3. Device: Continuously records user activity logs and collects them as application operation behavior. For example, it records which movies the user watched, which trailers they viewed, etc.

[0608] 4. Server: Stores collected user data in a database.

[0609] Analysis of popular trends

[0610] 5. Server: Collects the latest movie trend data from the internet. This includes popular movies, notable actors, trending themes, etc.

[0611] 6. Server: Analyzes collected trend data and identifies trending elements.

[0612] Creating a film project

[0613] 7. Server: An analytical AI combines user data with current trends to generate original movie concepts. These concepts include genre, story setting, and main characters.

[0614] 8. Server: Saves the generated film proposals to the database and sends them to the generation AI.

[0615] The creation of a film

[0616] 9. Generating AI: Automatically generates detailed scenarios based on film proposals. This includes scriptwriting, casting, location scouting, and music selection.

[0617] 10. Generative AI: Creates films in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[0618] Movie preservation and distribution

[0619] 11. Server: Stores the generated movie data and prepares it for streaming.

[0620] 12. Server: Generates and displays a viewing link on the user's My Page.

[0621] Watching and sharing movies

[0622] 13. Device: User A can click the provided viewing link and watch the movie.

[0623] 14. Terminal: Displays options for User A to share a movie with their followers.

[0624] 15. User: Share the viewing link with your followers.

[0625] Profit calculation and distribution

[0626] 16. Server: Records the viewing history and advertising revenue of generated movies.

[0627] 17. Server: Revenue is distributed 1:1 between User A and the site operator and reflected in the user's account.

[0628] Movie customization

[0629] 18. Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[0630] 19. User: Enter a movie change request and pay the corresponding fee.

[0631] 20. Server: Notifies the generation AI of the request content and regenerates the movie script and direction.

[0632] 21. Server: Upload the regenerated movie to the streaming server so that users and followers can watch it again.

[0633] Specific example

[0634] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates a movie concept that includes popular heroes and magical elements. The generating AI creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. If user A watches the movie and wants to add new scenes, they can submit a change request via prompt payment and enjoy the regenerated movie.

[0635] The above describes the embodiments for carrying out the present invention. The present invention enables users to easily create, view, and share original movies optimized for themselves.

[0636] The following describes the processing flow.

[0637] Step 1:

[0638] Device: After launching the app, an input form will be displayed regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[0639] Step 2:

[0640] User: Enter the specified information and press the submit button.

[0641] Step 3:

[0642] Terminal: Sends the entered user information to the server.

[0643] Step 4:

[0644] Server: Stores the received user information in the database.

[0645] Step 5:

[0646] Device: Records user actions within the app (which movies were watched, which trailers were viewed) and collects this data as app operation behavior.

[0647] Step 6:

[0648] Server: Receives application operation behavior and saves it to the database.

[0649] Step 7:

[0650] Terminal: Displays a survey to the user and collects responses.

[0651] Step 8:

[0652] User: Answers the survey and presses the submit button.

[0653] Step 9:

[0654] Terminal: Sends survey responses to the server.

[0655] Step 10:

[0656] Server: Saves survey results to the database.

[0657] Step 11:

[0658] Server: Automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet.

[0659] Step 12:

[0660] Server: Analyzes collected trend data and identifies trending elements.

[0661] Step 13:

[0662] Server: An analytical AI combines user data with current trends to generate original movie concepts.

[0663] Step 14:

[0664] Server: Saves the generated film proposals to a database and sends them to the generation AI.

[0665] Step 15:

[0666] Generating AI: Automatically generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection.

[0667] Step 16:

[0668] Generative AI: Generates movies in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[0669] Step 17:

[0670] Server: Uploads the generated movie data to the streaming server.

[0671] Step 18:

[0672] Server: Generates and displays a viewing link on the user's My Page.

[0673] Step 19:

[0674] Device: User A clicks on the provided viewing link and watches the movie.

[0675] Step 20:

[0676] Terminal: Displays options for User A to share a movie with their followers.

[0677] Step 21:

[0678] User: Share the viewing link with your followers.

[0679] Step 22:

[0680] Server: Records the viewing history of shared movies and collects revenue data.

[0681] Step 23:

[0682] Server: Revenue is distributed 1:1 between User A and the site operator and reflected in the user's account.

[0683] Step 24:

[0684] Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[0685] Step 25:

[0686] User: Enter a movie change request and pay the corresponding fee.

[0687] Step 26:

[0688] Terminal: Sends a request to the server.

[0689] Step 27:

[0690] Server: Notifies the generating AI of the request details.

[0691] Step 28:

[0692] Generative AI: Updates the movie by generating additional scenes and different endings.

[0693] Step 29:

[0694] Server: Uploads the updated movie to the streaming server and prepares it for distribution again.

[0695] Step 30:

[0696] Terminal: Allows User A and their followers to watch the regenerated movie.

[0697] (Example 1)

[0698] Next, we will describe Example 1. 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".

[0699] In the current film production process, it is difficult to create original films that reflect the individual preferences and attributes of users, making it challenging for films to fully meet user expectations. Furthermore, customizing the content and direction of films, as well as efficiently distributing revenue from the resulting films, is also difficult. Therefore, there is a need for a system that efficiently and easily creates, customizes, and distributes revenue from original films that reflect user wishes and preferences.

[0700] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0701] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for recording user operation logs; means for storing the collected user data in a database; means for collecting the latest movie trend data from the internet; means for analyzing the collected trend data to identify trend elements; means for generating customized movie plans based on user data and trend elements; means for storing the generated movie plans in a database and transmitting them to a generating AI model; means for generating detailed scenarios based on the generating AI model; means for creating movies in formats such as live-action, animation, special effects, and CG using the generating AI model and saving them as video data; means for saving the generated movie data and preparing it for streaming distribution; and means for generating and displaying viewing links on the user's My Page. This makes it possible to create, customize, and distribute revenue from movies that reflect the individual preferences and wishes of the user.

[0702] "User preferences, attributes, and tastes" refer to the specific demands and preferences that users have regarding movies, including genre, theme, and favorite actors.

[0703] "Operational behavior" refers to the actions and patterns a user exhibits when interacting with an application, including operational information such as which movies were watched or which trailers were viewed.

[0704] A "database" is a system for efficiently storing, managing, searching, and using collected user data and trend data.

[0705] "Methods for collecting the latest movie trend data from the internet" refers to the process of automatically obtaining the latest movie information from online resources such as movie review sites and social media.

[0706] "Trend elements" refer to characteristics such as themes, actors, and genres of movies that are generally popular with the public today.

[0707] A "generative AI model" is a program and algorithm that uses artificial intelligence to automatically generate movie plans and scripts.

[0708] A "detailed scenario" refers to a plan that includes specific elements such as the film's script, casting, filming locations, and music.

[0709] "Live-action, animation, special effects, and CG" are different formats and types of techniques used to produce films, each possessing its own unique visual expression.

[0710] "Preparing for streaming distribution" refers to the process of converting file formats and uploading to servers in order to make the generated movie viewable online.

[0711] A "viewing link" refers to a URL or access method that allows a user to watch a generated movie online.

[0712] A "customized film project" refers to a basic plan or proposal for a film that is specially designed to reflect user preferences and current trends.

[0713] "Regeneration" refers to the process of regenerating a movie that has already been created, based on a new request from the user.

[0714] This invention is a system that automatically generates original movies based on user preferences, attributes, tastes, app operation behavior, and current trends. A specific embodiment of this system is described below.

[0715] When a user launches the application, the device displays an input form for their preferences, attributes, and tastes. This includes their name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The device collects this information as the user enters it.

[0716] The collected data is recorded by the terminal along with the user's operation log. This includes information such as which movies the user watched and which trailers they viewed. This data is then stored in a database by the server. Relational databases such as MySQL or PostgreSQL are used for this database.

[0717] The server collects the latest movie trend data from the internet. This data is obtained from movie review sites and social media. The collected data is analyzed by analytical algorithms on the server to identify trending elements. This utilizes techniques such as natural language processing and data mining.

[0718] Next, the server uses analytical AI to combine user data and trending elements to generate a customized movie proposal. This proposal includes genre, story setting, main characters, and other elements. The generated movie proposal is stored in a database and sent to the generating AI model.

[0719] The generative AI model automatically generates a detailed scenario based on the received film proposal. This includes scriptwriting, casting, location scouting, and music selection. The AI ​​model then uses the model to create the film in various formats, such as live-action, animation, special effects, or CGI. The film, saved as video data, is then prepared for streaming distribution by a server.

[0720] Users can watch movies by accessing their personal page and clicking on a viewing link. The viewing page also has a sharing option, allowing users to share movies with their followers. Viewing history and advertising revenue for shared movies are recorded by the server, and these revenues are shared between the user and the site operator.

[0721] Additionally, users can request changes to the movie's content and direction using a prompt billing feature. Once a user enters a change request and pays the corresponding fee, the server notifies the generation AI model of the request, and the movie's script and direction are regenerated. The regenerated movie is uploaded to the streaming server and becomes available for viewing again by the user and their followers.

[0722] Specific example

[0723] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates a movie concept that includes popular heroes and magical elements. The generating AI model creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. If user A watches the movie and wants to add new scenes, they can submit a change request via prompt billing and enjoy the regenerated movie.

[0724] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0725] Step 1:

[0726] Launching the app and entering user information

[0727] Terminal: When a user launches the application, a form is displayed for them to enter their preferences, attributes, and tastes.

[0728] Input: User's name, age, gender, movie preferences (genre, theme, favorite actor, etc.).

[0729] Output: User-entered data on preferences, attributes, and tastes.

[0730] Specific operation: The terminal stores data in each field according to the user's input.

[0731] Step 2:

[0732] Recording user behavior

[0733] Terminal: Continuously records logs of user actions within the application.

[0734] Input: User actions (movies watched, trailers viewed, etc.).

[0735] Output: Operation log data.

[0736] Specific operation: The device saves user actions such as taps, clicks, and scrolls to a log file.

[0737] Step 3:

[0738] Data storage

[0739] Server: Stores collected user data and operation logs in a database.

[0740] Input: Data on preferences, attributes, and actions.

[0741] Output: User information and operation logs stored in the database.

[0742] Specific operation: The server issues an INSERT statement to the database and persists the data.

[0743] Step 4:

[0744] Collection and analysis of trending elements

[0745] Server: Collects and analyzes the latest movie trend data from the internet.

[0746] Input: Trend data obtained from movie review sites and social media.

[0747] Output: Analyzed trend elements.

[0748] Specific operation: A crawler periodically collects data from websites, and an analysis algorithm on the server processes that data using natural language processing.

[0749] Step 5:

[0750] Creating a film project

[0751] Server: Combines user data and trending elements to generate customized movie concepts.

[0752] Input: User data, operation logs, analyzed trending factors.

[0753] Output: Film project data (genre, story setting, main characters, etc.).

[0754] Specific operation: An analytical AI on the server creates a movie plot based on the user's preferences and the latest trends.

[0755] Step 6:

[0756] Scenario and film generation

[0757] Generative AI Model: Automatically generates detailed scenarios based on generated film plans and creates films.

[0758] Input: Film project data.

[0759] Output: Video data of the completed film.

[0760] Specific operation: The generation AI model automatically handles scriptwriting, casting, location selection, music selection, etc., and generates the film in CG, animation, and live-action formats.

[0761] Step 7:

[0762] Saving movie data and preparing for streaming

[0763] Server: Stores the generated movie data and prepares it for streaming.

[0764] Input: Video data of the completed film.

[0765] Output: Movie data prepared for streaming.

[0766] Specific operation: Convert movie data to the appropriate format and upload it to the streaming server.

[0767] Step 8:

[0768] Generating and displaying viewing links

[0769] Server: Generates and displays a viewing link on the user's My Page.

[0770] Input: Movie data prepared for streaming, user account information.

[0771] Output: The viewing link displayed on your My Page.

[0772] Specific operation: The server generates a unique viewing link for the user and displays it on the user's My Page.

[0773] Step 9:

[0774] Watch and share movies

[0775] Device: Users can watch generated movies and share them with their followers if desired.

[0776] Input: The viewing link displayed on your My Page.

[0777] Output: Viewing history, sharing information.

[0778] Specific actions: The user clicks the link to play the movie and uses the sharing option to send the link to their followers.

[0779] Step 10:

[0780] Profit calculation and distribution

[0781] Server: Records viewing history and advertising revenue, and distributes it to users and operators.

[0782] Input: Viewing history data, advertising revenue data.

[0783] Output: Distributed revenue information.

[0784] Specific operation: The server uses revenue data to reflect the revenue in the user and operator accounts.

[0785] Step 11:

[0786] Movie customization

[0787] Terminal: Accepts requests for changes to movie content and presentation via prompt payment.

[0788] Input: User request details, billing information.

[0789] Output: Regenerated movie data based on the request.

[0790] Specific operation: The user fills out a change request and submits billing information. The request is sent to the server, and the generation AI model generates the movie again.

[0791] (Application Example 1)

[0792] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0793] Traditional content distribution services struggle to provide original films tailored to individual user preferences, and it's also difficult for users to request and modify the content or direction of films themselves. Furthermore, easily creating and making available original films compatible with virtual reality viewing environments is another challenge.

[0794] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0795] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for analyzing current trends; means for generating customized movie plans based on the user data and trends; means for generating a movie based on the generated movie plan; means for making the generated movie viewable by the user and their followers; and means for making the generated movie viewable in a virtual reality environment. This makes it possible to easily generate original movies optimized for the user's individual preferences and enjoy them in a virtual reality environment.

[0796] "User data" refers to information about a user's wishes, attributes, preferences, and operational behavior.

[0797] "Trend elements" refer to data on the latest trends collected from the internet and other sources.

[0798] A "customized film project" is a film project proposal that is individually designed based on user data and trending elements.

[0799] "Means of creating films" refers to the technology of creating visuals in various formats such as live-action, animation, special effects, and computer graphics based on a customized film project.

[0800] A "virtual reality environment" is a virtual visual world that users can experience using VR head-mounted displays or other VR devices.

[0801] "Available for viewing" means that the generated film is provided to users and followers in a form that is accessible online.

[0802] "Request details" refer to specific changes that the user would like to see made to the content or direction of the film.

[0803] "Method of regeneration" refers to a technology that regenerates already created movies based on user requests.

[0804] The "means of revenue distribution" refer to a system that distributes the revenue generated between users and operators based on the viewing history of the movies that have been produced.

[0805] System Overview

[0806] This invention is a system that collects user wishes, attributes, preferences, and operational behaviors, combines them with current trends to generate customized movies, and makes them viewable in a virtual reality environment.

[0807] Hardware and software to be used

[0808] Hardware: Smartphones, VR head-mounted displays (e.g., Oculus Quest 2)

[0809] Software: Flask (web framework), Python (programming language), generative AI model

[0810] Data collection and storage

[0811] 1. Device (smartphone or VR device):

[0812] When a user launches the application, an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor).

[0813] 2. User:

[0814] Enter the specified information.

[0815] 3. Server:

[0816] The system continuously records user activity logs and collects them as application operation behavior. For example, it records which movies a user watched, which trailers they viewed, and so on.

[0817] Analysis of popular trends

[0818] 4. Server:

[0819] We collect the latest movie trend data from the internet. This includes popular movies, notable actors, and trending themes.

[0820] 5. Server:

[0821] We analyze collected trend data to identify trending elements.

[0822] Film planning and creation

[0823] 6. Server:

[0824] An analytical AI combines user data with current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[0825] 7. Server:

[0826] Using a generative AI model, detailed scenarios are automatically generated based on the plan.

[0827] 8. Server:

[0828] We create films in various formats such as live-action, animation, special effects, and CGI, and save them as video data.

[0829] Watch and customize movies

[0830] 9. Server:

[0831] The generated movie data is saved and prepared for streaming distribution.

