System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a generation request; means for obtaining parameters related to a theme, a difficulty level, and a play style based on the generation request; generation model means for automatically generating a world or a dungeon from the obtained parameters; and means for storing and responding to data of the generated world or dungeon.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In game and RPG production, designing worlds and dungeons can be a time-consuming and labor-intensive process. Other challenges include running out of ideas midway through production and limiting the variety of worlds available. In these circumstances, creators find it difficult to quickly provide diverse content, preventing players from enjoying new adventures. This invention aims to solve these challenges, enabling creators to build diverse content in a short amount of time, improving the player experience. [Means for solving the problem]

[0005] The system of the present invention includes a means for accepting a generation request, a means for acquiring parameters related to theme, difficulty, and play style based on the generation request, a generation model means for automatically generating worlds and dungeons from the acquired parameters, and a means for saving and responding to data on the generated worlds and dungeons. This allows creators to quickly generate a variety of worlds and dungeons based on their desired conditions, streamlining the production process. Furthermore, the generated worlds and dungeons can be customized according to user requests, providing players with a new adventure experience.

[0006] A "generation request" refers to a request regarding a specific theme, difficulty level, and play style that a user enters to request the generation of a world or dungeon.

[0007] "Means" refers to modules or algorithms for performing specific functions within a system, and are designed to achieve specific processing.

[0008] "Theme" is a fundamental element that determines the overall design and atmosphere of a world or dungeon, and refers to different settings such as medieval fantasy or cyberpunk.

[0009] "Difficulty" is a factor that determines the level of challenge the player faces, and refers to settings such as easy, medium, and difficult.

[0010] "Play style" is a factor that determines how a player will enjoy the game, and includes different styles such as exploration-focused or combat-focused.

[0011] "Generative model means" refers to an AI model or algorithm that receives acquired parameters such as theme, difficulty, and play style as input and automatically generates worlds and dungeons based on these.

[0012] "Database" refers to a storage system for systematically storing and managing data and related information about generated worlds and dungeons.

[0013] "Means for responding" refers to a communication interface or protocol for returning data about the world or dungeon generated by the generative model means to the user.

[0014] "Customizable" refers to the ability for users to edit, adjust, and change elements of the generated world and dungeons as they wish.

[0015] "Creators" refers to developers who are responsible for designing and generating the worlds and dungeons of games and RPGs.

[0016] "Player" refers to the user who actually plays the game in the generated world or dungeon. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention is a system that automatically generates worlds and dungeons for games and RPGs using a generative AI model, and mainly includes the following main components and processes.

[0039] System Configuration

[0040] This system consists of the following components:

[0041] 1. How to accept creation requests

[0042] The terminal provides a user interface that allows the user to input parameters required for generating a world or dungeon. Through this interface, the user specifies the desired theme, difficulty level, and play style.

[0043] 2. How to get parameters

[0044] The server receives the creation request sent from the device and detects the parameters of theme, difficulty, and play style. Data validation is also performed at this stage.

[0045] 3. Generative Modeling Methods

[0046] The server maintains a generation AI model, which inputs the acquired parameters into the AI ​​model, which then automatically generates appropriate worlds and dungeons based on the input.

[0047] 4. Data storage and response methods

[0048] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[0049] The terminal displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[0050] Program processing

[0051] Specifically, the program of this system performs the following processing.

[0052] Accepting a generation request

[0053] Users input parameters (theme, difficulty, play style) to generate new worlds and dungeons using the UI on their device. For example, they can select a "medieval fantasy" theme, a "medium" difficulty level, and an "exploration-focused" play style.

[0054] Parameter retrieval and validation

[0055] The terminal generates request data including the parameters entered by the user and sends it to the server, which receives the request and validates the parameters.

[0056] World and dungeon generation

[0057] The server inputs the successfully validated parameters into the generative AI model, which then automatically generates new worlds and dungeons based on these inputs. During this process, the server retrieves appropriate materials, layouts, enemy characters, items, etc. from the database and generates a structure that matches the parameters.

[0058] Data storage and return

[0059] The server stores the generated world and dungeon data in a database, generates a response, and sends it back to the device. The device receives this data and displays a preview of the generated world or dungeon to the user.

[0060] Specific examples

[0061] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[0062] 1. A request containing parameters entered by the user is sent from the terminal.

[0063] 2. The server receives the request, validates it, and then inputs data based on the theme "Medieval Fantasy," difficulty level "Medium," and play style "Exploration-focused" into the generative AI model.

[0064] 3. The generative AI model generates the basic structure of a medieval castle or dungeon, and places enemy characters of moderate difficulty, numerous traps, secret rooms, etc.

[0065] 4. The server stores the generated data and sends it back to the device.

[0066] 5. Users can preview the generated world or dungeon on their device and make any adjustments or customizations they like.

[0067] In this way, a system is created that allows creators to quickly generate diverse worlds and dungeons, providing players with new adventures.

[0068] The processing flow will be explained below.

[0069] Specific processing steps of the program

[0070] Accepting a creation request and obtaining parameters

[0071] Step 1:

[0072] Users access a user interface (UI) on their device and input parameters for generating new worlds and dungeons, such as a theme of "medieval fantasy," a difficulty level of "medium," and a play style of "exploration-focused."

[0073] Step 2:

[0074] The terminal receives the parameters entered by the user and generates request data in JSON format. Example of request data:

[0075] json

[0076] {

[0077] "theme": "Medieval Fantasy",

[0078] "difficulty": "medium level",

[0079] "playStyle": "Exploration-oriented"

[0080] }

[0081] Step 3:

[0082] The device sends the generated request data to the server's API endpoint. This communication uses the HTTP protocol.

[0083] Receiving and Validating a Request

[0084] Step 4:

[0085] The server receives the request sent through the API and validates the request data, checking that all required fields are present and that the values ​​are valid.

[0086] Step 5:

[0087] The server validates the request parameters, and if validation is successful, proceeds to the next step. If validation fails, it returns an error response to the terminal.

[0088] World and dungeon generation

[0089] Step 6:

[0090] The server accesses the database and retrieves data (terrain, enemy characters, items, etc.) related to the requested theme "Medieval Fantasy," difficulty level "Medium," and play style "Exploration-focused."

[0091] Step 7:

[0092] The server inputs the acquired data and request parameters into a generative AI model, which then generates new worlds and dungeons based on this data.

[0093] Step 8:

[0094] The generative AI model creates the basic structure of a medieval fantasy castle or dungeon, with a layout that emphasizes exploration, and features enemies, traps, secret rooms, and other elements of moderate difficulty.

[0095] Saving and returning generated results

[0096] Step 9:

[0097] The server stores generated world and dungeon data in a database, including the generation ID, generation data, and generation date and time.

[0098] Step 10:

[0099] The server converts the generated results into JSON format and generates a response, which contains details about the generated world and dungeon.

[0100] Step 11:

[0101] The server sends a response containing the generated data back to the device via the API.

[0102] Viewing and customizing the results

[0103] Step 12:

[0104] The device parses the generated data received from the server and displays it in a user interface, including a visual preview of the generated world and dungeon.

[0105] Step 13:

[0106] The user can preview the generated world and dungeon and customize it as needed, for example by rearranging specific rooms or adding items.

[0107] Step 14:

[0108] The device saves any customizations made by the user and finalizes them as world and dungeon data.

[0109] Example 1

[0110] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0111] The generation of worlds and dungeons in conventional games and RPGs is often done manually, requiring a great deal of time and effort. This makes it difficult to quickly generate diverse worlds and dungeons. Furthermore, existing automatic generation systems have the problem of making it difficult to customize them to fit a user's desired theme or play style. Therefore, there is a demand for technology that can efficiently generate diverse, high-quality worlds and dungeons that meet user needs.

[0112] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0113] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style based on the generation request and validating the parameters, means for inputting the acquired parameters into a generation AI model and automatically generating appropriate worlds and dungeons, means for storing data of the generated worlds and dungeons in a database and returning the data to the terminal as a response, and means for displaying the returned data on the terminal and providing a user interface that can be customized by the user. This allows for the efficient generation of diverse, high-quality worlds and dungeons that meet the user's needs and also allows the user to customize them themselves.

[0114] The "means for accepting a generation request" is a device or function that provides an interface that allows a user to input parameters necessary to generate a world or dungeon.

[0115] "Parameters" are information required by the generation AI model to generate a world or dungeon, such as the theme, difficulty, and play style of the generated world or dungeon.

[0116] "Validation means" refers to a device or function that verifies the validity of data by checking whether the acquired parameters are in the correct format or range.

[0117] A "generative AI model" is an algorithm or system that takes acquired parameters as input and automatically generates appropriate worlds and dungeons based on them.

[0118] A "generative model means" is a device or function that uses a generative AI model to automatically generate worlds and dungeons based on parameters.

[0119] A "database" is a storage device or system for storing data on generated worlds and dungeons.

[0120] The "means for returning as a response" is a device or function that sends data of the generated world or dungeon to the terminal and displays it to the user.

[0121] "User interface" is a function that provides a screen and operating means that allows users to preview the worlds and dungeons generated on their device and customize them as needed.

[0122] This invention is a system that uses a generative AI model to automatically generate worlds and dungeons for games and RPGs. This system mainly uses three main components: a server, a terminal, and a user, as well as various data processing means. The specific form and operation of the system are shown below.

[0123] Components and Operation

[0124] A means of accepting creation requests

[0125] The terminal provides the user with a user interface that allows them to input the parameters required to generate a world or dungeon. Through this interface, the user can specify the desired theme, difficulty level, and play style. For example, the user might input parameters such as "Theme: Medieval Fantasy," "Difficulty: Medium level," and "Play Style: Exploration-focused."

[0126] A means of obtaining and validating parameters

[0127] The device generates request data including the parameters entered by the user and sends it to the server. The server analyzes the received request data and extracts the parameters for theme, difficulty, and play style. The extracted parameters are then validated to ensure they are in the correct format and range. For example, it verifies that "difficulty" is either "low," "medium," or "high."

[0128] A means of generating worlds and dungeons using generative AI models

[0129] The server uses the validated parameters to input the generative AI model, generating a prompt like this:

[0130] Theme: Medieval Fantasy

[0131] Difficulty: Medium

[0132] Playstyle: Exploration-focused

[0133] Specific instructions:

[0134] Generate the basic structure of a medieval castle or dungeon

[0135] Place enemy characters with a moderate level of difficulty

[0136] Lots of traps and secret rooms

[0137] Based on these prompts, a generative AI model (such as GPT-4) automatically generates appropriate world and dungeon structures, layouts, enemy characters, items, etc.

[0138] A means to save the generated results and return them as a response

[0139] The server saves the generated world and dungeon data in a database. It then sends the saved data back to the device as a response. The device can then analyze the received data and display a preview of the world or dungeon to the user.

[0140] A means of displaying generated results and providing a customizable user interface

[0141] The device visually displays the generated world and dungeon to the user. The user can check the displayed world and dungeon and customize parts of it as needed. For example, they can change the layout of the generated dungeon by dragging and dropping, or add new enemy characters or items.

[0142] Specific examples

[0143] For example, if a user inputs the parameters "Theme: Medieval Fantasy", "Difficulty: Medium", and "Playstyle: Exploration-Oriented", the following sequence of actions will occur:

[0144] 1. The user enters parameters using the terminal interface.

[0145] 2. The terminal generates request data and sends it to the server.

[0146] 3. The server receives the request and validates the parameters.

[0147] 4. The server uses the generative AI model to generate worlds and dungeons based on the parameters.

[0148] 5. The generative AI model generates the basic structure of medieval castles and dungeons, as well as enemy characters, traps, secret rooms, and other elements of moderate difficulty.

[0149] 6. The server stores the generated data and sends it back to the device.

[0150] 7. The user can preview the generated world and dungeon on their device and customize it as needed.

[0151] This system allows users to quickly generate diverse, high-quality worlds and dungeons, providing players with new adventures.

[0152] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0153] Step 1:

[0154] The user uses the terminal's user interface to create new worlds and dungeons, inputting parameters such as theme, difficulty level, and play style.

[0155] Inputs: Theme (medieval fantasy), difficulty (medium), playstyle (exploration-focused).

[0156] Operation: Each parameter is selected using a drop-down menu, radio button, checkbox, etc. on the user interface.

[0157] Output: The parameter set entered by the user.

[0158] Step 2:

[0159] The terminal generates request data including the parameters input by the user and transmits it to the server.

[0160] Input: A set of parameters entered by the user.

[0161] Data processing: Converts parameters into JSON format request data.

[0162] What it does: Sends the request data to the server using an HTTP POST request.

[0163] Output: The request data sent to the server.

[0164] Step 3:

[0165] The server receives the request data sent from the terminal and validates the parameters.

[0166] Input: Request data sent from the terminal (JSON format).

[0167] Data processing: Parse the JSON data, extract the theme, difficulty, and playstyle parameters, and ensure they are in the correct format and values.

[0168] What it does: Validates each extracted parameter (e.g., checks that the difficulty is either "low", "medium", or "high").

[0169] Output: The validated parameter set.

[0170] Step 4:

[0171] The server uses the successfully validated parameters to input a prompt sentence into the generative AI model.

[0172] Input: A validated set of parameters.

[0173] Data calculation: Generate prompt sentences and input them into the generative AI model.

[0174] How it works: Generate a prompt sentence like the one below and pass it to a generative AI model (e.g., GPT-4).

[0175] Theme: Medieval Fantasy

[0176] Difficulty: Medium

[0177] Playstyle: Exploration-focused

[0178] Specific instructions:

[0179] Generate the basic structure of a medieval castle or dungeon

[0180] Place enemy characters with a moderate level of difficulty

[0181] Lots of traps and secret rooms

[0182] Output: Output data from the generative AI model (detailed world and dungeon generation data).

[0183] Step 5:

[0184] The server stores the generated data obtained from the generative AI model in a database.

[0185] Input: The output data from the generative AI model.

[0186] Data processing: Organizing the generated data and converting it into a format that can be stored in a database.

[0187] What it does: Executes a SQL query that inserts the generated data into a database.

[0188] Output: Generated data stored in a database.

[0189] Step 6:

[0190] The server returns the generated data stored in the database to the terminal as a response.

[0191] Input: Generated data stored in a database.

[0192] Data processing: Converting some or all of the generated data into a JSON response.

[0193] Operation: Sends to the terminal as an HTTP response.

[0194] Output: The JSON response sent to the terminal.

[0195] Step 7:

[0196] The terminal analyzes the generated data received from the server and displays it to the user.

[0197] Input: The JSON response received from the server.

[0198] Data processing: Parse JSON data to extract world and dungeon structure.

[0199] How it works: It uses the extracted data to visually display worlds and dungeons in a user interface, and also provides an edit mode for user customization.

[0200] Output: A user-viewable and customizable representation of the world and dungeon.

[0201] In this way, users can easily create high-quality worlds and dungeons and customize them as needed.

[0202] (Application example 1)

[0203] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0204] Conventional world and dungeon generation systems require users to manually create detailed settings and layouts, which takes time and effort. Furthermore, customization of the generated worlds and dungeons is limited, making it difficult for users to fully express their creativity. Therefore, there is a demand for a system that allows users to easily generate worlds and dungeons on their smartphones and freely customize their content.

[0205] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0206] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style, generation model means for automatically generating worlds and dungeons from the acquired parameters, means for saving and responding to data on the generated worlds and dungeons, and means for the user to preview and customize the generated worlds and dungeons on their smartphones. This allows users to easily generate worlds and dungeons using their smartphones and freely customize their contents.

[0207] A "generation request" is a request entered by a user to generate a world or dungeon based on specific conditions.

[0208] "Theme" is a category that determines the overall setting and atmosphere of the generated world or dungeon.

[0209] "Difficulty" is a parameter that indicates the difficulty of playing in the generated world or dungeon.

[0210] "Play style" is a parameter that indicates the user's desired game progression style, tactics, etc.

[0211] "Parameters" are input data such as theme, difficulty level, play style, etc., obtained based on a generation request.

[0212] A "generative model means" is an AI-based algorithm or system that automatically generates worlds and dungeons based on acquired parameters.

[0213] "Means for saving and responding to data" refers to the function of saving the data of the generated world and dungeon in a database and sending that data to the user.

[0214] "Preview" is a function that displays the contents of the generated world or dungeon so that the user can check them.

[0215] "Means for customization" refers to a feature that allows users to freely modify and adjust the details of the generated worlds and dungeons.

[0216] A "smartphone" is a mobile information device that allows users to use applications to create and customize worlds and dungeons.

[0217] The system for implementing this invention mainly includes a terminal that accepts generation requests, a server that generates worlds and dungeons based on acquired parameters, and a means for saving and responding to the generated data. This system allows users to easily generate and customize original worlds and dungeons on their own smartphones.

[0218] Hardware and Software Configuration

[0219] Hardware

[0220] Device: Smartphone (Android or iOS device)

[0221] Server: Cloud server

[0222] software

[0223] Frontend: React Native

[0224] Backend: Node.js, Express

[0225] Database: MongoDB

[0226] Generative AI model: GPT-4 or other generative AI model (OpenAI API)

[0227] Specific processing of the system

[0228] Accepting a generation request

[0229] Users open the app on their smartphone and input parameters to generate a new world or dungeon. They can choose from a variety of themes, difficulty levels, and play styles. They can choose from a "future city" theme, a "high level" difficulty level, or a "battle-focused" play style.

[0230] Parameter retrieval and validation

[0231] The creation request sent from the terminal is passed to the server, which validates the received parameters to ensure that they do not contain invalid data.

[0232] World and dungeon generation

[0233] Parameters are input into the generative AI model, which automatically generates worlds and dungeons based on these parameters. During this process, the appropriate materials, layouts, enemy characters, items, etc. are retrieved from the database and configured to fit the parameters.

[0234] Data storage and response

[0235] The generated world and dungeon data is stored in a database and sent back to the device as a response. The device displays the received data in a user interface, allowing the user to preview and customize the content as needed.

[0236] Specific examples

[0237] For example, if a user selects a "future city" theme, a "high level" difficulty level, and a "battle-focused" play style, the parameters are sent to the server and, after validation, input into the generative AI model. The generative AI model automatically generates a dungeon containing futuristic city-style buildings, corridors, enemy characters, and battle scenes. The generated data is stored in a database and sent back to the device, allowing the user to preview the new world on their smartphone and further customize it.

[0238] Example prompts for generative AI models

[0239] Generate a new dungeon based on the following parameters:

[0240] Theme: Future City

[0241] Difficulty: High level

[0242] Playstyle: Battle-focused

[0243] Dungeons must contain enemy characters and battle scenes.

[0244] This system allows users to easily generate advanced worlds and dungeons and customize them freely.

[0245] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0246] Step 1:

[0247] The user opens the smartphone application and inputs the theme, difficulty level, and play style to generate a new world or dungeon. At this time, the user inputs the specific parameters of the theme (e.g., "future city"), difficulty level (e.g., "high level"), and play style (e.g., "focus on battle") into the device. The input parameters are formatted as generation request data on the device, and the request data is created as output.

[0248] Step 2:

[0249] The generation request data is sent from the terminal to the server. The server analyzes the received request data and extracts the parameters of theme, difficulty, and play style. In this step, the received data is checked to see if it is valid (validation). After the consistency of the data is confirmed, it becomes a valid request. Consistent parameter data is obtained as the output.

