System

Abstract

A system is provided.SOLUTION: A system including means for acquiring information such as a name, an age, a hobby, and a gender input by a user, means for transmitting the acquired information to a server, means for calling a generative AI model that generates an avatar image by using the information received by the server, means for receiving an avatar image generated by the generative AI model, means for giving capability values and skills corresponding to the avatar image, means for displaying the avatar image and the capability values and skills thereof to the user, means for conducting a battle with another user, and means for displaying a battle result.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] Traditional avatar creation and game design required advanced programming knowledge, resulting in significant development time and costs. Furthermore, there was a lack of easy ways to provide personalized avatars and battle functions based on them, making it difficult for ordinary users to create and enjoy their own avatars. Furthermore, there was no standardized method for assigning appropriate ability scores and skills to the generated avatars, resulting in an inconsistent user experience. [Means for solving the problem]

[0005] The present invention provides a means for acquiring information such as a user's name, age, hobbies, and gender, and a means for transmitting the acquired information to a server. The server also includes a means for calling a generative AI model that generates an avatar image using the received information. The system further includes a means for receiving the avatar image generated by the generative AI model and a means for assigning ability scores and skills corresponding to the avatar image. The system also includes a means for displaying the avatar image, its ability scores, and skills to the user, a means for conducting matches with other users, and a means for displaying the results of the matches. This allows users to easily create original avatars and enjoy competing against other users, even without coding knowledge.

[0006] "User" means an individual or end user who uses the System.

[0007] "Name" is a character string for identifying a user, and corresponds to a person's name or nickname.

[0008] "Age" refers to the number of years that have passed since the user's date of birth and is usually expressed as a number.

[0009] "Hobbies" refer to subjects and activities that users enjoy in their daily lives, and are areas in which they have an interest or concern.

[0010] "Gender" refers to a user's biological sex or self-identified gender, such as male or female.

[0011] "Means for acquiring" refers to methods and devices for collecting information from users, and specifically includes input forms and sensors.

[0012] A "server" is a computer or system on a network that processes information and provides data to other computers.

[0013] A "generative AI model" refers to an artificial intelligence algorithm or system that automatically generates avatar images based on user input information.

[0014] An "avatar image" is a digital image that visually represents the information input by the user, and is a character that symbolizes the user.

[0015] "Ability scores" are numerical representations of specific abilities possessed by an avatar, such as knowledge and concentration.

[0016] "Skills" refer to specific techniques or characteristics that an avatar possesses that are useful during battle.

[0017] "Display means" refers to a method or device for visually presenting data generated by a server or terminal to a user, and includes a monitor or display.

[0018] "Means for conducting a match" refers to a method or system for executing a process in which users compete against each other using their respective avatars.

[0019] "Match results" refers to information such as victory or defeat and achievements obtained after the match is over. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] MODE FOR CARRYING OUT THE INVENTION

[0042] This invention is a system that uses a generative AI model to automatically generate an avatar image based on information entered by a user and assigns ability scores and skills appropriate to the avatar. Specific embodiments of the system and program processing are described here.

[0043] Basic system configuration

[0044] This system is broadly composed of the following three modules:

[0045] 1. User information input module

[0046] 2. Avatar Generation Module

[0047] 3. Game Battle Module

[0048] User information input module

[0049] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[0050] Avatar Generation Module

[0051] The server receives user information sent from the device. Based on this information, the server invokes a generative AI model to generate an avatar image. The generative AI model generates the avatar image taking into account the user's characteristics such as age, gender, and hobbies.

[0052] For example, if a user's hobby is "reading," the generative AI model will create an avatar with high knowledge and concentration. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "Knowledge 85" and "Concentration 90."

[0053] Game Battle Module

[0054] The user can select a generated avatar and choose an opponent. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability values ​​and skills of both avatars, and simulates the battle. The simulation results are generated as a log in the form of, for example, "User A's attack was effective and caused great damage to User B."

[0055] Finally, the server generates the match results and sends them to the device. The device displays the received match results to the user, notifying them, for example, "User A won."

[0056] In this way, this system allows users to easily input their own information and intuitively generate an original avatar using a generative AI model. They can then use that avatar to compete against other users and enjoy the results. This allows users to enjoy a sophisticated gaming experience without any programming knowledge.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] The user enters information such as name, age, hobbies, and gender into the application's input form. The user enters the required data into the form and presses the "Submit" button.

[0060] Step 2:

[0061] The terminal receives the information entered by the user, converts it into JSON format, and sends it to the server as an HTTP request.

[0062] Step 3:

[0063] The server receives the user information in JSON format sent from the device. It receives the HTTP request through the API endpoint, parses the JSON data, and converts it into an internal data structure.

[0064] Step 4:

[0065] The server calls the generative AI model based on the received user information, and passes the user information to the generative AI model as a parameter.

[0066] Step 5:

[0067] The generative AI model analyzes the input user information and generates an avatar image based on characteristics such as age, gender, and hobbies. The generated avatar image is then returned to the server.

[0068] Step 6:

[0069] The server receives the generated avatar image and assigns the corresponding ability scores and skills to the avatar image. These ability scores and skills are calculated based on predefined rules.

[0070] Step 7:

[0071] The server sends avatar information, including assigned ability values ​​and skills, to the device. The avatar image and ability value / skill data are then collected and returned to the device in JSON format.

[0072] Step 8:

[0073] The device displays the avatar information received from the server, allowing users to visually check their own avatar image, as well as their ability scores and skills.

[0074] Step 9:

[0075] The user selects their own avatar and chooses an opponent from the match list. After selecting an opponent, the user presses the "Challenge" button.

[0076] Step 10:

[0077] The device sends information about the selected opponent to the server, including the avatar IDs and user IDs of both players, in JSON format.

[0078] Step 11:

[0079] The server receives the matching information and simulates the battle, comparing the ability values ​​and skills of the avatars of both players and simulating the battle based on a predefined algorithm.

[0080] Step 12:

[0081] The server generates the match results, creating a match log with details such as "User A's attack was effective and caused a lot of damage to User B." It also generates the final victory or defeat result.

[0082] Step 13:

[0083] The server sends the generated match results to the device, formats the results in JSON format, and returns them to the device as an HTTP response.

[0084] Step 14:

[0085] The terminal displays the received match results to the user, who can receive a notification such as "User A won."

[0086] Example 1

[0087] 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."

[0088] Conventional avatar generation systems have had problems in that it is difficult to generate a unique avatar image based on information entered by the user and to assign appropriate ability scores and skills to that avatar. Furthermore, when playing against other users using the generated avatar, it is difficult to display the results of the match in real time.

[0089] 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.

[0090] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for converting the acquired information into a data format and transmitting the data to the server, means for analyzing the information received by the server, means for generating an avatar image by calling a generation AI model based on the analyzed information, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for displaying the avatar image, its ability values, and skills to the user, means for the user to select an opponent, means for transmitting information about the selected opponent to the server, means for the server to receive the opponent information and perform a battle simulation, and means for generating and displaying the battle results. This allows intuitive and attractive avatar images to be generated based on user information, and enables users to enjoy battles with other users in real time using the avatars.

[0091] In this invention, the term "user" refers to a person who uses the system.

[0092] "Terminal" refers to a device that a user inputs information into and communicates with a server. Examples include smartphones and personal computers.

[0093] "Server" refers to a high-performance computer or cloud service that performs central processing such as receiving and analyzing data, calling generative AI models, and conducting battle simulations.

[0094] "Generative AI models" refer to artificial intelligence models that generate avatar images based on user information. Examples include DALL-E and GPT-4.

[0095] "Prompt sentence" refers to the instruction sentence provided to the generative AI model when generating an avatar image.

[0096] "Avatar image" refers to an image of a virtual person or character generated by a generative AI model based on user information.

[0097] "Ability scores" refer to the numerical characteristics or skills given to an avatar, such as knowledge or concentration.

[0098] "Skills" refer to specific abilities or special techniques given to an avatar.

[0099] "Battle simulation" refers to the process of comparing the ability scores and skills of avatars selected by multiple users and virtually competing against each other.

[0100] "Match result" refers to the win / loss between users and other result information generated as a result of the match simulation.

[0101] "Means of obtaining information" refers to the function of the system receiving information such as name, age, hobbies, and gender entered by the user.

[0102] "Means for transmitting information" refers to the function of transferring acquired information to a server via a network.

[0103] "Means for receiving information" refers to the function of the server to receive information sent from the terminal.

[0104] "Means for parsing information" refers to the process by which the server breaks down and understands the user information it receives into individual data elements.

[0105] "Means for generating images" refers to the process of using a generative AI model to create an avatar image based on user information.

[0106] "Means for receiving images" refers to the function by which the server receives avatar images generated from the generative AI model.

[0107] "Means of assigning ability values ​​and skills" refers to the process of assigning specific characteristics and special moves to the generated avatar image.

[0108] "Means for displaying images" refers to the function of displaying the generated avatar image and its ability values ​​and skills on the user's device.

[0109] "Means for selecting an opponent" refers to a function that allows a user to select another user's avatar and designate it as an opponent.