[0832] 10. Terminal:

[0833] Users can watch the movie by clicking on the provided viewing link.

[0834] 11. Server:

[0835] It provides an interface for users to request specific content and direction for the film.

[0836] 12. Generative AI Models:

[0837] Based on the requested content, we will regenerate the movie's script and direction.

[0838] 13. Server:

[0839] The regenerated movie data is uploaded to a streaming server, allowing users and followers to watch it again.

[0840] Specific example

[0841] For example, if the user prefers "Actions" and "Magic," enter the following prompt:

[0842] "User ID: user123"

[0843] Genre: Action

[0844] "Theme: Magic"

[0845] Based on this prompt, the server generates movie recommendations tailored to the user's preferences and creates movie data using a generation AI model. The generated movies are provided to the user via a link, and the user can watch them using a smartphone or VR head-mounted display.

[0846] In this way, this system can easily generate original movies optimized to the user's individual preferences, allowing them to be viewed and enjoyed in a virtual reality environment. This provides a personalized experience that was difficult to achieve with conventional content distribution services.

[0847] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0848] Step 1:

[0849] Terminal:

[0850] The user launches the application, and an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor).

[0851] Input: Name, age, gender, movie preferences

[0852] Output: User input data

[0853] Step 2:

[0854] User:

[0855] Enter the desired information and submit the form.

[0856] Input: Input form

[0857] Output: User data (name, age, gender, movie preferences)

[0858] Step 3:

[0859] server:

[0860] The system continuously records user activity logs (which movies were watched, which trailers were viewed) and saves them to a database as application operation behavior.

[0861] Input: User data and operation logs

[0862] Output: Operation history data

[0863] Step 4:

[0864] server:

[0865] Collect the latest movie trend data from the internet (popular movies, notable actors, trending themes, etc.).

[0866] Input: Trending information on the internet

[0867] Output: Trend Data

[0868] Step 5:

[0869] server:

[0870] We analyze collected trend data to identify trending elements.

[0871] Input: Trend data

[0872] Output: Identified trend elements

[0873] Step 6:

[0874] server:

[0875] The analytical AI combines user data and trending elements to generate original movie concepts (genre, story setting, main characters).

[0876] Input: User data, trending topics

[0877] Output: Film project data

[0878] Step 7:

[0879] server:

[0880] The generative AI model automatically generates detailed scenarios based on film project data.

[0881] Input: Film project data

[0882] Output: Detailed Scenario

[0883] Step 8:

[0884] Generative AI models:

[0885] We create films in various formats such as live-action, animation, special effects, and CGI, and save them as video data.

[0886] Input: Detailed Scenario

[0887] Output: Video data

[0888] Step 9:

[0889] server:

[0890] The generated movie data is saved, and a link for streaming is generated.

[0891] Input: Video data

[0892] Output: Viewing link

[0893] Step 10:

[0894] Terminal:

[0895] Users click on the provided viewing link and watch the movie using their smartphone or VR head-mounted display.

[0896] Input: Viewing link

[0897] Output: Movie playback

[0898] Step 11:

[0899] server:

[0900] It provides an interface for users to request specific content and direction for the film.

[0901] Input: User Request

[0902] Output: Request details

[0903] Step 12:

[0904] Generative AI models:

[0905] Based on user requests, the system regenerates movie scripts and direction.

[0906] Input: Request details

[0907] Output: Regenerated movie script

[0908] Step 13:

[0909] server:

[0910] The regenerated movie data is uploaded to a streaming server, allowing users and followers to watch it again.

[0911] Input: Regenerated movie script, video data

[0912] Output: Regenerated movie viewing link

[0913] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0914] This invention is a system that creates original films incorporating popular trends based on users' wishes, attributes, preferences, app operation behavior, survey results, and emotions, and allows users and their followers to watch these films. Furthermore, it regenerates films according to user requests regarding content and direction, and distributes the revenue. The program processing of this system is described below in natural language.

[0915] Basic System Configuration

[0916] User data entry

[0917] 1. Terminal: When the application is launched, an input form will be displayed regarding the user's wishes, attributes, and preferences. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[0918] 2. User: Enter the specified information and press the submit button.

[0919] Data collection and storage

[0920] 3. Device: Collects data including user operation logs and app operation behavior. This includes which movies the user watched and which trailers they viewed.

[0921] 4. Server: Stores collected user data in a database.

[0922] emotion recognition

[0923] 5. Device: Captures the user's facial expressions and voice through the camera and microphone and sends them to the emotion engine.

[0924] 6. Emotion Engine: Analyzes the user's facial expressions and voice to generate emotion data.

[0925] 7. Server: Stores the emotion data sent from the emotion engine in the database.

[0926] Analysis of popular trends

[0927] 8. Server: Automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet.

[0928] 9. Server: Analyzes collected trend data and identifies trending elements.

[0929] Creating a film project

[0930] 10. Server: An analytical AI combines user data, sentiment data, and current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[0931] 11. Server: Saves the generated film proposals to the database and sends them to the generation AI.

[0932] The creation of a film

[0933] 12. Generating AI: Automatically generates a detailed scenario based on the content of the film project. This includes scriptwriting, casting, location selection, and music selection.

[0934] 13. Generative AI: Generates films in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[0935] Movie preservation and distribution

[0936] 14. Server: Stores the generated movie data and prepares it for streaming.

[0937] 15. Server: Generates and displays a viewing link on the user's My Page.

[0938] Watching and sharing movies

[0939] 16. Device: The user clicks the provided viewing link to watch the movie.

[0940] 17. Device: Displays options for users to share movies with their followers.

[0941] 18. User: Share the viewing link with your followers.

[0942] Profit calculation and distribution

[0943] 19. Server: Records the viewing history and advertising revenue of generated movies.

[0944] 20. Server: Distributes revenue 1:1 between users and site operators and reflects it in the user's account.

[0945] Movie customization

[0946] 21. Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[0947] 22. User: Enter a movie change request and pay the corresponding fee.

[0948] 23. Terminal: Sends the request to the server.

[0949] 24. Server: Notifies the generating AI of the request details.

[0950] 25. Generating AI: Updates the movie by generating additional scenes and different endings.

[0951] 26. Server: Upload the updated movie to the streaming server and prepare it for distribution again.

[0952] 27. Device: Allow users and followers to watch the regenerated movie.

[0953] Specific example

[0954] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates movie proposals that include popular hero and magical elements. The generating AI creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. Furthermore, an emotion engine analyzes the user's emotions while they are watching, and this data is used when generating future movie proposals, resulting in a more personalized movie.

[0955] This invention enables users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie-watching experience.

[0956] The following describes the processing flow.

[0957] Step 1:

[0958] Terminal: When the application is launched, it displays an input form regarding the user's wishes, attributes, and preferences. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[0959] Step 2:

[0960] User: Enter the specified information and press the submit button.

[0961] Step 3:

[0962] Terminal: Sends the entered user information to the server.

[0963] Step 4:

[0964] Server: Stores the received user information in the database.

[0965] Step 5:

[0966] Device: Records user activity logs and app operation behavior, collecting information such as which movies were watched and which trailers were viewed.

[0967] Step 6:

[0968] Server: Stores collected application operation behaviors in a database.

[0969] Step 7:

[0970] Terminal: Displays a survey to the user and collects responses.

[0971] Step 8:

[0972] User: Answers the survey and presses the submit button.

[0973] Step 9:

[0974] Terminal: Sends survey responses to the server.

[0975] Step 10:

[0976] Server: Saves survey results to the database.

[0977] Step 11:

[0978] Device: Captures the user's facial expressions and voice through the camera and microphone, and sends them to the emotion engine.

[0979] Step 12:

[0980] Emotion Engine: Analyzes the user's facial expressions and voice to generate emotion data.

[0981] Step 13:

[0982] Server: Stores emotion data sent from the emotion engine in the database.

[0983] Step 14:

[0984] Server: Automatically collects the latest movie trend data from the internet. This includes popular movies, featured actors, trending themes, and more.

[0985] Step 15:

[0986] Server: Analyzes collected trend data and identifies trending elements.

[0987] Step 16:

[0988] Server: An analytical AI combines user data, sentiment data, and current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[0989] Step 17:

[0990] Server: Saves the generated film proposals to a database and sends them to the generation AI.

[0991] Step 18:

[0992] Generating AI: Automatically generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection.

[0993] Step 19:

[0994] Generative AI: Generates movies in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[0995] Step 20:

[0996] Server: Stores the generated movie data and prepares it for streaming.

[0997] Step 21:

[0998] Server: Generates and displays a viewing link on the user's My Page.

[0999] Step 22:

[1000] Device: The user clicks the provided viewing link to watch the movie.

[1001] Step 23:

[1002] Device: Displays options for users to share movies with their followers.

[1003] Step 24:

[1004] User: Share the viewing link with your followers.

[1005] Step 25:

[1006] Server: Records the viewing history of shared movies and collects revenue data.

[1007] Step 26:

[1008] Server: Revenue is distributed 1:1 between users and site operators and reflected in the user's account.

[1009] Step 27:

[1010] Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[1011] Step 28:

[1012] User: Enter a movie change request and pay the corresponding fee.

[1013] Step 29:

[1014] Terminal: Sends a request to the server.

[1015] Step 30:

[1016] Server: Notifies the generating AI of the request details.

[1017] Step 31:

[1018] Generative AI: Updates the movie by generating additional scenes and different endings.

[1019] Step 32:

[1020] Server: Uploads the updated movie to the streaming server and prepares it for distribution again.

[1021] Step 33:

[1022] Device: Allows users and followers to watch the regenerated movie.

[1023] (Example 2)

[1024] Next, we will describe Example 2. 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".

[1025] Traditional film creation systems have struggled to automatically generate films that fully reflect the individual preferences and emotions of users. Furthermore, customizing films according to user requests and ensuring a fair distribution of revenue from generated films have been difficult. As a result, improving the user experience and optimizing revenue have been insufficient.

[1026] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1027] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for emotion recognition that captures the user's facial expressions and voice using a camera and microphone and analyzes their emotions; and means for collecting and analyzing movie trend data from the internet. This enables the automatic generation of more personalized movies that reflect the user's individual preferences, emotions, and the latest trending elements. The server also includes means for distributing the viewing history and revenue of the generated movies between the user and the operator, and means for providing a prompt billing function. This enables the customization of movies according to the user's requests and fair revenue distribution.

[1028] "Data relating to user preferences, attributes, tastes, and operational behavior" refers to information entered by the user into the system, such as name, age, gender, preferences for movie genres and themes, and viewing history of movies and trailers.

[1029] "Emotion recognition means" refers to technology that uses cameras and microphones to capture the user's facial expressions and voice, analyzes them, and generates emotional data such as positive, negative, and neutral.

[1030] "Movie trend data" refers to information collected from the internet about the latest popular movies, notable actors, trending themes, and more.

[1031] "Film planning" refers to the initial design of a film, including its genre, story setting, and main characters, which is generated based on user data and trend data.

[1032] "Generative AI" refers to artificial intelligence that automatically generates detailed scenarios based on film concepts and then produces films in various formats such as live-action, animation, special effects, and CGI.

[1033] "Means of making the content viewable by users and followers" refers to technologies that save the generated movie data, create a viewing link to display on the user's profile page, and enable streaming playback of the movie.

[1034] "Means for recording viewing history and advertising revenue" refers to technology that records in a database the history of movies a user has watched and the revenue generated from advertisements displayed during movie viewing.

[1035] A "payment gateway" refers to an online payment system that securely processes the payment a user makes for their movie request.

[1036] "Prompt billing" refers to a billing technology that allows users to pay a fee when they request changes to the content or presentation of a movie.

[1037] This invention is a system that creates original films incorporating popular trends based on users' wishes, attributes, preferences, operational behavior, survey results, and emotions, and allows users and their followers to watch these films. Furthermore, it is possible to regenerate films according to user requests regarding content and direction, and distribute the revenue. The following describes specific embodiments of this system.

[1038] Basic System Configuration

[1039] This system consists of a user terminal, a server that processes and stores data, and a generative AI that generates movies.

[1040] User data entry

[1041] 1. When the device launches the application, an input form will appear regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the information and clicks the submit button. For example, they might enter, "I like action movies, especially those with sci-fi elements."

[1042] Data collection and storage

[1043] 2. The device collects real-time activity logs, such as which movies the user watched and which trailers they viewed. This data is sent to a server and stored in a database.

[1044] emotion recognition

[1045] 3. The device uses its camera and microphone to capture the user's facial expressions and voice, and sends them to the emotion analysis engine. The emotion engine uses OpenCV and Deep Learning models to analyze the user's emotions and generates emotion data such as positive, negative, and neutral. This emotion data is sent to a server and stored in a database.

[1046] Analysis of popular trends

[1047] 4. The server uses web crawling technologies (e.g., BeautifulSoup or Scrapy) to collect the latest movie trend data from the internet. This data is analyzed using natural language processing technologies (e.g., NLTK or SpaCy) to identify trending elements.

[1048] Creating a film project

[1049] 5. An analysis AI on the server (using, for example, TensorFlow or PyTorch) combines user data, sentiment data, and trending elements to generate a movie concept. This movie concept includes genre, story setting, main characters, etc.

[1050] The creation of a film

[1051] 6. The generative AI generates a detailed scenario based on the film project. This scenario includes the script, casting, location selection, and music selection. The generative AI uses frameworks such as Unreal Engine and Unity to produce the film in various formats including live-action, animation, special effects, and CG, and the video data is stored in cloud storage.

[1052] Movie preservation and distribution

[1053] 7. The server stores the generated movie data in high-performance storage (e.g., AWS S3) and generates metadata for streaming. A viewing link is generated and displayed on the user's My Page.

[1054] Watching and sharing movies

[1055] 8. The device prompts the user to click a viewing link and streams the movie. Streaming technologies such as HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) are used. Users can share the viewing link with their followers by clicking the share button, and share the movie via social media and messaging apps.

[1056] Profit calculation and distribution

[1057] 9. The server records movie viewing history and advertising revenue. Revenue data is obtained from external advertising APIs (e.g., Google AdSense). The server distributes the revenue to users and site operators in a 1:1 ratio and reflects it in the user's account. Specifically, payments are made using payment gateways (e.g., Stripe or PayPal).

[1058] Movie customization

[1059] 10. The device provides a prompt billing function and displays a page where users can request changes to the movie's content or presentation. Users enter their requests and pay the corresponding fees through a payment gateway. The requests are notified to the generation AI via the server. The generation AI regenerates the movie based on the requested changes (e.g., additional scenes or a different ending) and updates the movie data. The updated movie data is uploaded back to the streaming server and made available for viewing by the user and their followers.

[1060] Specific example

[1061] For example, if a user requests a "moving ending," the AI ​​will generate a new scene that replaces the current movie's ending. This modified movie will then reappear on the user's profile page and become available for viewing. Based on the user's emotional data and viewing history, this modified movie will be reused when generating future movie projects.

[1062] As described above, the present invention allows users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie viewing experience.

[1063] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1064] Step 1:

[1065] When the device launches the application, an input form is displayed that asks about the user's preferences, attributes, and tastes. The input form includes fields such as name, age, gender, movie genre, theme, and favorite actor. The user enters information into these fields and clicks the submit button. The entered data is sent from the device to the server in JSON format. The sent data becomes a JSON object containing the user's personal information and preference information.

[1066] Step 2:

[1067] The terminal collects user activity logs. This includes activity data such as which movies the user watched and which trailers they viewed. The terminal saves this activity data to a log file in real time and sends it to the server as a batch process at regular intervals. The server analyzes the received log data and stores it in a database as user-specific data. Here, the input is the activity log, and the output is user-specific activity data.

[1068] Step 3:

[1069] The device uses its camera and microphone to capture the user's facial expressions and voice. The resulting video and audio data is sent to the server. The input data consists of the user's facial expressions and voice, which the emotion engine analyzes to generate emotion data (positive, negative, neutral, etc.). The generated emotion data is stored on the server. The output is the analyzed emotion data.