[0250] Step 3:

[0251] The server inputs the successfully validated parameters into the generative AI model. At this time, the parameter data is formatted as a prompt for the generative AI model. The prompt is converted into a format that is easy for the generative AI model to understand (e.g., "Generate a new dungeon based on the following parameters: Theme: futuristic city, Difficulty: high level, Play style: battle-focused"). The prompt is input into the generative AI model, and an appropriate world or dungeon is generated. The data for the generated world or dungeon is obtained as output.

[0252] Step 4:

[0253] The generated world and dungeon data is saved on the server. A database (MongoDB) is used for saving. This data is associated with user identification information and managed as a different world or dungeon for each user. A save completion message is returned from the server as output.

[0254] Step 5:

[0255] Once the world or dungeon data has been saved, it is sent back to the device from the server. The device displays the received data in the user interface. It is visually rendered in the UI so that the user can see a preview of the generated world or dungeon. A preview screen is provided as output for the user to view.

[0256] Step 6:

[0257] The user checks the displayed preview and customizes it as necessary. In this step, the user edits the details of the generated world or dungeon (e.g., enemy character placement, item location, layout, etc.) on their smartphone. The edited data is then sent back to the server and updated. The final customized world or dungeon data is obtained as output.

[0258] By following these steps, users can easily create original worlds and dungeons on their smartphones and customize them to their liking.

[0259] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0260] The system of the present invention combines a generative AI model with an emotion engine that recognizes user emotions to automatically generate worlds and dungeons for games and RPGs, and provide content optimized according to the user's emotions. This system includes the following main components and processes:

[0261] System Configuration

[0262] This system consists of the following components:

[0263] 1. How to accept creation requests

[0264] The terminal provides a user interface that allows the user to input parameters required for generating a world or dungeon. Through this interface, the user specifies the desired theme, difficulty level, and play style.

[0265] 2. How to get parameters

[0266] The server receives the creation request sent from the device and detects the parameters of theme, difficulty, and play style. Data validation is also performed at this stage.

[0267] 3. Emotion Engine

[0268] The device's built-in camera and microphone capture the user's facial expressions and voice, and then analyzes them to recognize the user's emotions.

[0269] The server adjusts the parameters of the generation request based on this emotion data, for example, setting the difficulty level low if the user is tired and high if the user is excited.

[0270] 4. Generative Modeling Methods

[0271] The server maintains a generation AI model, which inputs the acquired parameters into the AI ​​model, which then automatically generates appropriate worlds and dungeons based on the input.

[0272] 5. Data storage and response measures

[0273] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[0274] The device displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[0275] Program processing

[0276] Specifically, the program of this system performs the following processing.

[0277] Accepting a generation request

[0278] Users use the on-device UI to input parameters (theme, difficulty level, play style) to generate new worlds and dungeons. At that time, the device's camera and microphone capture the user's facial expressions and voice, and the emotion engine analyzes the user's emotional state.

[0279] Parameter retrieval and validation

[0280] The device combines the parameters entered by the user and the emotional data analyzed by the emotion engine to generate request data and sends it to the server. The server receives this request and validates the parameters.

[0281] Emotion-based parameter adjustment

[0282] The server automatically adjusts the generation parameters based on the user's emotional data. For example, if the user is feeling relaxed, the server changes the theme to a soothing one and sets the difficulty level lower.

[0283] World and dungeon generation

[0284] The server inputs the adjusted parameters based on validation and emotion into the generative AI model, which then automatically generates new worlds and dungeons based on this data.

[0285] Saving and returning generated results

[0286] The server stores the generated world and dungeon data in a database, generates a response, and sends it back to the device, which receives the data and displays it on the user interface.

[0287] Specific examples

[0288] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[0289] 1. The user inputs their choices into the device, while the camera and microphone capture the user's emotions.

[0290] 2. The device sends the user's input parameters and emotion data to the server, which then inputs optimized generation parameters based on this data into the generative AI model.

[0291] 3. The generative AI model creates the basic structure of castles and dungeons based on a "medieval fantasy" theme, and places appropriate difficulty and exploration elements depending on the user's emotional state.

[0292] 4. The server stores the generated data and sends it back to the device.

[0293] 5. Users can preview the generated world or dungeon on their device and enjoy the optimal experience suggested based on their emotions.

[0294] In this way, the system can quickly generate worlds and dungeons that correspond to the user's emotional state, providing an individually optimized adventure.

[0295] The processing flow will be explained below.

[0296] Specific processing steps of the program

[0297] Automatic world and dungeon generation system using emotion engine

[0298] Step 1:

[0299] Using the device's user interface (UI), users input parameters for generating new worlds and dungeons, including a "medieval fantasy" theme, a "medium" difficulty level, and an "exploration-focused" play style.

[0300] Step 2:

[0301] The device acquires the parameters entered by the user and also uses a camera and microphone to collect the user's facial expressions and voice data.

[0302] Step 3:

[0303] The device inputs the collected facial and voice data into an emotion engine to analyze the user's emotional state. For example, the facial recognition system can detect excitement from the user's smile, and voice analysis can assess stress levels from the tone of voice.

[0304] Step 4:

[0305] Based on the analysis, the emotion engine determines whether the user is currently relaxed, stressed, or excited, and sends this information along with the parameters of the generation request to the server.

[0306] Step 5:

[0307] The device generates JSON-formatted request data containing the parameters entered by the user and the emotion engine's analysis results, and sends it to the server's API endpoint. Request data example:

[0308] json

[0309] {

[0310] "theme": "Medieval Fantasy",

[0311] "difficulty": "medium level",

[0312] "playStyle": "Exploration-oriented",

[0313] "emotionalState": "Relaxed"

[0314] }

[0315] Receiving and Validating a Request

[0316] Step 6:

[0317] The server receives the request at the API endpoint and validates the request data, checking that all required fields are present and that the values ​​are valid.

[0318] Step 7:

[0319] The server validates the request parameters, and if validation is successful, proceeds to the next step. If validation fails, it returns an error response to the terminal.

[0320] Emotion-based parameter adjustment

[0321] Step 8:

[0322] The server adjusts parameters based on the user's emotional state received from the emotion engine. For example, if the user is relaxed, the difficulty level is lowered slightly and the exploration element is increased.

[0323] World and dungeon generation

[0324] Step 9:

[0325] The server accesses the database and retrieves data (terrain, enemy characters, items, etc.) related to the requested theme "medieval fantasy," difficulty level "medium level," and play style "exploration-oriented."

[0326] Step 10:

[0327] The server inputs the adjusted parameters and acquired data into the generative AI model, which generates new worlds and dungeons based on this data.

[0328] Step 11:

[0329] The generative AI model creates the basic structure of castles and dungeons with a medieval fantasy layout, populating them with enemies, traps, and exploration elements of moderate difficulty.

[0330] Saving and returning generated results

[0331] Step 12:

[0332] The server stores generated world and dungeon data in a database, including the generation ID, generation data, and generation date and time.

[0333] Step 13:

[0334] The server converts the generated results into JSON format and generates a response, which contains details about the generated world and dungeon.

[0335] Step 14:

[0336] The server sends a response containing the generated data back to the device via the API.

[0337] Viewing and customizing the results

[0338] Step 15:

[0339] The device parses the generated data received from the server and displays it in a user interface, including a visual preview of the generated world and dungeon.

[0340] Step 16:

[0341] Users can preview the generated world and dungeon and customize it as needed, for example by rearranging specific rooms or adding items.

[0342] Step 17:

[0343] The device saves any customizations made by the user and finalizes them as world and dungeon data.

[0344] In this way, a system is realized that can provide a superior gaming experience that is tailored to the user's emotional state.

[0345] Example 2

[0346] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0347] Conventional game and RPG world and dungeon generation systems only provide static content based on user input parameters, making it difficult to dynamically adjust to the user's emotional state. This can result in a consistently inoffensive gaming experience, as users are presented with content that is not optimized for their current emotional state.

[0348] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0349] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style, means for acquiring emotional data using an emotion engine that recognizes the user's emotions, means for automatically adjusting the parameters based on the acquired emotional data, generative model means for automatically generating worlds and dungeons based on the adjusted parameters, and means for saving and responding to the generated data, thereby enabling the automatic generation of worlds and dungeons optimized according to the user's emotional state.

[0350] The "means for accepting a generation request" is a means by which a user inputs parameters for generating a new world or dungeon, and the system accepts them.

[0351] "Theme" refers to the basic concept or style of the generated world or dungeon, such as a category like "medieval fantasy" or "cyberpunk."

[0352] "Difficulty" is a parameter that indicates the level of challenge in the game in the generated world or dungeon, and is set at levels such as easy, medium level, or difficult.

[0353] "Play style" is a parameter that indicates how a user enjoys a game, and examples include styles such as "exploration-oriented" and "combat-oriented."

[0354] "Means for acquiring parameters" refers to means for receiving information such as theme, difficulty level, play style, etc. input by the user and storing it within the system.

[0355] An "emotion engine" is a software or hardware technology that recognizes a user's emotional state at any given time by analyzing the user's facial expressions and voice.

[0356] The "means for acquiring emotion data" is a means for acquiring data relating to the user's emotional state using an emotion engine.

[0357] The "means for automatically adjusting parameters" is a means for automatically changing parameters such as theme, difficulty level, and play style input by the user based on the acquired emotional data.

[0358] "Generative model means" refers to means that includes models and algorithms for automatically generating worlds and dungeons based on adjusted parameters.

[0359] "Means for saving and responding to generated data" refers to means for saving data on the generated worlds and dungeons in a database and providing it to the user.

[0360] "World" refers to the virtual world or area that serves as the playing environment for a game or RPG.

[0361] A "dungeon" is a complex structure or area in a game or RPG that players explore to progress through missions or quests.

[0362] The system of the present invention combines a generative AI model with an emotion engine that recognizes user emotions to automatically generate worlds and dungeons for games and RPGs, and provides content optimized according to the user's emotions. This system includes the following main components and processes:

[0363] System Configuration

[0364] This system consists of the following components:

[0365] 1. How to accept creation requests

[0366] The terminal provides a user interface for inputting the parameters (theme, difficulty, play style) required when a user wishes to generate a world or dungeon. Through this interface, the user can create a specific generation request.

[0367] 2. How to get parameters

[0368] The server receives the creation request sent from the device and detects and validates the theme, difficulty, and play style parameters to ensure that the creation request is processed properly.

[0369] 3. Emotion Engine

[0370] The device's built-in camera and microphone capture the user's facial expressions and voice, and then analyzes them to recognize the user's emotions.

[0371] The server adjusts the parameters of the generation request based on this emotion data, for example, setting the difficulty level low if the user is tired and high if the user is excited.

[0372] 4. Generative Modeling Methods

[0373] The server maintains a generative AI model, which automatically generates appropriate worlds and dungeons based on the parameters and emotional data acquired from the AI ​​model. Examples of generative AI models used include GPT-3 and DALL-E.

[0374] 5. Data storage and response measures

[0375] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[0376] The terminal displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[0377] Specific examples

[0378] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[0379] 1. The user inputs their choices into the device, while the camera and microphone capture the user's emotions.

[0380] 2. The device sends the user's input parameters and emotion data to the server, which then inputs optimized generation parameters based on this data into the generative AI model.

[0381] 3. The generative AI model creates the basic structure of castles and dungeons based on a "medieval fantasy" theme, and places appropriate difficulty and exploration elements depending on the user's emotional state.

[0382] 4. The server stores the generated data and sends it back to the device.

[0383] 5. Users can preview the generated world or dungeon on their device and enjoy the optimal experience suggested based on their emotions.

[0384] Prompt Sentence Examples

[0385] Examples of prompts to drive a generative AI model include:

[0386] "Theme: Medieval fantasy, Difficulty: Medium, Play style: Exploration-focused, User emotion: Relaxed"

[0387] In this way, the system can quickly generate optimized worlds and dungeons that correspond to the user's emotional state, providing an individually optimized adventure.

[0388] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0389] Step 1: Accepting the generation request

[0390] The user uses the user interface on the device to input the desired parameters (theme, difficulty, play style) for generating a world or dungeon. The input theme is often "medieval fantasy," the difficulty level is "medium level," and the play style is "exploration-oriented." The device receives the user's input and stores these parameters in an internal data structure. At the same time, the device's camera and microphone collect the user's facial expressions and voice. The collected data is analyzed in real time by the emotion engine.

[0391] input:

[0392] Theme, difficulty, playstyle (via user interface)

[0393] User's facial expressions and voice (via camera and microphone)

[0394] output:

[0395] Analyzed parameters and emotion data

[0396] Step 2: Obtaining and validating parameters

[0397] The device combines the parameters entered by the user (theme, difficulty level, play style) with the emotional data analyzed by the emotion engine and sends it to the server as request data. The server receives this data and verifies the appropriateness and validity of each parameter. For example, it checks whether the theme is appropriate and whether the difficulty level is within an acceptable range.

[0398] input:

[0399] User-entered parameters

[0400] Emotion data acquired by the emotion engine

[0401] output:

[0402] Validated parameters and emotion data

[0403] Step 3: Collecting emotion data

[0404] The device's built-in camera and microphone are used to collect the user's facial expressions and voice. This is partially done in Step 1, but is done again with the aim of accurately obtaining the user's emotional data. The emotion engine analyzes this data and determines the user's emotions, such as whether they are relaxed, excited, or tired, using numerical values ​​and categories.

[0405] input:

[0406] User's facial expressions and voice (via camera and microphone)

[0407] output:

[0408] Emotion data analyzed by the emotion engine

[0409] Step 4: Emotion-based parameter adjustment

[0410] The server automatically adjusts the generation parameters entered by the user based on the emotion data sent from the emotion engine. For example, if the server determines that the user is relaxed, it will set the difficulty to "low" and change the theme to "relaxing." These adjusted parameters will provide a more appropriate gaming experience for the user.

[0411] input:

[0412] Verified parameters

[0413] Emotional Data

[0414] output:

[0415] Adjusted parameters

[0416] Step 5: World and dungeon generation

[0417] The server inputs the adjusted emotion-based parameters into a generative AI model, which uses algorithms such as GPT-3 or DALL-E to generate detailed structures and designs for new worlds and dungeons based on the input parameters.

[0418] input:

[0419] Adjusted parameters (theme, difficulty, play style)

[0420] output:

[0421] Generated world and dungeon data

[0422] Step 6: Save and return the generated results

[0423] The server stores the generated world and dungeon data in a database and sends it back to the device as a response. The device receives the generated data and displays it on the user interface, allowing the user to preview the generated world and dungeon and begin their experience.

[0424] input:

[0425] Generated world and dungeon data

[0426] output:

[0427] World and dungeon previews

[0428] Through this process, the system quickly generates optimized worlds and dungeons according to the user's emotional state, providing an individually optimized adventure experience.

[0429] (Application example 2)

[0430] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0431] Conventional content generation systems generate game and RPG worlds and dungeons based on fixed parameters without taking user emotions into account. This makes it difficult to provide an optimal play experience according to the user's emotional state. Furthermore, conventional systems have difficulty responding to situations where content needs to be instantly adjusted according to the user's temporary emotional state.

[0432] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0433] In this invention, the server includes means for accepting generation requests, means for recognizing the user's emotions and adjusting parameters, and generative model means for automatically generating worlds and dungeons from the acquired parameters, thereby enabling the parameters to be instantly adjusted based on the user's emotional state, enabling optimized content generation.

[0434] A "generation request" is information regarding the theme, difficulty level, and play style that a user specifies when they wish to generate a world or dungeon.

[0435] The term "means" refers to components or functional units necessary for carrying out the present invention.

[0436] "Theme" is a category that defines the basic setting and background of the generated world or dungeon.

[0437] "Difficulty" defines the degree of challenge and obstacles the player faces in a generated world or dungeon.

[0438] "Play style" is a concept that indicates how a user wants to progress through a game and what they value in their experience.

[0439] An "emotion engine" is a technology that analyzes a user's facial expressions and voice to recognize their emotional state.

[0440] "Generative model means" is a general term for algorithms and models that automatically generate worlds and dungeons based on acquired parameters.

[0441] "Means for saving and responding to data" refers to a function for saving data of generated worlds and dungeons in a storage system such as a database, and providing that data to users as needed.

[0442] The system of the present invention automatically generates worlds and dungeons based on the user's emotions and has the following configuration: First, the user inputs a generation request through a user interface on a terminal. The generation request includes parameters related to theme, difficulty, and play style.

[0443] System configuration

[0444] 1. Terminal: An input device where the user inputs the generation request and captures the emotional state in real time. This is often a smartphone or tablet.

[0445] 2. Server: Receives generation requests sent by users, analyzes emotional data, and generates worlds and dungeons using generative AI models. This also includes data storage and response functions.

[0446] Program processing

[0447] 1. Receiving a generation request: The device accepts a generation request from the user. The user specifies the theme, difficulty level, and play style. The device also captures the user's facial expressions and voice using the device's camera and microphone, and sends them to the emotion engine.

[0448] 2. Emotion Data Analysis: The server analyzes the captured emotion data using an emotion engine, which uses technologies such as OpenCV and DeepFace to determine whether the user is relaxed, excited, tired, etc.

[0449] 3. Adjustment of generation parameters: The server adjusts the generation parameters based on the analyzed emotional data. For example, if the user is relaxed, it will set the difficulty level low and change the theme to a soothing one.

[0450] 4. World and dungeon generation: The server generates worlds and dungeons based on the adjusted parameters using a generative AI model, such as GPT-3 or a similar AI model.

[0451] 5. Data storage and response: The server stores the generated data in a database and responds to the terminal. The terminal displays the received data on the user interface, allowing the user to check the generated world and dungeon.

[0452] Specific examples

[0453] If a user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, a world is generated through the following steps. First, the device accepts the user's input and sends facial expressions and voice captured by the camera to the emotion engine. Next, the server uses the emotion engine to analyze the user's emotional state and adjusts the generation parameters appropriately. The generative AI model automatically generates the world and dungeons based on this data, and the generated data is stored in a database and provided to the user on the device.

[0454] Example prompt sentence:

[0455] "Generate a medieval fantasy-themed world with a medium level of difficulty and a focus on exploration based on user emotional data. The user is very happy."

[0456] As described above, this system can automatically generate optimal worlds and dungeons according to the user's emotional state, providing an individually optimized playing experience.

[0457] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0458] Step 1:

[0459] Accepting a generation request

[0460] The device receives a generation request from the user. The user inputs the theme, difficulty level, and play style into the device's user interface. At this time, the device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The input data includes the theme, difficulty level, play style, and facial and voice data.

[0461] Step 2:

[0462] Sentiment Data Analysis

[0463] The server receives facial and voice data sent from the device and analyzes it using an emotion engine. It uses technologies such as OpenCV and DeepFace to determine the user's emotional state (relaxed, excited, tired, etc.). The input is the captured facial and voice data, and the output is data indicating the emotional state.

[0464] Step 3:

[0465] Adjusting generation parameters

[0466] The server automatically adjusts the generation parameters based on the analyzed emotional data. For example, if the user is relaxed, it sets the difficulty to low and changes the theme to soothing. The inputs are theme, difficulty, play style, and emotional data, and the output is the adjusted generation parameters. These parameters are used as input for the generative AI model.

[0467] Step 4:

[0468] World and dungeon generation

[0469] The server uses a generative AI model to generate worlds and dungeons based on the adjusted parameters. Examples of generative AI models used here include GPT-3. By providing the adjusted parameters as input to the generative AI model, an appropriate world or dungeon is output. The input is the adjusted generation parameters, and the output is the data for the generated world or dungeon.