[0110] "Means for transmitting opponent information" refers to a function for transmitting information about a selected opponent to the server.

[0111] "Means for performing battle simulation" refers to a function for conducting a virtual battle by comparing the ability values ​​and skills of each avatar based on the opponent information received by the server.

[0112] The "means for generating a match result" refers to a process for compiling information such as wins and losses between users based on the results of the match simulation.

[0113] "Means for displaying battle results" refers to a function for displaying the generated battle results on the user's terminal.

[0114] MODE FOR CARRYING OUT THE INVENTION

[0115] This system uses a generative AI model to automatically generate an avatar image based on information entered by the user, and assigns appropriate ability scores and skills to the avatar.It also has the ability to use the generated avatar to compete against other users and display the results of the competition in real time.

[0116] Basic system configuration

[0117] This system is broadly composed of the following three modules:

[0118] 1. User information input module

[0119] 2. Avatar Generation Module

[0120] 3. Game Battle Module

[0121] User information input module

[0122] The user enters information such as name, age, hobbies, and gender into the application's input form. For example, if the user enters "Hanako Sato, 25 years old, reading, female," each piece of information is entered appropriately into the form.

[0123] The device receives the information entered by the user and converts it into JSON format. For example, the input information is converted into the format {"name":"Hanako Sato","age":25,"hobby":"reading","gender":"female"}. Then, this JSON data is sent to the server.

[0124] Avatar Generation Module

[0125] The server receives and analyzes the JSON data sent from the device, identifying individual information (name, age, hobbies, gender).

[0126] The server calls a generative AI model (e.g., DALL-E or GPT-4) based on the analyzed information. The prompt used here is in the format, "Hanako Sato is 25 years old, female, and her hobby is reading. Please generate an avatar image that shows high knowledge and concentration based on this information."

[0127] The generative AI model generates an avatar image based on this prompt. After the generated avatar image is returned to the server, the server assigns the avatar ability scores and skills, such as "Knowledge 85" and "Concentration 90."

[0128] Game Battle Module

[0129] The user can select the generated avatar and choose an opponent. For example, if the user selects "Yamada Taro" from among the other candidates, the selection is complete.

[0130] The device sends information about the opponent selected by the user to the server. For example, information such as "Yamada Taro, ability values: Strength 75, Defense 60" is sent.

[0131] The server receives information about the opponent and performs a battle simulation along with the avatar information to compare. For example, the server compares User A's avatar (Knowledge 85, Concentration 90) with User B's avatar (Strength 75, Defense 60) and generates a simulation result. As a result of the battle simulation, a log is generated stating, for example, "User A's attack was effective and caused great damage to User B," and the result is "User A won."

[0132] The device receives the match result sent from the server and notifies the user. For example, it displays a message to the user saying "User A won."

[0133] The specific hardware and software used

[0134] Terminal: A device such as a smartphone or PC that inputs user information and communicates with the server.

[0135] Server: A high-performance computer or cloud service (e.g., AWS, Google Cloud) used for processing information and calling generative AI models.

[0136] Generative AI models: Uses generative AI models such as DALL-E and GPT-4.

[0137] This system allows users to intuitively create original avatars and enjoy playing against other users using those avatars. Using a generative AI model, it is possible to automatically generate avatars with rich individuality and appropriate ability scores and skills, and provides an advanced gaming experience through real-time battle simulations and results displays.

[0138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0139] System program processing flow

[0140] Step 1:

[0141] The user enters information such as name, age, hobbies, and gender into the application's input form. For example, the user might enter "Hanako Sato, 25 years old, reading, female." The application receives this information and this becomes input.

[0142] Step 2:

[0143] The device receives the information entered by the user and converts it into JSON format. For example, the input information is converted into data such as {"name":"Hanako Sato","age":25,"hobby":"reading","gender":"female"}. This is then sent to the server as output.

[0144] Step 3:

[0145] The server receives the JSON data sent from the device. The received data is analyzed to identify individual information such as name, age, hobbies, and gender. The analysis results are output.

[0146] Step 4:

[0147] The server calls a generative AI model (e.g., DALL-E, GPT-4) based on the analyzed information. The prompt used at this time is in the form of, "Hanako Sato is 25 years old, female, and her hobby is reading. Please generate an avatar image that shows high knowledge and concentration based on this information." Sending this prompt to the generative AI model is the input, and the generation of an avatar image from the generative AI model is the output.

[0148] Step 5:

[0149] When the generated avatar image is returned to the server, the server assigns the avatar ability values ​​and skills, such as "Knowledge 85" and "Concentration 90." These ability values ​​and skills are stored in a database. This assigned information becomes the output.

[0150] Step 6:

[0151] The user selects an avatar created on the application and decides on an opponent. For example, they select "Yamada Taro." This opponent information is input.

[0152] Step 7:

[0153] The terminal sends information about the opponent selected by the user to the server. For example, the output would be "Yamada Taro, ability values: Strength 75, Defense 60."

[0154] Step 8:

[0155] The server receives information about the opponent and performs a battle simulation along with the avatar information of the opponent to be compared. In this battle, the server compares the ability values ​​and skills of User A's avatar with User B's avatar. The winner is determined based on this comparison. For example, a log such as "User A's attack was effective and caused great damage to User B" is generated.

[0156] Step 9:

[0157] The server generates a battle log based on the results of the battle simulation. The generated battle result, for example, "User A won," is output.

[0158] Step 10:

[0159] The terminal receives the match result sent from the server and displays it to the user. For example, it displays a message saying "User A won." This is the final output.

[0160] Through this series of processes, users can generate unique avatars based on input information and enjoy the results of matches against other users through battle simulations. By using a generative AI model, we can provide users with an intuitive and engaging gaming experience.

[0161] (Application example 1)

[0162] 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."

[0163] Conventional avatar generation systems were limited to avatar generation based on user information and battle simulations, limiting the means by which users could engage in virtual experiences using their own avatars. Furthermore, the user experience was not sufficiently enhanced, as no real-time try-on experience was provided in a virtual store. This meant that users were unable to try on items before purchasing, which was one of the reasons for the decline in purchasing motivation.

[0164] 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.

[0165] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for displaying the avatar image, its ability values, and skills to the user, means for conducting a match with another user, means for displaying the match results, means for conducting a virtual try-on based on the generated avatar image, and means for displaying the results of the virtual try-on. This allows users to virtually try on clothes using their own avatar in real time, thereby increasing purchasing motivation and improving the user experience.

[0166] The "user information input module" is a means for acquiring information such as name, age, hobbies, and gender input by the user.

[0167] A "server" is a central device that receives information sent by users and performs different processing based on it.

[0168] A "generative AI model" is an artificial intelligence model that generates avatar images based on user information.

[0169] An "avatar" is a virtual persona or character that is generated based on information entered by a user.

[0170] "Ability scores" are numerical representations of specific skills and characteristics given to an avatar.

[0171] "Skills" represent specific abilities or techniques that an avatar possesses.

[0172] "Virtual try-on" is a feature that allows you to try on items such as clothes and accessories on a virtual avatar.

[0173] "Virtual try-on results" are results that display the appearance and feedback of the item tried on by the avatar.

[0174] The "game battle module" is a means for a user to use a generated avatar to battle other users in a virtual space.

[0175] "Battle simulation" is the process of comparing the ability values ​​and skills of avatars and calculating the results of a hypothetical battle.

[0176] "Displaying battle results" is a means for providing the results of the battle simulation to the user.

[0177] The present invention is a system that uses a generative AI model to automatically create an avatar image based on information entered by a user and assigns appropriate ability scores and skills to the avatar. Furthermore, the system is equipped with a function that provides a fitting experience in a virtual store. Specific examples are described below.

[0178] Basic system configuration

[0179] This system mainly utilizes the following modules, hardware, and software.

[0180] 1. User information input module:

[0181] The user uses the device to input information such as name, age, hobbies, and gender. The input information is acquired by the device, converted into JSON format, and sent to the server.

[0182] 2. Generative AI Model:

[0183] The server receives the information sent from the device and generates an avatar image based on that information. The generative AI model generates the avatar image taking into account the user's characteristics such as age, gender, and hobbies. For example, if a user's hobby is "reading," it creates an avatar that is highly knowledgeable and focused.

[0184] 3. Attributes and Skills:

[0185] The generated avatar image is returned to the server, which then assigns the avatar ability values ​​such as "Knowledge 85" and "Concentration 90."

[0186] 4. Virtual Try-on Module:

[0187] Users can try on clothes and accessories in a virtual store using the generated avatar, using virtual avatar generation libraries such as MakeHuman and Unity to simulate the try-on experience in real time.

[0188] 5. Try-on result display:

[0189] The results of the virtual try-on are sent from the server to the device and displayed to the user, providing specific feedback such as "I tried on the red dress and it looks great on me."

[0190] Example

[0191] 1. Example user input:

[0192] Name: Hanako Sato

[0193] Age: 25

[0194] Hobbies: Reading

[0195] Gender: Female

[0196] 2. Avatar generation example:

[0197] A generative AI model creates an avatar with enhanced knowledge and focus, trying on muted shirts and black-framed glasses that match the user's hobbies.