[1070] Step 4:

[1071] The server uses web crawling technology to collect the latest movie trend data from the internet. This includes popular movies, notable actors, and trending themes. The server analyzes the collected trend data using natural language processing technology to identify current trend elements. The data input is trend information collected from the web, and the output is the analyzed trend elements.

[1072] Step 5:

[1073] An analytical AI on the server generates a movie concept by combining user data, sentiment data, and trend data. This movie concept includes genre, story setting, main characters, and other elements. The input is user data and trend data, and the output is a specific movie concept. The server stores this concept data in a database and sends it to the generating AI.

[1074] Step 6:

[1075] The generative AI automatically generates a detailed scenario based on a film project proposal. This scenario includes the script, casting, location selection, and music selection. The input is a film project proposal, and the output is a detailed scenario. Based on the generated scenario, the generative AI uses tools such as Unreal Engine or Unity to create the film, and saves the final video data to cloud storage.

[1076] Step 7:

[1077] The server saves the generated movie data to high-performance storage (e.g., AWS S3) and generates metadata for streaming. The output is a viewing link, which is displayed on the user's My Page on their device. The input here is the completed video data.

[1078] Step 8:

[1079] The device prompts the user to click a viewing link, and the movie is streamed. Streaming technologies such as HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) are used. The input is the viewing link, and the output is the movie being played. The user clicks a share button to share the viewing link with their followers, spreading the movie through social media and messaging apps.

[1080] Step 9:

[1081] The server records movie viewing history and advertising revenue. Revenue data is obtained from an external advertising API. Based on the aggregated information, the server distributes the revenue to the user and the site operator in a 1:1 ratio and reflects it in the user's account. The input is viewing history and advertising revenue data, and the output is the distributed revenue.

[1082] Step 10:

[1083] The device provides a prompt billing function and displays a page where the user can request changes to the movie's content or presentation. The user enters their request and pays the fee through a payment gateway. The device sends the request and payment information to the server. The server notifies the generation AI of the request, and the generation AI regenerates the movie reflecting the requested changes. The regenerated movie is saved to cloud storage, and the viewing link is displayed again on the device's My Page. The input is the user's request and payment information, and the output is the updated movie data and viewing link.

[1084] (Application Example 2)

[1085] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1086] In recent years, the diversification of entertainment has led to a growing demand for customized films tailored to individual preferences and emotions. However, a system that efficiently generates films that reflect user preferences, emotions, and operational behavior in real time, and distributes revenue based on these films, still does not exist. This invention aims to solve these problems and provide a system that enables the generation, viewing, and sharing of films optimized for individual users.

[1087] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data relating to the user's wishes, attributes, preferences, and operational behavior; means for analyzing popular trends; means for generating a customized movie plan based on the user data and popular trends; means for generating a movie based on the generated movie plan; means for making the generated movie viewable by the user and followers; means for recognizing the user's emotions and generating and storing emotion data; and means for providing the user with a viewing link to the generated movie. This enables the generation of customized movies based on the user's preferences and emotions, as well as efficient viewing and sharing.

[1088] "User preferences" refer to specific requirements that users have for movies, such as genres, themes, and favorite actors.

[1089] "Attributes" refer to personal background information of the user, such as age, gender, occupation, and hobbies.

[1090] "Preferences" refer to the genres and themes of movies that a user enjoys, as well as their preferences and interests in the types of movies that have been produced.

[1091] "Operational behavior" refers to the actions and patterns of operation that a user exhibits while using an application.

[1092] "Popular trends" refer to the latest movie trends, popular actors, and trending themes and storylines, gathered from the internet and other sources.

[1093] A "customized film project" refers to a film story and setting that is specially designed based on individual user data and trending elements.

[1094] "Means of producing a film" refers to the processes and systems used to create films in various formats, such as live-action, animation, special effects, and computer graphics, based on a generated film project.

[1095] "Emotional data" refers to emotional information analyzed from the user's facial expressions and voice.

[1096] A "viewing link" refers to a URL or access method provided for viewing a generated movie online.

[1097] "Followers" refer to other users who track a specific user online and view their activities and shared content.

[1098] This invention relates to a system that creates an original film incorporating popular trends based on the user's wishes, attributes, preferences, operational behavior, survey results, and emotions, and allows the user and their followers to watch this film. Specific embodiments are described below.

[1099] Basic System Configuration

[1100] User data entry

[1101] When the application is launched, the device displays an input form regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the requested information and presses the submit button.

[1102] Data collection and storage

[1103] The device collects data including user activity logs and app operation behavior. This includes information such as which movies the user watched and which trailers they viewed. The server stores the collected user data in a database.

[1104] emotion recognition

[1105] The device captures the user's facial expressions and voice through its camera and microphone and sends this data to the emotion engine. The emotion engine analyzes the user's emotions from their facial expressions and voice and generates emotion data. The server stores this emotion data in a database.

[1106] Analysis of popular trends

[1107] The server automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet and analyzes it to identify trending elements.

[1108] Creating a film project

[1109] The server uses a generative AI to combine user data, emotional data, and current trends to generate original movie concepts. These concepts include genre, story setting, and main characters. The generated movie concepts are stored in a database and sent back to the generative AI.

[1110] The creation of a film

[1111] The AI ​​generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection. It also generates films in various formats such as live-action, animation, special effects, and CGI, and saves them as video data.

[1112] Movie preservation and distribution

[1113] The server stores the generated movie data and prepares it for streaming. It generates and displays a viewing link on the user's My Page.

[1114] Watching and sharing movies

[1115] The device allows the user to click the provided viewing link and watch the movie. It then displays an option for the user to share the movie with their followers. The user can then share the viewing link with their followers.

[1116] Specific example

[1117] For example, if user B inputs that they like movies in the "comedy" and "romance" genres, the system will generate an original movie incorporating the latest trends in comedy romance films. User B can watch the generated movie on their smartphone and, if necessary, send scene change requests to customize specific scenes to their liking. The following example prompts can also be used to input data into the generation AI model.

[1118] "User movie preferences: Comedy and Romance"

[1119] User's favorite actor: A specific actor

[1120] Latest trends: Romantic happenings and funny events

[1121] User sentiment data: Mostly smiles

[1122] Based on this data, please create a hilarious romantic comedy film.

[1123] This invention enables users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie-watching experience.

[1124] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1125] Step 1:

[1126] When the application is launched, the device displays an input form regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the requested information and presses the submit button. The input in this step is the user's personal information and preferences, and the device sends this data to the server as output.

[1127] Step 2:

[1128] The device collects data including user operation logs and application operation behavior. Information such as which movies the user watched and which trailers they viewed is collected. This data is temporarily stored on the device and then sent to the server. The input is user operation data, and this is sent to the server as output.

[1129] Step 3:

[1130] The server stores the collected user data in a database. This stored data is used for subsequent processing. The input is user data sent from the terminal, and the output is stored in the database.

[1131] Step 4:

[1132] The device captures the user's facial expressions and voice through its camera and microphone, and sends this data to the emotion engine. The input is the user's face and voice data, and the output is sent to the emotion engine.

[1133] Step 5:

[1134] The emotion engine analyzes the user's facial expressions and voice to generate emotion data. This analysis is performed using machine learning algorithms. The input is the user's face and voice data, and the output is generated emotion data.

[1135] Step 6:

[1136] The server stores this emotion data in a database. The input is emotion data sent from the emotion engine, and the output is stored in the database.

[1137] Step 7:

[1138] The server automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet and analyzes it to identify trending elements. This process uses web scraping and data analysis techniques. The input is trend data from the internet, and the output is the analyzed trending elements.

[1139] Step 8:

[1140] The server uses a generative AI to combine user data, sentiment data, and current trends to generate original film proposals. These proposals include genre, story setting, and main characters. The input is user data, sentiment data, and current trends, and the output is a film proposal.

[1141] Step 9:

[1142] The AI ​​generator automatically produces a detailed scenario based on the content of a film project. This includes the script, casting, location selection, and music selection. It also generates the film in various formats such as live-action, animation, special effects, and CG, and saves it as video data. The input is film project data, and the output is the scenario and video data.

[1143] Step 10:

[1144] The server stores the generated movie data and prepares it for streaming. The input is the generated movie data, and the output is a viewing link.

[1145] Step 11:

[1146] The device plays the movie when the user clicks on the provided viewing link. The input is the viewing link, and the output is the movie being played.

[1147] Step 12:

[1148] The device displays options for the user to share a movie with their followers. The user can share a viewing link with their followers. The input is the viewing link, and the output is sharing with followers.

[1149] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1150] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1151] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1152] [Third Embodiment]

[1153] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1154] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1155] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1156] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1157] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1158] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1159] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1160] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1161] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1162] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1163] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1164] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1165] This invention provides a system that creates original films incorporating popular trends based on user preferences, attributes, tastes, app operation behavior, and survey results, and allows users and their followers to watch these films. The program processing of this system is described below in natural language.

[1166] Basic System Configuration

[1167] User data entry

[1168] 1. Terminal: When a user launches the application, an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[1169] 2. User: Enter the specified information.

[1170] Data collection and storage

[1171] 3. Device: Continuously records user activity logs and collects them as application operation behavior. For example, it records which movies the user watched, which trailers they viewed, etc.

[1172] 4. Server: Stores collected user data in a database.

[1173] Analysis of popular trends

[1174] 5. Server: Collects the latest movie trend data from the internet. This includes popular movies, notable actors, trending themes, etc.

[1175] 6. Server: Analyzes collected trend data and identifies trending elements.

[1176] Creating a film project

[1177] 7. Server: An analytical AI combines user data with current trends to generate original movie concepts. These concepts include genre, story setting, and main characters.

[1178] 8. Server: Saves the generated film proposals to the database and sends them to the generation AI.

[1179] The creation of a film

[1180] 9. Generating AI: Automatically generates detailed scenarios based on film proposals. This includes scriptwriting, casting, location scouting, and music selection.

[1181] 10. Generative AI: Creates films in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[1182] Movie preservation and distribution

[1183] 11. Server: Stores the generated movie data and prepares it for streaming.

[1184] 12. Server: Generates and displays a viewing link on the user's My Page.

[1185] Watching and sharing movies

[1186] 13. Device: User A can click the provided viewing link and watch the movie.

[1187] 14. Terminal: Displays options for User A to share a movie with their followers.

[1188] 15. User: Share the viewing link with your followers.

[1189] Profit calculation and distribution

[1190] 16. Server: Records the viewing history and advertising revenue of generated movies.

[1191] 17. Server: Revenue is distributed 1:1 between User A and the site operator and reflected in the user's account.

[1192] Movie customization

[1193] 18. Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[1194] 19. User: Enter a movie change request and pay the corresponding fee.

[1195] 20. Server: Notifies the generation AI of the request content and regenerates the movie script and direction.

[1196] 21. Server: Upload the regenerated movie to the streaming server so that users and followers can watch it again.

[1197] Specific example

[1198] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates a movie concept that includes popular heroes and magical elements. The generating AI creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. If user A watches the movie and wants to add new scenes, they can submit a change request via prompt payment and enjoy the regenerated movie.

[1199] The above describes the embodiments for carrying out the present invention. The present invention enables users to easily create, view, and share original movies optimized for themselves.

[1200] The following describes the processing flow.

[1201] Step 1:

[1202] Device: After launching the app, an input form will be displayed regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[1203] Step 2:

[1204] User: Enter the specified information and press the submit button.

[1205] Step 3:

[1206] Terminal: Sends the entered user information to the server.

[1207] Step 4:

[1208] Server: Stores the received user information in the database.

[1209] Step 5:

[1210] Device: Records user actions within the app (which movies were watched, which trailers were viewed) and collects this data as app operation behavior.

[1211] Step 6:

[1212] Server: Receives application operation behavior and saves it to the database.

[1213] Step 7:

[1214] Terminal: Displays a survey to the user and collects responses.

[1215] Step 8:

[1216] User: Answers the survey and presses the submit button.

[1217] Step 9:

[1218] Terminal: Sends survey responses to the server.

[1219] Step 10:

[1220] Server: Saves survey results to the database.

[1221] Step 11:

[1222] Server: Automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet.

[1223] Step 12:

[1224] Server: Analyzes collected trend data and identifies trending elements.

[1225] Step 13:

[1226] Server: An analytical AI combines user data with current trends to generate original movie concepts.

[1227] Step 14:

[1228] Server: Saves the generated film proposals to a database and sends them to the generation AI.

[1229] Step 15:

[1230] Generating AI: Automatically generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection.

[1231] Step 16:

[1232] Generative AI: Generates movies in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[1233] Step 17:

[1234] Server: Uploads the generated movie data to the streaming server.

[1235] Step 18:

[1236] Server: Generates and displays a viewing link on the user's My Page.

[1237] Step 19:

[1238] Device: User A clicks on the provided viewing link and watches the movie.

[1239] Step 20:

[1240] Terminal: Displays options for User A to share a movie with their followers.

[1241] Step 21:

[1242] User: Share the viewing link with your followers.

[1243] Step 22:

[1244] Server: Records the viewing history of shared movies and collects revenue data.

[1245] Step 23:

[1246] Server: Revenue is distributed 1:1 between User A and the site operator and reflected in the user's account.

[1247] Step 24:

[1248] Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[1249] Step 25:

[1250] User: Enter a movie change request and pay the corresponding fee.

[1251] Step 26:

[1252] Terminal: Sends a request to the server.

[1253] Step 27:

[1254] Server: Notifies the generating AI of the request details.

[1255] Step 28:

[1256] Generative AI: Updates the movie by generating additional scenes and different endings.

[1257] Step 29:

[1258] Server: Uploads the updated movie to the streaming server and prepares it for distribution again.

[1259] Step 30:

[1260] Terminal: Allows User A and their followers to watch the regenerated movie.

[1261] (Example 1)

[1262] Next, we will describe Example 1. 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."

[1263] In the current film production process, it is difficult to create original films that reflect the individual preferences and attributes of users, making it challenging for films to fully meet user expectations. Furthermore, customizing the content and direction of films, as well as efficiently distributing revenue from the resulting films, is also difficult. Therefore, there is a need for a system that efficiently and easily creates, customizes, and distributes revenue from original films that reflect user wishes and preferences.

[1264] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1265] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for recording user operation logs; means for storing the collected user data in a database; means for collecting the latest movie trend data from the internet; means for analyzing the collected trend data to identify trend elements; means for generating customized movie plans based on user data and trend elements; means for storing the generated movie plans in a database and transmitting them to a generating AI model; means for generating detailed scenarios based on the generating AI model; means for creating movies in formats such as live-action, animation, special effects, and CG using the generating AI model and saving them as video data; means for saving the generated movie data and preparing it for streaming distribution; and means for generating and displaying viewing links on the user's My Page. This makes it possible to create, customize, and distribute revenue from movies that reflect the individual preferences and wishes of the user.

[1266] "User preferences, attributes, and tastes" refer to the specific demands and preferences that users have regarding movies, including genre, theme, and favorite actors.

[1267] "Operational behavior" refers to the actions and patterns a user exhibits when interacting with an application, including operational information such as which movies were watched or which trailers were viewed.

[1268] A "database" is a system for efficiently storing, managing, searching, and using collected user data and trend data.

[1269] "Methods for collecting the latest movie trend data from the internet" refers to the process of automatically obtaining the latest movie information from online resources such as movie review sites and social media.

[1270] "Trend elements" refer to characteristics such as themes, actors, and genres of movies that are generally popular with the public today.

[1271] A "generative AI model" is a program and algorithm that uses artificial intelligence to automatically generate movie plans and scripts.

[1272] A "detailed scenario" refers to a plan that includes specific elements such as the film's script, casting, filming locations, and music.

[1273] "Live-action, animation, special effects, and CG" are different formats and types of techniques used to produce films, each possessing its own unique visual expression.