[0470] Step 5:

[0471] Data Storage and Response

[0472] The server stores the generated data in a database and responds to the terminal. The terminal displays the received world and dungeon data on the user interface. The user can check the generated world and dungeon and customize it as needed. The input is the generated world and dungeon data, and the output is preview information of the world and dungeon displayed to the user.

[0473] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0474] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0475] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0476] [Second embodiment]

[0477] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0478] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0479] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0480] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0481] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0482] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0483] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0484] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0485] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0486] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0487] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0488] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0489] The present invention is a system that automatically generates worlds and dungeons for games and RPGs using a generative AI model, and mainly includes the following main components and processes.

[0490] System Configuration

[0491] This system consists of the following components:

[0492] 1. How to accept creation requests

[0493] The terminal provides a user interface that allows the user to input parameters required for generating a world or dungeon. Through this interface, the user specifies the desired theme, difficulty level, and play style.

[0494] 2. How to get parameters

[0495] The server receives the creation request sent from the device and detects the parameters of theme, difficulty, and play style. Data validation is also performed at this stage.

[0496] 3. Generative Modeling Methods

[0497] The server maintains a generation AI model, which inputs the acquired parameters into the AI ​​model, which then automatically generates appropriate worlds and dungeons based on the input.

[0498] 4. Data storage and response methods

[0499] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[0500] The terminal displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[0501] Program processing

[0502] Specifically, the program of this system performs the following processing.

[0503] Accepting a generation request

[0504] Users input parameters (theme, difficulty, play style) to generate new worlds and dungeons using the UI on their device. For example, they can select a "medieval fantasy" theme, a "medium" difficulty level, and an "exploration-focused" play style.

[0505] Parameter retrieval and validation

[0506] The terminal generates request data including the parameters entered by the user and sends it to the server, which receives the request and validates the parameters.

[0507] World and dungeon generation

[0508] The server inputs the successfully validated parameters into the generative AI model, which then automatically generates new worlds and dungeons based on these inputs. During this process, the server retrieves appropriate materials, layouts, enemy characters, items, etc. from the database and generates a structure that matches the parameters.

[0509] Data storage and return

[0510] The server stores the generated world and dungeon data in a database, generates a response, and sends it back to the device. The device receives this data and displays a preview of the generated world or dungeon to the user.

[0511] Specific examples

[0512] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[0513] 1. A request containing parameters entered by the user is sent from the terminal.

[0514] 2. The server receives the request, validates it, and then inputs data based on the theme "Medieval Fantasy," difficulty level "Medium," and play style "Exploration-focused" into the generative AI model.

[0515] 3. The generative AI model generates the basic structure of a medieval castle or dungeon, and places enemy characters of moderate difficulty, numerous traps, secret rooms, etc.

[0516] 4. The server stores the generated data and sends it back to the device.

[0517] 5. Users can preview the generated world or dungeon on their device and make any adjustments or customizations they like.

[0518] In this way, a system is created that allows creators to quickly generate diverse worlds and dungeons, providing players with new adventures.

[0519] The processing flow will be explained below.

[0520] Specific processing steps of the program

[0521] Accepting a creation request and obtaining parameters

[0522] Step 1:

[0523] Users access a user interface (UI) on their device and input parameters for generating new worlds and dungeons, such as a theme of "medieval fantasy," a difficulty level of "medium," and a play style of "exploration-focused."

[0524] Step 2:

[0525] The terminal receives the parameters entered by the user and generates request data in JSON format. Example of request data:

[0526] json

[0527] {

[0528] "theme": "Medieval Fantasy",

[0529] "difficulty": "medium level",

[0530] "playStyle": "Exploration-oriented"

[0531] }

[0532] Step 3:

[0533] The device sends the generated request data to the server's API endpoint. This communication uses the HTTP protocol.

[0534] Receiving and Validating a Request

[0535] Step 4:

[0536] The server receives the request sent through the API and validates the request data, checking that all required fields are present and that the values ​​are valid.

[0537] Step 5:

[0538] The server validates the request parameters, and if validation is successful, proceeds to the next step. If validation fails, it returns an error response to the terminal.

[0539] World and dungeon generation

[0540] Step 6:

[0541] The server accesses the database and retrieves data (terrain, enemy characters, items, etc.) related to the requested theme "Medieval Fantasy," difficulty level "Medium," and play style "Exploration-focused."

[0542] Step 7:

[0543] The server inputs the acquired data and request parameters into a generative AI model, which then generates new worlds and dungeons based on this data.

[0544] Step 8:

[0545] The generative AI model creates the basic structure of a medieval fantasy castle or dungeon, with a layout that emphasizes exploration, and features enemies, traps, secret rooms, and other elements of moderate difficulty.

[0546] Saving and returning generated results

[0547] Step 9:

[0548] The server stores generated world and dungeon data in a database, including the generation ID, generation data, and generation date and time.

[0549] Step 10:

[0550] The server converts the generated results into JSON format and generates a response, which contains details about the generated world and dungeon.

[0551] Step 11:

[0552] The server sends a response containing the generated data back to the device via the API.

[0553] Viewing and customizing the results

[0554] Step 12:

[0555] The device parses the generated data received from the server and displays it in a user interface, including a visual preview of the generated world and dungeon.

[0556] Step 13:

[0557] The user can preview the generated world and dungeon and customize it as needed, for example by rearranging specific rooms or adding items.

[0558] Step 14:

[0559] The device saves any customizations made by the user and finalizes them as world and dungeon data.

[0560] Example 1

[0561] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0562] The generation of worlds and dungeons in conventional games and RPGs is often done manually, requiring a great deal of time and effort. This makes it difficult to quickly generate diverse worlds and dungeons. Furthermore, existing automatic generation systems have the problem of making it difficult to customize them to fit a user's desired theme or play style. Therefore, there is a demand for technology that can efficiently generate diverse, high-quality worlds and dungeons that meet user needs.

[0563] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0564] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style based on the generation request and validating the parameters, means for inputting the acquired parameters into a generation AI model and automatically generating appropriate worlds and dungeons, means for storing data of the generated worlds and dungeons in a database and returning the data to the terminal as a response, and means for displaying the returned data on the terminal and providing a user interface that can be customized by the user. This allows for the efficient generation of diverse, high-quality worlds and dungeons that meet the user's needs and also allows the user to customize them themselves.

[0565] The "means for accepting a generation request" is a device or function that provides an interface that allows a user to input parameters necessary to generate a world or dungeon.

[0566] "Parameters" are information required by the generation AI model to generate a world or dungeon, such as the theme, difficulty, and play style of the generated world or dungeon.

[0567] "Validation means" refers to a device or function that verifies the validity of data by checking whether the acquired parameters are in the correct format or range.

[0568] A "generative AI model" is an algorithm or system that takes acquired parameters as input and automatically generates appropriate worlds and dungeons based on them.

[0569] A "generative model means" is a device or function that uses a generative AI model to automatically generate worlds and dungeons based on parameters.

[0570] A "database" is a storage device or system for storing data on generated worlds and dungeons.

[0571] The "means for returning as a response" is a device or function that sends data of the generated world or dungeon to the terminal and displays it to the user.

[0572] "User interface" is a function that provides a screen and operating means that allows users to preview the worlds and dungeons generated on their device and customize them as needed.

[0573] This invention is a system that uses a generative AI model to automatically generate worlds and dungeons for games and RPGs. This system mainly uses three main components: a server, a terminal, and a user, as well as various data processing means. The specific form and operation of the system are shown below.

[0574] Components and Operation

[0575] A means of accepting creation requests

[0576] The terminal provides the user with a user interface that allows them to input the parameters required to generate a world or dungeon. Through this interface, the user can specify the desired theme, difficulty level, and play style. For example, the user might input parameters such as "Theme: Medieval Fantasy," "Difficulty: Medium level," and "Play Style: Exploration-focused."

[0577] A means of obtaining and validating parameters

[0578] The device generates request data including the parameters entered by the user and sends it to the server. The server analyzes the received request data and extracts the parameters for theme, difficulty, and play style. The extracted parameters are then validated to ensure they are in the correct format and range. For example, it verifies that "difficulty" is either "low," "medium," or "high."

[0579] A means of generating worlds and dungeons using generative AI models

[0580] The server uses the validated parameters to input the generative AI model, generating a prompt like this:

[0581] Theme: Medieval Fantasy

[0582] Difficulty: Medium

[0583] Playstyle: Exploration-focused

[0584] Specific instructions:

[0585] Generate the basic structure of a medieval castle or dungeon

[0586] Place enemy characters with a moderate level of difficulty

[0587] Lots of traps and secret rooms

[0588] Based on these prompts, a generative AI model (such as GPT-4) automatically generates appropriate world and dungeon structures, layouts, enemy characters, items, etc.

[0589] A means to save the generated results and return them as a response

[0590] The server saves the generated world and dungeon data in a database. It then sends the saved data back to the device as a response. The device can then analyze the received data and display a preview of the world or dungeon to the user.

[0591] A means of displaying generated results and providing a customizable user interface

[0592] The device visually displays the generated world and dungeon to the user. The user can check the displayed world and dungeon and customize parts of it as needed. For example, they can change the layout of the generated dungeon by dragging and dropping, or add new enemy characters or items.

[0593] Specific examples

[0594] For example, if a user inputs the parameters "Theme: Medieval Fantasy", "Difficulty: Medium", and "Playstyle: Exploration-Oriented", the following sequence of actions will occur:

[0595] 1. The user enters parameters using the terminal interface.

[0596] 2. The terminal generates request data and sends it to the server.

[0597] 3. The server receives the request and validates the parameters.

[0598] 4. The server uses the generative AI model to generate worlds and dungeons based on the parameters.

[0599] 5. The generative AI model generates the basic structure of medieval castles and dungeons, as well as enemy characters, traps, secret rooms, and other elements of moderate difficulty.

[0600] 6. The server stores the generated data and sends it back to the device.

[0601] 7. The user can preview the generated world and dungeon on their device and customize it as needed.

[0602] This system allows users to quickly generate diverse, high-quality worlds and dungeons, providing players with new adventures.

[0603] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0604] Step 1:

[0605] The user uses the terminal's user interface to create new worlds and dungeons, inputting parameters such as theme, difficulty level, and play style.

[0606] Inputs: Theme (medieval fantasy), difficulty (medium), playstyle (exploration-focused).

[0607] Operation: Each parameter is selected using a drop-down menu, radio button, checkbox, etc. on the user interface.

[0608] Output: The parameter set entered by the user.

[0609] Step 2:

[0610] The terminal generates request data including the parameters input by the user and transmits it to the server.

[0611] Input: A set of parameters entered by the user.

[0612] Data processing: Converts parameters into JSON format request data.

[0613] What it does: Sends the request data to the server using an HTTP POST request.

[0614] Output: The request data sent to the server.

[0615] Step 3:

[0616] The server receives the request data sent from the terminal and validates the parameters.

[0617] Input: Request data sent from the terminal (JSON format).

[0618] Data processing: Parse the JSON data, extract the theme, difficulty, and playstyle parameters, and ensure they are in the correct format and values.

[0619] What it does: Validates each extracted parameter (e.g., checks that the difficulty is either "low", "medium", or "high").

[0620] Output: The validated parameter set.

[0621] Step 4:

[0622] The server uses the successfully validated parameters to input a prompt sentence into the generative AI model.

[0623] Input: A validated set of parameters.

[0624] Data calculation: Generate prompt sentences and input them into the generative AI model.

[0625] How it works: Generate a prompt sentence like the one below and pass it to a generative AI model (e.g., GPT-4).

[0626] Theme: Medieval Fantasy

[0627] Difficulty: Medium

[0628] Playstyle: Exploration-focused

[0629] Specific instructions:

[0630] Generate the basic structure of a medieval castle or dungeon

[0631] Place enemy characters with a moderate level of difficulty

[0632] Lots of traps and secret rooms

[0633] Output: Output data from the generative AI model (detailed world and dungeon generation data).

[0634] Step 5:

[0635] The server stores the generated data obtained from the generative AI model in a database.

[0636] Input: The output data from the generative AI model.

[0637] Data processing: Organizing the generated data and converting it into a format that can be stored in a database.

[0638] What it does: Executes a SQL query that inserts the generated data into a database.

[0639] Output: Generated data stored in a database.

[0640] Step 6:

[0641] The server returns the generated data stored in the database to the terminal as a response.

[0642] Input: Generated data stored in a database.

[0643] Data processing: Converting some or all of the generated data into a JSON response.

[0644] Operation: Sends to the terminal as an HTTP response.

[0645] Output: The JSON response sent to the terminal.

[0646] Step 7:

[0647] The terminal analyzes the generated data received from the server and displays it to the user.

[0648] Input: The JSON response received from the server.

[0649] Data processing: Parse JSON data to extract world and dungeon structure.

[0650] How it works: It uses the extracted data to visually display worlds and dungeons in a user interface, and also provides an edit mode for user customization.

[0651] Output: A user-viewable and customizable representation of the world and dungeon.

[0652] In this way, users can easily create high-quality worlds and dungeons and customize them as needed.

[0653] (Application example 1)

[0654] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0655] Conventional world and dungeon generation systems require users to manually create detailed settings and layouts, which takes time and effort. Furthermore, customization of the generated worlds and dungeons is limited, making it difficult for users to fully express their creativity. Therefore, there is a demand for a system that allows users to easily generate worlds and dungeons on their smartphones and freely customize their content.

[0656] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0657] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style, generation model means for automatically generating worlds and dungeons from the acquired parameters, means for saving and responding to data on the generated worlds and dungeons, and means for the user to preview and customize the generated worlds and dungeons on their smartphones. This allows users to easily generate worlds and dungeons using their smartphones and freely customize their contents.

[0658] A "generation request" is a request entered by a user to generate a world or dungeon based on specific conditions.

[0659] "Theme" is a category that determines the overall setting and atmosphere of the generated world or dungeon.

[0660] "Difficulty" is a parameter that indicates the difficulty of playing in the generated world or dungeon.

[0661] "Play style" is a parameter that indicates the user's desired game progression style, tactics, etc.

[0662] "Parameters" are input data such as theme, difficulty level, play style, etc., obtained based on a generation request.

[0663] A "generative model means" is an AI-based algorithm or system that automatically generates worlds and dungeons based on acquired parameters.

[0664] "Means for saving and responding to data" refers to the function of saving the data of the generated world and dungeon in a database and sending that data to the user.

[0665] "Preview" is a function that displays the contents of the generated world or dungeon so that the user can check them.

[0666] "Means for customization" refers to a feature that allows users to freely modify and adjust the details of the generated worlds and dungeons.

[0667] A "smartphone" is a mobile information device that allows users to use applications to create and customize worlds and dungeons.

[0668] The system for implementing this invention mainly includes a terminal that accepts generation requests, a server that generates worlds and dungeons based on acquired parameters, and a means for saving and responding to the generated data. This system allows users to easily generate and customize original worlds and dungeons on their own smartphones.

[0669] Hardware and Software Configuration

[0670] Hardware

[0671] Device: Smartphone (Android or iOS device)

[0672] Server: Cloud server

[0673] software

[0674] Frontend: React Native

[0675] Backend: Node.js, Express

[0676] Database: MongoDB

[0677] Generative AI model: GPT-4 or other generative AI model (OpenAI API)

[0678] Specific processing of the system

[0679] Accepting a generation request

[0680] Users open the app on their smartphone and input parameters to generate a new world or dungeon. They can choose from a variety of themes, difficulty levels, and play styles. They can choose from a "future city" theme, a "high level" difficulty level, or a "battle-focused" play style.

[0681] Parameter retrieval and validation

[0682] The creation request sent from the terminal is passed to the server, which validates the received parameters to ensure that they do not contain invalid data.

[0683] World and dungeon generation

[0684] Parameters are input into the generative AI model, which automatically generates worlds and dungeons based on these parameters. During this process, the appropriate materials, layouts, enemy characters, items, etc. are retrieved from the database and configured to fit the parameters.

[0685] Data storage and response

[0686] The generated world and dungeon data is stored in a database and sent back to the device as a response. The device displays the received data in a user interface, allowing the user to preview and customize the content as needed.

[0687] Specific examples

[0688] For example, if a user selects a "future city" theme, a "high level" difficulty level, and a "battle-focused" play style, the parameters are sent to the server and, after validation, input into the generative AI model. The generative AI model automatically generates a dungeon containing futuristic city-style buildings, corridors, enemy characters, and battle scenes. The generated data is stored in a database and sent back to the device, allowing the user to preview the new world on their smartphone and further customize it.

[0689] Example prompts for generative AI models

[0690] Generate a new dungeon based on the following parameters:

[0691] Theme: Future City

[0692] Difficulty: High level

[0693] Playstyle: Battle-focused

[0694] Dungeons must contain enemy characters and battle scenes.

[0695] This system allows users to easily generate advanced worlds and dungeons and customize them freely.

[0696] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0697] Step 1:

[0698] The user opens the smartphone application and inputs the theme, difficulty level, and play style to generate a new world or dungeon. At this time, the user inputs the specific parameters of the theme (e.g., "future city"), difficulty level (e.g., "high level"), and play style (e.g., "focus on battle") into the device. The input parameters are formatted as generation request data on the device, and the request data is created as output.

[0699] Step 2:

[0700] The generation request data is sent from the terminal to the server. The server analyzes the received request data and extracts the parameters of theme, difficulty, and play style. In this step, the received data is checked to see if it is valid (validation). After the consistency of the data is confirmed, it becomes a valid request. Consistent parameter data is obtained as the output.

[0701] Step 3:

[0702] The server inputs the successfully validated parameters into the generative AI model. At this time, the parameter data is formatted as a prompt for the generative AI model. The prompt is converted into a format that is easy for the generative AI model to understand (e.g., "Generate a new dungeon based on the following parameters: Theme: futuristic city, Difficulty: high level, Play style: battle-focused"). The prompt is input into the generative AI model, and an appropriate world or dungeon is generated. The data for the generated world or dungeon is obtained as output.

[0703] Step 4:

[0704] The generated world and dungeon data is saved on the server. A database (MongoDB) is used for saving. This data is associated with user identification information and managed as a different world or dungeon for each user. A save completion message is returned from the server as output.

[0705] Step 5:

[0706] Once the world or dungeon data has been saved, it is sent back to the device from the server. The device displays the received data in the user interface. It is visually rendered in the UI so that the user can see a preview of the generated world or dungeon. A preview screen is provided as output for the user to view.

[0707] Step 6:

[0708] The user checks the displayed preview and customizes it as necessary. In this step, the user edits the details of the generated world or dungeon (e.g., enemy character placement, item location, layout, etc.) on their smartphone. The edited data is then sent back to the server and updated. The final customized world or dungeon data is obtained as output.

[0709] By following these steps, users can easily create original worlds and dungeons on their smartphones and customize them to their liking.

[0710] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0711] The system of the present invention combines a generative AI model with an emotion engine that recognizes user emotions to automatically generate worlds and dungeons for games and RPGs, and provide content optimized according to the user's emotions. This system includes the following main components and processes:

[0712] System Configuration

[0713] This system consists of the following components:

[0714] 1. How to accept creation requests

[0715] The terminal provides a user interface that allows the user to input parameters required for generating a world or dungeon. Through this interface, the user specifies the desired theme, difficulty level, and play style.

[0716] 2. How to get parameters

[0717] The server receives the creation request sent from the device and detects the parameters of theme, difficulty, and play style. Data validation is also performed at this stage.