[0198] 3. Virtual try-on example:

[0199] The user selects a red dress and has the avatar try it on. As a result, the server generates feedback such as "This dress looks great on you" and sends it to the terminal.

[0200] Example prompt sentence:

[0201] Name: Hanako Sato

[0202] Age: 25

[0203] Hobbies: Reading

[0204] Gender: Female

[0205] Avatar characteristics: Appearance of knowledgeable and focused, clothing that reflects reading

[0206] This allows users to have a more personalized virtual try-on experience based on their own personal information. It is also possible for the generated avatar to compete against other users, and the system is expected to be applicable to a variety of scenarios.

[0207] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0208] Step 1:

[0209] The user enters information such as name, age, hobbies, and gender using a device such as a smartphone or computer. The entered information is converted into JSON format.

[0210] Input: Name, age, hobbies, gender

[0211] Output: User information in JSON format

[0212] Example: A user enters "Hanako Sato, 25 years old, reading, female", which is converted to JSON format as {'name': 'Hanako Sato', 'age': 25, 'hobby': 'reading', 'gender': 'female'}.

[0213] Step 2:

[0214] The terminal sends the acquired user information in JSON format to the server.

[0215] Input: JSON data of user information

[0216] Output: Send data to the server

[0217] Example: JSON data containing user information is sent from the terminal to the server via a POST request.

[0218] Step 3:

[0219] The server calls a generative AI model based on the received user information and generates an avatar image.

[0220] Input: User information in JSON format

[0221] Output: Generated avatar image

[0222] Example: The server passes user information in JSON format to the generative AI model, and asks it to generate an avatar image. For example, the generative AI model creates a female avatar whose hobby is reading.

[0223] Step 4:

[0224] The server receives the avatar image generated by the generative AI model and assigns the avatar ability values ​​such as "Knowledge 85" and "Concentration 90."

[0225] Input: Generated avatar image

[0226] Output: Avatar image with ability scores

[0227] Example: The generated avatar image is assigned specific numerical values ​​such as knowledge and concentration.

[0228] Step 5:

[0229] The server transmits the generated avatar image, its ability values, and skills to the terminal, which then displays them to the user.

[0230] Input: Avatar image with ability values

[0231] Output: Display of avatar image and ability scores to the user

[0232] Example: The device displays the avatar image and ability values ​​received from the server on the screen.

[0233] Step 6:

[0234] Using the generated avatar, users can try on clothes and accessories in a virtual store.

[0235] Input: Generated avatar image

[0236] Output: Simulation results for virtual try-on

[0237] Example: You can have your avatar try on a red dress to see how it looks.

[0238] Step 7:

[0239] The server transmits the results of the virtual try-on to the terminal, which then displays the results to the user.

[0240] Input: Virtual try-on simulation results

[0241] Output: Display of fitting results to the user

[0242] Example: A user is shown a rating that a red dress looks good on the avatar.

[0243] Step 8:

[0244] When a user wishes to compete against another user, the server compares the ability values ​​and skills of the avatars of both users and simulates a battle.

[0245] Input: Opponent information, avatar ability values, skills

[0246] Output: Match result log

[0247] Example: User A's avatar plays against User B's avatar, and the result is generated as a log in the format "User A won."

[0248] Step 9:

[0249] The server transmits the results of the match to the terminal, and the terminal displays the results to the user.

[0250] Input: Match result log

[0251] Output: Display the match result to the user

[0252] Example: The match result "User A won" is displayed on the screen.

[0253] 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.

[0254] MODE FOR CARRYING OUT THE INVENTION

[0255] This invention is a system that uses a generative AI model to generate an avatar image based on information entered by a user and assigns ability scores and skills appropriate to the avatar. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to generate an avatar and adjust ability scores according to the user's emotional state. A specific embodiment of this system and the program processing are described below.

[0256] Basic system configuration

[0257] This system is broadly composed of the following modules:

[0258] 1. User information input module

[0259] 2. Emotion Engine Module

[0260] 3. Avatar Generation Module

[0261] 4. Game Battle Module

[0262] User information input module

[0263] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[0264] Emotion Engine Module

[0265] The device is equipped with a camera that captures the user's facial expressions in real time. The emotion engine module analyzes the user's emotions from the captured facial expressions. The information entered by the user and the emotion data obtained from the facial expressions are sent to the server. For example, if the user is smiling, the emotion engine analyzes it as "happiness" and sends the data to the server.

[0266] Avatar Generation Module

[0267] The server receives user information and emotion data sent from the device. Based on this information, it calls a generative AI model to generate an avatar image. The generative AI model generates the avatar image by taking into account the user's characteristics such as age, gender, hobbies, and emotions.

[0268] For example, if a user's hobby is "reading" and emotional data of "happiness" is sent, the generative AI model will create an avatar with high knowledge and concentration, and a positive facial expression. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[0269] Game Battle Module

[0270] The user can select a generated avatar and choose an opponent from the match list. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability scores and skills of both avatars, and simulates a match.

[0271] The simulation results are generated in the form of, for example, "User A's attack was effective and caused great damage to User B." Finally, the server generates the match results and sends them to the device. The device then displays the received match results to the user, notifying them, for example, "User A won."

[0272] This system allows users to create avatars that reflect their own emotional state and enjoy playing against other users. By combining it with an emotion engine, it is possible to provide a more realistic gaming experience in which the user's emotional state affects the game experience.

[0273] The processing flow will be explained below.

[0274] Step 1:

[0275] The user enters information such as name, age, hobbies, and gender into the application's input form. The user enters the required data into the form and presses the "Submit" button.

[0276] Step 2:

[0277] The terminal acquires the information entered by the user, converts it into JSON format, and sends it to the server as an HTTP request.

[0278] Step 3:

[0279] The camera on the device captures the user's facial expressions in real time and sends the captured images to the emotion engine.

[0280] Step 4:

[0281] The emotion engine analyzes the captured facial images to identify the user's emotional state. For example, a smile might be interpreted as "happiness," while a crease in the brow might be interpreted as "anger." The emotion data is then sent back to the device.

[0282] Step 5:

[0283] The device acquires the analyzed emotion data and sends it along with the user information to the server, where it is converted back into JSON format.

[0284] Step 6:

[0285] The server receives user information and emotion data in JSON format sent from the device, receives HTTP requests through the API endpoint, and converts the data into an internal data structure.

[0286] Step 7:

[0287] The server calls the generative AI model based on the received information, and passes the user information and emotion data to the generative AI model as parameters.

[0288] Step 8:

[0289] The generative AI model analyzes the input user information and emotional data and generates an avatar image based on this. For example, if a user's hobby is "reading" and the emotional data is "happiness," the model will create an avatar image that shows high knowledge and concentration, as well as a positive expression. The generated avatar image is then returned to the server.

[0290] Step 9:

[0291] The server receives the generated avatar image and assigns the corresponding ability scores and skills to the avatar image. These ability scores and skills are determined based on the user's hobbies and emotional data. For example, the avatar may be assigned "knowledge 85," "concentration 90," or "happiness 95."

[0292] Step 10:

[0293] The server sends avatar information, including assigned ability values ​​and skills, to the device. The avatar image and ability value / skill data are then collected and returned to the device in JSON format.

[0294] Step 11:

[0295] The terminal displays the avatar information received from the server to the user, who can visually check their own avatar image, its ability scores, and skills.

[0296] Step 12:

[0297] The user selects their own avatar and chooses an opponent from the match list. After selecting an opponent, the user presses the "Challenge" button.

[0298] Step 13:

[0299] The device sends information about the selected opponent to the server, including the avatar IDs and user IDs of both players, in JSON format.

[0300] Step 14:

[0301] The server receives the matching information and simulates the battle, comparing the ability values ​​and skills of the avatars of both players and simulating the battle based on a predefined algorithm.

[0302] Step 15:

[0303] The server generates the match results, creating a match log with details such as "User A's attack was effective and caused a lot of damage to User B," and then generates the final winner / loser result.

[0304] Step 16:

[0305] The server sends the generated match results to the device, formats the results in JSON format, and returns them to the device as an HTTP response.

[0306] Step 17:

[0307] The terminal displays the received match results to the user, who can receive a notification such as "User A won."

[0308] Example 2

[0309] 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."

[0310] Conventional systems could generate avatars based on basic information entered by the user (such as name, age, hobbies, and gender) and assign ability scores and skills, but they had the problem of not being able to generate avatars that reflected the user's emotional state or adjust ability scores. As a result, the user's emotional state was not reflected in the game experience, making it difficult to provide a more realistic feel.

[0311] 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.

[0312] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability scores and skills corresponding to the avatar image, means for displaying the avatar image, its ability scores, and skills to the user, means for capturing the user's facial expression, means for analyzing emotional data from the captured facial expression, means for transmitting the analyzed emotional data to the server, means for adjusting the ability scores and skills using the emotional data, means for conducting a match against another user, and means for displaying the match results. This enables the generation of an avatar and the adjustment of ability scores to reflect the user's emotional state, providing a more realistic experience.