[1274] "Preparing for streaming distribution" refers to the process of converting file formats and uploading to servers in order to make the generated movie viewable online.

[1275] A "viewing link" refers to a URL or access method that allows a user to watch a generated movie online.

[1276] A "customized film project" refers to a basic plan or proposal for a film that is specially designed to reflect user preferences and current trends.

[1277] "Regeneration" refers to the process of regenerating a movie that has already been created, based on a new request from the user.

[1278] This invention is a system that automatically generates original movies based on user preferences, attributes, tastes, app operation behavior, and current trends. A specific embodiment of this system is described below.

[1279] When a user launches the application, the device displays an input form for their preferences, attributes, and tastes. This includes their name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The device collects this information as the user enters it.

[1280] The collected data is recorded by the terminal along with the user's operation log. This includes information such as which movies the user watched and which trailers they viewed. This data is then stored in a database by the server. Relational databases such as MySQL or PostgreSQL are used for this database.

[1281] The server collects the latest movie trend data from the internet. This data is obtained from movie review sites and social media. The collected data is analyzed by analytical algorithms on the server to identify trending elements. This utilizes techniques such as natural language processing and data mining.

[1282] Next, the server uses analytical AI to combine user data and trending elements to generate a customized movie proposal. This proposal includes genre, story setting, main characters, and other elements. The generated movie proposal is stored in a database and sent to the generating AI model.

[1283] The generative AI model automatically generates a detailed scenario based on the received film proposal. This includes scriptwriting, casting, location scouting, and music selection. The AI ​​model then uses the model to create the film in various formats, such as live-action, animation, special effects, or CGI. The film, saved as video data, is then prepared for streaming distribution by a server.

[1284] Users can watch movies by accessing their personal page and clicking on a viewing link. The viewing page also has a sharing option, allowing users to share movies with their followers. Viewing history and advertising revenue for shared movies are recorded by the server, and these revenues are shared between the user and the site operator.

[1285] Additionally, users can request changes to the movie's content and direction using a prompt billing feature. Once a user enters a change request and pays the corresponding fee, the server notifies the generation AI model of the request, and the movie's script and direction are regenerated. The regenerated movie is uploaded to the streaming server and becomes available for viewing again by the user and their followers.

[1286] Specific example

[1287] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates a movie concept that includes popular heroes and magical elements. The generating AI model creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. If user A watches the movie and wants to add new scenes, they can submit a change request via prompt billing and enjoy the regenerated movie.

[1288] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1289] Step 1:

[1290] Launching the app and entering user information

[1291] Terminal: When a user launches the application, a form is displayed for them to enter their preferences, attributes, and tastes.

[1292] Input: User's name, age, gender, movie preferences (genre, theme, favorite actor, etc.).

[1293] Output: User-entered data on preferences, attributes, and tastes.

[1294] Specific operation: The terminal stores data in each field according to the user's input.

[1295] Step 2:

[1296] Recording user behavior

[1297] Terminal: Continuously records logs of user actions within the application.

[1298] Input: User actions (movies watched, trailers viewed, etc.).

[1299] Output: Operation log data.

[1300] Specific operation: The device saves user actions such as taps, clicks, and scrolls to a log file.

[1301] Step 3:

[1302] Data storage

[1303] Server: Stores collected user data and operation logs in a database.

[1304] Input: Data on preferences, attributes, and actions.

[1305] Output: User information and operation logs stored in the database.

[1306] Specific operation: The server issues an INSERT statement to the database and persists the data.

[1307] Step 4:

[1308] Collection and analysis of trending elements

[1309] Server: Collects and analyzes the latest movie trend data from the internet.

[1310] Input: Trend data obtained from movie review sites and social media.

[1311] Output: Analyzed trend elements.

[1312] Specific operation: A crawler periodically collects data from websites, and an analysis algorithm on the server processes that data using natural language processing.

[1313] Step 5:

[1314] Creating a film project

[1315] Server: Combines user data and trending elements to generate customized movie concepts.

[1316] Input: User data, operation logs, analyzed trending factors.

[1317] Output: Film project data (genre, story setting, main characters, etc.).

[1318] Specific operation: An analytical AI on the server creates a movie plot based on the user's preferences and the latest trends.

[1319] Step 6:

[1320] Scenario and film generation

[1321] Generative AI Model: Automatically generates detailed scenarios based on generated film plans and creates films.

[1322] Input: Film project data.

[1323] Output: Video data of the completed film.

[1324] Specific operation: The generation AI model automatically handles scriptwriting, casting, location selection, music selection, etc., and generates the film in CG, animation, and live-action formats.

[1325] Step 7:

[1326] Saving movie data and preparing for streaming

[1327] Server: Stores the generated movie data and prepares it for streaming.

[1328] Input: Video data of the completed film.

[1329] Output: Movie data prepared for streaming.

[1330] Specific operation: Convert movie data to the appropriate format and upload it to the streaming server.

[1331] Step 8:

[1332] Generating and displaying viewing links

[1333] Server: Generates and displays a viewing link on the user's My Page.

[1334] Input: Movie data prepared for streaming, user account information.

[1335] Output: The viewing link displayed on your My Page.

[1336] Specific operation: The server generates a unique viewing link for the user and displays it on the user's My Page.

[1337] Step 9:

[1338] Watch and share movies

[1339] Device: Users can watch generated movies and share them with their followers if desired.

[1340] Input: The viewing link displayed on your My Page.

[1341] Output: Viewing history, sharing information.

[1342] Specific actions: The user clicks the link to play the movie and uses the sharing option to send the link to their followers.

[1343] Step 10:

[1344] Profit calculation and distribution

[1345] Server: Records viewing history and advertising revenue, and distributes it to users and operators.

[1346] Input: Viewing history data, advertising revenue data.

[1347] Output: Distributed revenue information.

[1348] Specific operation: The server uses revenue data to reflect the revenue in the user and operator accounts.

[1349] Step 11:

[1350] Movie customization

[1351] Terminal: Accepts requests for changes to movie content and presentation via prompt payment.

[1352] Input: User request details, billing information.

[1353] Output: Regenerated movie data based on the request.

[1354] Specific operation: The user fills out a change request and submits billing information. The request is sent to the server, and the generation AI model generates the movie again.

[1355] (Application Example 1)

[1356] Next, we will explain Application Example 1. In the following explanation, 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."

[1357] Traditional content distribution services struggle to provide original films tailored to individual user preferences, and it's also difficult for users to request and modify the content or direction of films themselves. Furthermore, easily creating and making available original films compatible with virtual reality viewing environments is another challenge.

[1358] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1359] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for analyzing current trends; means for generating customized movie plans based on the user data and trends; means for generating a movie based on the generated movie plan; means for making the generated movie viewable by the user and their followers; and means for making the generated movie viewable in a virtual reality environment. This makes it possible to easily generate original movies optimized for the user's individual preferences and enjoy them in a virtual reality environment.

[1360] "User data" refers to information about a user's wishes, attributes, preferences, and operational behavior.

[1361] "Trend elements" refer to data on the latest trends collected from the internet and other sources.

[1362] A "customized film project" is a film project proposal that is individually designed based on user data and trending elements.

[1363] "Means of creating films" refers to the technology of creating visuals in various formats such as live-action, animation, special effects, and computer graphics based on a customized film project.

[1364] A "virtual reality environment" is a virtual visual world that users can experience using VR head-mounted displays or other VR devices.

[1365] "Available for viewing" means that the generated film is provided to users and followers in a form that is accessible online.

[1366] "Request details" refer to specific changes that the user would like to see made to the content or direction of the film.

[1367] "Method of regeneration" refers to a technology that regenerates already created movies based on user requests.

[1368] The "means of revenue distribution" refer to a system that distributes the revenue generated between users and operators based on the viewing history of the movies that have been produced.

[1369] System Overview

[1370] This invention is a system that collects user wishes, attributes, preferences, and operational behaviors, combines them with current trends to generate customized movies, and makes them viewable in a virtual reality environment.

[1371] Hardware and software to be used

[1372] Hardware: Smartphones, VR head-mounted displays (e.g., Oculus Quest 2)

[1373] Software: Flask (web framework), Python (programming language), generative AI model

[1374] Data collection and storage

[1375] 1. Device (smartphone or VR device):

[1376] When a user launches the application, an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor).

[1377] 2. User:

[1378] Enter the specified information.

[1379] 3. Server:

[1380] The system continuously records user activity logs and collects them as application operation behavior. For example, it records which movies a user watched, which trailers they viewed, and so on.

[1381] Analysis of popular trends

[1382] 4. Server:

[1383] We collect the latest movie trend data from the internet. This includes popular movies, notable actors, and trending themes.

[1384] 5. Server:

[1385] We analyze collected trend data to identify trending elements.

[1386] Film planning and creation

[1387] 6. Server:

[1388] An analytical AI combines user data with current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[1389] 7. Server:

[1390] Using a generative AI model, detailed scenarios are automatically generated based on the plan.

[1391] 8. Server:

[1392] We create films in various formats such as live-action, animation, special effects, and CGI, and save them as video data.

[1393] Watch and customize movies

[1394] 9. Server:

[1395] The generated movie data is saved and prepared for streaming distribution.

[1396] 10. Terminal:

[1397] Users can watch the movie by clicking on the provided viewing link.

[1398] 11. Server:

[1399] It provides an interface for users to request specific content and direction for the film.

[1400] 12. Generative AI Models:

[1401] Based on the requested content, we will regenerate the movie's script and direction.

[1402] 13. Server:

[1403] The regenerated movie data is uploaded to a streaming server, allowing users and followers to watch it again.

[1404] Specific example

[1405] For example, if the user prefers "Actions" and "Magic," enter the following prompt:

[1406] "User ID: user123"

[1407] Genre: Action

[1408] "Theme: Magic"

[1409] Based on this prompt, the server generates movie recommendations tailored to the user's preferences and creates movie data using a generation AI model. The generated movies are provided to the user via a link, and the user can watch them using a smartphone or VR head-mounted display.

[1410] In this way, this system can easily generate original movies optimized to the user's individual preferences, allowing them to be viewed and enjoyed in a virtual reality environment. This provides a personalized experience that was difficult to achieve with conventional content distribution services.

[1411] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1412] Step 1:

[1413] Terminal:

[1414] The user launches the application, and an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor).

[1415] Input: Name, age, gender, movie preferences

[1416] Output: User input data

[1417] Step 2:

[1418] User:

[1419] Enter the desired information and submit the form.

[1420] Input: Input form

[1421] Output: User data (name, age, gender, movie preferences)

[1422] Step 3:

[1423] server:

[1424] The system continuously records user activity logs (which movies were watched, which trailers were viewed) and saves them to a database as application operation behavior.

[1425] Input: User data and operation logs

[1426] Output: Operation history data

[1427] Step 4:

[1428] server:

[1429] Collect the latest movie trend data from the internet (popular movies, notable actors, trending themes, etc.).

[1430] Input: Trending information on the internet

[1431] Output: Trend Data

[1432] Step 5:

[1433] server:

[1434] We analyze collected trend data to identify trending elements.

[1435] Input: Trend data

[1436] Output: Identified trend elements

[1437] Step 6:

[1438] server:

[1439] The analytical AI combines user data and trending elements to generate original movie concepts (genre, story setting, main characters).

[1440] Input: User data, trending topics

[1441] Output: Film project data

[1442] Step 7:

[1443] server:

[1444] The generative AI model automatically generates detailed scenarios based on film project data.

[1445] Input: Film project data

[1446] Output: Detailed Scenario

[1447] Step 8:

[1448] Generative AI models:

[1449] We create films in various formats such as live-action, animation, special effects, and CGI, and save them as video data.

[1450] Input: Detailed Scenario

[1451] Output: Video data

[1452] Step 9:

[1453] server:

[1454] The generated movie data is saved, and a link for streaming is generated.

[1455] Input: Video data

[1456] Output: Viewing link

[1457] Step 10:

[1458] Terminal:

[1459] Users click on the provided viewing link and watch the movie using their smartphone or VR head-mounted display.

[1460] Input: Viewing link

[1461] Output: Movie playback

[1462] Step 11:

[1463] server:

[1464] It provides an interface for users to request specific content and direction for the film.

[1465] Input: User Request

[1466] Output: Request details

[1467] Step 12:

[1468] Generative AI models:

[1469] Based on user requests, the system regenerates movie scripts and direction.

[1470] Input: Request details

[1471] Output: Regenerated movie script

[1472] Step 13:

[1473] server:

[1474] The regenerated movie data is uploaded to a streaming server, allowing users and followers to watch it again.

[1475] Input: Regenerated movie script, video data

[1476] Output: Regenerated movie viewing link

[1477] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1478] This invention is a system that creates original films incorporating popular trends based on users' wishes, attributes, preferences, app operation behavior, survey results, and emotions, and allows users and their followers to watch these films. Furthermore, it regenerates films according to user requests regarding content and direction, and distributes the revenue. The program processing of this system is described below in natural language.

[1479] Basic System Configuration

[1480] User data entry

[1481] 1. Terminal: When the application is launched, an input form will be displayed regarding the user's wishes, attributes, and preferences. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[1482] 2. User: Enter the specified information and press the submit button.

[1483] Data collection and storage

[1484] 3. Device: Collects data including user operation logs and app operation behavior. This includes which movies the user watched and which trailers they viewed.

[1485] 4. Server: Stores collected user data in a database.

[1486] emotion recognition

[1487] 5. Device: Captures the user's facial expressions and voice through the camera and microphone and sends them to the emotion engine.

[1488] 6. Emotion Engine: Analyzes the user's facial expressions and voice to generate emotion data.

[1489] 7. Server: Stores the emotion data sent from the emotion engine in the database.

[1490] Analysis of popular trends

[1491] 8. Server: Automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet.

[1492] 9. Server: Analyzes collected trend data and identifies trending elements.

[1493] Creating a film project

[1494] 10. Server: An analytical AI combines user data, sentiment data, and current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[1495] 11. Server: Saves the generated film proposals to the database and sends them to the generation AI.

[1496] The creation of a film

[1497] 12. Generating AI: Automatically generates a detailed scenario based on the content of the film project. This includes scriptwriting, casting, location selection, and music selection.

[1498] 13. Generative AI: Generates films in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[1499] Movie preservation and distribution

[1500] 14. Server: Stores the generated movie data and prepares it for streaming.

[1501] 15. Server: Generates and displays a viewing link on the user's My Page.

[1502] Watching and sharing movies

[1503] 16. Device: The user clicks the provided viewing link to watch the movie.

[1504] 17. Device: Displays options for users to share movies with their followers.

[1505] 18. User: Share the viewing link with your followers.

[1506] Profit calculation and distribution

[1507] 19. Server: Records the viewing history and advertising revenue of generated movies.

[1508] 20. Server: Distributes revenue 1:1 between users and site operators and reflects it in the user's account.

[1509] Movie customization

[1510] 21. Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[1511] 22. User: Enter a movie change request and pay the corresponding fee.

[1512] 23. Terminal: Sends the request to the server.

[1513] 24. Server: Notifies the generating AI of the request details.

[1514] 25. Generating AI: Updates the movie by generating additional scenes and different endings.

[1515] 26. Server: Upload the updated movie to the streaming server and prepare it for distribution again.

[1516] 27. Device: Allow users and followers to watch the regenerated movie.

[1517] Specific example

[1518] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates movie proposals that include popular hero and magical elements. The generating AI creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. Furthermore, an emotion engine analyzes the user's emotions while they are watching, and this data is used when generating future movie proposals, resulting in a more personalized movie.

[1519] This invention enables users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie-watching experience.

[1520] The following describes the processing flow.

[1521] Step 1:

[1522] Terminal: When the application is launched, it displays an input form regarding the user's wishes, attributes, and preferences. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[1523] Step 2:

[1524] User: Enter the specified information and press the submit button.