[0718] 3. Emotion Engine

[0719] The device's built-in camera and microphone capture the user's facial expressions and voice, and then analyzes them to recognize the user's emotions.

[0720] The server adjusts the parameters of the generation request based on this emotion data, for example, setting the difficulty level low if the user is tired and high if the user is excited.

[0721] 4. Generative Modeling Methods

[0722] The server maintains a generation AI model, which inputs the acquired parameters into the AI ​​model, which then automatically generates appropriate worlds and dungeons based on the input.

[0723] 5. Data storage and response measures

[0724] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[0725] The device displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[0726] Program processing

[0727] Specifically, the program of this system performs the following processing.

[0728] Accepting a generation request

[0729] Users use the on-device UI to input parameters (theme, difficulty level, play style) to generate new worlds and dungeons. At that time, the device's camera and microphone capture the user's facial expressions and voice, and the emotion engine analyzes the user's emotional state.

[0730] Parameter retrieval and validation

[0731] The device combines the parameters entered by the user and the emotional data analyzed by the emotion engine to generate request data and sends it to the server. The server receives this request and validates the parameters.

[0732] Emotion-based parameter adjustment

[0733] The server automatically adjusts the generation parameters based on the user's emotional data. For example, if the user is feeling relaxed, the server changes the theme to a soothing one and sets the difficulty level lower.

[0734] World and dungeon generation

[0735] The server inputs the adjusted parameters based on validation and emotion into the generative AI model, which then automatically generates new worlds and dungeons based on this data.

[0736] Saving and returning generated results

[0737] The server stores the generated world and dungeon data in a database, generates a response, and sends it back to the device, which receives the data and displays it on the user interface.

[0738] Specific examples

[0739] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[0740] 1. The user inputs their choices into the device, while the camera and microphone capture the user's emotions.

[0741] 2. The device sends the user's input parameters and emotion data to the server, which then inputs optimized generation parameters based on this data into the generative AI model.

[0742] 3. The generative AI model creates the basic structure of castles and dungeons based on a "medieval fantasy" theme, and places appropriate difficulty and exploration elements depending on the user's emotional state.

[0743] 4. The server stores the generated data and sends it back to the device.

[0744] 5. Users can preview the generated world or dungeon on their device and enjoy the optimal experience suggested based on their emotions.

[0745] In this way, the system can quickly generate worlds and dungeons that correspond to the user's emotional state, providing an individually optimized adventure.

[0746] The processing flow will be explained below.

[0747] Specific processing steps of the program

[0748] Automatic world and dungeon generation system using emotion engine

[0749] Step 1:

[0750] Using the device's user interface (UI), users input parameters for generating new worlds and dungeons, including a "medieval fantasy" theme, a "medium" difficulty level, and an "exploration-focused" play style.

[0751] Step 2:

[0752] The device acquires the parameters entered by the user and also uses a camera and microphone to collect the user's facial expressions and voice data.

[0753] Step 3:

[0754] The device inputs the collected facial and voice data into an emotion engine to analyze the user's emotional state. For example, the facial recognition system can detect excitement from the user's smile, and voice analysis can assess stress levels from the tone of voice.

[0755] Step 4:

[0756] Based on the analysis, the emotion engine determines whether the user is currently relaxed, stressed, or excited, and sends this information along with the parameters of the generation request to the server.

[0757] Step 5:

[0758] The device generates JSON-formatted request data containing the parameters entered by the user and the emotion engine's analysis results, and sends it to the server's API endpoint. Request data example:

[0759] json

[0760] {

[0761] "theme": "Medieval Fantasy",

[0762] "difficulty": "medium level",

[0763] "playStyle": "Exploration-oriented",

[0764] "emotionalState": "Relaxed"

[0765] }

[0766] Receiving and Validating a Request

[0767] Step 6:

[0768] The server receives the request at the API endpoint and validates the request data, checking that all required fields are present and that the values ​​are valid.

[0769] Step 7:

[0770] The server validates the request parameters, and if validation is successful, proceeds to the next step. If validation fails, it returns an error response to the terminal.

[0771] Emotion-based parameter adjustment

[0772] Step 8:

[0773] The server adjusts parameters based on the user's emotional state received from the emotion engine. For example, if the user is relaxed, the difficulty level is lowered slightly and the exploration element is increased.

[0774] World and dungeon generation

[0775] Step 9:

[0776] The server accesses the database and retrieves data (terrain, enemy characters, items, etc.) related to the requested theme "medieval fantasy," difficulty level "medium level," and play style "exploration-oriented."

[0777] Step 10:

[0778] The server inputs the adjusted parameters and acquired data into the generative AI model, which generates new worlds and dungeons based on this data.

[0779] Step 11:

[0780] The generative AI model creates the basic structure of castles and dungeons with a medieval fantasy layout, populating them with enemies, traps, and exploration elements of moderate difficulty.

[0781] Saving and returning generated results

[0782] Step 12:

[0783] The server stores generated world and dungeon data in a database, including the generation ID, generation data, and generation date and time.

[0784] Step 13:

[0785] The server converts the generated results into JSON format and generates a response, which contains details about the generated world and dungeon.

[0786] Step 14:

[0787] The server sends a response containing the generated data back to the device via the API.

[0788] Viewing and customizing the results

[0789] Step 15:

[0790] The device parses the generated data received from the server and displays it in a user interface, including a visual preview of the generated world and dungeon.

[0791] Step 16:

[0792] Users can preview the generated world and dungeon and customize it as needed, for example by rearranging specific rooms or adding items.

[0793] Step 17:

[0794] The device saves any customizations made by the user and finalizes them as world and dungeon data.

[0795] In this way, a system is realized that can provide a superior gaming experience that is tailored to the user's emotional state.

[0796] Example 2

[0797] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0798] Conventional game and RPG world and dungeon generation systems only provide static content based on user input parameters, making it difficult to dynamically adjust to the user's emotional state. This can result in a consistently inoffensive gaming experience, as users are presented with content that is not optimized for their current emotional state.

[0799] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0800] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style, means for acquiring emotional data using an emotion engine that recognizes the user's emotions, means for automatically adjusting the parameters based on the acquired emotional data, generative model means for automatically generating worlds and dungeons based on the adjusted parameters, and means for saving and responding to the generated data, thereby enabling the automatic generation of worlds and dungeons optimized according to the user's emotional state.

[0801] The "means for accepting a generation request" is a means by which a user inputs parameters for generating a new world or dungeon, and the system accepts them.

[0802] "Theme" refers to the basic concept or style of the generated world or dungeon, such as a category like "medieval fantasy" or "cyberpunk."

[0803] "Difficulty" is a parameter that indicates the level of challenge in the game in the generated world or dungeon, and is set at levels such as easy, medium level, or difficult.

[0804] "Play style" is a parameter that indicates how a user enjoys a game, and examples include styles such as "exploration-oriented" and "combat-oriented."

[0805] "Means for acquiring parameters" refers to means for receiving information such as theme, difficulty level, play style, etc. input by the user and storing it within the system.

[0806] An "emotion engine" is a software or hardware technology that recognizes a user's emotional state at any given time by analyzing the user's facial expressions and voice.

[0807] The "means for acquiring emotion data" is a means for acquiring data relating to the user's emotional state using an emotion engine.

[0808] The "means for automatically adjusting parameters" is a means for automatically changing parameters such as theme, difficulty level, and play style input by the user based on the acquired emotional data.

[0809] "Generative model means" refers to means that includes models and algorithms for automatically generating worlds and dungeons based on adjusted parameters.

[0810] "Means for saving and responding to generated data" refers to means for saving data on the generated worlds and dungeons in a database and providing it to the user.

[0811] "World" refers to the virtual world or area that serves as the playing environment for a game or RPG.

[0812] A "dungeon" is a complex structure or area in a game or RPG that players explore to progress through missions or quests.

[0813] The system of the present invention combines a generative AI model with an emotion engine that recognizes user emotions to automatically generate worlds and dungeons for games and RPGs, and provides content optimized according to the user's emotions. This system includes the following main components and processes:

[0814] System Configuration

[0815] This system consists of the following components:

[0816] 1. How to accept creation requests

[0817] The terminal provides a user interface for inputting the parameters (theme, difficulty, play style) required when a user wishes to generate a world or dungeon. Through this interface, the user can create a specific generation request.

[0818] 2. How to get parameters

[0819] The server receives the creation request sent from the device and detects and validates the theme, difficulty, and play style parameters to ensure that the creation request is processed properly.

[0820] 3. Emotion Engine

[0821] The device's built-in camera and microphone capture the user's facial expressions and voice, and then analyzes them to recognize the user's emotions.

[0822] The server adjusts the parameters of the generation request based on this emotion data, for example, setting the difficulty level low if the user is tired and high if the user is excited.

[0823] 4. Generative Modeling Methods

[0824] The server maintains a generative AI model, which automatically generates appropriate worlds and dungeons based on the parameters and emotional data acquired from the AI ​​model. Examples of generative AI models used include GPT-3 and DALL-E.

[0825] 5. Data storage and response measures

[0826] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[0827] The terminal displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[0828] Specific examples

[0829] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[0830] 1. The user inputs their choices into the device, while the camera and microphone capture the user's emotions.

[0831] 2. The device sends the user's input parameters and emotion data to the server, which then inputs optimized generation parameters based on this data into the generative AI model.

[0832] 3. The generative AI model creates the basic structure of castles and dungeons based on a "medieval fantasy" theme, and places appropriate difficulty and exploration elements depending on the user's emotional state.

[0833] 4. The server stores the generated data and sends it back to the device.

[0834] 5. Users can preview the generated world or dungeon on their device and enjoy the optimal experience suggested based on their emotions.

[0835] Prompt Sentence Examples

[0836] Examples of prompts to drive a generative AI model include:

[0837] "Theme: Medieval fantasy, Difficulty: Medium, Play style: Exploration-focused, User emotion: Relaxed"

[0838] In this way, the system can quickly generate optimized worlds and dungeons that correspond to the user's emotional state, providing an individually optimized adventure.

[0839] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0840] Step 1: Accepting the generation request

[0841] The user uses the user interface on the device to input the desired parameters (theme, difficulty, play style) for generating a world or dungeon. The input theme is often "medieval fantasy," the difficulty level is "medium level," and the play style is "exploration-oriented." The device receives the user's input and stores these parameters in an internal data structure. At the same time, the device's camera and microphone collect the user's facial expressions and voice. The collected data is analyzed in real time by the emotion engine.

[0842] input:

[0843] Theme, difficulty, playstyle (via user interface)

[0844] User's facial expressions and voice (via camera and microphone)

[0845] output:

[0846] Analyzed parameters and emotion data

[0847] Step 2: Obtaining and validating parameters

[0848] The device combines the parameters entered by the user (theme, difficulty level, play style) with the emotional data analyzed by the emotion engine and sends it to the server as request data. The server receives this data and verifies the appropriateness and validity of each parameter. For example, it checks whether the theme is appropriate and whether the difficulty level is within an acceptable range.

[0849] input:

[0850] User-entered parameters

[0851] Emotion data acquired by the emotion engine

[0852] output:

[0853] Validated parameters and emotion data

[0854] Step 3: Collecting emotion data

[0855] The device's built-in camera and microphone are used to collect the user's facial expressions and voice. This is partially done in Step 1, but is done again with the aim of accurately obtaining the user's emotional data. The emotion engine analyzes this data and determines the user's emotions, such as whether they are relaxed, excited, or tired, using numerical values ​​and categories.

[0856] input:

[0857] User's facial expressions and voice (via camera and microphone)

[0858] output:

[0859] Emotion data analyzed by the emotion engine

[0860] Step 4: Emotion-based parameter adjustment

[0861] The server automatically adjusts the generation parameters entered by the user based on the emotion data sent from the emotion engine. For example, if the server determines that the user is relaxed, it will set the difficulty to "low" and change the theme to "relaxing." These adjusted parameters will provide a more appropriate gaming experience for the user.

[0862] input:

[0863] Verified parameters

[0864] Emotional Data

[0865] output:

[0866] Adjusted parameters

[0867] Step 5: World and dungeon generation

[0868] The server inputs the adjusted emotion-based parameters into a generative AI model, which uses algorithms such as GPT-3 or DALL-E to generate detailed structures and designs for new worlds and dungeons based on the input parameters.

[0869] input:

[0870] Adjusted parameters (theme, difficulty, play style)

[0871] output:

[0872] Generated world and dungeon data

[0873] Step 6: Save and return the generated results

[0874] The server stores the generated world and dungeon data in a database and sends it back to the device as a response. The device receives the generated data and displays it on the user interface, allowing the user to preview the generated world and dungeon and begin their experience.

[0875] input:

[0876] Generated world and dungeon data

[0877] output:

[0878] World and dungeon previews

[0879] Through this process, the system quickly generates optimized worlds and dungeons according to the user's emotional state, providing an individually optimized adventure experience.

[0880] (Application example 2)

[0881] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0882] Conventional content generation systems generate game and RPG worlds and dungeons based on fixed parameters without taking user emotions into account. This makes it difficult to provide an optimal play experience according to the user's emotional state. Furthermore, conventional systems have difficulty responding to situations where content needs to be instantly adjusted according to the user's temporary emotional state.

[0883] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0884] In this invention, the server includes means for accepting generation requests, means for recognizing the user's emotions and adjusting parameters, and generative model means for automatically generating worlds and dungeons from the acquired parameters, thereby enabling the parameters to be instantly adjusted based on the user's emotional state, enabling optimized content generation.

[0885] A "generation request" is information regarding the theme, difficulty level, and play style that a user specifies when they wish to generate a world or dungeon.

[0886] The term "means" refers to components or functional units necessary for carrying out the present invention.

[0887] "Theme" is a category that defines the basic setting and background of the generated world or dungeon.

[0888] "Difficulty" defines the degree of challenge and obstacles the player faces in a generated world or dungeon.

[0889] "Play style" is a concept that indicates how a user wants to progress through a game and what they value in their experience.

[0890] An "emotion engine" is a technology that analyzes a user's facial expressions and voice to recognize their emotional state.

[0891] "Generative model means" is a general term for algorithms and models that automatically generate worlds and dungeons based on acquired parameters.

[0892] "Means for saving and responding to data" refers to a function for saving data of generated worlds and dungeons in a storage system such as a database, and providing that data to users as needed.

[0893] The system of the present invention automatically generates worlds and dungeons based on the user's emotions and has the following configuration: First, the user inputs a generation request through a user interface on a terminal. The generation request includes parameters related to theme, difficulty, and play style.

[0894] System configuration

[0895] 1. Terminal: An input device where the user inputs the generation request and captures the emotional state in real time. This is often a smartphone or tablet.

[0896] 2. Server: Receives generation requests sent by users, analyzes emotional data, and generates worlds and dungeons using generative AI models. This also includes data storage and response functions.

[0897] Program processing

[0898] 1. Receiving a generation request: The device accepts a generation request from the user. The user specifies the theme, difficulty level, and play style. The device also captures the user's facial expressions and voice using the device's camera and microphone, and sends them to the emotion engine.

[0899] 2. Emotion Data Analysis: The server analyzes the captured emotion data using an emotion engine, which uses technologies such as OpenCV and DeepFace to determine whether the user is relaxed, excited, tired, etc.

[0900] 3. Adjustment of generation parameters: The server adjusts the generation parameters based on the analyzed emotional data. For example, if the user is relaxed, it will set the difficulty level low and change the theme to a soothing one.

[0901] 4. World and dungeon generation: The server generates worlds and dungeons based on the adjusted parameters using a generative AI model, such as GPT-3 or a similar AI model.

[0902] 5. Data storage and response: The server stores the generated data in a database and responds to the terminal. The terminal displays the received data on the user interface, allowing the user to check the generated world and dungeon.

[0903] Specific examples

[0904] If a user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, a world is generated through the following steps. First, the device accepts the user's input and sends facial expressions and voice captured by the camera to the emotion engine. Next, the server uses the emotion engine to analyze the user's emotional state and adjusts the generation parameters appropriately. The generative AI model automatically generates the world and dungeons based on this data, and the generated data is stored in a database and provided to the user on the device.

[0905] Example prompt sentence:

[0906] "Generate a medieval fantasy-themed world with a medium level of difficulty and a focus on exploration based on user emotional data. The user is very happy."

[0907] As described above, this system can automatically generate optimal worlds and dungeons according to the user's emotional state, providing an individually optimized playing experience.

[0908] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0909] Step 1:

[0910] Accepting a generation request

[0911] The device receives a generation request from the user. The user inputs the theme, difficulty level, and play style into the device's user interface. At this time, the device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The input data includes the theme, difficulty level, play style, and facial and voice data.

[0912] Step 2:

[0913] Sentiment Data Analysis

[0914] The server receives facial and voice data sent from the device and analyzes it using an emotion engine. It uses technologies such as OpenCV and DeepFace to determine the user's emotional state (relaxed, excited, tired, etc.). The input is the captured facial and voice data, and the output is data indicating the emotional state.

[0915] Step 3:

[0916] Adjusting generation parameters

[0917] The server automatically adjusts the generation parameters based on the analyzed emotional data. For example, if the user is relaxed, it sets the difficulty to low and changes the theme to soothing. The inputs are theme, difficulty, play style, and emotional data, and the output is the adjusted generation parameters. These parameters are used as input for the generative AI model.

[0918] Step 4:

[0919] World and dungeon generation

[0920] The server uses a generative AI model to generate worlds and dungeons based on the adjusted parameters. Examples of generative AI models used here include GPT-3. By providing the adjusted parameters as input to the generative AI model, an appropriate world or dungeon is output. The input is the adjusted generation parameters, and the output is the data for the generated world or dungeon.

[0921] Step 5:

[0922] Data Storage and Response

[0923] The server stores the generated data in a database and responds to the terminal. The terminal displays the received world and dungeon data on the user interface. The user can check the generated world and dungeon and customize it as needed. The input is the generated world and dungeon data, and the output is preview information of the world and dungeon displayed to the user.

[0924] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0925] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0926] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0927] [Third embodiment]

[0928] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0929] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0930] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0931] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0932] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0933] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0934] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0935] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0936] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0937] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0938] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0939] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0940] The present invention is a system that automatically generates worlds and dungeons for games and RPGs using a generative AI model, and mainly includes the following main components and processes.

[0941] System Configuration

[0942] This system consists of the following components:

[0943] 1. How to accept creation requests

[0944] The terminal provides a user interface that allows the user to input parameters required for generating a world or dungeon. Through this interface, the user specifies the desired theme, difficulty level, and play style.

[0945] 2. How to get parameters

[0946] The server receives the creation request sent from the device and detects the parameters of theme, difficulty, and play style. Data validation is also performed at this stage.

[0947] 3. Generative Modeling Methods

[0948] The server maintains a generation AI model, which inputs the acquired parameters into the AI ​​model, which then automatically generates appropriate worlds and dungeons based on the input.

[0949] 4. Data storage and response methods

[0950] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[0951] The terminal displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[0952] Program processing

[0953] Specifically, the program of this system performs the following processing.

[0954] Accepting a generation request

[0955] Users input parameters (theme, difficulty, play style) to generate new worlds and dungeons using the UI on their device. For example, they can select a "medieval fantasy" theme, a "medium" difficulty level, and an "exploration-focused" play style.

[0956] Parameter retrieval and validation

[0957] The terminal generates request data including the parameters entered by the user and sends it to the server, which receives the request and validates the parameters.