[0313] "User information" refers to basic personal information such as name, age, hobbies, and gender that a user enters into an application.

[0314] A "terminal" is a device used by a user, and is a device for inputting and capturing information and transmitting and receiving data.

[0315] A "server" is a computer system that receives and processes data sent from a terminal.

[0316] A "generative AI model" is an artificial intelligence model for generating avatar images based on user information and emotional data.

[0317] An "avatar image" is visual data of a virtual character that represents a user and is created by a generative AI model.

[0318] "Ability score" is a numerical evaluation of a status given to an avatar, such as knowledge, concentration, happiness, etc.

[0319] A "skill" is an element that indicates a specific action or ability that is given to an avatar.

[0320] The "emotion engine module" is a software module that analyzes the user's facial expressions and identifies emotion data.

[0321] "Emotion data" is data that indicates the user's emotional state analyzed by the emotion engine module.

[0322] "Battle" means that the generated avatars virtually compete against each other based on their skills and ability values.

[0323] "Match results" refers to the result data such as win / loss and damage obtained from the match simulation.

[0324] This invention is a system that uses a generative AI model to generate an avatar image based on information and emotional data entered by a user, and assigns ability scores and skills appropriate to the avatar. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to generate an avatar and adjust its ability scores according to the user's emotional state. Specific embodiments of the invention are described in detail below.

[0325] Basic system configuration

[0326] This system is broadly composed of the following modules:

[0327] 1. User information input module

[0328] 2. Emotion Engine Module

[0329] 3. Avatar Generation Module

[0330] 4. Game Battle Module

[0331] User information input module

[0332] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[0333] Emotion Engine Module

[0334] The device is equipped with a camera that captures the user's facial expressions in real time. The emotion engine module analyzes the user's emotions from the captured facial expressions. The information entered by the user and the emotion data obtained from the facial expressions are sent to the server. For example, if the user is smiling, the emotion engine analyzes it as "happiness" and sends the data to the server.

[0335] Avatar Generation Module

[0336] The server receives user information and emotion data sent from the device. Based on this information, it calls a generative AI model to generate an avatar image. The generative AI model generates the avatar image by taking into account the user's characteristics such as age, gender, hobbies, and emotions.

[0337] For example, if a user's hobby is "reading" and emotional data of "happiness" is sent, the generative AI model will create an avatar with high knowledge and concentration, and a positive facial expression. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[0338] Game Battle Module

[0339] The user can select a generated avatar and choose an opponent from the match list. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability scores and skills of both avatars, and simulates a match.

[0340] The simulation results are generated in the form of, for example, "User A's attack was effective and caused great damage to User B." Finally, the server generates the match results and sends them to the device. The device then displays the received match results to the user, notifying them, for example, "User A won."

[0341] Specific examples

[0342] The user enters the following information:

[0343] Name: Hanako Sato

[0344] Age: 25

[0345] Hobbies: Reading

[0346] Gender: Female

[0347] The device converts this to JSON format and sends it to the server:

[0348] json

[0349] {

[0350] "Name": "Hanako Sato",

[0351] "age": "25 years old",

[0352] "Hobbies": "Reading",

[0353] "Gender": "Female"

[0354] }

[0355] Next, the user's smiling expression is captured by the device's camera. The emotion engine analyzes this expression and determines it as "happy." This data is also sent to the server:

[0356] json

[0357] {

[0358] "Emotion": "Happiness"

[0359] }

[0360] The server then calls the generative AI model based on the received data and generates an avatar, which is given knowledge of 85, concentration of 90, and happiness of 95.

[0361] When the user selects "User B" as their opponent, the device sends the following data to the server:

[0362] json

[0363] {

[0364] "Opponent": "User B"

[0365] }

[0366] The server performs a battle simulation, generates the results, and sends them to the device. The device then displays the results to the user, saying "User A won."

[0367] Prompt Sentence Examples

[0368] Here are some example prompts to input to a generative AI model:

[0369] "Generate the most suitable avatar based on the information (name, age, hobbies, gender) and emotional data (happiness, sadness, anger, etc.) entered by the user."

[0370] This system allows users to create avatars that reflect their own emotions and compete against other users. By utilizing the emotion engine, the user's emotional state directly affects the game experience, providing a greater sense of realism.

[0371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0372] System processing flow

[0373] Step 1: Enter your user information

[0374] explanation:

[0375] The user enters basic information such as name, age, hobbies, and gender into the application's input form.

[0376] input:

[0377] User information such as name, age, hobbies, and gender

[0378] output:

[0379] User-entered information

[0380] Step 2: Convert and send information

[0381] explanation:

[0382] The terminal acquires the information entered by the user, converts it into JSON format, and sends it to the server.

[0383] input:

[0384] User-entered information

[0385] output:

[0386] User information in JSON format

[0387] Specific behavior:

[0388] Convert the input "Hanako Sato, 25 years old, reading, female" into the following JSON format on the terminal:

[0389] json

[0390] {

[0391] "Name": "Hanako Sato",

[0392] "age": "25 years old",

[0393] "Hobbies": "Reading",

[0394] "Gender": "Female"

[0395] }

[0396] This data is sent to the server.

[0397] Step 3: Receiving and parsing by the server

[0398] explanation:

[0399] The server receives the user information in JSON format sent from the terminal.

[0400] input:

[0401] User information in JSON format

[0402] output:

[0403] User information analysis results

[0404] Step 4: Capture facial expressions

[0405] explanation:

[0406] The camera on the device captures the user's facial expressions in real time.

[0407] input:

[0408] User's facial expression

[0409] output:

[0410] Captured facial expression image data

[0411] Step 5: Analyze the sentiment data

[0412] explanation:

[0413] An emotion engine module analyzes the captured facial expressions and generates emotion data for the user.

[0414] input:

[0415] Facial image data

[0416] output:

[0417] Emotional data (e.g., "happiness")

[0418] Specific behavior:

[0419] If the user is smiling, the emotion engine will parse it as "happy" and generate the data in the following format:

[0420] json

[0421] {

[0422] "Emotion": "Happiness"

[0423] }

[0424] Step 6: Sending Emotion Data

[0425] explanation:

[0426] The device transmits the analyzed emotion data to the server.

[0427] input:

[0428] Emotional Data

[0429] output:

[0430] Emotion data sent to the server

[0431] Step 7: Invoke the generative AI model

[0432] explanation:

[0433] The server calls the generative AI model based on the received user information and emotion data.

[0434] input:

[0435] User information and emotional data

[0436] output:

[0437] Executing a generative AI model by inputting a prompt

[0438] Step 8: Generate Avatar Images

[0439] explanation:

[0440] The generative AI model generates an avatar image based on the prompt text.

[0441] input:

[0442] Prompt sentence, user information, emotion data

[0443] output:

[0444] Generated avatar image

[0445] Specific behavior:

[0446] Enter the following prompt into the generative AI model:

[0447] "Generate the most suitable avatar based on the information (name, age, hobbies, gender) and emotional data (happiness, sadness, anger, etc.) entered by the user."

[0448] Step 9: Adding Avatar Ability Scores

[0449] explanation:

[0450] The server assigns the generated avatar ability values ​​such as "Knowledge 85," "Concentration 90," and "Happiness 95."

[0451] input:

[0452] Generated avatar image

[0453] output:

[0454] Avatar with ability scores

[0455] Step 10: Choose your avatar and opponent

[0456] explanation:

[0457] The user selects a generated avatar and chooses an opponent from the match list.

[0458] input:

[0459] Avatar with ability scores

[0460] output:

[0461] Selected Opponents

[0462] Specific behavior:

[0463] The user uses the generated avatar to select "User B" as an opponent.

[0464] Step 11: Send Opponent Information

[0465] explanation:

[0466] The terminal transmits information about the opponent selected by the user to the server.

[0467] input:

[0468] Opponent Information

[0469] output:

[0470] Opponent information sent to the server

[0471] Specific behavior:

[0472] The device sends the following data to the server:

[0473] json

[0474] {

[0475] "Opponent": "User B"

[0476] }

[0477] Step 12: Run a match simulation

[0478] explanation:

[0479] The server receives information about the opponent, compares the ability values ​​and skills of both avatars, and simulates the match.

[0480] input:

[0481] Avatar ability scores and opponent information

[0482] output:

[0483] Battle simulation results

[0484] Step 13: Generate and send match results

[0485] explanation:

[0486] The server generates the results of the battle simulation in JSON format and sends them to the device.

[0487] input:

[0488] Battle simulation results

[0489] output:

[0490] Match results in JSON format

[0491] Specific behavior:

[0492] The server generates the result: "User A's attack was effective and caused a lot of damage to User B. User A wins."

[0493] Step 14: Viewing Match Results

[0494] explanation:

[0495] The terminal displays the received match results to the user and notifies the user, such as "User A won."

[0496] input:

[0497] Match results in JSON format

[0498] output:

[0499] Results displayed to the user

[0500] Specific behavior:

[0501] The device displays the message "User A has won" to the user.