[1525] Step 3:

[1526] Terminal: Sends the entered user information to the server.

[1527] Step 4:

[1528] Server: Stores the received user information in the database.

[1529] Step 5:

[1530] Device: Records user activity logs and app operation behavior, collecting information such as which movies were watched and which trailers were viewed.

[1531] Step 6:

[1532] Server: Stores collected application operation behaviors in a database.

[1533] Step 7:

[1534] Terminal: Displays a survey to the user and collects responses.

[1535] Step 8:

[1536] User: Answers the survey and presses the submit button.

[1537] Step 9:

[1538] Terminal: Sends survey responses to the server.

[1539] Step 10:

[1540] Server: Saves survey results to the database.

[1541] Step 11:

[1542] Device: Captures the user's facial expressions and voice through the camera and microphone, and sends them to the emotion engine.

[1543] Step 12:

[1544] Emotion Engine: Analyzes the user's facial expressions and voice to generate emotion data.

[1545] Step 13:

[1546] Server: Stores emotion data sent from the emotion engine in the database.

[1547] Step 14:

[1548] Server: Automatically collects the latest movie trend data from the internet. This includes popular movies, featured actors, trending themes, and more.

[1549] Step 15:

[1550] Server: Analyzes collected trend data and identifies trending elements.

[1551] Step 16:

[1552] Server: An analytical AI combines user data, sentiment data, and current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[1553] Step 17:

[1554] Server: Saves the generated film proposals to a database and sends them to the generation AI.

[1555] Step 18:

[1556] Generating AI: Automatically generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection.

[1557] Step 19:

[1558] Generative AI: Generates movies in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[1559] Step 20:

[1560] Server: Stores the generated movie data and prepares it for streaming.

[1561] Step 21:

[1562] Server: Generates and displays a viewing link on the user's My Page.

[1563] Step 22:

[1564] Device: The user clicks the provided viewing link to watch the movie.

[1565] Step 23:

[1566] Device: Displays options for users to share movies with their followers.

[1567] Step 24:

[1568] User: Share the viewing link with your followers.

[1569] Step 25:

[1570] Server: Records the viewing history of shared movies and collects revenue data.

[1571] Step 26:

[1572] Server: Revenue is distributed 1:1 between users and site operators and reflected in the user's account.

[1573] Step 27:

[1574] Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[1575] Step 28:

[1576] User: Enter a movie change request and pay the corresponding fee.

[1577] Step 29:

[1578] Terminal: Sends a request to the server.

[1579] Step 30:

[1580] Server: Notifies the generating AI of the request details.

[1581] Step 31:

[1582] Generative AI: Updates the movie by generating additional scenes and different endings.

[1583] Step 32:

[1584] Server: Uploads the updated movie to the streaming server and prepares it for distribution again.

[1585] Step 33:

[1586] Device: Allows users and followers to watch the regenerated movie.

[1587] (Example 2)

[1588] Next, we will describe Example 2. 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."

[1589] Traditional film creation systems have struggled to automatically generate films that fully reflect the individual preferences and emotions of users. Furthermore, customizing films according to user requests and ensuring a fair distribution of revenue from generated films have been difficult. As a result, improving the user experience and optimizing revenue have been insufficient.

[1590] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1591] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for emotion recognition that captures the user's facial expressions and voice using a camera and microphone and analyzes their emotions; and means for collecting and analyzing movie trend data from the internet. This enables the automatic generation of more personalized movies that reflect the user's individual preferences, emotions, and the latest trending elements. The server also includes means for distributing the viewing history and revenue of the generated movies between the user and the operator, and means for providing a prompt billing function. This enables the customization of movies according to the user's requests and fair revenue distribution.

[1592] "Data relating to user preferences, attributes, tastes, and operational behavior" refers to information entered by the user into the system, such as name, age, gender, preferences for movie genres and themes, and viewing history of movies and trailers.

[1593] "Emotion recognition means" refers to technology that uses cameras and microphones to capture the user's facial expressions and voice, analyzes them, and generates emotional data such as positive, negative, and neutral.

[1594] "Movie trend data" refers to information collected from the internet about the latest popular movies, notable actors, trending themes, and more.

[1595] "Film planning" refers to the initial design of a film, including its genre, story setting, and main characters, which is generated based on user data and trend data.

[1596] "Generative AI" refers to artificial intelligence that automatically generates detailed scenarios based on film concepts and then produces films in various formats such as live-action, animation, special effects, and CGI.

[1597] "Means of making the content viewable by users and followers" refers to technologies that save the generated movie data, create a viewing link to display on the user's profile page, and enable streaming playback of the movie.

[1598] "Means for recording viewing history and advertising revenue" refers to technology that records in a database the history of movies a user has watched and the revenue generated from advertisements displayed during movie viewing.

[1599] A "payment gateway" refers to an online payment system that securely processes the payment a user makes for their movie request.

[1600] "Prompt billing" refers to a billing technology that allows users to pay a fee when they request changes to the content or presentation of a movie.

[1601] This invention is a system that creates original films incorporating popular trends based on users' wishes, attributes, preferences, operational behavior, survey results, and emotions, and allows users and their followers to watch these films. Furthermore, it is possible to regenerate films according to user requests regarding content and direction, and distribute the revenue. The following describes specific embodiments of this system.

[1602] Basic System Configuration

[1603] This system consists of a user terminal, a server that processes and stores data, and a generative AI that generates movies.

[1604] User data entry

[1605] 1. When the device launches the application, an input form will appear regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the information and clicks the submit button. For example, they might enter, "I like action movies, especially those with sci-fi elements."

[1606] Data collection and storage

[1607] 2. The device collects real-time activity logs, such as which movies the user watched and which trailers they viewed. This data is sent to a server and stored in a database.

[1608] emotion recognition

[1609] 3. The device uses its camera and microphone to capture the user's facial expressions and voice, and sends them to the emotion analysis engine. The emotion engine uses OpenCV and Deep Learning models to analyze the user's emotions and generates emotion data such as positive, negative, and neutral. This emotion data is sent to a server and stored in a database.

[1610] Analysis of popular trends

[1611] 4. The server uses web crawling technologies (e.g., BeautifulSoup or Scrapy) to collect the latest movie trend data from the internet. This data is analyzed using natural language processing technologies (e.g., NLTK or SpaCy) to identify trending elements.

[1612] Creating a film project

[1613] 5. An analysis AI on the server (using, for example, TensorFlow or PyTorch) combines user data, sentiment data, and trending elements to generate a movie concept. This movie concept includes genre, story setting, main characters, etc.

[1614] The creation of a film

[1615] 6. The generative AI generates a detailed scenario based on the film project. This scenario includes the script, casting, location selection, and music selection. The generative AI uses frameworks such as Unreal Engine and Unity to produce the film in various formats including live-action, animation, special effects, and CG, and the video data is stored in cloud storage.

[1616] Movie preservation and distribution

[1617] 7. The server stores the generated movie data in high-performance storage (e.g., AWS S3) and generates metadata for streaming. A viewing link is generated and displayed on the user's My Page.

[1618] Watching and sharing movies

[1619] 8. The device prompts the user to click a viewing link and streams the movie. Streaming technologies such as HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) are used. Users can share the viewing link with their followers by clicking the share button, and share the movie via social media and messaging apps.

[1620] Profit calculation and distribution

[1621] 9. The server records movie viewing history and advertising revenue. Revenue data is obtained from external advertising APIs (e.g., Google AdSense). The server distributes the revenue to users and site operators in a 1:1 ratio and reflects it in the user's account. Specifically, payments are made using payment gateways (e.g., Stripe or PayPal).

[1622] Movie customization

[1623] 10. The device provides a prompt billing function and displays a page where users can request changes to the movie's content or presentation. Users enter their requests and pay the corresponding fees through a payment gateway. The requests are notified to the generation AI via the server. The generation AI regenerates the movie based on the requested changes (e.g., additional scenes or a different ending) and updates the movie data. The updated movie data is uploaded back to the streaming server and made available for viewing by the user and their followers.

[1624] Specific example

[1625] For example, if a user requests a "moving ending," the AI ​​will generate a new scene that replaces the current movie's ending. This modified movie will then reappear on the user's profile page and become available for viewing. Based on the user's emotional data and viewing history, this modified movie will be reused when generating future movie projects.

[1626] As described above, the present invention allows users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie viewing experience.

[1627] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1628] Step 1:

[1629] When the device launches the application, an input form is displayed that asks about the user's preferences, attributes, and tastes. The input form includes fields such as name, age, gender, movie genre, theme, and favorite actor. The user enters information into these fields and clicks the submit button. The entered data is sent from the device to the server in JSON format. The sent data becomes a JSON object containing the user's personal information and preference information.

[1630] Step 2:

[1631] The terminal collects user activity logs. This includes activity data such as which movies the user watched and which trailers they viewed. The terminal saves this activity data to a log file in real time and sends it to the server as a batch process at regular intervals. The server analyzes the received log data and stores it in a database as user-specific data. Here, the input is the activity log, and the output is user-specific activity data.

[1632] Step 3:

[1633] The device uses its camera and microphone to capture the user's facial expressions and voice. The resulting video and audio data is sent to the server. The input data consists of the user's facial expressions and voice, which the emotion engine analyzes to generate emotion data (positive, negative, neutral, etc.). The generated emotion data is stored on the server. The output is the analyzed emotion data.

[1634] Step 4:

[1635] The server uses web crawling technology to collect the latest movie trend data from the internet. This includes popular movies, notable actors, and trending themes. The server analyzes the collected trend data using natural language processing technology to identify current trend elements. The data input is trend information collected from the web, and the output is the analyzed trend elements.

[1636] Step 5:

[1637] An analytical AI on the server generates a movie concept by combining user data, sentiment data, and trend data. This movie concept includes genre, story setting, main characters, and other elements. The input is user data and trend data, and the output is a specific movie concept. The server stores this concept data in a database and sends it to the generating AI.

[1638] Step 6:

[1639] The generative AI automatically generates a detailed scenario based on a film project proposal. This scenario includes the script, casting, location selection, and music selection. The input is a film project proposal, and the output is a detailed scenario. Based on the generated scenario, the generative AI uses tools such as Unreal Engine or Unity to create the film, and saves the final video data to cloud storage.

[1640] Step 7:

[1641] The server saves the generated movie data to high-performance storage (e.g., AWS S3) and generates metadata for streaming. The output is a viewing link, which is displayed on the user's My Page on their device. The input here is the completed video data.

[1642] Step 8:

[1643] The device prompts the user to click a viewing link, and the movie is streamed. Streaming technologies such as HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) are used. The input is the viewing link, and the output is the movie being played. The user clicks a share button to share the viewing link with their followers, spreading the movie through social media and messaging apps.

[1644] Step 9:

[1645] The server records movie viewing history and advertising revenue. Revenue data is obtained from an external advertising API. Based on the aggregated information, the server distributes the revenue to the user and the site operator in a 1:1 ratio and reflects it in the user's account. The input is viewing history and advertising revenue data, and the output is the distributed revenue.

[1646] Step 10:

[1647] The device provides a prompt billing function and displays a page where the user can request changes to the movie's content or presentation. The user enters their request and pays the fee through a payment gateway. The device sends the request and payment information to the server. The server notifies the generation AI of the request, and the generation AI regenerates the movie reflecting the requested changes. The regenerated movie is saved to cloud storage, and the viewing link is displayed again on the device's My Page. The input is the user's request and payment information, and the output is the updated movie data and viewing link.

[1648] (Application Example 2)

[1649] Next, we will explain application example 2. In the following explanation, 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."

[1650] In recent years, the diversification of entertainment has led to a growing demand for customized films tailored to individual preferences and emotions. However, a system that efficiently generates films that reflect user preferences, emotions, and operational behavior in real time, and distributes revenue based on these films, still does not exist. This invention aims to solve these problems and provide a system that enables the generation, viewing, and sharing of films optimized for individual users.

[1651] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data relating to the user's wishes, attributes, preferences, and operational behavior; means for analyzing popular trends; means for generating a customized movie plan based on the user data and popular trends; means for generating a movie based on the generated movie plan; means for making the generated movie viewable by the user and followers; means for recognizing the user's emotions and generating and storing emotion data; and means for providing the user with a viewing link to the generated movie. This enables the generation of customized movies based on the user's preferences and emotions, as well as efficient viewing and sharing.

[1652] "User preferences" refer to specific requirements that users have for movies, such as genres, themes, and favorite actors.

[1653] "Attributes" refer to personal background information of the user, such as age, gender, occupation, and hobbies.

[1654] "Preferences" refer to the genres and themes of movies that a user enjoys, as well as their preferences and interests in the types of movies that have been produced.

[1655] "Operational behavior" refers to the actions and patterns of operation that a user exhibits while using an application.

[1656] "Popular trends" refer to the latest movie trends, popular actors, and trending themes and storylines, gathered from the internet and other sources.

[1657] A "customized film project" refers to a film story and setting that is specially designed based on individual user data and trending elements.

[1658] "Means of producing a film" refers to the processes and systems used to create films in various formats, such as live-action, animation, special effects, and computer graphics, based on a generated film project.

[1659] "Emotional data" refers to emotional information analyzed from the user's facial expressions and voice.

[1660] A "viewing link" refers to a URL or access method provided for viewing a generated movie online.

[1661] "Followers" refer to other users who track a specific user online and view their activities and shared content.

[1662] This invention relates to a system that creates an original film incorporating popular trends based on the user's wishes, attributes, preferences, operational behavior, survey results, and emotions, and allows the user and their followers to watch this film. Specific embodiments are described below.

[1663] Basic System Configuration

[1664] User data entry

[1665] When the application is launched, the device displays an input form regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the requested information and presses the submit button.

[1666] Data collection and storage

[1667] The device collects data including user activity logs and app operation behavior. This includes information such as which movies the user watched and which trailers they viewed. The server stores the collected user data in a database.

[1668] emotion recognition

[1669] The device captures the user's facial expressions and voice through its camera and microphone and sends this data to the emotion engine. The emotion engine analyzes the user's emotions from their facial expressions and voice and generates emotion data. The server stores this emotion data in a database.

[1670] Analysis of popular trends

[1671] The server automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet and analyzes it to identify trending elements.

[1672] Creating a film project

[1673] The server uses a generative AI to combine user data, emotional data, and current trends to generate original movie concepts. These concepts include genre, story setting, and main characters. The generated movie concepts are stored in a database and sent back to the generative AI.

[1674] The creation of a film

[1675] The AI ​​generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection. It also generates films in various formats such as live-action, animation, special effects, and CGI, and saves them as video data.

[1676] Movie preservation and distribution

[1677] The server stores the generated movie data and prepares it for streaming. It generates and displays a viewing link on the user's My Page.

[1678] Watching and sharing movies

[1679] The device allows the user to click the provided viewing link and watch the movie. It then displays an option for the user to share the movie with their followers. The user can then share the viewing link with their followers.

[1680] Specific example

[1681] For example, if user B inputs that they like movies in the "comedy" and "romance" genres, the system will generate an original movie incorporating the latest trends in comedy romance films. User B can watch the generated movie on their smartphone and, if necessary, send scene change requests to customize specific scenes to their liking. The following example prompts can also be used to input data into the generation AI model.

[1682] "User movie preferences: Comedy and Romance"

[1683] User's favorite actor: A specific actor

[1684] Latest trends: Romantic happenings and funny events

[1685] User sentiment data: Mostly smiles

[1686] Based on this data, please create a hilarious romantic comedy film.

[1687] This invention enables users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie-watching experience.

[1688] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1689] Step 1:

[1690] When the application is launched, the device displays an input form regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the requested information and presses the submit button. The input in this step is the user's personal information and preferences, and the device sends this data to the server as output.

[1691] Step 2:

[1692] The device collects data including user operation logs and application operation behavior. Information such as which movies the user watched and which trailers they viewed is collected. This data is temporarily stored on the device and then sent to the server. The input is user operation data, and this is sent to the server as output.