[0958] World and dungeon generation

[0959] The server inputs the successfully validated parameters into the generative AI model, which then automatically generates new worlds and dungeons based on these inputs. During this process, the server retrieves appropriate materials, layouts, enemy characters, items, etc. from the database and generates a structure that matches the parameters.

[0960] Data storage and return

[0961] The server stores the generated world and dungeon data in a database, generates a response, and sends it back to the device. The device receives this data and displays a preview of the generated world or dungeon to the user.

[0962] Specific examples

[0963] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[0964] 1. A request containing parameters entered by the user is sent from the terminal.

[0965] 2. The server receives the request, validates it, and then inputs data based on the theme "Medieval Fantasy," difficulty level "Medium," and play style "Exploration-focused" into the generative AI model.

[0966] 3. The generative AI model generates the basic structure of a medieval castle or dungeon, and places enemy characters of moderate difficulty, numerous traps, secret rooms, etc.

[0967] 4. The server stores the generated data and sends it back to the device.

[0968] 5. Users can preview the generated world or dungeon on their device and make any adjustments or customizations they like.

[0969] In this way, a system is created that allows creators to quickly generate diverse worlds and dungeons, providing players with new adventures.

[0970] The processing flow will be explained below.

[0971] Specific processing steps of the program

[0972] Accepting a creation request and obtaining parameters

[0973] Step 1:

[0974] Users access a user interface (UI) on their device and input parameters for generating new worlds and dungeons, such as a theme of "medieval fantasy," a difficulty level of "medium," and a play style of "exploration-focused."

[0975] Step 2:

[0976] The terminal receives the parameters entered by the user and generates request data in JSON format. Example of request data:

[0977] json

[0978] {

[0979] "theme": "Medieval Fantasy",

[0980] "difficulty": "medium level",

[0981] "playStyle": "Exploration-oriented"

[0982] }

[0983] Step 3:

[0984] The device sends the generated request data to the server's API endpoint. This communication uses the HTTP protocol.

[0985] Receiving and Validating a Request

[0986] Step 4:

[0987] The server receives the request sent through the API and validates the request data, checking that all required fields are present and that the values ​​are valid.

[0988] Step 5:

[0989] The server validates the request parameters, and if validation is successful, proceeds to the next step. If validation fails, it returns an error response to the terminal.

[0990] World and dungeon generation

[0991] Step 6:

[0992] The server accesses the database and retrieves data (terrain, enemy characters, items, etc.) related to the requested theme "Medieval Fantasy," difficulty level "Medium," and play style "Exploration-focused."

[0993] Step 7:

[0994] The server inputs the acquired data and request parameters into a generative AI model, which then generates new worlds and dungeons based on this data.

[0995] Step 8:

[0996] The generative AI model creates the basic structure of a medieval fantasy castle or dungeon, with a layout that emphasizes exploration, and features enemies, traps, secret rooms, and other elements of moderate difficulty.

[0997] Saving and returning generated results

[0998] Step 9:

[0999] The server stores generated world and dungeon data in a database, including the generation ID, generation data, and generation date and time.

[1000] Step 10:

[1001] The server converts the generated results into JSON format and generates a response, which contains details about the generated world and dungeon.

[1002] Step 11:

[1003] The server sends a response containing the generated data back to the device via the API.

[1004] Viewing and customizing the results

[1005] Step 12:

[1006] The device parses the generated data received from the server and displays it in a user interface, including a visual preview of the generated world and dungeon.

[1007] Step 13:

[1008] The user can preview the generated world and dungeon and customize it as needed, for example by rearranging specific rooms or adding items.

[1009] Step 14:

[1010] The device saves any customizations made by the user and finalizes them as world and dungeon data.

[1011] Example 1

[1012] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1013] The generation of worlds and dungeons in conventional games and RPGs is often done manually, requiring a great deal of time and effort. This makes it difficult to quickly generate diverse worlds and dungeons. Furthermore, existing automatic generation systems have the problem of making it difficult to customize them to fit a user's desired theme or play style. Therefore, there is a demand for technology that can efficiently generate diverse, high-quality worlds and dungeons that meet user needs.

[1014] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1015] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style based on the generation request and validating the parameters, means for inputting the acquired parameters into a generation AI model and automatically generating appropriate worlds and dungeons, means for storing data of the generated worlds and dungeons in a database and returning the data to the terminal as a response, and means for displaying the returned data on the terminal and providing a user interface that can be customized by the user. This allows for the efficient generation of diverse, high-quality worlds and dungeons that meet the user's needs and also allows the user to customize them themselves.

[1016] The "means for accepting a generation request" is a device or function that provides an interface that allows a user to input parameters necessary to generate a world or dungeon.

[1017] "Parameters" are information required by the generation AI model to generate a world or dungeon, such as the theme, difficulty, and play style of the generated world or dungeon.

[1018] "Validation means" refers to a device or function that verifies the validity of data by checking whether the acquired parameters are in the correct format or range.

[1019] A "generative AI model" is an algorithm or system that takes acquired parameters as input and automatically generates appropriate worlds and dungeons based on them.

[1020] A "generative model means" is a device or function that uses a generative AI model to automatically generate worlds and dungeons based on parameters.

[1021] A "database" is a storage device or system for storing data on generated worlds and dungeons.

[1022] The "means for returning as a response" is a device or function that sends data of the generated world or dungeon to the terminal and displays it to the user.

[1023] "User interface" is a function that provides a screen and operating means that allows users to preview the worlds and dungeons generated on their device and customize them as needed.

[1024] This invention is a system that uses a generative AI model to automatically generate worlds and dungeons for games and RPGs. This system mainly uses three main components: a server, a terminal, and a user, as well as various data processing means. The specific form and operation of the system are shown below.

[1025] Components and Operation

[1026] A means of accepting creation requests

[1027] The terminal provides the user with a user interface that allows them to input the parameters required to generate a world or dungeon. Through this interface, the user can specify the desired theme, difficulty level, and play style. For example, the user might input parameters such as "Theme: Medieval Fantasy," "Difficulty: Medium level," and "Play Style: Exploration-focused."

[1028] A means of obtaining and validating parameters

[1029] The device generates request data including the parameters entered by the user and sends it to the server. The server analyzes the received request data and extracts the parameters for theme, difficulty, and play style. The extracted parameters are then validated to ensure they are in the correct format and range. For example, it verifies that "difficulty" is either "low," "medium," or "high."

[1030] A means of generating worlds and dungeons using generative AI models

[1031] The server uses the validated parameters to input the generative AI model, generating a prompt like this:

[1032] Theme: Medieval Fantasy

[1033] Difficulty: Medium

[1034] Playstyle: Exploration-focused

[1035] Specific instructions:

[1036] Generate the basic structure of a medieval castle or dungeon

[1037] Place enemy characters with a moderate level of difficulty

[1038] Lots of traps and secret rooms

[1039] Based on these prompts, a generative AI model (such as GPT-4) automatically generates appropriate world and dungeon structures, layouts, enemy characters, items, etc.

[1040] A means to save the generated results and return them as a response

[1041] The server saves the generated world and dungeon data in a database. It then sends the saved data back to the device as a response. The device can then analyze the received data and display a preview of the world or dungeon to the user.

[1042] A means of displaying generated results and providing a customizable user interface

[1043] The device visually displays the generated world and dungeon to the user. The user can check the displayed world and dungeon and customize parts of it as needed. For example, they can change the layout of the generated dungeon by dragging and dropping, or add new enemy characters or items.

[1044] Specific examples

[1045] For example, if a user inputs the parameters "Theme: Medieval Fantasy", "Difficulty: Medium", and "Playstyle: Exploration-Oriented", the following sequence of actions will occur:

[1046] 1. The user enters parameters using the terminal interface.

[1047] 2. The terminal generates request data and sends it to the server.

[1048] 3. The server receives the request and validates the parameters.

[1049] 4. The server uses the generative AI model to generate worlds and dungeons based on the parameters.

[1050] 5. The generative AI model generates the basic structure of medieval castles and dungeons, as well as enemy characters, traps, secret rooms, and other elements of moderate difficulty.

[1051] 6. The server stores the generated data and sends it back to the device.

[1052] 7. The user can preview the generated world and dungeon on their device and customize it as needed.

[1053] This system allows users to quickly generate diverse, high-quality worlds and dungeons, providing players with new adventures.

[1054] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1055] Step 1:

[1056] The user uses the terminal's user interface to create new worlds and dungeons, inputting parameters such as theme, difficulty level, and play style.

[1057] Inputs: Theme (medieval fantasy), difficulty (medium), playstyle (exploration-focused).

[1058] Operation: Each parameter is selected using a drop-down menu, radio button, checkbox, etc. on the user interface.

[1059] Output: The parameter set entered by the user.

[1060] Step 2:

[1061] The terminal generates request data including the parameters input by the user and transmits it to the server.

[1062] Input: A set of parameters entered by the user.

[1063] Data processing: Converts parameters into JSON format request data.

[1064] What it does: Sends the request data to the server using an HTTP POST request.

[1065] Output: The request data sent to the server.

[1066] Step 3:

[1067] The server receives the request data sent from the terminal and validates the parameters.

[1068] Input: Request data sent from the terminal (JSON format).

[1069] Data processing: Parse the JSON data, extract the theme, difficulty, and playstyle parameters, and ensure they are in the correct format and values.

[1070] What it does: Validates each extracted parameter (e.g., checks that the difficulty is either "low", "medium", or "high").

[1071] Output: The validated parameter set.

[1072] Step 4:

[1073] The server uses the successfully validated parameters to input a prompt sentence into the generative AI model.

[1074] Input: A validated set of parameters.

[1075] Data calculation: Generate prompt sentences and input them into the generative AI model.

[1076] How it works: Generate a prompt sentence like the one below and pass it to a generative AI model (e.g., GPT-4).

[1077] Theme: Medieval Fantasy

[1078] Difficulty: Medium

[1079] Playstyle: Exploration-focused

[1080] Specific instructions:

[1081] Generate the basic structure of a medieval castle or dungeon

[1082] Place enemy characters with a moderate level of difficulty

[1083] Lots of traps and secret rooms

[1084] Output: Output data from the generative AI model (detailed world and dungeon generation data).

[1085] Step 5:

[1086] The server stores the generated data obtained from the generative AI model in a database.

[1087] Input: The output data from the generative AI model.

[1088] Data processing: Organizing the generated data and converting it into a format that can be stored in a database.

[1089] What it does: Executes a SQL query that inserts the generated data into a database.

[1090] Output: Generated data stored in a database.

[1091] Step 6:

[1092] The server returns the generated data stored in the database to the terminal as a response.

[1093] Input: Generated data stored in a database.

[1094] Data processing: Converting some or all of the generated data into a JSON response.

[1095] Operation: Sends to the terminal as an HTTP response.

[1096] Output: The JSON response sent to the terminal.

[1097] Step 7:

[1098] The terminal analyzes the generated data received from the server and displays it to the user.

[1099] Input: The JSON response received from the server.

[1100] Data processing: Parse JSON data to extract world and dungeon structure.

[1101] How it works: It uses the extracted data to visually display worlds and dungeons in a user interface, and also provides an edit mode for user customization.

[1102] Output: A user-viewable and customizable representation of the world and dungeon.

[1103] In this way, users can easily create high-quality worlds and dungeons and customize them as needed.

[1104] (Application example 1)

[1105] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1106] Conventional world and dungeon generation systems require users to manually create detailed settings and layouts, which takes time and effort. Furthermore, customization of the generated worlds and dungeons is limited, making it difficult for users to fully express their creativity. Therefore, there is a demand for a system that allows users to easily generate worlds and dungeons on their smartphones and freely customize their content.

[1107] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1108] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style, generation model means for automatically generating worlds and dungeons from the acquired parameters, means for saving and responding to data on the generated worlds and dungeons, and means for the user to preview and customize the generated worlds and dungeons on their smartphones. This allows users to easily generate worlds and dungeons using their smartphones and freely customize their contents.

[1109] A "generation request" is a request entered by a user to generate a world or dungeon based on specific conditions.

[1110] "Theme" is a category that determines the overall setting and atmosphere of the generated world or dungeon.

[1111] "Difficulty" is a parameter that indicates the difficulty of playing in the generated world or dungeon.

[1112] "Play style" is a parameter that indicates the user's desired game progression style, tactics, etc.

[1113] "Parameters" are input data such as theme, difficulty level, play style, etc., obtained based on a generation request.

[1114] A "generative model means" is an AI-based algorithm or system that automatically generates worlds and dungeons based on acquired parameters.

[1115] "Means for saving and responding to data" refers to the function of saving the data of the generated world and dungeon in a database and sending that data to the user.

[1116] "Preview" is a function that displays the contents of the generated world or dungeon so that the user can check them.

[1117] "Means for customization" refers to a feature that allows users to freely modify and adjust the details of the generated worlds and dungeons.

[1118] A "smartphone" is a mobile information device that allows users to use applications to create and customize worlds and dungeons.

[1119] The system for implementing this invention mainly includes a terminal that accepts generation requests, a server that generates worlds and dungeons based on acquired parameters, and a means for saving and responding to the generated data. This system allows users to easily generate and customize original worlds and dungeons on their own smartphones.

[1120] Hardware and Software Configuration

[1121] Hardware

[1122] Device: Smartphone (Android or iOS device)

[1123] Server: Cloud server

[1124] software

[1125] Frontend: React Native

[1126] Backend: Node.js, Express

[1127] Database: MongoDB

[1128] Generative AI model: GPT-4 or other generative AI model (OpenAI API)

[1129] Specific processing of the system

[1130] Accepting a generation request

[1131] Users open the app on their smartphone and input parameters to generate a new world or dungeon. They can choose from a variety of themes, difficulty levels, and play styles. They can choose from a "future city" theme, a "high level" difficulty level, or a "battle-focused" play style.

[1132] Parameter retrieval and validation

[1133] The creation request sent from the terminal is passed to the server, which validates the received parameters to ensure that they do not contain invalid data.

[1134] World and dungeon generation

[1135] Parameters are input into the generative AI model, which automatically generates worlds and dungeons based on these parameters. During this process, the appropriate materials, layouts, enemy characters, items, etc. are retrieved from the database and configured to fit the parameters.

[1136] Data storage and response

[1137] The generated world and dungeon data is stored in a database and sent back to the device as a response. The device displays the received data in a user interface, allowing the user to preview and customize the content as needed.

[1138] Specific examples

[1139] For example, if a user selects a "future city" theme, a "high level" difficulty level, and a "battle-focused" play style, the parameters are sent to the server and, after validation, input into the generative AI model. The generative AI model automatically generates a dungeon containing futuristic city-style buildings, corridors, enemy characters, and battle scenes. The generated data is stored in a database and sent back to the device, allowing the user to preview the new world on their smartphone and further customize it.

[1140] Example prompts for generative AI models

[1141] Generate a new dungeon based on the following parameters:

[1142] Theme: Future City

[1143] Difficulty: High level

[1144] Playstyle: Battle-focused

[1145] Dungeons must contain enemy characters and battle scenes.

[1146] This system allows users to easily generate advanced worlds and dungeons and customize them freely.

[1147] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1148] Step 1:

[1149] The user opens the smartphone application and inputs the theme, difficulty level, and play style to generate a new world or dungeon. At this time, the user inputs the specific parameters of the theme (e.g., "future city"), difficulty level (e.g., "high level"), and play style (e.g., "focus on battle") into the device. The input parameters are formatted as generation request data on the device, and the request data is created as output.

[1150] Step 2:

[1151] The generation request data is sent from the terminal to the server. The server analyzes the received request data and extracts the parameters of theme, difficulty, and play style. In this step, the received data is checked to see if it is valid (validation). After the consistency of the data is confirmed, it becomes a valid request. Consistent parameter data is obtained as the output.

[1152] Step 3:

[1153] The server inputs the successfully validated parameters into the generative AI model. At this time, the parameter data is formatted as a prompt for the generative AI model. The prompt is converted into a format that is easy for the generative AI model to understand (e.g., "Generate a new dungeon based on the following parameters: Theme: futuristic city, Difficulty: high level, Play style: battle-focused"). The prompt is input into the generative AI model, and an appropriate world or dungeon is generated. The data for the generated world or dungeon is obtained as output.

[1154] Step 4:

[1155] The generated world and dungeon data is saved on the server. A database (MongoDB) is used for saving. This data is associated with user identification information and managed as a different world or dungeon for each user. A save completion message is returned from the server as output.

[1156] Step 5:

[1157] Once the world or dungeon data has been saved, it is sent back to the device from the server. The device displays the received data in the user interface. It is visually rendered in the UI so that the user can see a preview of the generated world or dungeon. A preview screen is provided as output for the user to view.

[1158] Step 6:

[1159] The user checks the displayed preview and customizes it as necessary. In this step, the user edits the details of the generated world or dungeon (e.g., enemy character placement, item location, layout, etc.) on their smartphone. The edited data is then sent back to the server and updated. The final customized world or dungeon data is obtained as output.

[1160] By following these steps, users can easily create original worlds and dungeons on their smartphones and customize them to their liking.

[1161] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1162] The system of the present invention combines a generative AI model with an emotion engine that recognizes user emotions to automatically generate worlds and dungeons for games and RPGs, and provide content optimized according to the user's emotions. This system includes the following main components and processes:

[1163] System Configuration

[1164] This system consists of the following components:

[1165] 1. How to accept creation requests

[1166] The terminal provides a user interface that allows the user to input parameters required for generating a world or dungeon. Through this interface, the user specifies the desired theme, difficulty level, and play style.

[1167] 2. How to get parameters

[1168] The server receives the creation request sent from the device and detects the parameters of theme, difficulty, and play style. Data validation is also performed at this stage.

[1169] 3. Emotion Engine

[1170] The device's built-in camera and microphone capture the user's facial expressions and voice, and then analyzes them to recognize the user's emotions.

[1171] The server adjusts the parameters of the generation request based on this emotion data, for example, setting the difficulty level low if the user is tired and high if the user is excited.

[1172] 4. Generative Modeling Methods

[1173] The server maintains a generation AI model, which inputs the acquired parameters into the AI ​​model, which then automatically generates appropriate worlds and dungeons based on the input.

[1174] 5. Data storage and response measures

[1175] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[1176] The device displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[1177] Program processing

[1178] Specifically, the program of this system performs the following processing.

[1179] Accepting a generation request

[1180] Users use the on-device UI to input parameters (theme, difficulty level, play style) to generate new worlds and dungeons. At that time, the device's camera and microphone capture the user's facial expressions and voice, and the emotion engine analyzes the user's emotional state.

[1181] Parameter retrieval and validation

[1182] The device combines the parameters entered by the user and the emotional data analyzed by the emotion engine to generate request data and sends it to the server. The server receives this request and validates the parameters.

[1183] Emotion-based parameter adjustment

[1184] The server automatically adjusts the generation parameters based on the user's emotional data. For example, if the user is feeling relaxed, the server changes the theme to a soothing one and sets the difficulty level lower.

[1185] World and dungeon generation

[1186] The server inputs the adjusted parameters based on validation and emotion into the generative AI model, which then automatically generates new worlds and dungeons based on this data.

[1187] Saving and returning generated results

[1188] The server stores the generated world and dungeon data in a database, generates a response, and sends it back to the device, which receives the data and displays it on the user interface.

[1189] Specific examples

[1190] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[1191] 1. The user inputs their choices into the device, while the camera and microphone capture the user's emotions.

[1192] 2. The device sends the user's input parameters and emotion data to the server, which then inputs optimized generation parameters based on this data into the generative AI model.