[0502] The above is the processing flow and specific steps of this system's program.

[0503] (Application example 2)

[0504] 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."

[0505] Conventional avatar generation systems rely solely on user information, making it difficult to generate personalized avatars that reflect the user's real-time emotional state. Furthermore, in virtual shopping experiences, they are unable to recommend products based on the user's emotions. Therefore, there is a need for a method to improve the quality of the shopping experience.

[0506] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring information such as the name, age, hobbies, and gender input by the user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for adjusting the avatar's ability values ​​and skills using an emotion engine that analyzes the user's emotions, means for displaying the avatar image, its ability values, and skills to the user, means for conducting a battle with other users, means for displaying the battle results, and means for recommending products in a virtual store based on the user's emotions. This makes it possible to generate an avatar that reflects the user's emotional state, improving the quality of the battle and shopping experience.

[0507] "User information" is information about a user's personal information, such as the user's name, age, hobbies, and gender, that is obtained by the application.

[0508] An "emotion engine" refers to technology or software that analyzes a user's facial expressions and behavior to detect their emotional state.

[0509] "Generative AI model" refers to an artificial intelligence algorithm that generates high-quality avatar images based on user information and emotional data.

[0510] "Avatar image" refers to a character image that reflects the user's characteristics and is generated by a generative AI model.

[0511] "Ability scores" are numerical representations of specific characteristics or status given to an avatar.

[0512] "Skills" refer to specific techniques or abilities that an avatar possesses and are used in battles and other actions.

[0513] "Virtual Store" refers to a virtual store where users can browse and purchase products via the Internet.

[0514] "Product recommendation" refers to suggesting appropriate products to a user based on the user's past behavior and current emotional state.

[0515] "Competition" refers to an activity in which generated avatars compete against each other in simulation or real time.

[0516] "Match results" refers to the information on victory or defeat and results that is displayed after avatars have competed against each other.

[0517] In this invention, a system is constructed that generates an avatar image and its ability values ​​and skills based on information and emotional state input by a user, and uses these to provide a personalized shopping experience in a virtual store.

[0518] First, the device acquires information such as the user's name, age, hobbies, and gender, which is then converted into JSON format and sent to the server.

[0519] The device captures the user's facial expressions through the camera. The emotion engine analyzes the user's emotions from the captured facial expressions and generates emotion data such as "happiness" or "sadness." This emotion data is also sent to the server.

[0520] The server receives user information and emotion data sent from the device. Using this information, the server invokes a generative AI model to generate an avatar image that reflects the user's characteristics. The generative AI model uses technologies such as Stable Diffusion and Midjourney.

[0521] The generated avatar image is returned to the server, and the avatar is given ability scores and skills such as "knowledge" and "concentration." This allows the ability scores to be adjusted according to the user's emotions.

[0522] Next, the user shops in the virtual store through the generated avatar. The server uses the user's emotional data to recommend appropriate products. This product recommendation is also performed by the server, providing the user with an optimal shopping experience.

[0523] For example, if a user enters information such as "Hanako Sato, 25 years old, reading, female" and smiles at the camera, the emotion engine will interpret this as "happiness." The generative AI model will generate an avatar with high knowledge and concentration, and a positive expression. This avatar will be given ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[0524] The system of this invention makes it possible to generate an avatar that reflects the user's emotional state and to recommend products based on that avatar, thereby improving the quality of the shopping experience in a virtual store.

[0525] Examples of prompts are:

[0526] "Create an avatar based on the following user information: {'Name': 'Hanako Sato', 'Age': 25, 'Hobbies': 'Reading', 'Gender': 'Female'}, Emotion: 'Happiness'. Give the avatar a costume that is easy to read and the ability scores of Knowledge 85, Concentration 90, and Happiness 95."

[0527] By inputting this prompt into a generative AI model, an avatar that best suits the user can be created.

[0528] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0529] Step 1:

[0530] The user inputs information such as name, age, hobbies, and gender into the device. The input data is converted to JSON format by the device. This data is sent to the server as user information. The input here is the user's personal information, and the output is user information in JSON format.

[0531] Step 2:

[0532] The device's camera captures the user's facial expression. The captured image data is sent to the emotion engine. The emotion engine analyzes the image data and recognizes the user's emotion. The input in this step is the image data, and the output is the analyzed emotion data.

[0533] Step 3:

[0534] The device transmits the captured emotion data to the server, which receives the transmitted user information and emotion data and integrates this data. The input is the user information and emotion data, and the output is the integrated dataset.

[0535] Step 4:

[0536] The server uses the integrated dataset to call the generative AI model to generate a prompt. The generated prompt sentence is input to the AI ​​model to generate an avatar image. The input is the prompt sentence, and the output is the generated avatar image.

[0537] Step 5:

[0538] The server receives the generated avatar image and assigns appropriate ability scores and skills to the avatar. These ability scores and skills are determined based on the user's personal information and emotional data. The input is the avatar image and user data, and the output is an avatar with the assigned ability scores and skills.

[0539] Step 6:

[0540] The server sends an avatar with assigned ability scores and skills to the device. The device displays this avatar to the user, who can then customize it. The input is the avatar with assigned ability scores and skills, and the output is the avatar displayed to the user.

[0541] Step 7:

[0542] The user receives product recommendations in a virtual store using an avatar. The server recommends optimal products based on the user's emotional data. The input is the emotional data and the avatar, and the output is a list of recommended products.

[0543] Step 8:

[0544] The user browses and purchases the recommended products in the virtual store. The purchase data is sent to the server, which then provides the products to the user. The input is a list of recommended products, and the output is information about the purchased products.

[0545] This allows users to enjoy a more personalized shopping experience through avatars that reflect their emotional state.

[0546] 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.

[0547] 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.

[0548] 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.

[0549] [Second embodiment]

[0550] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0551] 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.

[0552] 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).

[0553] 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.

[0554] 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.

[0555] 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).

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] 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."

[0562] MODE FOR CARRYING OUT THE INVENTION

[0563] This invention is a system that uses a generative AI model to automatically generate an avatar image based on information entered by a user and assigns ability scores and skills appropriate to the avatar. Specific embodiments of the system and program processing are described here.

[0564] Basic system configuration

[0565] This system is broadly composed of the following three modules:

[0566] 1. User information input module

[0567] 2. Avatar Generation Module

[0568] 3. Game Battle Module

[0569] User information input module

[0570] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[0571] Avatar Generation Module

[0572] The server receives user information sent from the device. Based on this information, the server invokes a generative AI model to generate an avatar image. The generative AI model generates the avatar image taking into account the user's characteristics such as age, gender, and hobbies.

[0573] For example, if a user's hobby is "reading," the generative AI model will create an avatar with high knowledge and concentration. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "Knowledge 85" and "Concentration 90."

[0574] Game Battle Module

[0575] The user can select a generated avatar and choose an opponent. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability values ​​and skills of both avatars, and simulates the battle. The simulation results are generated as a log in the form of, for example, "User A's attack was effective and caused great damage to User B."

[0576] Finally, the server generates the match results and sends them to the device. The device displays the received match results to the user, notifying them, for example, "User A won."

[0577] In this way, this system allows users to easily input their own information and intuitively generate an original avatar using a generative AI model. They can then use that avatar to compete against other users and enjoy the results. This allows users to enjoy a sophisticated gaming experience without any programming knowledge.

[0578] The processing flow will be explained below.

[0579] Step 1:

[0580] The user enters information such as name, age, hobbies, and gender into the application's input form. The user enters the required data into the form and presses the "Submit" button.

[0581] Step 2:

[0582] The terminal receives the information entered by the user, converts it into JSON format, and sends it to the server as an HTTP request.

[0583] Step 3:

[0584] The server receives the user information in JSON format sent from the device. It receives the HTTP request through the API endpoint, parses the JSON data, and converts it into an internal data structure.

[0585] Step 4:

[0586] The server calls the generative AI model based on the received user information, and passes the user information to the generative AI model as a parameter.

[0587] Step 5:

[0588] The generative AI model analyzes the input user information and generates an avatar image based on characteristics such as age, gender, and hobbies. The generated avatar image is then returned to the server.

[0589] Step 6:

[0590] The server receives the generated avatar image and assigns the corresponding ability scores and skills to the avatar image. These ability scores and skills are calculated based on predefined rules.

[0591] Step 7:

[0592] The server sends avatar information, including assigned ability values ​​and skills, to the device. The avatar image and ability value / skill data are then collected and returned to the device in JSON format.

[0593] Step 8:

[0594] The device displays the avatar information received from the server, allowing users to visually check their own avatar image, as well as their ability scores and skills.

[0595] Step 9:

[0596] The user selects their own avatar and chooses an opponent from the match list. After selecting an opponent, the user presses the "Challenge" button.

[0597] Step 10:

[0598] The device sends information about the selected opponent to the server, including the avatar IDs and user IDs of both players, in JSON format.

[0599] Step 11:

[0600] The server receives the matching information and simulates the battle, comparing the ability values ​​and skills of the avatars of both players and simulating the battle based on a predefined algorithm.