[1693] Step 3:

[1694] The server stores the collected user data in a database. This stored data is used for subsequent processing. The input is user data sent from the terminal, and the output is stored in the database.

[1695] Step 4:

[1696] The device captures the user's facial expressions and voice through its camera and microphone, and sends this data to the emotion engine. The input is the user's face and voice data, and the output is sent to the emotion engine.

[1697] Step 5:

[1698] The emotion engine analyzes the user's facial expressions and voice to generate emotion data. This analysis is performed using machine learning algorithms. The input is the user's face and voice data, and the output is generated emotion data.

[1699] Step 6:

[1700] The server stores this emotion data in a database. The input is emotion data sent from the emotion engine, and the output is stored in the database.

[1701] Step 7:

[1702] The server automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet and analyzes it to identify trending elements. This process uses web scraping and data analysis techniques. The input is trend data from the internet, and the output is the analyzed trending elements.

[1703] Step 8:

[1704] The server uses a generative AI to combine user data, sentiment data, and current trends to generate original film proposals. These proposals include genre, story setting, and main characters. The input is user data, sentiment data, and current trends, and the output is a film proposal.

[1705] Step 9:

[1706] The AI ​​generator automatically produces a detailed scenario based on the content of a film project. This includes the script, casting, location selection, and music selection. It also generates the film in various formats such as live-action, animation, special effects, and CG, and saves it as video data. The input is film project data, and the output is the scenario and video data.

[1707] Step 10:

[1708] The server stores the generated movie data and prepares it for streaming. The input is the generated movie data, and the output is a viewing link.

[1709] Step 11:

[1710] The device plays the movie when the user clicks on the provided viewing link. The input is the viewing link, and the output is the movie being played.

[1711] Step 12:

[1712] The device displays options for the user to share a movie with their followers. The user can share a viewing link with their followers. The input is the viewing link, and the output is sharing with followers.

[1713] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1714] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1715] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1716] [Fourth Embodiment]

[1717] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1718] As shown in Figure 7, the 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.

[1719] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1720] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1721] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1722] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1723] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1724] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1725] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1726] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1727] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1728] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1729] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1730] This invention provides a system that creates original films incorporating popular trends based on user preferences, attributes, tastes, app operation behavior, and survey results, and allows users and their followers to watch these films. The program processing of this system is described below in natural language.

[1731] Basic System Configuration

[1732] User data entry

[1733] 1. Terminal: When a user launches the application, an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[1734] 2. User: Enter the specified information.

[1735] Data collection and storage

[1736] 3. Device: Continuously records user activity logs and collects them as application operation behavior. For example, it records which movies the user watched, which trailers they viewed, etc.

[1737] 4. Server: Stores collected user data in a database.

[1738] Analysis of popular trends

[1739] 5. Server: Collects the latest movie trend data from the internet. This includes popular movies, notable actors, trending themes, etc.

[1740] 6. Server: Analyzes collected trend data and identifies trending elements.

[1741] Creating a film project

[1742] 7. Server: An analytical AI combines user data with current trends to generate original movie concepts. These concepts include genre, story setting, and main characters.

[1743] 8. Server: Saves the generated film proposals to the database and sends them to the generation AI.

[1744] The creation of a film

[1745] 9. Generating AI: Automatically generates detailed scenarios based on film proposals. This includes scriptwriting, casting, location scouting, and music selection.

[1746] 10. Generative AI: Creates films in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[1747] Movie preservation and distribution

[1748] 11. Server: Stores the generated movie data and prepares it for streaming.

[1749] 12. Server: Generates and displays a viewing link on the user's My Page.

[1750] Watching and sharing movies

[1751] 13. Device: User A can click the provided viewing link and watch the movie.

[1752] 14. Terminal: Displays options for User A to share a movie with their followers.

[1753] 15. User: Share the viewing link with your followers.

[1754] Profit calculation and distribution

[1755] 16. Server: Records the viewing history and advertising revenue of generated movies.

[1756] 17. Server: Revenue is distributed 1:1 between User A and the site operator and reflected in the user's account.

[1757] Movie customization

[1758] 18. Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[1759] 19. User: Enter a movie change request and pay the corresponding fee.

[1760] 20. Server: Notifies the generation AI of the request content and regenerates the movie script and direction.

[1761] 21. Server: Upload the regenerated movie to the streaming server so that users and followers can watch it again.

[1762] Specific example

[1763] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates a movie concept that includes popular heroes and magical elements. The generating AI creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. If user A watches the movie and wants to add new scenes, they can submit a change request via prompt payment and enjoy the regenerated movie.

[1764] The above describes the embodiments for carrying out the present invention. The present invention enables users to easily create, view, and share original movies optimized for themselves.

[1765] The following describes the processing flow.

[1766] Step 1:

[1767] Device: After launching the app, an input form will be displayed regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[1768] Step 2:

[1769] User: Enter the specified information and press the submit button.

[1770] Step 3:

[1771] Terminal: Sends the entered user information to the server.

[1772] Step 4:

[1773] Server: Stores the received user information in the database.

[1774] Step 5:

[1775] Device: Records user actions within the app (which movies were watched, which trailers were viewed) and collects this data as app operation behavior.

[1776] Step 6:

[1777] Server: Receives application operation behavior and saves it to the database.

[1778] Step 7:

[1779] Terminal: Displays a survey to the user and collects responses.

[1780] Step 8:

[1781] User: Answers the survey and presses the submit button.

[1782] Step 9:

[1783] Terminal: Sends survey responses to the server.

[1784] Step 10:

[1785] Server: Saves survey results to the database.

[1786] Step 11:

[1787] Server: Automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet.

[1788] Step 12:

[1789] Server: Analyzes collected trend data and identifies trending elements.

[1790] Step 13:

[1791] Server: An analytical AI combines user data with current trends to generate original movie concepts.

[1792] Step 14:

[1793] Server: Saves the generated film proposals to a database and sends them to the generation AI.

[1794] Step 15:

[1795] Generating AI: Automatically generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection.

[1796] Step 16:

[1797] Generative AI: Generates movies in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[1798] Step 17:

[1799] Server: Uploads the generated movie data to the streaming server.

[1800] Step 18:

[1801] Server: Generates and displays a viewing link on the user's My Page.

[1802] Step 19:

[1803] Device: User A clicks on the provided viewing link and watches the movie.

[1804] Step 20:

[1805] Terminal: Displays options for User A to share a movie with their followers.

[1806] Step 21:

[1807] User: Share the viewing link with your followers.

[1808] Step 22:

[1809] Server: Records the viewing history of shared movies and collects revenue data.

[1810] Step 23:

[1811] Server: Revenue is distributed 1:1 between User A and the site operator and reflected in the user's account.

[1812] Step 24:

[1813] Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[1814] Step 25:

[1815] User: Enter a movie change request and pay the corresponding fee.

[1816] Step 26:

[1817] Terminal: Sends a request to the server.

[1818] Step 27:

[1819] Server: Notifies the generating AI of the request details.

[1820] Step 28:

[1821] Generative AI: Updates the movie by generating additional scenes and different endings.

[1822] Step 29:

[1823] Server: Uploads the updated movie to the streaming server and prepares it for distribution again.

[1824] Step 30:

[1825] Terminal: Allows User A and their followers to watch the regenerated movie.

[1826] (Example 1)

[1827] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1828] In the current film production process, it is difficult to create original films that reflect the individual preferences and attributes of users, making it challenging for films to fully meet user expectations. Furthermore, customizing the content and direction of films, as well as efficiently distributing revenue from the resulting films, is also difficult. Therefore, there is a need for a system that efficiently and easily creates, customizes, and distributes revenue from original films that reflect user wishes and preferences.

[1829] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1830] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for recording user operation logs; means for storing the collected user data in a database; means for collecting the latest movie trend data from the internet; means for analyzing the collected trend data to identify trend elements; means for generating customized movie plans based on user data and trend elements; means for storing the generated movie plans in a database and transmitting them to a generating AI model; means for generating detailed scenarios based on the generating AI model; means for creating movies in formats such as live-action, animation, special effects, and CG using the generating AI model and saving them as video data; means for saving the generated movie data and preparing it for streaming distribution; and means for generating and displaying viewing links on the user's My Page. This makes it possible to create, customize, and distribute revenue from movies that reflect the individual preferences and wishes of the user.

[1831] "User preferences, attributes, and tastes" refer to the specific demands and preferences that users have regarding movies, including genre, theme, and favorite actors.

[1832] "Operational behavior" refers to the actions and patterns a user exhibits when interacting with an application, including operational information such as which movies were watched or which trailers were viewed.

[1833] A "database" is a system for efficiently storing, managing, searching, and using collected user data and trend data.

[1834] "Methods for collecting the latest movie trend data from the internet" refers to the process of automatically obtaining the latest movie information from online resources such as movie review sites and social media.

[1835] "Trend elements" refer to characteristics such as themes, actors, and genres of movies that are generally popular with the public today.

[1836] A "generative AI model" is a program and algorithm that uses artificial intelligence to automatically generate movie plans and scripts.

[1837] A "detailed scenario" refers to a plan that includes specific elements such as the film's script, casting, filming locations, and music.

[1838] "Live-action, animation, special effects, and CG" are different formats and types of techniques used to produce films, each possessing its own unique visual expression.

[1839] "Preparing for streaming distribution" refers to the process of converting file formats and uploading to servers in order to make the generated movie viewable online.

[1840] A "viewing link" refers to a URL or access method that allows a user to watch a generated movie online.

[1841] A "customized film project" refers to a basic plan or proposal for a film that is specially designed to reflect user preferences and current trends.

[1842] "Regeneration" refers to the process of regenerating a movie that has already been created, based on a new request from the user.

[1843] This invention is a system that automatically generates original movies based on user preferences, attributes, tastes, app operation behavior, and current trends. A specific embodiment of this system is described below.

[1844] When a user launches the application, the device displays an input form for their preferences, attributes, and tastes. This includes their name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The device collects this information as the user enters it.

[1845] The collected data is recorded by the terminal along with the user's operation log. This includes information such as which movies the user watched and which trailers they viewed. This data is then stored in a database by the server. Relational databases such as MySQL or PostgreSQL are used for this database.

[1846] The server collects the latest movie trend data from the internet. This data is obtained from movie review sites and social media. The collected data is analyzed by analytical algorithms on the server to identify trending elements. This utilizes techniques such as natural language processing and data mining.

[1847] Next, the server uses analytical AI to combine user data and trending elements to generate a customized movie proposal. This proposal includes genre, story setting, main characters, and other elements. The generated movie proposal is stored in a database and sent to the generating AI model.

[1848] The generative AI model automatically generates a detailed scenario based on the received film proposal. This includes scriptwriting, casting, location scouting, and music selection. The AI ​​model then uses the model to create the film in various formats, such as live-action, animation, special effects, or CGI. The film, saved as video data, is then prepared for streaming distribution by a server.

[1849] Users can watch movies by accessing their personal page and clicking on a viewing link. The viewing page also has a sharing option, allowing users to share movies with their followers. Viewing history and advertising revenue for shared movies are recorded by the server, and these revenues are shared between the user and the site operator.

[1850] Additionally, users can request changes to the movie's content and direction using a prompt billing feature. Once a user enters a change request and pays the corresponding fee, the server notifies the generation AI model of the request, and the movie's script and direction are regenerated. The regenerated movie is uploaded to the streaming server and becomes available for viewing again by the user and their followers.

[1851] Specific example

[1852] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates a movie concept that includes popular heroes and magical elements. The generating AI model creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. If user A watches the movie and wants to add new scenes, they can submit a change request via prompt billing and enjoy the regenerated movie.

[1853] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1854] Step 1:

[1855] Launching the app and entering user information

[1856] Terminal: When a user launches the application, a form is displayed for them to enter their preferences, attributes, and tastes.

[1857] Input: User's name, age, gender, movie preferences (genre, theme, favorite actor, etc.).

[1858] Output: User-entered data on preferences, attributes, and tastes.

[1859] Specific operation: The terminal stores data in each field according to the user's input.

[1860] Step 2:

[1861] Recording user behavior

[1862] Terminal: Continuously records logs of user actions within the application.

[1863] Input: User actions (movies watched, trailers viewed, etc.).

[1864] Output: Operation log data.

[1865] Specific operation: The device saves user actions such as taps, clicks, and scrolls to a log file.

[1866] Step 3:

[1867] Data storage

[1868] Server: Stores collected user data and operation logs in a database.

[1869] Input: Data on preferences, attributes, and actions.

[1870] Output: User information and operation logs stored in the database.

[1871] Specific operation: The server issues an INSERT statement to the database and persists the data.

[1872] Step 4:

[1873] Collection and analysis of trending elements

[1874] Server: Collects and analyzes the latest movie trend data from the internet.

[1875] Input: Trend data obtained from movie review sites and social media.

[1876] Output: Analyzed trend elements.

[1877] Specific operation: A crawler periodically collects data from websites, and an analysis algorithm on the server processes that data using natural language processing.

[1878] Step 5:

[1879] Creating a film project

[1880] Server: Combines user data and trending elements to generate customized movie concepts.

[1881] Input: User data, operation logs, analyzed trending factors.

[1882] Output: Film project data (genre, story setting, main characters, etc.).

[1883] Specific operation: An analytical AI on the server creates a movie plot based on the user's preferences and the latest trends.

[1884] Step 6:

[1885] Scenario and film generation

[1886] Generative AI Model: Automatically generates detailed scenarios based on generated film plans and creates films.

[1887] Input: Film project data.

[1888] Output: Video data of the completed film.

[1889] Specific operation: The generation AI model automatically handles scriptwriting, casting, location selection, music selection, etc., and generates the film in CG, animation, and live-action formats.

[1890] Step 7:

[1891] Saving movie data and preparing for streaming

[1892] Server: Stores the generated movie data and prepares it for streaming.

[1893] Input: Video data of the completed film.

[1894] Output: Movie data prepared for streaming.

[1895] Specific operation: Convert movie data to the appropriate format and upload it to the streaming server.

[1896] Step 8:

[1897] Generating and displaying viewing links

[1898] Server: Generates and displays a viewing link on the user's My Page.

[1899] Input: Movie data prepared for streaming, user account information.

[1900] Output: The viewing link displayed on your My Page.

[1901] Specific operation: The server generates a unique viewing link for the user and displays it on the user's My Page.

[1902] Step 9:

[1903] Watch and share movies

[1904] Device: Users can watch generated movies and share them with their followers if desired.

[1905] Input: The viewing link displayed on your My Page.

[1906] Output: Viewing history, sharing information.

[1907] Specific actions: The user clicks the link to play the movie and uses the sharing option to send the link to their followers.

[1908] Step 10:

[1909] Profit calculation and distribution

[1910] Server: Records viewing history and advertising revenue, and distributes it to users and operators.

[1911] Input: Viewing history data, advertising revenue data.

[1912] Output: Distributed revenue information.

[1913] Specific operation: The server uses revenue data to reflect the revenue in the user and operator accounts.

[1914] Step 11:

[1915] Movie customization

[1916] Terminal: Accepts requests for changes to movie content and presentation via prompt payment.

[1917] Input: User request details, billing information.

[1918] Output: Regenerated movie data based on the request.

[1919] Specific operation: The user fills out a change request and submits billing information. The request is sent to the server, and the generation AI model generates the movie again.

[1920] (Application Example 1)

[1921] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1922] Traditional content distribution services struggle to provide original films tailored to individual user preferences, and it's also difficult for users to request and modify the content or direction of films themselves. Furthermore, easily creating and making available original films compatible with virtual reality viewing environments is another challenge.

[1923] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1924] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for analyzing current trends; means for generating customized movie plans based on the user data and trends; means for generating a movie based on the generated movie plan; means for making the generated movie viewable by the user and their followers; and means for making the generated movie viewable in a virtual reality environment. This makes it possible to easily generate original movies optimized for the user's individual preferences and enjoy them in a virtual reality environment.