[1193] 3. The generative AI model creates the basic structure of castles and dungeons based on a "medieval fantasy" theme, and places appropriate difficulty and exploration elements depending on the user's emotional state.

[1194] 4. The server stores the generated data and sends it back to the device.

[1195] 5. Users can preview the generated world or dungeon on their device and enjoy the optimal experience suggested based on their emotions.

[1196] In this way, the system can quickly generate worlds and dungeons that correspond to the user's emotional state, providing an individually optimized adventure.

[1197] The processing flow will be explained below.

[1198] Specific processing steps of the program

[1199] Automatic world and dungeon generation system using emotion engine

[1200] Step 1:

[1201] Using the device's user interface (UI), users input parameters for generating new worlds and dungeons, including a "medieval fantasy" theme, a "medium" difficulty level, and an "exploration-focused" play style.

[1202] Step 2:

[1203] The device acquires the parameters entered by the user and also uses a camera and microphone to collect the user's facial expressions and voice data.

[1204] Step 3:

[1205] The device inputs the collected facial and voice data into an emotion engine to analyze the user's emotional state. For example, the facial recognition system can detect excitement from the user's smile, and voice analysis can assess stress levels from the tone of voice.

[1206] Step 4:

[1207] Based on the analysis, the emotion engine determines whether the user is currently relaxed, stressed, or excited, and sends this information along with the parameters of the generation request to the server.

[1208] Step 5:

[1209] The device generates JSON-formatted request data containing the parameters entered by the user and the emotion engine's analysis results, and sends it to the server's API endpoint. Request data example:

[1210] json

[1211] {

[1212] "theme": "Medieval Fantasy",

[1213] "difficulty": "medium level",

[1214] "playStyle": "Exploration-oriented",

[1215] "emotionalState": "Relaxed"

[1216] }

[1217] Receiving and Validating a Request

[1218] Step 6:

[1219] The server receives the request at the API endpoint and validates the request data, checking that all required fields are present and that the values ​​are valid.

[1220] Step 7:

[1221] The server validates the request parameters, and if validation is successful, proceeds to the next step. If validation fails, it returns an error response to the terminal.

[1222] Emotion-based parameter adjustment

[1223] Step 8:

[1224] The server adjusts parameters based on the user's emotional state received from the emotion engine. For example, if the user is relaxed, the difficulty level is lowered slightly and the exploration element is increased.

[1225] World and dungeon generation

[1226] Step 9:

[1227] The server accesses the database and retrieves data (terrain, enemy characters, items, etc.) related to the requested theme "medieval fantasy," difficulty level "medium level," and play style "exploration-oriented."

[1228] Step 10:

[1229] The server inputs the adjusted parameters and acquired data into the generative AI model, which generates new worlds and dungeons based on this data.

[1230] Step 11:

[1231] The generative AI model creates the basic structure of castles and dungeons with a medieval fantasy layout, populating them with enemies, traps, and exploration elements of moderate difficulty.

[1232] Saving and returning generated results

[1233] Step 12:

[1234] The server stores generated world and dungeon data in a database, including the generation ID, generation data, and generation date and time.

[1235] Step 13:

[1236] The server converts the generated results into JSON format and generates a response, which contains details about the generated world and dungeon.

[1237] Step 14:

[1238] The server sends a response containing the generated data back to the device via the API.

[1239] Viewing and customizing the results

[1240] Step 15:

[1241] The device parses the generated data received from the server and displays it in a user interface, including a visual preview of the generated world and dungeon.

[1242] Step 16:

[1243] Users can preview the generated world and dungeon and customize it as needed, for example by rearranging specific rooms or adding items.

[1244] Step 17:

[1245] The device saves any customizations made by the user and finalizes them as world and dungeon data.

[1246] In this way, a system is realized that can provide a superior gaming experience that is tailored to the user's emotional state.

[1247] Example 2

[1248] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1249] Conventional game and RPG world and dungeon generation systems only provide static content based on user input parameters, making it difficult to dynamically adjust to the user's emotional state. This can result in a consistently inoffensive gaming experience, as users are presented with content that is not optimized for their current emotional state.

[1250] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1251] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style, means for acquiring emotional data using an emotion engine that recognizes the user's emotions, means for automatically adjusting the parameters based on the acquired emotional data, generative model means for automatically generating worlds and dungeons based on the adjusted parameters, and means for saving and responding to the generated data, thereby enabling the automatic generation of worlds and dungeons optimized according to the user's emotional state.

[1252] The "means for accepting a generation request" is a means by which a user inputs parameters for generating a new world or dungeon, and the system accepts them.

[1253] "Theme" refers to the basic concept or style of the generated world or dungeon, such as a category like "medieval fantasy" or "cyberpunk."

[1254] "Difficulty" is a parameter that indicates the level of challenge in the game in the generated world or dungeon, and is set at levels such as easy, medium level, or difficult.

[1255] "Play style" is a parameter that indicates how a user enjoys a game, and examples include styles such as "exploration-oriented" and "combat-oriented."

[1256] "Means for acquiring parameters" refers to means for receiving information such as theme, difficulty level, play style, etc. input by the user and storing it within the system.

[1257] An "emotion engine" is a software or hardware technology that recognizes a user's emotional state at any given time by analyzing the user's facial expressions and voice.

[1258] The "means for acquiring emotion data" is a means for acquiring data relating to the user's emotional state using an emotion engine.

[1259] The "means for automatically adjusting parameters" is a means for automatically changing parameters such as theme, difficulty level, and play style input by the user based on the acquired emotional data.

[1260] "Generative model means" refers to means that includes models and algorithms for automatically generating worlds and dungeons based on adjusted parameters.

[1261] "Means for saving and responding to generated data" refers to means for saving data on the generated worlds and dungeons in a database and providing it to the user.

[1262] "World" refers to the virtual world or area that serves as the playing environment for a game or RPG.

[1263] A "dungeon" is a complex structure or area in a game or RPG that players explore to progress through missions or quests.

[1264] The system of the present invention combines a generative AI model with an emotion engine that recognizes user emotions to automatically generate worlds and dungeons for games and RPGs, and provides content optimized according to the user's emotions. This system includes the following main components and processes:

[1265] System Configuration

[1266] This system consists of the following components:

[1267] 1. How to accept creation requests

[1268] The terminal provides a user interface for inputting the parameters (theme, difficulty, play style) required when a user wishes to generate a world or dungeon. Through this interface, the user can create a specific generation request.

[1269] 2. How to get parameters

[1270] The server receives the creation request sent from the device and detects and validates the theme, difficulty, and play style parameters to ensure that the creation request is processed properly.

[1271] 3. Emotion Engine

[1272] The device's built-in camera and microphone capture the user's facial expressions and voice, and then analyzes them to recognize the user's emotions.

[1273] The server adjusts the parameters of the generation request based on this emotion data, for example, setting the difficulty level low if the user is tired and high if the user is excited.

[1274] 4. Generative Modeling Methods

[1275] The server maintains a generative AI model, which automatically generates appropriate worlds and dungeons based on the parameters and emotional data acquired from the AI ​​model. Examples of generative AI models used include GPT-3 and DALL-E.

[1276] 5. Data storage and response measures

[1277] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[1278] The terminal displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[1279] Specific examples

[1280] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[1281] 1. The user inputs their choices into the device, while the camera and microphone capture the user's emotions.

[1282] 2. The device sends the user's input parameters and emotion data to the server, which then inputs optimized generation parameters based on this data into the generative AI model.

[1283] 3. The generative AI model creates the basic structure of castles and dungeons based on a "medieval fantasy" theme, and places appropriate difficulty and exploration elements depending on the user's emotional state.

[1284] 4. The server stores the generated data and sends it back to the device.

[1285] 5. Users can preview the generated world or dungeon on their device and enjoy the optimal experience suggested based on their emotions.

[1286] Prompt Sentence Examples

[1287] Examples of prompts to drive a generative AI model include:

[1288] "Theme: Medieval fantasy, Difficulty: Medium, Play style: Exploration-focused, User emotion: Relaxed"

[1289] In this way, the system can quickly generate optimized worlds and dungeons that correspond to the user's emotional state, providing an individually optimized adventure.

[1290] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1291] Step 1: Accepting the generation request

[1292] The user uses the user interface on the device to input the desired parameters (theme, difficulty, play style) for generating a world or dungeon. The input theme is often "medieval fantasy," the difficulty level is "medium level," and the play style is "exploration-oriented." The device receives the user's input and stores these parameters in an internal data structure. At the same time, the device's camera and microphone collect the user's facial expressions and voice. The collected data is analyzed in real time by the emotion engine.

[1293] input:

[1294] Theme, difficulty, playstyle (via user interface)

[1295] User's facial expressions and voice (via camera and microphone)

[1296] output:

[1297] Analyzed parameters and emotion data

[1298] Step 2: Obtaining and validating parameters

[1299] The device combines the parameters entered by the user (theme, difficulty level, play style) with the emotional data analyzed by the emotion engine and sends it to the server as request data. The server receives this data and verifies the appropriateness and validity of each parameter. For example, it checks whether the theme is appropriate and whether the difficulty level is within an acceptable range.

[1300] input:

[1301] User-entered parameters

[1302] Emotion data acquired by the emotion engine

[1303] output:

[1304] Validated parameters and emotion data

[1305] Step 3: Collecting emotion data

[1306] The device's built-in camera and microphone are used to collect the user's facial expressions and voice. This is partially done in Step 1, but is done again with the aim of accurately obtaining the user's emotional data. The emotion engine analyzes this data and determines the user's emotions, such as whether they are relaxed, excited, or tired, using numerical values ​​and categories.

[1307] input:

[1308] User's facial expressions and voice (via camera and microphone)

[1309] output:

[1310] Emotion data analyzed by the emotion engine

[1311] Step 4: Emotion-based parameter adjustment

[1312] The server automatically adjusts the generation parameters entered by the user based on the emotion data sent from the emotion engine. For example, if the server determines that the user is relaxed, it will set the difficulty to "low" and change the theme to "relaxing." These adjusted parameters will provide a more appropriate gaming experience for the user.

[1313] input:

[1314] Verified parameters

[1315] Emotional Data

[1316] output:

[1317] Adjusted parameters

[1318] Step 5: World and dungeon generation

[1319] The server inputs the adjusted emotion-based parameters into a generative AI model, which uses algorithms such as GPT-3 or DALL-E to generate detailed structures and designs for new worlds and dungeons based on the input parameters.

[1320] input:

[1321] Adjusted parameters (theme, difficulty, play style)

[1322] output:

[1323] Generated world and dungeon data

[1324] Step 6: Save and return the generated results

[1325] The server stores the generated world and dungeon data in a database and sends it back to the device as a response. The device receives the generated data and displays it on the user interface, allowing the user to preview the generated world and dungeon and begin their experience.

[1326] input:

[1327] Generated world and dungeon data

[1328] output:

[1329] World and dungeon previews

[1330] Through this process, the system quickly generates optimized worlds and dungeons according to the user's emotional state, providing an individually optimized adventure experience.

[1331] (Application example 2)

[1332] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1333] Conventional content generation systems generate game and RPG worlds and dungeons based on fixed parameters without taking user emotions into account. This makes it difficult to provide an optimal play experience according to the user's emotional state. Furthermore, conventional systems have difficulty responding to situations where content needs to be instantly adjusted according to the user's temporary emotional state.

[1334] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1335] In this invention, the server includes means for accepting generation requests, means for recognizing the user's emotions and adjusting parameters, and generative model means for automatically generating worlds and dungeons from the acquired parameters, thereby enabling the parameters to be instantly adjusted based on the user's emotional state, enabling optimized content generation.

[1336] A "generation request" is information regarding the theme, difficulty level, and play style that a user specifies when they wish to generate a world or dungeon.

[1337] The term "means" refers to components or functional units necessary for carrying out the present invention.

[1338] "Theme" is a category that defines the basic setting and background of the generated world or dungeon.

[1339] "Difficulty" defines the degree of challenge and obstacles the player faces in a generated world or dungeon.

[1340] "Play style" is a concept that indicates how a user wants to progress through a game and what they value in their experience.

[1341] An "emotion engine" is a technology that analyzes a user's facial expressions and voice to recognize their emotional state.

[1342] "Generative model means" is a general term for algorithms and models that automatically generate worlds and dungeons based on acquired parameters.

[1343] "Means for saving and responding to data" refers to a function for saving data of generated worlds and dungeons in a storage system such as a database, and providing that data to users as needed.

[1344] The system of the present invention automatically generates worlds and dungeons based on the user's emotions and has the following configuration: First, the user inputs a generation request through a user interface on a terminal. The generation request includes parameters related to theme, difficulty, and play style.

[1345] System configuration

[1346] 1. Terminal: An input device where the user inputs the generation request and captures the emotional state in real time. This is often a smartphone or tablet.

[1347] 2. Server: Receives generation requests sent by users, analyzes emotional data, and generates worlds and dungeons using generative AI models. This also includes data storage and response functions.

[1348] Program processing

[1349] 1. Receiving a generation request: The device accepts a generation request from the user. The user specifies the theme, difficulty level, and play style. The device also captures the user's facial expressions and voice using the device's camera and microphone, and sends them to the emotion engine.

[1350] 2. Emotion Data Analysis: The server analyzes the captured emotion data using an emotion engine, which uses technologies such as OpenCV and DeepFace to determine whether the user is relaxed, excited, tired, etc.

[1351] 3. Adjustment of generation parameters: The server adjusts the generation parameters based on the analyzed emotional data. For example, if the user is relaxed, it will set the difficulty level low and change the theme to a soothing one.

[1352] 4. World and dungeon generation: The server generates worlds and dungeons based on the adjusted parameters using a generative AI model, such as GPT-3 or a similar AI model.

[1353] 5. Data storage and response: The server stores the generated data in a database and responds to the terminal. The terminal displays the received data on the user interface, allowing the user to check the generated world and dungeon.

[1354] Specific examples

[1355] If a user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, a world is generated through the following steps. First, the device accepts the user's input and sends facial expressions and voice captured by the camera to the emotion engine. Next, the server uses the emotion engine to analyze the user's emotional state and adjusts the generation parameters appropriately. The generative AI model automatically generates the world and dungeons based on this data, and the generated data is stored in a database and provided to the user on the device.

[1356] Example prompt sentence:

[1357] "Generate a medieval fantasy-themed world with a medium level of difficulty and a focus on exploration based on user emotional data. The user is very happy."

[1358] As described above, this system can automatically generate optimal worlds and dungeons according to the user's emotional state, providing an individually optimized playing experience.

[1359] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1360] Step 1:

[1361] Accepting a generation request

[1362] The device receives a generation request from the user. The user inputs the theme, difficulty level, and play style into the device's user interface. At this time, the device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The input data includes the theme, difficulty level, play style, and facial and voice data.

[1363] Step 2:

[1364] Sentiment Data Analysis

[1365] The server receives facial and voice data sent from the device and analyzes it using an emotion engine. It uses technologies such as OpenCV and DeepFace to determine the user's emotional state (relaxed, excited, tired, etc.). The input is the captured facial and voice data, and the output is data indicating the emotional state.

[1366] Step 3:

[1367] Adjusting generation parameters

[1368] The server automatically adjusts the generation parameters based on the analyzed emotional data. For example, if the user is relaxed, it sets the difficulty to low and changes the theme to soothing. The inputs are theme, difficulty, play style, and emotional data, and the output is the adjusted generation parameters. These parameters are used as input for the generative AI model.

[1369] Step 4:

[1370] World and dungeon generation

[1371] The server uses a generative AI model to generate worlds and dungeons based on the adjusted parameters. Examples of generative AI models used here include GPT-3. By providing the adjusted parameters as input to the generative AI model, an appropriate world or dungeon is output. The input is the adjusted generation parameters, and the output is the data for the generated world or dungeon.

[1372] Step 5:

[1373] Data Storage and Response

[1374] The server stores the generated data in a database and responds to the terminal. The terminal displays the received world and dungeon data on the user interface. The user can check the generated world and dungeon and customize it as needed. The input is the generated world and dungeon data, and the output is preview information of the world and dungeon displayed to the user.

[1375] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1376] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1377] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1378] [Fourth embodiment]

[1379] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1380] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1381] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1382] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1383] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1384] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1385] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1386] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1387] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1388] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1389] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1390] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1391] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1392] The present invention is a system that automatically generates worlds and dungeons for games and RPGs using a generative AI model, and mainly includes the following main components and processes.

[1393] System Configuration

[1394] This system consists of the following components:

[1395] 1. How to accept creation requests

[1396] The terminal provides a user interface that allows the user to input parameters required for generating a world or dungeon. Through this interface, the user specifies the desired theme, difficulty level, and play style.

[1397] 2. How to get parameters

[1398] The server receives the creation request sent from the device and detects the parameters of theme, difficulty, and play style. Data validation is also performed at this stage.

[1399] 3. Generative Modeling Methods

[1400] The server maintains a generation AI model, which inputs the acquired parameters into the AI ​​model, which then automatically generates appropriate worlds and dungeons based on the input.

[1401] 4. Data storage and response methods

[1402] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[1403] The terminal displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[1404] Program processing

[1405] Specifically, the program of this system performs the following processing.

[1406] Accepting a generation request

[1407] Users input parameters (theme, difficulty, play style) to generate new worlds and dungeons using the UI on their device. For example, they can select a "medieval fantasy" theme, a "medium" difficulty level, and an "exploration-focused" play style.

[1408] Parameter retrieval and validation

[1409] The terminal generates request data including the parameters entered by the user and sends it to the server, which receives the request and validates the parameters.

[1410] World and dungeon generation

[1411] The server inputs the successfully validated parameters into the generative AI model, which then automatically generates new worlds and dungeons based on these inputs. During this process, the server retrieves appropriate materials, layouts, enemy characters, items, etc. from the database and generates a structure that matches the parameters.

[1412] Data storage and return

[1413] The server stores the generated world and dungeon data in a database, generates a response, and sends it back to the device. The device receives this data and displays a preview of the generated world or dungeon to the user.

[1414] Specific examples

[1415] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[1416] 1. A request containing parameters entered by the user is sent from the terminal.

[1417] 2. The server receives the request, validates it, and then inputs data based on the theme "Medieval Fantasy," difficulty level "Medium," and play style "Exploration-focused" into the generative AI model.

[1418] 3. The generative AI model generates the basic structure of a medieval castle or dungeon, and places enemy characters of moderate difficulty, numerous traps, secret rooms, etc.

[1419] 4. The server stores the generated data and sends it back to the device.

[1420] 5. Users can preview the generated world or dungeon on their device and make any adjustments or customizations they like.

[1421] In this way, a system is created that allows creators to quickly generate diverse worlds and dungeons, providing players with new adventures.

[1422] The processing flow will be explained below.

[1423] Specific processing steps of the program

[1424] Accepting a creation request and obtaining parameters

[1425] Step 1:

[1426] Users access a user interface (UI) on their device and input parameters for generating new worlds and dungeons, such as a theme of "medieval fantasy," a difficulty level of "medium," and a play style of "exploration-focused."

[1427] Step 2:

[1428] The terminal receives the parameters entered by the user and generates request data in JSON format. Example of request data:

[1429] json

[1430] {

[1431] "theme": "Medieval Fantasy",

[1432] "difficulty": "medium level",

[1433] "playStyle": "Exploration-oriented"

[1434] }

[1435] Step 3:

[1436] The device sends the generated request data to the server's API endpoint. This communication uses the HTTP protocol.