[0601] Step 12:

[0602] The server generates the match results, creating a match log with details such as "User A's attack was effective and caused a lot of damage to User B." It also generates the final victory or defeat result.

[0603] Step 13:

[0604] The server sends the generated match results to the device, formats the results in JSON format, and returns them to the device as an HTTP response.

[0605] Step 14:

[0606] The terminal displays the received match results to the user, who can receive a notification such as "User A won."

[0607] Example 1

[0608] 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."

[0609] Conventional avatar generation systems have had problems in that it is difficult to generate a unique avatar image based on information entered by the user and to assign appropriate ability scores and skills to that avatar. Furthermore, when playing against other users using the generated avatar, it is difficult to display the results of the match in real time.

[0610] 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.

[0611] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for converting the acquired information into a data format and transmitting the data to the server, means for analyzing the information received by the server, means for generating an avatar image by calling a generation AI model based on the analyzed information, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for displaying the avatar image, its ability values, and skills to the user, means for the user to select an opponent, means for transmitting information about the selected opponent to the server, means for the server to receive the opponent information and perform a battle simulation, and means for generating and displaying the battle results. This allows intuitive and attractive avatar images to be generated based on user information, and enables users to enjoy battles with other users in real time using the avatars.

[0612] In this invention, the term "user" refers to a person who uses the system.

[0613] "Terminal" refers to a device that a user inputs information into and communicates with a server. Examples include smartphones and personal computers.

[0614] "Server" refers to a high-performance computer or cloud service that performs central processing such as receiving and analyzing data, calling generative AI models, and conducting battle simulations.

[0615] "Generative AI models" refer to artificial intelligence models that generate avatar images based on user information. Examples include DALL-E and GPT-4.

[0616] "Prompt sentence" refers to the instruction sentence provided to the generative AI model when generating an avatar image.

[0617] "Avatar image" refers to an image of a virtual person or character generated by a generative AI model based on user information.

[0618] "Ability scores" refer to the numerical characteristics or skills given to an avatar, such as knowledge or concentration.

[0619] "Skills" refer to specific abilities or special techniques given to an avatar.

[0620] "Battle simulation" refers to the process of comparing the ability scores and skills of avatars selected by multiple users and virtually competing against each other.

[0621] "Match result" refers to the win / loss between users and other result information generated as a result of the match simulation.

[0622] "Means of obtaining information" refers to the function of the system receiving information such as name, age, hobbies, and gender entered by the user.

[0623] "Means for transmitting information" refers to the function of transferring acquired information to a server via a network.

[0624] "Means for receiving information" refers to the function of the server to receive information sent from the terminal.

[0625] "Means for parsing information" refers to the process by which the server breaks down and understands the user information it receives into individual data elements.

[0626] "Means for generating images" refers to the process of using a generative AI model to create an avatar image based on user information.

[0627] "Means for receiving images" refers to the function by which the server receives avatar images generated from the generative AI model.

[0628] "Means of assigning ability values ​​and skills" refers to the process of assigning specific characteristics and special moves to the generated avatar image.

[0629] "Means for displaying images" refers to the function of displaying the generated avatar image and its ability values ​​and skills on the user's device.

[0630] "Means for selecting an opponent" refers to a function that allows a user to select another user's avatar and designate it as an opponent.

[0631] "Means for transmitting opponent information" refers to a function for transmitting information about a selected opponent to the server.

[0632] "Means for performing battle simulation" refers to a function for conducting a virtual battle by comparing the ability values ​​and skills of each avatar based on the opponent information received by the server.

[0633] The "means for generating a match result" refers to a process for compiling information such as wins and losses between users based on the results of the match simulation.

[0634] "Means for displaying battle results" refers to a function for displaying the generated battle results on the user's terminal.

[0635] MODE FOR CARRYING OUT THE INVENTION

[0636] This system uses a generative AI model to automatically generate an avatar image based on information entered by the user, and assigns appropriate ability scores and skills to the avatar.It also has the ability to use the generated avatar to compete against other users and display the results of the competition in real time.

[0637] Basic system configuration

[0638] This system is broadly composed of the following three modules:

[0639] 1. User information input module

[0640] 2. Avatar Generation Module

[0641] 3. Game Battle Module

[0642] User information input module

[0643] The user enters information such as name, age, hobbies, and gender into the application's input form. For example, if the user enters "Hanako Sato, 25 years old, reading, female," each piece of information is entered appropriately into the form.

[0644] The device receives the information entered by the user and converts it into JSON format. For example, the input information is converted into the format {"name":"Hanako Sato","age":25,"hobby":"reading","gender":"female"}. Then, this JSON data is sent to the server.

[0645] Avatar Generation Module

[0646] The server receives and analyzes the JSON data sent from the device, identifying individual information (name, age, hobbies, gender).

[0647] The server calls a generative AI model (e.g., DALL-E or GPT-4) based on the analyzed information. The prompt used here is in the format, "Hanako Sato is 25 years old, female, and her hobby is reading. Please generate an avatar image that shows high knowledge and concentration based on this information."

[0648] The generative AI model generates an avatar image based on this prompt. After the generated avatar image is returned to the server, the server assigns the avatar ability scores and skills, such as "Knowledge 85" and "Concentration 90."

[0649] Game Battle Module

[0650] The user can select the generated avatar and choose an opponent. For example, if the user selects "Yamada Taro" from among the other candidates, the selection is complete.

[0651] The device sends information about the opponent selected by the user to the server. For example, information such as "Yamada Taro, ability values: Strength 75, Defense 60" is sent.

[0652] The server receives information about the opponent and performs a battle simulation along with the avatar information to compare. For example, the server compares User A's avatar (Knowledge 85, Concentration 90) with User B's avatar (Strength 75, Defense 60) and generates a simulation result. As a result of the battle simulation, a log is generated stating, for example, "User A's attack was effective and caused great damage to User B," and the result is "User A won."

[0653] The device receives the match result sent from the server and notifies the user. For example, it displays a message to the user saying "User A won."

[0654] The specific hardware and software used

[0655] Terminal: A device such as a smartphone or PC that inputs user information and communicates with the server.

[0656] Server: A high-performance computer or cloud service (e.g., AWS, Google Cloud) used for processing information and calling generative AI models.

[0657] Generative AI models: Uses generative AI models such as DALL-E and GPT-4.

[0658] This system allows users to intuitively create original avatars and enjoy playing against other users using those avatars. Using a generative AI model, it is possible to automatically generate avatars with rich individuality and appropriate ability scores and skills, and provides an advanced gaming experience through real-time battle simulations and results displays.

[0659] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0660] System program processing flow

[0661] Step 1:

[0662] The user enters information such as name, age, hobbies, and gender into the application's input form. For example, the user might enter "Hanako Sato, 25 years old, reading, female." The application receives this information and this becomes input.

[0663] Step 2:

[0664] The device receives the information entered by the user and converts it into JSON format. For example, the input information is converted into data such as {"name":"Hanako Sato","age":25,"hobby":"reading","gender":"female"}. This is then sent to the server as output.

[0665] Step 3:

[0666] The server receives the JSON data sent from the device. The received data is analyzed to identify individual information such as name, age, hobbies, and gender. The analysis results are output.

[0667] Step 4:

[0668] The server calls a generative AI model (e.g., DALL-E, GPT-4) based on the analyzed information. The prompt used at this time is in the form of, "Hanako Sato is 25 years old, female, and her hobby is reading. Please generate an avatar image that shows high knowledge and concentration based on this information." Sending this prompt to the generative AI model is the input, and the generation of an avatar image from the generative AI model is the output.

[0669] Step 5:

[0670] When the generated avatar image is returned to the server, the server assigns the avatar ability values ​​and skills, such as "Knowledge 85" and "Concentration 90." These ability values ​​and skills are stored in a database. This assigned information becomes the output.

[0671] Step 6:

[0672] The user selects an avatar created on the application and decides on an opponent. For example, they select "Yamada Taro." This opponent information is input.

[0673] Step 7:

[0674] The terminal sends information about the opponent selected by the user to the server. For example, the output would be "Yamada Taro, ability values: Strength 75, Defense 60."

[0675] Step 8:

[0676] The server receives information about the opponent and performs a battle simulation along with the avatar information of the opponent to be compared. In this battle, the server compares the ability values ​​and skills of User A's avatar with User B's avatar. The winner is determined based on this comparison. For example, a log such as "User A's attack was effective and caused great damage to User B" is generated.

[0677] Step 9:

[0678] The server generates a battle log based on the results of the battle simulation. The generated battle result, for example, "User A won," is output.

[0679] Step 10:

[0680] The terminal receives the match result sent from the server and displays it to the user. For example, it displays a message saying "User A won." This is the final output.

[0681] Through this series of processes, users can generate unique avatars based on input information and enjoy the results of matches against other users through battle simulations. By using a generative AI model, we can provide users with an intuitive and engaging gaming experience.

[0682] (Application example 1)

[0683] 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."