[1925] "User data" refers to information about a user's wishes, attributes, preferences, and operational behavior.

[1926] "Trend elements" refer to data on the latest trends collected from the internet and other sources.

[1927] A "customized film project" is a film project proposal that is individually designed based on user data and trending elements.

[1928] "Means of creating films" refers to the technology of creating visuals in various formats such as live-action, animation, special effects, and computer graphics based on a customized film project.

[1929] A "virtual reality environment" is a virtual visual world that users can experience using VR head-mounted displays or other VR devices.

[1930] "Available for viewing" means that the generated film is provided to users and followers in a form that is accessible online.

[1931] "Request details" refer to specific changes that the user would like to see made to the content or direction of the film.

[1932] "Method of regeneration" refers to a technology that regenerates already created movies based on user requests.

[1933] The "means of revenue distribution" refer to a system that distributes the revenue generated between users and operators based on the viewing history of the movies that have been produced.

[1934] System Overview

[1935] This invention is a system that collects user wishes, attributes, preferences, and operational behaviors, combines them with current trends to generate customized movies, and makes them viewable in a virtual reality environment.

[1936] Hardware and software to be used

[1937] Hardware: Smartphones, VR head-mounted displays (e.g., Oculus Quest 2)

[1938] Software: Flask (web framework), Python (programming language), generative AI model

[1939] Data collection and storage

[1940] 1. Device (smartphone or VR device):

[1941] When a user launches the application, an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor).

[1942] 2. User:

[1943] Enter the specified information.

[1944] 3. Server:

[1945] The system continuously records user activity logs and collects them as application operation behavior. For example, it records which movies a user watched, which trailers they viewed, and so on.

[1946] Analysis of popular trends

[1947] 4. Server:

[1948] We collect the latest movie trend data from the internet. This includes popular movies, notable actors, and trending themes.

[1949] 5. Server:

[1950] We analyze collected trend data to identify trending elements.

[1951] Film planning and creation

[1952] 6. Server:

[1953] An analytical AI combines user data with current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[1954] 7. Server:

[1955] Using a generative AI model, detailed scenarios are automatically generated based on the plan.

[1956] 8. Server:

[1957] We create films in various formats such as live-action, animation, special effects, and CGI, and save them as video data.

[1958] Watch and customize movies

[1959] 9. Server:

[1960] The generated movie data is saved and prepared for streaming distribution.

[1961] 10. Terminal:

[1962] Users can watch the movie by clicking on the provided viewing link.

[1963] 11. Server:

[1964] It provides an interface for users to request specific content and direction for the film.

[1965] 12. Generative AI Models:

[1966] Based on the requested content, we will regenerate the movie's script and direction.

[1967] 13. Server:

[1968] The regenerated movie data is uploaded to a streaming server, allowing users and followers to watch it again.

[1969] Specific example

[1970] For example, if the user prefers "Actions" and "Magic," enter the following prompt:

[1971] "User ID: user123"

[1972] Genre: Action

[1973] "Theme: Magic"

[1974] Based on this prompt, the server generates movie recommendations tailored to the user's preferences and creates movie data using a generation AI model. The generated movies are provided to the user via a link, and the user can watch them using a smartphone or VR head-mounted display.

[1975] In this way, this system can easily generate original movies optimized to the user's individual preferences, allowing them to be viewed and enjoyed in a virtual reality environment. This provides a personalized experience that was difficult to achieve with conventional content distribution services.

[1976] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1977] Step 1:

[1978] Terminal:

[1979] The user launches the application, and an input form is displayed containing information about their preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor).

[1980] Input: Name, age, gender, movie preferences

[1981] Output: User input data

[1982] Step 2:

[1983] User:

[1984] Enter the desired information and submit the form.

[1985] Input: Input form

[1986] Output: User data (name, age, gender, movie preferences)

[1987] Step 3:

[1988] server:

[1989] The system continuously records user activity logs (which movies were watched, which trailers were viewed) and saves them to a database as application operation behavior.

[1990] Input: User data and operation logs

[1991] Output: Operation history data

[1992] Step 4:

[1993] server:

[1994] Collect the latest movie trend data from the internet (popular movies, notable actors, trending themes, etc.).

[1995] Input: Trending information on the internet

[1996] Output: Trend Data

[1997] Step 5:

[1998] server:

[1999] We analyze collected trend data to identify trending elements.

[2000] Input: Trend data

[2001] Output: Identified trend elements

[2002] Step 6:

[2003] server:

[2004] The analytical AI combines user data and trending elements to generate original movie concepts (genre, story setting, main characters).

[2005] Input: User data, trending topics

[2006] Output: Film project data

[2007] Step 7:

[2008] server:

[2009] The generative AI model automatically generates detailed scenarios based on film project data.

[2010] Input: Film project data

[2011] Output: Detailed Scenario

[2012] Step 8:

[2013] Generative AI models:

[2014] We create films in various formats such as live-action, animation, special effects, and CGI, and save them as video data.

[2015] Input: Detailed Scenario

[2016] Output: Video data

[2017] Step 9:

[2018] server:

[2019] The generated movie data is saved, and a link for streaming is generated.

[2020] Input: Video data

[2021] Output: Viewing link

[2022] Step 10:

[2023] Terminal:

[2024] Users click on the provided viewing link and watch the movie using their smartphone or VR head-mounted display.

[2025] Input: Viewing link

[2026] Output: Movie playback

[2027] Step 11:

[2028] server:

[2029] It provides an interface for users to request specific content and direction for the film.

[2030] Input: User Request

[2031] Output: Request details

[2032] Step 12:

[2033] Generative AI models:

[2034] Based on user requests, the system regenerates movie scripts and direction.

[2035] Input: Request details

[2036] Output: Regenerated movie script

[2037] Step 13:

[2038] server:

[2039] The regenerated movie data is uploaded to a streaming server, allowing users and followers to watch it again.

[2040] Input: Regenerated movie script, video data

[2041] Output: Regenerated movie viewing link

[2042] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2043] This invention is a system that creates original films incorporating popular trends based on users' wishes, attributes, preferences, app operation behavior, survey results, and emotions, and allows users and their followers to watch these films. Furthermore, it regenerates films according to user requests regarding content and direction, and distributes the revenue. The program processing of this system is described below in natural language.

[2044] Basic System Configuration

[2045] User data entry

[2046] 1. Terminal: When the application is launched, an input form will be displayed regarding the user's wishes, attributes, and preferences. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[2047] 2. User: Enter the specified information and press the submit button.

[2048] Data collection and storage

[2049] 3. Device: Collects data including user operation logs and app operation behavior. This includes which movies the user watched and which trailers they viewed.

[2050] 4. Server: Stores collected user data in a database.

[2051] emotion recognition

[2052] 5. Device: Captures the user's facial expressions and voice through the camera and microphone and sends them to the emotion engine.

[2053] 6. Emotion Engine: Analyzes the user's facial expressions and voice to generate emotion data.

[2054] 7. Server: Stores the emotion data sent from the emotion engine in the database.

[2055] Analysis of popular trends

[2056] 8. Server: Automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet.

[2057] 9. Server: Analyzes collected trend data and identifies trending elements.

[2058] Creating a film project

[2059] 10. Server: An analytical AI combines user data, sentiment data, and current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[2060] 11. Server: Saves the generated film proposals to the database and sends them to the generation AI.

[2061] The creation of a film

[2062] 12. Generating AI: Automatically generates a detailed scenario based on the content of the film project. This includes scriptwriting, casting, location selection, and music selection.

[2063] 13. Generative AI: Generates films in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[2064] Movie preservation and distribution

[2065] 14. Server: Stores the generated movie data and prepares it for streaming.

[2066] 15. Server: Generates and displays a viewing link on the user's My Page.

[2067] Watching and sharing movies

[2068] 16. Device: The user clicks the provided viewing link to watch the movie.

[2069] 17. Device: Displays options for users to share movies with their followers.

[2070] 18. User: Share the viewing link with your followers.

[2071] Profit calculation and distribution

[2072] 19. Server: Records the viewing history and advertising revenue of generated movies.

[2073] 20. Server: Distributes revenue 1:1 between users and site operators and reflects it in the user's account.

[2074] Movie customization

[2075] 21. Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[2076] 22. User: Enter a movie change request and pay the corresponding fee.

[2077] 23. Terminal: Sends the request to the server.

[2078] 24. Server: Notifies the generating AI of the request details.

[2079] 25. Generating AI: Updates the movie by generating additional scenes and different endings.

[2080] 26. Server: Upload the updated movie to the streaming server and prepare it for distribution again.

[2081] 27. Device: Allow users and followers to watch the regenerated movie.

[2082] Specific example

[2083] For example, if user A likes action and fantasy movies, they input these preferences when launching the app. Based on this, the server generates movie proposals that include popular hero and magical elements. The generating AI creates a script and footage for a fantasy action movie set in a city and provides user A with a streaming link. Furthermore, an emotion engine analyzes the user's emotions while they are watching, and this data is used when generating future movie proposals, resulting in a more personalized movie.

[2084] This invention enables users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie-watching experience.

[2085] The following describes the processing flow.

[2086] Step 1:

[2087] Terminal: When the application is launched, it displays an input form regarding the user's wishes, attributes, and preferences. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.).

[2088] Step 2:

[2089] User: Enter the specified information and press the submit button.

[2090] Step 3:

[2091] Terminal: Sends the entered user information to the server.

[2092] Step 4:

[2093] Server: Stores the received user information in the database.

[2094] Step 5:

[2095] Device: Records user activity logs and app operation behavior, collecting information such as which movies were watched and which trailers were viewed.

[2096] Step 6:

[2097] Server: Stores collected application operation behaviors in a database.

[2098] Step 7:

[2099] Terminal: Displays a survey to the user and collects responses.

[2100] Step 8:

[2101] User: Answers the survey and presses the submit button.

[2102] Step 9:

[2103] Terminal: Sends survey responses to the server.

[2104] Step 10:

[2105] Server: Saves survey results to the database.

[2106] Step 11:

[2107] Device: Captures the user's facial expressions and voice through the camera and microphone, and sends them to the emotion engine.

[2108] Step 12:

[2109] Emotion Engine: Analyzes the user's facial expressions and voice to generate emotion data.

[2110] Step 13:

[2111] Server: Stores emotion data sent from the emotion engine in the database.

[2112] Step 14:

[2113] Server: Automatically collects the latest movie trend data from the internet. This includes popular movies, featured actors, trending themes, and more.

[2114] Step 15:

[2115] Server: Analyzes collected trend data and identifies trending elements.

[2116] Step 16:

[2117] Server: An analytical AI combines user data, sentiment data, and current trends to generate original film concepts. These concepts include genre, story setting, and main characters.

[2118] Step 17:

[2119] Server: Saves the generated film proposals to a database and sends them to the generation AI.

[2120] Step 18:

[2121] Generating AI: Automatically generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection.

[2122] Step 19:

[2123] Generative AI: Generates movies in various formats such as live-action, animation, special effects, and CG, and saves them as video data.

[2124] Step 20:

[2125] Server: Stores the generated movie data and prepares it for streaming.

[2126] Step 21:

[2127] Server: Generates and displays a viewing link on the user's My Page.

[2128] Step 22:

[2129] Device: The user clicks the provided viewing link to watch the movie.

[2130] Step 23:

[2131] Device: Displays options for users to share movies with their followers.

[2132] Step 24:

[2133] User: Share the viewing link with your followers.

[2134] Step 25:

[2135] Server: Records the viewing history of shared movies and collects revenue data.

[2136] Step 26:

[2137] Server: Revenue is distributed 1:1 between users and site operators and reflected in the user's account.

[2138] Step 27:

[2139] Terminal: Provides users with a prompt billing function and displays a page where they can request changes to the movie's content or presentation.

[2140] Step 28:

[2141] User: Enter a movie change request and pay the corresponding fee.

[2142] Step 29:

[2143] Terminal: Sends a request to the server.

[2144] Step 30:

[2145] Server: Notifies the generating AI of the request details.

[2146] Step 31:

[2147] Generative AI: Updates the movie by generating additional scenes and different endings.

[2148] Step 32:

[2149] Server: Uploads the updated movie to the streaming server and prepares it for distribution again.

[2150] Step 33:

[2151] Device: Allows users and followers to watch the regenerated movie.

[2152] (Example 2)

[2153] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2154] Traditional film creation systems have struggled to automatically generate films that fully reflect the individual preferences and emotions of users. Furthermore, customizing films according to user requests and ensuring a fair distribution of revenue from generated films have been difficult. As a result, improving the user experience and optimizing revenue have been insufficient.

[2155] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[2156] In this invention, the server includes means for collecting data on the user's wishes, attributes, preferences, and operational behavior; means for emotion recognition that captures the user's facial expressions and voice using a camera and microphone and analyzes their emotions; and means for collecting and analyzing movie trend data from the internet. This enables the automatic generation of more personalized movies that reflect the user's individual preferences, emotions, and the latest trending elements. The server also includes means for distributing the viewing history and revenue of the generated movies between the user and the operator, and means for providing a prompt billing function. This enables the customization of movies according to the user's requests and fair revenue distribution.

[2157] "Data relating to user preferences, attributes, tastes, and operational behavior" refers to information entered by the user into the system, such as name, age, gender, preferences for movie genres and themes, and viewing history of movies and trailers.

[2158] "Emotion recognition means" refers to technology that uses cameras and microphones to capture the user's facial expressions and voice, analyzes them, and generates emotional data such as positive, negative, and neutral.

[2159] "Movie trend data" refers to information collected from the internet about the latest popular movies, notable actors, trending themes, and more.

[2160] "Film planning" refers to the initial design of a film, including its genre, story setting, and main characters, which is generated based on user data and trend data.

[2161] "Generative AI" refers to artificial intelligence that automatically generates detailed scenarios based on film concepts and then produces films in various formats such as live-action, animation, special effects, and CGI.

[2162] "Means of making the content viewable by users and followers" refers to technologies that save the generated movie data, create a viewing link to display on the user's profile page, and enable streaming playback of the movie.

[2163] "Means for recording viewing history and advertising revenue" refers to technology that records in a database the history of movies a user has watched and the revenue generated from advertisements displayed during movie viewing.

[2164] A "payment gateway" refers to an online payment system that securely processes the payment a user makes for their movie request.

[2165] "Prompt billing" refers to a billing technology that allows users to pay a fee when they request changes to the content or presentation of a movie.

[2166] This invention is a system that creates original films incorporating popular trends based on users' wishes, attributes, preferences, operational behavior, survey results, and emotions, and allows users and their followers to watch these films. Furthermore, it is possible to regenerate films according to user requests regarding content and direction, and distribute the revenue. The following describes specific embodiments of this system.

[2167] Basic System Configuration

[2168] This system consists of a user terminal, a server that processes and stores data, and a generative AI that generates movies.

[2169] User data entry

[2170] 1. When the device launches the application, an input form will appear regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the information and clicks the submit button. For example, they might enter, "I like action movies, especially those with sci-fi elements."

[2171] Data collection and storage

[2172] 2. The device collects real-time activity logs, such as which movies the user watched and which trailers they viewed. This data is sent to a server and stored in a database.

[2173] emotion recognition

[2174] 3. The device uses its camera and microphone to capture the user's facial expressions and voice, and sends them to the emotion analysis engine. The emotion engine uses OpenCV and Deep Learning models to analyze the user's emotions and generates emotion data such as positive, negative, and neutral. This emotion data is sent to a server and stored in a database.

[2175] Analysis of popular trends

[2176] 4. The server uses web crawling technologies (e.g., BeautifulSoup or Scrapy) to collect the latest movie trend data from the internet. This data is analyzed using natural language processing technologies (e.g., NLTK or SpaCy) to identify trending elements.