[1437] Receiving and Validating a Request

[1438] Step 4:

[1439] The server receives the request sent through the API and validates the request data, checking that all required fields are present and that the values ​​are valid.

[1440] Step 5:

[1441] The server validates the request parameters, and if validation is successful, proceeds to the next step. If validation fails, it returns an error response to the terminal.

[1442] World and dungeon generation

[1443] Step 6:

[1444] The server accesses the database and retrieves data (terrain, enemy characters, items, etc.) related to the requested theme "Medieval Fantasy," difficulty level "Medium," and play style "Exploration-focused."

[1445] Step 7:

[1446] The server inputs the acquired data and request parameters into a generative AI model, which then generates new worlds and dungeons based on this data.

[1447] Step 8:

[1448] The generative AI model creates the basic structure of a medieval fantasy castle or dungeon, with a layout that emphasizes exploration, and features enemies, traps, secret rooms, and other elements of moderate difficulty.

[1449] Saving and returning generated results

[1450] Step 9:

[1451] The server stores generated world and dungeon data in a database, including the generation ID, generation data, and generation date and time.

[1452] Step 10:

[1453] The server converts the generated results into JSON format and generates a response, which contains details about the generated world and dungeon.

[1454] Step 11:

[1455] The server sends a response containing the generated data back to the device via the API.

[1456] Viewing and customizing the results

[1457] Step 12:

[1458] The device parses the generated data received from the server and displays it in a user interface, including a visual preview of the generated world and dungeon.

[1459] Step 13:

[1460] The user can preview the generated world and dungeon and customize it as needed, for example by rearranging specific rooms or adding items.

[1461] Step 14:

[1462] The device saves any customizations made by the user and finalizes them as world and dungeon data.

[1463] Example 1

[1464] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1465] The generation of worlds and dungeons in conventional games and RPGs is often done manually, requiring a great deal of time and effort. This makes it difficult to quickly generate diverse worlds and dungeons. Furthermore, existing automatic generation systems have the problem of making it difficult to customize them to fit a user's desired theme or play style. Therefore, there is a demand for technology that can efficiently generate diverse, high-quality worlds and dungeons that meet user needs.

[1466] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1467] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style based on the generation request and validating the parameters, means for inputting the acquired parameters into a generation AI model and automatically generating appropriate worlds and dungeons, means for storing data of the generated worlds and dungeons in a database and returning the data to the terminal as a response, and means for displaying the returned data on the terminal and providing a user interface that can be customized by the user. This allows for the efficient generation of diverse, high-quality worlds and dungeons that meet the user's needs and also allows the user to customize them themselves.

[1468] The "means for accepting a generation request" is a device or function that provides an interface that allows a user to input parameters necessary to generate a world or dungeon.

[1469] "Parameters" are information required by the generation AI model to generate a world or dungeon, such as the theme, difficulty, and play style of the generated world or dungeon.

[1470] "Validation means" refers to a device or function that verifies the validity of data by checking whether the acquired parameters are in the correct format or range.

[1471] A "generative AI model" is an algorithm or system that takes acquired parameters as input and automatically generates appropriate worlds and dungeons based on them.

[1472] A "generative model means" is a device or function that uses a generative AI model to automatically generate worlds and dungeons based on parameters.

[1473] A "database" is a storage device or system for storing data on generated worlds and dungeons.

[1474] The "means for returning as a response" is a device or function that sends data of the generated world or dungeon to the terminal and displays it to the user.

[1475] "User interface" is a function that provides a screen and operating means that allows users to preview the worlds and dungeons generated on their device and customize them as needed.

[1476] This invention is a system that uses a generative AI model to automatically generate worlds and dungeons for games and RPGs. This system mainly uses three main components: a server, a terminal, and a user, as well as various data processing means. The specific form and operation of the system are shown below.

[1477] Components and Operation

[1478] A means of accepting creation requests

[1479] The terminal provides the user with a user interface that allows them to input the parameters required to generate a world or dungeon. Through this interface, the user can specify the desired theme, difficulty level, and play style. For example, the user might input parameters such as "Theme: Medieval Fantasy," "Difficulty: Medium level," and "Play Style: Exploration-focused."

[1480] A means of obtaining and validating parameters

[1481] The device generates request data including the parameters entered by the user and sends it to the server. The server analyzes the received request data and extracts the parameters for theme, difficulty, and play style. The extracted parameters are then validated to ensure they are in the correct format and range. For example, it verifies that "difficulty" is either "low," "medium," or "high."

[1482] A means of generating worlds and dungeons using generative AI models

[1483] The server uses the validated parameters to input the generative AI model, generating a prompt like this:

[1484] Theme: Medieval Fantasy

[1485] Difficulty: Medium

[1486] Playstyle: Exploration-focused

[1487] Specific instructions:

[1488] Generate the basic structure of a medieval castle or dungeon

[1489] Place enemy characters with a moderate level of difficulty

[1490] Lots of traps and secret rooms

[1491] Based on these prompts, a generative AI model (such as GPT-4) automatically generates appropriate world and dungeon structures, layouts, enemy characters, items, etc.

[1492] A means to save the generated results and return them as a response

[1493] The server saves the generated world and dungeon data in a database. It then sends the saved data back to the device as a response. The device can then analyze the received data and display a preview of the world or dungeon to the user.

[1494] A means of displaying generated results and providing a customizable user interface

[1495] The device visually displays the generated world and dungeon to the user. The user can check the displayed world and dungeon and customize parts of it as needed. For example, they can change the layout of the generated dungeon by dragging and dropping, or add new enemy characters or items.

[1496] Specific examples

[1497] For example, if a user inputs the parameters "Theme: Medieval Fantasy", "Difficulty: Medium", and "Playstyle: Exploration-Oriented", the following sequence of actions will occur:

[1498] 1. The user enters parameters using the terminal interface.

[1499] 2. The terminal generates request data and sends it to the server.

[1500] 3. The server receives the request and validates the parameters.

[1501] 4. The server uses the generative AI model to generate worlds and dungeons based on the parameters.

[1502] 5. The generative AI model generates the basic structure of medieval castles and dungeons, as well as enemy characters, traps, secret rooms, and other elements of moderate difficulty.

[1503] 6. The server stores the generated data and sends it back to the device.

[1504] 7. The user can preview the generated world and dungeon on their device and customize it as needed.

[1505] This system allows users to quickly generate diverse, high-quality worlds and dungeons, providing players with new adventures.

[1506] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1507] Step 1:

[1508] The user uses the terminal's user interface to create new worlds and dungeons, inputting parameters such as theme, difficulty level, and play style.

[1509] Inputs: Theme (medieval fantasy), difficulty (medium), playstyle (exploration-focused).

[1510] Operation: Each parameter is selected using a drop-down menu, radio button, checkbox, etc. on the user interface.

[1511] Output: The parameter set entered by the user.

[1512] Step 2:

[1513] The terminal generates request data including the parameters input by the user and transmits it to the server.

[1514] Input: A set of parameters entered by the user.

[1515] Data processing: Converts parameters into JSON format request data.

[1516] What it does: Sends the request data to the server using an HTTP POST request.

[1517] Output: The request data sent to the server.

[1518] Step 3:

[1519] The server receives the request data sent from the terminal and validates the parameters.

[1520] Input: Request data sent from the terminal (JSON format).

[1521] Data processing: Parse the JSON data, extract the theme, difficulty, and playstyle parameters, and ensure they are in the correct format and values.

[1522] What it does: Validates each extracted parameter (e.g., checks that the difficulty is either "low", "medium", or "high").

[1523] Output: The validated parameter set.

[1524] Step 4:

[1525] The server uses the successfully validated parameters to input a prompt sentence into the generative AI model.

[1526] Input: A validated set of parameters.

[1527] Data calculation: Generate prompt sentences and input them into the generative AI model.

[1528] How it works: Generate a prompt sentence like the one below and pass it to a generative AI model (e.g., GPT-4).

[1529] Theme: Medieval Fantasy

[1530] Difficulty: Medium

[1531] Playstyle: Exploration-focused

[1532] Specific instructions:

[1533] Generate the basic structure of a medieval castle or dungeon

[1534] Place enemy characters with a moderate level of difficulty

[1535] Lots of traps and secret rooms

[1536] Output: Output data from the generative AI model (detailed world and dungeon generation data).

[1537] Step 5:

[1538] The server stores the generated data obtained from the generative AI model in a database.

[1539] Input: The output data from the generative AI model.

[1540] Data processing: Organizing the generated data and converting it into a format that can be stored in a database.

[1541] What it does: Executes a SQL query that inserts the generated data into a database.

[1542] Output: Generated data stored in a database.

[1543] Step 6:

[1544] The server returns the generated data stored in the database to the terminal as a response.

[1545] Input: Generated data stored in a database.

[1546] Data processing: Converting some or all of the generated data into a JSON response.

[1547] Operation: Sends to the terminal as an HTTP response.

[1548] Output: The JSON response sent to the terminal.

[1549] Step 7:

[1550] The terminal analyzes the generated data received from the server and displays it to the user.

[1551] Input: The JSON response received from the server.

[1552] Data processing: Parse JSON data to extract world and dungeon structure.

[1553] How it works: It uses the extracted data to visually display worlds and dungeons in a user interface, and also provides an edit mode for user customization.

[1554] Output: A user-viewable and customizable representation of the world and dungeon.

[1555] In this way, users can easily create high-quality worlds and dungeons and customize them as needed.

[1556] (Application example 1)

[1557] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1558] Conventional world and dungeon generation systems require users to manually create detailed settings and layouts, which takes time and effort. Furthermore, customization of the generated worlds and dungeons is limited, making it difficult for users to fully express their creativity. Therefore, there is a demand for a system that allows users to easily generate worlds and dungeons on their smartphones and freely customize their content.

[1559] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1560] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style, generation model means for automatically generating worlds and dungeons from the acquired parameters, means for saving and responding to data on the generated worlds and dungeons, and means for the user to preview and customize the generated worlds and dungeons on their smartphones. This allows users to easily generate worlds and dungeons using their smartphones and freely customize their contents.

[1561] A "generation request" is a request entered by a user to generate a world or dungeon based on specific conditions.

[1562] "Theme" is a category that determines the overall setting and atmosphere of the generated world or dungeon.

[1563] "Difficulty" is a parameter that indicates the difficulty of playing in the generated world or dungeon.

[1564] "Play style" is a parameter that indicates the user's desired game progression style, tactics, etc.

[1565] "Parameters" are input data such as theme, difficulty level, play style, etc., obtained based on a generation request.

[1566] A "generative model means" is an AI-based algorithm or system that automatically generates worlds and dungeons based on acquired parameters.

[1567] "Means for saving and responding to data" refers to the function of saving the data of the generated world and dungeon in a database and sending that data to the user.

[1568] "Preview" is a function that displays the contents of the generated world or dungeon so that the user can check them.

[1569] "Means for customization" refers to a feature that allows users to freely modify and adjust the details of the generated worlds and dungeons.

[1570] A "smartphone" is a mobile information device that allows users to use applications to create and customize worlds and dungeons.

[1571] The system for implementing this invention mainly includes a terminal that accepts generation requests, a server that generates worlds and dungeons based on acquired parameters, and a means for saving and responding to the generated data. This system allows users to easily generate and customize original worlds and dungeons on their own smartphones.

[1572] Hardware and Software Configuration

[1573] Hardware

[1574] Device: Smartphone (Android or iOS device)

[1575] Server: Cloud server

[1576] software

[1577] Frontend: React Native

[1578] Backend: Node.js, Express

[1579] Database: MongoDB

[1580] Generative AI model: GPT-4 or other generative AI model (OpenAI API)

[1581] Specific processing of the system

[1582] Accepting a generation request

[1583] Users open the app on their smartphone and input parameters to generate a new world or dungeon. They can choose from a variety of themes, difficulty levels, and play styles. They can choose from a "future city" theme, a "high level" difficulty level, or a "battle-focused" play style.

[1584] Parameter retrieval and validation

[1585] The creation request sent from the terminal is passed to the server, which validates the received parameters to ensure that they do not contain invalid data.

[1586] World and dungeon generation

[1587] Parameters are input into the generative AI model, which automatically generates worlds and dungeons based on these parameters. During this process, the appropriate materials, layouts, enemy characters, items, etc. are retrieved from the database and configured to fit the parameters.

[1588] Data storage and response

[1589] The generated world and dungeon data is stored in a database and sent back to the device as a response. The device displays the received data in a user interface, allowing the user to preview and customize the content as needed.

[1590] Specific examples

[1591] For example, if a user selects a "future city" theme, a "high level" difficulty level, and a "battle-focused" play style, the parameters are sent to the server and, after validation, input into the generative AI model. The generative AI model automatically generates a dungeon containing futuristic city-style buildings, corridors, enemy characters, and battle scenes. The generated data is stored in a database and sent back to the device, allowing the user to preview the new world on their smartphone and further customize it.

[1592] Example prompts for generative AI models

[1593] Generate a new dungeon based on the following parameters:

[1594] Theme: Future City

[1595] Difficulty: High level

[1596] Playstyle: Battle-focused

[1597] Dungeons must contain enemy characters and battle scenes.

[1598] This system allows users to easily generate advanced worlds and dungeons and customize them freely.

[1599] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1600] Step 1:

[1601] The user opens the smartphone application and inputs the theme, difficulty level, and play style to generate a new world or dungeon. At this time, the user inputs the specific parameters of the theme (e.g., "future city"), difficulty level (e.g., "high level"), and play style (e.g., "focus on battle") into the device. The input parameters are formatted as generation request data on the device, and the request data is created as output.

[1602] Step 2:

[1603] The generation request data is sent from the terminal to the server. The server analyzes the received request data and extracts the parameters of theme, difficulty, and play style. In this step, the received data is checked to see if it is valid (validation). After the consistency of the data is confirmed, it becomes a valid request. Consistent parameter data is obtained as the output.

[1604] Step 3:

[1605] The server inputs the successfully validated parameters into the generative AI model. At this time, the parameter data is formatted as a prompt for the generative AI model. The prompt is converted into a format that is easy for the generative AI model to understand (e.g., "Generate a new dungeon based on the following parameters: Theme: futuristic city, Difficulty: high level, Play style: battle-focused"). The prompt is input into the generative AI model, and an appropriate world or dungeon is generated. The data for the generated world or dungeon is obtained as output.

[1606] Step 4:

[1607] The generated world and dungeon data is saved on the server. A database (MongoDB) is used for saving. This data is associated with user identification information and managed as a different world or dungeon for each user. A save completion message is returned from the server as output.

[1608] Step 5:

[1609] Once the world or dungeon data has been saved, it is sent back to the device from the server. The device displays the received data in the user interface. It is visually rendered in the UI so that the user can see a preview of the generated world or dungeon. A preview screen is provided as output for the user to view.

[1610] Step 6:

[1611] The user checks the displayed preview and customizes it as necessary. In this step, the user edits the details of the generated world or dungeon (e.g., enemy character placement, item location, layout, etc.) on their smartphone. The edited data is then sent back to the server and updated. The final customized world or dungeon data is obtained as output.

[1612] By following these steps, users can easily create original worlds and dungeons on their smartphones and customize them to their liking.

[1613] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1614] The system of the present invention combines a generative AI model with an emotion engine that recognizes user emotions to automatically generate worlds and dungeons for games and RPGs, and provide content optimized according to the user's emotions. This system includes the following main components and processes:

[1615] System Configuration

[1616] This system consists of the following components:

[1617] 1. How to accept creation requests

[1618] The terminal provides a user interface that allows the user to input parameters required for generating a world or dungeon. Through this interface, the user specifies the desired theme, difficulty level, and play style.

[1619] 2. How to get parameters

[1620] The server receives the creation request sent from the device and detects the parameters of theme, difficulty, and play style. Data validation is also performed at this stage.

[1621] 3. Emotion Engine

[1622] The device's built-in camera and microphone capture the user's facial expressions and voice, and then analyzes them to recognize the user's emotions.

[1623] The server adjusts the parameters of the generation request based on this emotion data, for example, setting the difficulty level low if the user is tired and high if the user is excited.

[1624] 4. Generative Modeling Methods

[1625] The server maintains a generation AI model, which inputs the acquired parameters into the AI ​​model, which then automatically generates appropriate worlds and dungeons based on the input.

[1626] 5. Data storage and response measures

[1627] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[1628] The device displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[1629] Program processing

[1630] Specifically, the program of this system performs the following processing.

[1631] Accepting a generation request

[1632] Users use the on-device UI to input parameters (theme, difficulty level, play style) to generate new worlds and dungeons. At that time, the device's camera and microphone capture the user's facial expressions and voice, and the emotion engine analyzes the user's emotional state.

[1633] Parameter retrieval and validation

[1634] The device combines the parameters entered by the user and the emotional data analyzed by the emotion engine to generate request data and sends it to the server. The server receives this request and validates the parameters.

[1635] Emotion-based parameter adjustment

[1636] The server automatically adjusts the generation parameters based on the user's emotional data. For example, if the user is feeling relaxed, the server changes the theme to a soothing one and sets the difficulty level lower.

[1637] World and dungeon generation

[1638] The server inputs the adjusted parameters based on validation and emotion into the generative AI model, which then automatically generates new worlds and dungeons based on this data.

[1639] Saving and returning generated results

[1640] The server stores the generated world and dungeon data in a database, generates a response, and sends it back to the device, which receives the data and displays it on the user interface.

[1641] Specific examples

[1642] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[1643] 1. The user inputs their choices into the device, while the camera and microphone capture the user's emotions.

[1644] 2. The device sends the user's input parameters and emotion data to the server, which then inputs optimized generation parameters based on this data into the generative AI model.

[1645] 3. The generative AI model creates the basic structure of castles and dungeons based on a "medieval fantasy" theme, and places appropriate difficulty and exploration elements depending on the user's emotional state.

[1646] 4. The server stores the generated data and sends it back to the device.

[1647] 5. Users can preview the generated world or dungeon on their device and enjoy the optimal experience suggested based on their emotions.

[1648] In this way, the system can quickly generate worlds and dungeons that correspond to the user's emotional state, providing an individually optimized adventure.

[1649] The processing flow will be explained below.

[1650] Specific processing steps of the program

[1651] Automatic world and dungeon generation system using emotion engine

[1652] Step 1:

[1653] Using the device's user interface (UI), users input parameters for generating new worlds and dungeons, including a "medieval fantasy" theme, a "medium" difficulty level, and an "exploration-focused" play style.

[1654] Step 2:

[1655] The device acquires the parameters entered by the user and also uses a camera and microphone to collect the user's facial expressions and voice data.

[1656] Step 3:

[1657] The device inputs the collected facial and voice data into an emotion engine to analyze the user's emotional state. For example, the facial recognition system can detect excitement from the user's smile, and voice analysis can assess stress levels from the tone of voice.

[1658] Step 4:

[1659] Based on the analysis, the emotion engine determines whether the user is currently relaxed, stressed, or excited, and sends this information along with the parameters of the generation request to the server.

[1660] Step 5:

[1661] The device generates JSON-formatted request data containing the parameters entered by the user and the emotion engine's analysis results, and sends it to the server's API endpoint. Request data example:

[1662] json

[1663] {

[1664] "theme": "Medieval Fantasy",

[1665] "difficulty": "medium level",

[1666] "playStyle": "Exploration-oriented",

[1667] "emotionalState": "Relaxed"

[1668] }

[1669] Receiving and Validating a Request

[1670] Step 6:

[1671] The server receives the request at the API endpoint and validates the request data, checking that all required fields are present and that the values ​​are valid.