[0684] Conventional avatar generation systems were limited to avatar generation based on user information and battle simulations, limiting the means by which users could engage in virtual experiences using their own avatars. Furthermore, the user experience was not sufficiently enhanced, as no real-time try-on experience was provided in a virtual store. This meant that users were unable to try on items before purchasing, which was one of the reasons for the decline in purchasing motivation.

[0685] 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.

[0686] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for displaying the avatar image, its ability values, and skills to the user, means for conducting a match with another user, means for displaying the match results, means for conducting a virtual try-on based on the generated avatar image, and means for displaying the results of the virtual try-on. This allows users to virtually try on clothes using their own avatar in real time, thereby increasing purchasing motivation and improving the user experience.

[0687] The "user information input module" is a means for acquiring information such as name, age, hobbies, and gender input by the user.

[0688] A "server" is a central device that receives information sent by users and performs different processing based on it.

[0689] A "generative AI model" is an artificial intelligence model that generates avatar images based on user information.

[0690] An "avatar" is a virtual persona or character that is generated based on information entered by a user.

[0691] "Ability scores" are numerical representations of specific skills and characteristics given to an avatar.

[0692] "Skills" represent specific abilities or techniques that an avatar possesses.

[0693] "Virtual try-on" is a feature that allows you to try on items such as clothes and accessories on a virtual avatar.

[0694] "Virtual try-on results" are results that display the appearance and feedback of the item tried on by the avatar.

[0695] The "game battle module" is a means for a user to use a generated avatar to battle other users in a virtual space.

[0696] "Battle simulation" is the process of comparing the ability values ​​and skills of avatars and calculating the results of a hypothetical battle.

[0697] "Displaying battle results" is a means for providing the results of the battle simulation to the user.

[0698] The present invention is a system that uses a generative AI model to automatically create an avatar image based on information entered by a user and assigns appropriate ability scores and skills to the avatar. Furthermore, the system is equipped with a function that provides a fitting experience in a virtual store. Specific examples are described below.

[0699] Basic system configuration

[0700] This system mainly utilizes the following modules, hardware, and software.

[0701] 1. User information input module:

[0702] The user uses the device to input information such as name, age, hobbies, and gender. The input information is acquired by the device, converted into JSON format, and sent to the server.

[0703] 2. Generative AI Model:

[0704] The server receives the information sent from the device and generates an avatar image based on that information. The generative AI model generates the avatar image taking into account the user's characteristics such as age, gender, and hobbies. For example, if a user's hobby is "reading," it creates an avatar that is highly knowledgeable and focused.

[0705] 3. Attributes and Skills:

[0706] The generated avatar image is returned to the server, which then assigns the avatar ability values ​​such as "Knowledge 85" and "Concentration 90."

[0707] 4. Virtual Try-on Module:

[0708] Users can try on clothes and accessories in a virtual store using the generated avatar, using virtual avatar generation libraries such as MakeHuman and Unity to simulate the try-on experience in real time.

[0709] 5. Try-on result display:

[0710] The results of the virtual try-on are sent from the server to the device and displayed to the user, providing specific feedback such as "I tried on the red dress and it looks great on me."

[0711] Example

[0712] 1. Example user input:

[0713] Name: Hanako Sato

[0714] Age: 25

[0715] Hobbies: Reading

[0716] Gender: Female

[0717] 2. Avatar generation example:

[0718] A generative AI model creates an avatar with enhanced knowledge and focus, trying on muted shirts and black-framed glasses that match the user's hobbies.

[0719] 3. Virtual try-on example:

[0720] The user selects a red dress and has the avatar try it on. As a result, the server generates feedback such as "This dress looks great on you" and sends it to the terminal.

[0721] Example prompt sentence:

[0722] Name: Hanako Sato

[0723] Age: 25

[0724] Hobbies: Reading

[0725] Gender: Female

[0726] Avatar characteristics: Appearance of knowledgeable and focused, clothing that reflects reading

[0727] This allows users to have a more personalized virtual try-on experience based on their own personal information. It is also possible for the generated avatar to compete against other users, and the system is expected to be applicable to a variety of scenarios.

[0728] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0729] Step 1:

[0730] The user enters information such as name, age, hobbies, and gender using a device such as a smartphone or computer. The entered information is converted into JSON format.

[0731] Input: Name, age, hobbies, gender

[0732] Output: User information in JSON format

[0733] Example: A user enters "Hanako Sato, 25 years old, reading, female", which is converted to JSON format as {'name': 'Hanako Sato', 'age': 25, 'hobby': 'reading', 'gender': 'female'}.

[0734] Step 2:

[0735] The terminal sends the acquired user information in JSON format to the server.

[0736] Input: JSON data of user information

[0737] Output: Send data to the server

[0738] Example: JSON data containing user information is sent from the terminal to the server via a POST request.

[0739] Step 3:

[0740] The server calls a generative AI model based on the received user information and generates an avatar image.

[0741] Input: User information in JSON format

[0742] Output: Generated avatar image

[0743] Example: The server passes user information in JSON format to the generative AI model, and asks it to generate an avatar image. For example, the generative AI model creates a female avatar whose hobby is reading.

[0744] Step 4:

[0745] The server receives the avatar image generated by the generative AI model and assigns the avatar ability values ​​such as "Knowledge 85" and "Concentration 90."

[0746] Input: Generated avatar image

[0747] Output: Avatar image with ability scores

[0748] Example: The generated avatar image is assigned specific numerical values ​​such as knowledge and concentration.

[0749] Step 5:

[0750] The server transmits the generated avatar image, its ability values, and skills to the terminal, which then displays them to the user.

[0751] Input: Avatar image with ability values

[0752] Output: Display of avatar image and ability scores to the user

[0753] Example: The device displays the avatar image and ability values ​​received from the server on the screen.

[0754] Step 6:

[0755] Using the generated avatar, users can try on clothes and accessories in a virtual store.

[0756] Input: Generated avatar image

[0757] Output: Simulation results for virtual try-on

[0758] Example: You can have your avatar try on a red dress to see how it looks.

[0759] Step 7:

[0760] The server transmits the results of the virtual try-on to the terminal, which then displays the results to the user.

[0761] Input: Virtual try-on simulation results

[0762] Output: Display of fitting results to the user

[0763] Example: A user is shown a rating that a red dress looks good on the avatar.

[0764] Step 8:

[0765] When a user wishes to compete against another user, the server compares the ability values ​​and skills of the avatars of both users and simulates a battle.

[0766] Input: Opponent information, avatar ability values, skills

[0767] Output: Match result log

[0768] Example: User A's avatar plays against User B's avatar, and the result is generated as a log in the format "User A won."

[0769] Step 9:

[0770] The server transmits the results of the match to the terminal, and the terminal displays the results to the user.

[0771] Input: Match result log

[0772] Output: Display the match result to the user

[0773] Example: The match result "User A won" is displayed on the screen.

[0774] 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.

[0775] MODE FOR CARRYING OUT THE INVENTION

[0776] This invention is a system that uses a generative AI model to generate an avatar image based on information entered by a user and assigns ability scores and skills appropriate to the avatar. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to generate an avatar and adjust ability scores according to the user's emotional state. A specific embodiment of this system and the program processing are described below.

[0777] Basic system configuration

[0778] This system is broadly composed of the following modules:

[0779] 1. User information input module

[0780] 2. Emotion Engine Module

[0781] 3. Avatar Generation Module

[0782] 4. Game Battle Module

[0783] User information input module

[0784] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[0785] Emotion Engine Module

[0786] The device is equipped with a camera that captures the user's facial expressions in real time. The emotion engine module analyzes the user's emotions from the captured facial expressions. The information entered by the user and the emotion data obtained from the facial expressions are sent to the server. For example, if the user is smiling, the emotion engine analyzes it as "happiness" and sends the data to the server.

[0787] Avatar Generation Module

[0788] The server receives user information and emotion data sent from the device. Based on this information, it calls a generative AI model to generate an avatar image. The generative AI model generates the avatar image by taking into account the user's characteristics such as age, gender, hobbies, and emotions.

[0789] For example, if a user's hobby is "reading" and emotional data of "happiness" is sent, the generative AI model will create an avatar with high knowledge and concentration, and a positive facial expression. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[0790] Game Battle Module

[0791] The user can select a generated avatar and choose an opponent from the match list. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability scores and skills of both avatars, and simulates a match.

[0792] The simulation results are generated in the form of, for example, "User A's attack was effective and caused great damage to User B." Finally, the server generates the match results and sends them to the device. The device then displays the received match results to the user, notifying them, for example, "User A won."

[0793] This system allows users to create avatars that reflect their own emotional state and enjoy playing against other users. By combining it with an emotion engine, it is possible to provide a more realistic gaming experience in which the user's emotional state affects the game experience.

[0794] The processing flow will be explained below.

[0795] Step 1:

[0796] The user enters information such as name, age, hobbies, and gender into the application's input form. The user enters the required data into the form and presses the "Submit" button.

[0797] Step 2:

[0798] The terminal acquires the information entered by the user, converts it into JSON format, and sends it to the server as an HTTP request.

[0799] Step 3:

[0800] The camera on the device captures the user's facial expressions in real time and sends the captured images to the emotion engine.