[2177] Creating a film project

[2178] 5. An analysis AI on the server (using, for example, TensorFlow or PyTorch) combines user data, sentiment data, and trending elements to generate a movie concept. This movie concept includes genre, story setting, main characters, etc.

[2179] The creation of a film

[2180] 6. The generative AI generates a detailed scenario based on the film project. This scenario includes the script, casting, location selection, and music selection. The generative AI uses frameworks such as Unreal Engine and Unity to produce the film in various formats including live-action, animation, special effects, and CG, and the video data is stored in cloud storage.

[2181] Movie preservation and distribution

[2182] 7. The server stores the generated movie data in high-performance storage (e.g., AWS S3) and generates metadata for streaming. A viewing link is generated and displayed on the user's My Page.

[2183] Watching and sharing movies

[2184] 8. The device prompts the user to click a viewing link and streams the movie. Streaming technologies such as HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) are used. Users can share the viewing link with their followers by clicking the share button, and share the movie via social media and messaging apps.

[2185] Profit calculation and distribution

[2186] 9. The server records movie viewing history and advertising revenue. Revenue data is obtained from external advertising APIs (e.g., Google AdSense). The server distributes the revenue to users and site operators in a 1:1 ratio and reflects it in the user's account. Specifically, payments are made using payment gateways (e.g., Stripe or PayPal).

[2187] Movie customization

[2188] 10. The device provides a prompt billing function and displays a page where users can request changes to the movie's content or presentation. Users enter their requests and pay the corresponding fees through a payment gateway. The requests are notified to the generation AI via the server. The generation AI regenerates the movie based on the requested changes (e.g., additional scenes or a different ending) and updates the movie data. The updated movie data is uploaded back to the streaming server and made available for viewing by the user and their followers.

[2189] Specific example

[2190] For example, if a user requests a "moving ending," the AI ​​will generate a new scene that replaces the current movie's ending. This modified movie will then reappear on the user's profile page and become available for viewing. Based on the user's emotional data and viewing history, this modified movie will be reused when generating future movie projects.

[2191] As described above, the present invention allows users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie viewing experience.

[2192] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2193] Step 1:

[2194] When the device launches the application, an input form is displayed that asks about the user's preferences, attributes, and tastes. The input form includes fields such as name, age, gender, movie genre, theme, and favorite actor. The user enters information into these fields and clicks the submit button. The entered data is sent from the device to the server in JSON format. The sent data becomes a JSON object containing the user's personal information and preference information.

[2195] Step 2:

[2196] The terminal collects user activity logs. This includes activity data such as which movies the user watched and which trailers they viewed. The terminal saves this activity data to a log file in real time and sends it to the server as a batch process at regular intervals. The server analyzes the received log data and stores it in a database as user-specific data. Here, the input is the activity log, and the output is user-specific activity data.

[2197] Step 3:

[2198] The device uses its camera and microphone to capture the user's facial expressions and voice. The resulting video and audio data is sent to the server. The input data consists of the user's facial expressions and voice, which the emotion engine analyzes to generate emotion data (positive, negative, neutral, etc.). The generated emotion data is stored on the server. The output is the analyzed emotion data.

[2199] Step 4:

[2200] The server uses web crawling technology to collect the latest movie trend data from the internet. This includes popular movies, notable actors, and trending themes. The server analyzes the collected trend data using natural language processing technology to identify current trend elements. The data input is trend information collected from the web, and the output is the analyzed trend elements.

[2201] Step 5:

[2202] An analytical AI on the server generates a movie concept by combining user data, sentiment data, and trend data. This movie concept includes genre, story setting, main characters, and other elements. The input is user data and trend data, and the output is a specific movie concept. The server stores this concept data in a database and sends it to the generating AI.

[2203] Step 6:

[2204] The generative AI automatically generates a detailed scenario based on a film project proposal. This scenario includes the script, casting, location selection, and music selection. The input is a film project proposal, and the output is a detailed scenario. Based on the generated scenario, the generative AI uses tools such as Unreal Engine or Unity to create the film, and saves the final video data to cloud storage.

[2205] Step 7:

[2206] The server saves the generated movie data to high-performance storage (e.g., AWS S3) and generates metadata for streaming. The output is a viewing link, which is displayed on the user's My Page on their device. The input here is the completed video data.

[2207] Step 8:

[2208] The device prompts the user to click a viewing link, and the movie is streamed. Streaming technologies such as HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) are used. The input is the viewing link, and the output is the movie being played. The user clicks a share button to share the viewing link with their followers, spreading the movie through social media and messaging apps.

[2209] Step 9:

[2210] The server records movie viewing history and advertising revenue. Revenue data is obtained from an external advertising API. Based on the aggregated information, the server distributes the revenue to the user and the site operator in a 1:1 ratio and reflects it in the user's account. The input is viewing history and advertising revenue data, and the output is the distributed revenue.

[2211] Step 10:

[2212] The device provides a prompt billing function and displays a page where the user can request changes to the movie's content or presentation. The user enters their request and pays the fee through a payment gateway. The device sends the request and payment information to the server. The server notifies the generation AI of the request, and the generation AI regenerates the movie reflecting the requested changes. The regenerated movie is saved to cloud storage, and the viewing link is displayed again on the device's My Page. The input is the user's request and payment information, and the output is the updated movie data and viewing link.

[2213] (Application Example 2)

[2214] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2215] In recent years, the diversification of entertainment has led to a growing demand for customized films tailored to individual preferences and emotions. However, a system that efficiently generates films that reflect user preferences, emotions, and operational behavior in real time, and distributes revenue based on these films, still does not exist. This invention aims to solve these problems and provide a system that enables the generation, viewing, and sharing of films optimized for individual users.

[2216] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data relating to the user's wishes, attributes, preferences, and operational behavior; means for analyzing popular trends; means for generating a customized movie plan based on the user data and popular trends; means for generating a movie based on the generated movie plan; means for making the generated movie viewable by the user and followers; means for recognizing the user's emotions and generating and storing emotion data; and means for providing the user with a viewing link to the generated movie. This enables the generation of customized movies based on the user's preferences and emotions, as well as efficient viewing and sharing.

[2217] "User preferences" refer to specific requirements that users have for movies, such as genres, themes, and favorite actors.

[2218] "Attributes" refer to personal background information of the user, such as age, gender, occupation, and hobbies.

[2219] "Preferences" refer to the genres and themes of movies that a user enjoys, as well as their preferences and interests in the types of movies that have been produced.

[2220] "Operational behavior" refers to the actions and patterns of operation that a user exhibits while using an application.

[2221] "Popular trends" refer to the latest movie trends, popular actors, and trending themes and storylines, gathered from the internet and other sources.

[2222] A "customized film project" refers to a film story and setting that is specially designed based on individual user data and trending elements.

[2223] "Means of producing a film" refers to the processes and systems used to create films in various formats, such as live-action, animation, special effects, and computer graphics, based on a generated film project.

[2224] "Emotional data" refers to emotional information analyzed from the user's facial expressions and voice.

[2225] A "viewing link" refers to a URL or access method provided for viewing a generated movie online.

[2226] "Followers" refer to other users who track a specific user online and view their activities and shared content.

[2227] This invention relates to a system that creates an original film incorporating popular trends based on the user's wishes, attributes, preferences, operational behavior, survey results, and emotions, and allows the user and their followers to watch this film. Specific embodiments are described below.

[2228] Basic System Configuration

[2229] User data entry

[2230] When the application is launched, the device displays an input form regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the requested information and presses the submit button.

[2231] Data collection and storage

[2232] The device collects data including user activity logs and app operation behavior. This includes information such as which movies the user watched and which trailers they viewed. The server stores the collected user data in a database.

[2233] emotion recognition

[2234] The device captures the user's facial expressions and voice through its camera and microphone and sends this data to the emotion engine. The emotion engine analyzes the user's emotions from their facial expressions and voice and generates emotion data. The server stores this emotion data in a database.

[2235] Analysis of popular trends

[2236] The server automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet and analyzes it to identify trending elements.

[2237] Creating a film project

[2238] The server uses a generative AI to combine user data, emotional data, and current trends to generate original movie concepts. These concepts include genre, story setting, and main characters. The generated movie concepts are stored in a database and sent back to the generative AI.

[2239] The creation of a film

[2240] The AI ​​generates detailed scenarios based on the content of a film project. This includes scriptwriting, casting, location scouting, and music selection. It also generates films in various formats such as live-action, animation, special effects, and CGI, and saves them as video data.

[2241] Movie preservation and distribution

[2242] The server stores the generated movie data and prepares it for streaming. It generates and displays a viewing link on the user's My Page.

[2243] Watching and sharing movies

[2244] The device allows the user to click the provided viewing link and watch the movie. It then displays an option for the user to share the movie with their followers. The user can then share the viewing link with their followers.

[2245] Specific example

[2246] For example, if user B inputs that they like movies in the "comedy" and "romance" genres, the system will generate an original movie incorporating the latest trends in comedy romance films. User B can watch the generated movie on their smartphone and, if necessary, send scene change requests to customize specific scenes to their liking. The following example prompts can also be used to input data into the generation AI model.

[2247] "User movie preferences: Comedy and Romance"

[2248] User's favorite actor: A specific actor

[2249] Latest trends: Romantic happenings and funny events

[2250] User sentiment data: Mostly smiles

[2251] Based on this data, please create a hilarious romantic comedy film.

[2252] This invention enables users to easily create, watch, and share original movies optimized for themselves. Furthermore, the introduction of an emotion engine further enhances the movie-watching experience.

[2253] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2254] Step 1:

[2255] When the application is launched, the device displays an input form regarding the user's preferences, attributes, and tastes. This includes name, age, gender, and movie preferences (genre, theme, favorite actor, etc.). The user enters the requested information and presses the submit button. The input in this step is the user's personal information and preferences, and the device sends this data to the server as output.

[2256] Step 2:

[2257] The device collects data including user operation logs and application operation behavior. Information such as which movies the user watched and which trailers they viewed is collected. This data is temporarily stored on the device and then sent to the server. The input is user operation data, and this is sent to the server as output.

[2258] Step 3:

[2259] The server stores the collected user data in a database. This stored data is used for subsequent processing. The input is user data sent from the terminal, and the output is stored in the database.

[2260] Step 4:

[2261] The device captures the user's facial expressions and voice through its camera and microphone, and sends this data to the emotion engine. The input is the user's face and voice data, and the output is sent to the emotion engine.

[2262] Step 5:

[2263] The emotion engine analyzes the user's facial expressions and voice to generate emotion data. This analysis is performed using machine learning algorithms. The input is the user's face and voice data, and the output is generated emotion data.

[2264] Step 6:

[2265] The server stores this emotion data in a database. The input is emotion data sent from the emotion engine, and the output is stored in the database.

[2266] Step 7:

[2267] The server automatically collects the latest movie trend data (popular movies, notable actors, trending themes, etc.) from the internet and analyzes it to identify trending elements. This process uses web scraping and data analysis techniques. The input is trend data from the internet, and the output is the analyzed trending elements.

[2268] Step 8:

[2269] The server uses a generative AI to combine user data, sentiment data, and current trends to generate original film proposals. These proposals include genre, story setting, and main characters. The input is user data, sentiment data, and current trends, and the output is a film proposal.

[2270] Step 9:

[2271] The AI ​​generator automatically produces a detailed scenario based on the content of a film project. This includes the script, casting, location selection, and music selection. It also generates the film in various formats such as live-action, animation, special effects, and CG, and saves it as video data. The input is film project data, and the output is the scenario and video data.

[2272] Step 10:

[2273] The server stores the generated movie data and prepares it for streaming. The input is the generated movie data, and the output is a viewing link.

[2274] Step 11:

[2275] The device plays the movie when the user clicks on the provided viewing link. The input is the viewing link, and the output is the movie being played.

[2276] Step 12:

[2277] The device displays options for the user to share a movie with their followers. The user can share a viewing link with their followers. The input is the viewing link, and the output is sharing with followers.

[2278] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2279] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2280] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2281] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2282] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2283] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2284] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2285] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2286] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2287] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2288] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2289] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2290] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2291] 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.

[2292] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2293] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2294] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2295] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2296] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2297] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2298] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2299] The following is further disclosed regarding the embodiments described above.

[2300] (Claim 1)

[2301] A means for collecting data on user preferences, attributes, tastes, and operational behavior,

[2302] A means of analyzing the elements of current trends,

[2303] A means for generating a customized film plan based on the above user data and trending elements,

[2304] Based on the generated film project, means for producing a film,

[2305] A means of making the generated movie viewable by users and followers,

[2306] A system that includes this.

[2307] (Claim 2)

[2308] A means for users to request the content and direction of the film,

[2309] Based on the request, a means to recreate the movie,

[2310] The system according to claim 1, further comprising:

[2311] (Claim 3)

[2312] A means of distributing the viewing history and revenue of generated movies between the user and the operator,

[2313] The system according to claim 1, further comprising:

[2314] "Example 1"

[2315] (Claim 1)

[2316] A means for collecting data on user preferences, attributes, tastes, and operational behavior,

[2317] A means of recording user operation logs,

[2318] A means of storing collected user data in a database,

[2319] Methods for collecting the latest movie trend data from the internet,

[2320] A means of analyzing collected trend data to identify trend elements,

[2321] A means for generating a customized film project based on user data and trending elements,

[2322] A means of saving the generated film project to a database and sending it to a generation AI model,

[2323] A means for generating detailed scenarios based on a generative AI model,

[2324] A method for creating films in formats such as live-action, animation, special effects, and CG using generative AI models and saving them as video data,

[2325] A means of saving the generated movie data and preparing it for streaming distribution,

[2326] A means of generating and displaying a viewing link on the user's My Page,

[2327] A system that includes this.

[2328] (Claim 2)

[2329] A means for users to request the content and direction of the film,

[2330] A means of regenerating a movie based on the requested content,

[2331] A means of notifying the generation AI model of the request content and regenerating the scenario and direction,

[2332] The system according to claim 1.

[2333] (Claim 3)

[2334] A means of distributing the viewing history and revenue of generated movies between the user and the operator,

[2335] The system according to claim 1.

[2336] "Application Example 1"

[2337] (Claim 1)

[2338] A means for collecting data on user preferences, attributes, tastes, and operational behavior,

[2339] A means of analyzing the elements of current trends,

[2340] A means for generating a customized film plan based on the above user data and trending elements,

[2341] Based on the generated film project, means for producing a film,

[2342] A means of making the generated movie viewable by users and followers,

[2343] A means to make the generated movie viewable in a virtual reality environment,

[2344] A system that includes this.

[2345] (Claim 2)

[2346] A means for users to request the content and direction of the film,

[2347] Based on the request, a means to recreate the movie,

[2348] A means to make the generated movie viewable in a virtual reality environment,

[2349] The system according to claim 1, further comprising:

[2350] (Claim 3)

[2351] A means of distributing the viewing history and revenue of generated movies between the user and the operator,

[2352] The system according to claim 1, further comprising:

[2353] "Example 2 of combining an emotion engine"

[2354] (Claim 1)

[2355] A means for collecting data on user preferences, attributes, tastes, and operational behavior,

[2356] An emotion recognition system that uses a camera and microphone to capture the user's facial expressions and voice, and analyzes their emotions,

[2357] Methods for collecting and analyzing movie trend data from the internet,

[2358] A means for generating a custo...

Claims

1. A means for collecting data on user preferences, attributes, tastes, and operational behavior, A means of analyzing the elements of current trends, A means for generating a customized film plan based on the above user data and trending elements, Based on the generated film project, means for producing a film, A means of making the generated movie viewable by users and followers, A system that includes this.

2. A means for users to request the content and direction of the film, Based on the request, a means to recreate the movie, The system according to claim 1, further comprising:

3. A means of distributing the viewing history and revenue of generated movies between the user and the operator, The system according to claim 1, further comprising:

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