[1672] Step 7:

[1673] The server validates the request parameters, and if validation is successful, proceeds to the next step. If validation fails, it returns an error response to the terminal.

[1674] Emotion-based parameter adjustment

[1675] Step 8:

[1676] The server adjusts parameters based on the user's emotional state received from the emotion engine. For example, if the user is relaxed, the difficulty level is lowered slightly and the exploration element is increased.

[1677] World and dungeon generation

[1678] Step 9:

[1679] The server accesses the database and retrieves data (terrain, enemy characters, items, etc.) related to the requested theme "medieval fantasy," difficulty level "medium level," and play style "exploration-oriented."

[1680] Step 10:

[1681] The server inputs the adjusted parameters and acquired data into the generative AI model, which generates new worlds and dungeons based on this data.

[1682] Step 11:

[1683] The generative AI model creates the basic structure of castles and dungeons with a medieval fantasy layout, populating them with enemies, traps, and exploration elements of moderate difficulty.

[1684] Saving and returning generated results

[1685] Step 12:

[1686] The server stores generated world and dungeon data in a database, including the generation ID, generation data, and generation date and time.

[1687] Step 13:

[1688] The server converts the generated results into JSON format and generates a response, which contains details about the generated world and dungeon.

[1689] Step 14:

[1690] The server sends a response containing the generated data back to the device via the API.

[1691] Viewing and customizing the results

[1692] Step 15:

[1693] The device parses the generated data received from the server and displays it in a user interface, including a visual preview of the generated world and dungeon.

[1694] Step 16:

[1695] Users can preview the generated world and dungeon and customize it as needed, for example by rearranging specific rooms or adding items.

[1696] Step 17:

[1697] The device saves any customizations made by the user and finalizes them as world and dungeon data.

[1698] In this way, a system is realized that can provide a superior gaming experience that is tailored to the user's emotional state.

[1699] Example 2

[1700] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1701] Conventional game and RPG world and dungeon generation systems only provide static content based on user input parameters, making it difficult to dynamically adjust to the user's emotional state. This can result in a consistently inoffensive gaming experience, as users are presented with content that is not optimized for their current emotional state.

[1702] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1703] In this invention, the server includes means for accepting a generation request, means for acquiring parameters related to theme, difficulty level, and play style, means for acquiring emotional data using an emotion engine that recognizes the user's emotions, means for automatically adjusting the parameters based on the acquired emotional data, generative model means for automatically generating worlds and dungeons based on the adjusted parameters, and means for saving and responding to the generated data, thereby enabling the automatic generation of worlds and dungeons optimized according to the user's emotional state.

[1704] The "means for accepting a generation request" is a means by which a user inputs parameters for generating a new world or dungeon, and the system accepts them.

[1705] "Theme" refers to the basic concept or style of the generated world or dungeon, such as a category like "medieval fantasy" or "cyberpunk."

[1706] "Difficulty" is a parameter that indicates the level of challenge in the game in the generated world or dungeon, and is set at levels such as easy, medium level, or difficult.

[1707] "Play style" is a parameter that indicates how a user enjoys a game, and examples include styles such as "exploration-oriented" and "combat-oriented."

[1708] "Means for acquiring parameters" refers to means for receiving information such as theme, difficulty level, play style, etc. input by the user and storing it within the system.

[1709] An "emotion engine" is a software or hardware technology that recognizes a user's emotional state at any given time by analyzing the user's facial expressions and voice.

[1710] The "means for acquiring emotion data" is a means for acquiring data relating to the user's emotional state using an emotion engine.

[1711] The "means for automatically adjusting parameters" is a means for automatically changing parameters such as theme, difficulty level, and play style input by the user based on the acquired emotional data.

[1712] "Generative model means" refers to means that includes models and algorithms for automatically generating worlds and dungeons based on adjusted parameters.

[1713] "Means for saving and responding to generated data" refers to means for saving data on the generated worlds and dungeons in a database and providing it to the user.

[1714] "World" refers to the virtual world or area that serves as the playing environment for a game or RPG.

[1715] A "dungeon" is a complex structure or area in a game or RPG that players explore to progress through missions or quests.

[1716] The system of the present invention combines a generative AI model with an emotion engine that recognizes user emotions to automatically generate worlds and dungeons for games and RPGs, and provides content optimized according to the user's emotions. This system includes the following main components and processes:

[1717] System Configuration

[1718] This system consists of the following components:

[1719] 1. How to accept creation requests

[1720] The terminal provides a user interface for inputting the parameters (theme, difficulty, play style) required when a user wishes to generate a world or dungeon. Through this interface, the user can create a specific generation request.

[1721] 2. How to get parameters

[1722] The server receives the creation request sent from the device and detects and validates the theme, difficulty, and play style parameters to ensure that the creation request is processed properly.

[1723] 3. Emotion Engine

[1724] The device's built-in camera and microphone capture the user's facial expressions and voice, and then analyzes them to recognize the user's emotions.

[1725] The server adjusts the parameters of the generation request based on this emotion data, for example, setting the difficulty level low if the user is tired and high if the user is excited.

[1726] 4. Generative Modeling Methods

[1727] The server maintains a generative AI model, which automatically generates appropriate worlds and dungeons based on the parameters and emotional data acquired from the AI ​​model. Examples of generative AI models used include GPT-3 and DALL-E.

[1728] 5. Data storage and response measures

[1729] The server stores the generated world and dungeon data in a database and sends that data back to the device.

[1730] The terminal displays the received data on a user interface, allowing the user to check the generated world and dungeon and customize them as needed.

[1731] Specific examples

[1732] For example, if the user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, the following processing will be performed.

[1733] 1. The user inputs their choices into the device, while the camera and microphone capture the user's emotions.

[1734] 2. The device sends the user's input parameters and emotion data to the server, which then inputs optimized generation parameters based on this data into the generative AI model.

[1735] 3. The generative AI model creates the basic structure of castles and dungeons based on a "medieval fantasy" theme, and places appropriate difficulty and exploration elements depending on the user's emotional state.

[1736] 4. The server stores the generated data and sends it back to the device.

[1737] 5. Users can preview the generated world or dungeon on their device and enjoy the optimal experience suggested based on their emotions.

[1738] Prompt Sentence Examples

[1739] Examples of prompts to drive a generative AI model include:

[1740] "Theme: Medieval fantasy, Difficulty: Medium, Play style: Exploration-focused, User emotion: Relaxed"

[1741] In this way, the system can quickly generate optimized worlds and dungeons that correspond to the user's emotional state, providing an individually optimized adventure.

[1742] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1743] Step 1: Accepting the generation request

[1744] The user uses the user interface on the device to input the desired parameters (theme, difficulty, play style) for generating a world or dungeon. The input theme is often "medieval fantasy," the difficulty level is "medium level," and the play style is "exploration-oriented." The device receives the user's input and stores these parameters in an internal data structure. At the same time, the device's camera and microphone collect the user's facial expressions and voice. The collected data is analyzed in real time by the emotion engine.

[1745] input:

[1746] Theme, difficulty, playstyle (via user interface)

[1747] User's facial expressions and voice (via camera and microphone)

[1748] output:

[1749] Analyzed parameters and emotion data

[1750] Step 2: Obtaining and validating parameters

[1751] The device combines the parameters entered by the user (theme, difficulty level, play style) with the emotional data analyzed by the emotion engine and sends it to the server as request data. The server receives this data and verifies the appropriateness and validity of each parameter. For example, it checks whether the theme is appropriate and whether the difficulty level is within an acceptable range.

[1752] input:

[1753] User-entered parameters

[1754] Emotion data acquired by the emotion engine

[1755] output:

[1756] Validated parameters and emotion data

[1757] Step 3: Collecting emotion data

[1758] The device's built-in camera and microphone are used to collect the user's facial expressions and voice. This is partially done in Step 1, but is done again with the aim of accurately obtaining the user's emotional data. The emotion engine analyzes this data and determines the user's emotions, such as whether they are relaxed, excited, or tired, using numerical values ​​and categories.

[1759] input:

[1760] User's facial expressions and voice (via camera and microphone)

[1761] output:

[1762] Emotion data analyzed by the emotion engine

[1763] Step 4: Emotion-based parameter adjustment

[1764] The server automatically adjusts the generation parameters entered by the user based on the emotion data sent from the emotion engine. For example, if the server determines that the user is relaxed, it will set the difficulty to "low" and change the theme to "relaxing." These adjusted parameters will provide a more appropriate gaming experience for the user.

[1765] input:

[1766] Verified parameters

[1767] Emotional Data

[1768] output:

[1769] Adjusted parameters

[1770] Step 5: World and dungeon generation

[1771] The server inputs the adjusted emotion-based parameters into a generative AI model, which uses algorithms such as GPT-3 or DALL-E to generate detailed structures and designs for new worlds and dungeons based on the input parameters.

[1772] input:

[1773] Adjusted parameters (theme, difficulty, play style)

[1774] output:

[1775] Generated world and dungeon data

[1776] Step 6: Save and return the generated results

[1777] The server stores the generated world and dungeon data in a database and sends it back to the device as a response. The device receives the generated data and displays it on the user interface, allowing the user to preview the generated world and dungeon and begin their experience.

[1778] input:

[1779] Generated world and dungeon data

[1780] output:

[1781] World and dungeon previews

[1782] Through this process, the system quickly generates optimized worlds and dungeons according to the user's emotional state, providing an individually optimized adventure experience.

[1783] (Application example 2)

[1784] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1785] Conventional content generation systems generate game and RPG worlds and dungeons based on fixed parameters without taking user emotions into account. This makes it difficult to provide an optimal play experience according to the user's emotional state. Furthermore, conventional systems have difficulty responding to situations where content needs to be instantly adjusted according to the user's temporary emotional state.

[1786] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1787] In this invention, the server includes means for accepting generation requests, means for recognizing the user's emotions and adjusting parameters, and generative model means for automatically generating worlds and dungeons from the acquired parameters, thereby enabling the parameters to be instantly adjusted based on the user's emotional state, enabling optimized content generation.

[1788] A "generation request" is information regarding the theme, difficulty level, and play style that a user specifies when they wish to generate a world or dungeon.

[1789] The term "means" refers to components or functional units necessary for carrying out the present invention.

[1790] "Theme" is a category that defines the basic setting and background of the generated world or dungeon.

[1791] "Difficulty" defines the degree of challenge and obstacles the player faces in a generated world or dungeon.

[1792] "Play style" is a concept that indicates how a user wants to progress through a game and what they value in their experience.

[1793] An "emotion engine" is a technology that analyzes a user's facial expressions and voice to recognize their emotional state.

[1794] "Generative model means" is a general term for algorithms and models that automatically generate worlds and dungeons based on acquired parameters.

[1795] "Means for saving and responding to data" refers to a function for saving data of generated worlds and dungeons in a storage system such as a database, and providing that data to users as needed.

[1796] The system of the present invention automatically generates worlds and dungeons based on the user's emotions and has the following configuration: First, the user inputs a generation request through a user interface on a terminal. The generation request includes parameters related to theme, difficulty, and play style.

[1797] System configuration

[1798] 1. Terminal: An input device where the user inputs the generation request and captures the emotional state in real time. This is often a smartphone or tablet.

[1799] 2. Server: Receives generation requests sent by users, analyzes emotional data, and generates worlds and dungeons using generative AI models. This also includes data storage and response functions.

[1800] Program processing

[1801] 1. Receiving a generation request: The device accepts a generation request from the user. The user specifies the theme, difficulty level, and play style. The device also captures the user's facial expressions and voice using the device's camera and microphone, and sends them to the emotion engine.

[1802] 2. Emotion Data Analysis: The server analyzes the captured emotion data using an emotion engine, which uses technologies such as OpenCV and DeepFace to determine whether the user is relaxed, excited, tired, etc.

[1803] 3. Adjustment of generation parameters: The server adjusts the generation parameters based on the analyzed emotional data. For example, if the user is relaxed, it will set the difficulty level low and change the theme to a soothing one.

[1804] 4. World and dungeon generation: The server generates worlds and dungeons based on the adjusted parameters using a generative AI model, such as GPT-3 or a similar AI model.

[1805] 5. Data storage and response: The server stores the generated data in a database and responds to the terminal. The terminal displays the received data on the user interface, allowing the user to check the generated world and dungeon.

[1806] Specific examples

[1807] If a user selects a "medieval fantasy" theme, a "medium level" difficulty level, and an "exploration-focused" play style, a world is generated through the following steps. First, the device accepts the user's input and sends facial expressions and voice captured by the camera to the emotion engine. Next, the server uses the emotion engine to analyze the user's emotional state and adjusts the generation parameters appropriately. The generative AI model automatically generates the world and dungeons based on this data, and the generated data is stored in a database and provided to the user on the device.

[1808] Example prompt sentence:

[1809] "Generate a medieval fantasy-themed world with a medium level of difficulty and a focus on exploration based on user emotional data. The user is very happy."

[1810] As described above, this system can automatically generate optimal worlds and dungeons according to the user's emotional state, providing an individually optimized playing experience.

[1811] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1812] Step 1:

[1813] Accepting a generation request

[1814] The device receives a generation request from the user. The user inputs the theme, difficulty level, and play style into the device's user interface. At this time, the device's camera and microphone capture the user's facial expressions and voice and send them to the emotion engine. The input data includes the theme, difficulty level, play style, and facial and voice data.

[1815] Step 2:

[1816] Sentiment Data Analysis

[1817] The server receives facial and voice data sent from the device and analyzes it using an emotion engine. It uses technologies such as OpenCV and DeepFace to determine the user's emotional state (relaxed, excited, tired, etc.). The input is the captured facial and voice data, and the output is data indicating the emotional state.

[1818] Step 3:

[1819] Adjusting generation parameters

[1820] The server automatically adjusts the generation parameters based on the analyzed emotional data. For example, if the user is relaxed, it sets the difficulty to low and changes the theme to soothing. The inputs are theme, difficulty, play style, and emotional data, and the output is the adjusted generation parameters. These parameters are used as input for the generative AI model.

[1821] Step 4:

[1822] World and dungeon generation

[1823] The server uses a generative AI model to generate worlds and dungeons based on the adjusted parameters. Examples of generative AI models used here include GPT-3. By providing the adjusted parameters as input to the generative AI model, an appropriate world or dungeon is output. The input is the adjusted generation parameters, and the output is the data for the generated world or dungeon.

[1824] Step 5:

[1825] Data Storage and Response

[1826] The server stores the generated data in a database and responds to the terminal. The terminal displays the received world and dungeon data on the user interface. The user can check the generated world and dungeon and customize it as needed. The input is the generated world and dungeon data, and the output is preview information of the world and dungeon displayed to the user.

[1827] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1828] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1829] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1830] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1831] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1832] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1833] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1834] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1835] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1836] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1837] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1838] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1839] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1840] 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.

[1841] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1842] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1843] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1844] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1845] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1846] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1847] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1848] The following is further disclosed regarding the above embodiment.

[1849] (Claim 1)

[1850] means for accepting a generation request;

[1851] means for acquiring parameters relating to theme, difficulty level, and play style based on the generation request;

[1852] a generative modeling means for automatically generating a world or dungeon from the acquired parameters;

[1853] A means of storing and responding to generated world and dungeon data,

[1854] A system including:

[1855] (Claim 2)

[1856] The system of claim 1 , wherein the creation request includes a selection of a theme, a difficulty level, and a play style.

[1857] (Claim 3)

[1858] The system of claim 1, wherein the generative model means includes means for placing world and dungeon layouts, enemy characters, and items that are appropriate for the input theme, difficulty level, and play style.

[1859] "Example 1"

[1860] (Claim 1)

[1861] means for accepting a generation request;

[1862] a means for acquiring parameters relating to theme, difficulty level, and play style based on the generation request, and validating the parameters;

[1863] A generative model means for inputting the acquired parameters into a generative AI model and automatically generating an appropriate world or dungeon;

[1864] A means to save the generated world and dungeon data in a database and return it to the device as a response.

[1865] means for displaying the returned data on a terminal and providing a user-customizable user interface;

[1866] A system including:

[1867] (Claim 2)

[1868] The system of claim 1 , wherein the creation request includes a selection of a theme, a difficulty level, and a play style.

[1869] (Claim 3)

[1870] The system of claim 1, wherein the generative model means includes means for placing world and dungeon layouts, enemy characters, and items that are appropriate for the input theme, difficulty level, and play style.

[1871] "Application Example 1"

[1872] (Claim 1)

[1873] means for accepting a generation request;

[1874] means for acquiring parameters relating to theme, difficulty level, and play style based on the generation request;

[1875] a generative modeling means for automatically generating a world or dungeon from the acquired parameters;

[1876] A means of storing and responding to generated world and dungeon data,

[1877] A means for a user to preview and customize the generated world or dungeon on a smartphone;

[1878] A system including:

[1879] (Claim 2)

[1880] The system of claim 1 , wherein the creation request includes a selection of a theme, a difficulty level, and a play style.

[1881] (Claim 3)

[1882] The system of claim 1, wherein the generative model means includes means for placing world and dungeon layouts, enemy characters, and items that are appropriate for the input theme, difficulty level, and play style.

[1883] "Example 2: Combining Emotion Engines"

[1884] (Claim 1)

[1885] means for accepting a generation request;

[1886] means for acquiring parameters relating to theme, difficulty level, and play style based on the generation request;

[1887] means for verifying said theme, difficulty, and play style parameters;

[1888] A means for acquiring emotion data using an emotion engine that recognizes the emotion of a user;

[1889] means for automatically adjusting the parameters based on the acquired emotion data;

[1890] a generative model means for automatically generating worlds and dungeons based on the adjusted parameters;

[1891] A means of storing and responding to generated world and dungeon data,

[1892] A system including:

[1893] (Claim 2)

[1894] the creation request includes a selection of a theme, difficulty level, and play style;

[1895] 10. The system of claim 1, wherein the emotion engine acquires emotion data by analyzing a user's facial expression and voice.

[1896] (Claim 3)

[1897] The system of claim 1, wherein the generative model means includes means for arranging world and dungeon layouts, enemy characters, and items based on the input theme, difficulty level, and play style and the adjusted parameters.

[1898] "Application example 2 when combining emotion engines"

[1899] (Claim 1)

[1900] means for accepting a generation request;

[1901] means for acquiring parameters relating to theme, difficulty level, and play style based on the generation request;

[1902] an emotion engine means for recognizing a user's emotion and adjusting parameters;

[1903] a generative modeling means for automatically generating a world or dungeon from the acquired parameters;

[1904] A means of storing and responding to generated world and dungeon data,

[1905] A system including:

[1906] (Claim 2)

[1907] the creation request includes a selection of theme, difficulty level, and play style;

[1908] The system of claim 1.

[1909] (Claim 3)

[1910] the generation model means includes means for arranging world and dungeon layouts, enemy characters, and items that are suited to the input theme, difficulty level, and play style, and further includes means for making adjustments based on the user's emotions;

[1911] 10. The system of claim 1. [Explanation of symbols]

[1912] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for accepting a generation request; means for acquiring parameters relating to theme, difficulty level, and play style based on the generation request; a generative modeling means for automatically generating a world or dungeon from the acquired parameters; A means of storing and responding to generated world and dungeon data, A system including:

2. The system of claim 1 , wherein the creation request includes a selection of a theme, a difficulty level, and a play style.

3. The system according to claim 1 , wherein the generative model means includes means for arranging world and dungeon layouts, enemy characters, and items that are suited to the input theme, difficulty level, and play style.

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