[0801] Step 4:

[0802] The emotion engine analyzes the captured facial images to identify the user's emotional state. For example, a smile might be interpreted as "happiness," while a crease in the brow might be interpreted as "anger." The emotion data is then sent back to the device.

[0803] Step 5:

[0804] The device acquires the analyzed emotion data and sends it along with the user information to the server, where it is converted back into JSON format.

[0805] Step 6:

[0806] The server receives user information and emotion data in JSON format sent from the device, receives HTTP requests through the API endpoint, and converts the data into an internal data structure.

[0807] Step 7:

[0808] The server calls the generative AI model based on the received information, and passes the user information and emotion data to the generative AI model as parameters.

[0809] Step 8:

[0810] The generative AI model analyzes the input user information and emotional data and generates an avatar image based on this. For example, if a user's hobby is "reading" and the emotional data is "happiness," the model will create an avatar image that shows high knowledge and concentration, as well as a positive expression. The generated avatar image is then returned to the server.

[0811] Step 9:

[0812] The server receives the generated avatar image and assigns the corresponding ability scores and skills to the avatar image. These ability scores and skills are determined based on the user's hobbies and emotional data. For example, the avatar may be assigned "knowledge 85," "concentration 90," or "happiness 95."

[0813] Step 10:

[0814] The server sends avatar information, including assigned ability values ​​and skills, to the device. The avatar image and ability value / skill data are then collected and returned to the device in JSON format.

[0815] Step 11:

[0816] The terminal displays the avatar information received from the server to the user, who can visually check their own avatar image, its ability scores, and skills.

[0817] Step 12:

[0818] The user selects their own avatar and chooses an opponent from the match list. After selecting an opponent, the user presses the "Challenge" button.

[0819] Step 13:

[0820] The device sends information about the selected opponent to the server, including the avatar IDs and user IDs of both players, in JSON format.

[0821] Step 14:

[0822] The server receives the matching information and simulates the battle, comparing the ability values ​​and skills of the avatars of both players and simulating the battle based on a predefined algorithm.

[0823] Step 15:

[0824] The server generates the match results, creating a match log with details such as "User A's attack was effective and caused a lot of damage to User B," and then generates the final winner / loser result.

[0825] Step 16:

[0826] The server sends the generated match results to the device, formats the results in JSON format, and returns them to the device as an HTTP response.

[0827] Step 17:

[0828] The terminal displays the received match results to the user, who can receive a notification such as "User A won."

[0829] Example 2

[0830] 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."

[0831] Conventional systems could generate avatars based on basic information entered by the user (such as name, age, hobbies, and gender) and assign ability scores and skills, but they had the problem of not being able to generate avatars that reflected the user's emotional state or adjust ability scores. As a result, the user's emotional state was not reflected in the game experience, making it difficult to provide a more realistic feel.

[0832] 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.

[0833] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability scores and skills corresponding to the avatar image, means for displaying the avatar image, its ability scores, and skills to the user, means for capturing the user's facial expression, means for analyzing emotional data from the captured facial expression, means for transmitting the analyzed emotional data to the server, means for adjusting the ability scores and skills using the emotional data, means for conducting a match against another user, and means for displaying the match results. This enables the generation of an avatar and the adjustment of ability scores to reflect the user's emotional state, providing a more realistic experience.

[0834] "User information" refers to basic personal information such as name, age, hobbies, and gender that a user enters into an application.

[0835] A "terminal" is a device used by a user, and is a device for inputting and capturing information and transmitting and receiving data.

[0836] A "server" is a computer system that receives and processes data sent from a terminal.

[0837] A "generative AI model" is an artificial intelligence model for generating avatar images based on user information and emotional data.

[0838] An "avatar image" is visual data of a virtual character that represents a user and is created by a generative AI model.

[0839] "Ability score" is a numerical evaluation of a status given to an avatar, such as knowledge, concentration, happiness, etc.

[0840] A "skill" is an element that indicates a specific action or ability that is given to an avatar.

[0841] The "emotion engine module" is a software module that analyzes the user's facial expressions and identifies emotion data.

[0842] "Emotion data" is data that indicates the user's emotional state analyzed by the emotion engine module.

[0843] "Battle" means that the generated avatars virtually compete against each other based on their skills and ability values.

[0844] "Match results" refers to the result data such as win / loss and damage obtained from the match simulation.

[0845] This invention is a system that uses a generative AI model to generate an avatar image based on information and emotional data entered by a user, and assigns ability scores and skills appropriate to the avatar. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to generate an avatar and adjust its ability scores according to the user's emotional state. Specific embodiments of the invention are described in detail below.

[0846] Basic system configuration

[0847] This system is broadly composed of the following modules:

[0848] 1. User information input module

[0849] 2. Emotion Engine Module

[0850] 3. Avatar Generation Module

[0851] 4. Game Battle Module

[0852] User information input module

[0853] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[0854] Emotion Engine Module

[0855] The device is equipped with a camera that captures the user's facial expressions in real time. The emotion engine module analyzes the user's emotions from the captured facial expressions. The information entered by the user and the emotion data obtained from the facial expressions are sent to the server. For example, if the user is smiling, the emotion engine analyzes it as "happiness" and sends the data to the server.

[0856] Avatar Generation Module

[0857] The server receives user information and emotion data sent from the device. Based on this information, it calls a generative AI model to generate an avatar image. The generative AI model generates the avatar image by taking into account the user's characteristics such as age, gender, hobbies, and emotions.

[0858] For example, if a user's hobby is "reading" and emotional data of "happiness" is sent, the generative AI model will create an avatar with high knowledge and concentration, and a positive facial expression. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[0859] Game Battle Module

[0860] The user can select a generated avatar and choose an opponent from the match list. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability scores and skills of both avatars, and simulates a match.

[0861] The simulation results are generated in the form of, for example, "User A's attack was effective and caused great damage to User B." Finally, the server generates the match results and sends them to the device. The device then displays the received match results to the user, notifying them, for example, "User A won."

[0862] Specific examples

[0863] The user enters the following information:

[0864] Name: Hanako Sato

[0865] Age: 25

[0866] Hobbies: Reading

[0867] Gender: Female

[0868] The device converts this to JSON format and sends it to the server:

[0869] json

[0870] {

[0871] "Name": "Hanako Sato",

[0872] "age": "25 years old",

[0873] "Hobbies": "Reading",

[0874] "Gender": "Female"

[0875] }

[0876] Next, the user's smiling expression is captured by the device's camera. The emotion engine analyzes this expression and determines it as "happy." This data is also sent to the server:

[0877] json

[0878] {

[0879] "Emotion": "Happiness"

[0880] }

[0881] The server then calls the generative AI model based on the received data and generates an avatar, which is given knowledge of 85, concentration of 90, and happiness of 95.

[0882] When the user selects "User B" as their opponent, the device sends the following data to the server:

[0883] json

[0884] {

[0885] "Opponent": "User B"

[0886] }

[0887] The server performs a battle simulation, generates the results, and sends them to the device. The device then displays the results to the user, saying "User A won."

[0888] Prompt Sentence Examples

[0889] Here are some example prompts to input to a generative AI model:

[0890] "Generate the most suitable avatar based on the information (name, age, hobbies, gender) and emotional data (happiness, sadness, anger, etc.) entered by the user."

[0891] This system allows users to create avatars that reflect their own emotions and compete against other users. By utilizing the emotion engine, the user's emotional state directly affects the game experience, providing a greater sense of realism.

[0892] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0893] System processing flow

[0894] Step 1: Enter your user information

[0895] explanation:

[0896] The user enters basic information such as name, age, hobbies, and gender into the application's input form.

[0897] input:

[0898] User information such as name, age, hobbies, and gender

[0899] output:

[0900] User-entered information

[0901] Step 2: Convert and send information

[0902] explanation:

[0903] The terminal acquires the information entered by the user, converts it into JSON format, and sends it to the server.

[0904] input:

[0905] User-entered information

[0906] output:

[0907] User information in JSON format

[0908] Specific behavior:

[0909] Convert the input "Hanako Sato, 25 years old, reading, female" into the following JSON format on the terminal:

[0910] json

[0911] {

[0912] "Name": "Hanako Sato",

[0913] "age": "25 years old",

[0914] "Hobbies": "Reading",

[0915] "Gender": "Female"

[0916] }

[0917] This data is sent to the server.

[0918] Step 3: Receiving and parsing by the server

[0919] explanation:

[0920] The server receives the user information in JSON format sent from the terminal.

[0921] input:

[0922] User information in JSON format

[0923] output:

[0924] User information analysis results

[0925] Step 4: Capture facial expressions

[0926] explanation:

[0927] The camera on the device captures the user's facial expressions in real time.

[0928] input:

[0929] User's facial expression

[0930] output:

[0931] Captured facial expression image data

[0932] Step 5: Analyze the sentiment data

[0933] explanation:

[0934] An emotion engine module analyzes the captured facial expressions and generates emotion data for the user.

[0935] input:

[0936] Facial image data

[0937] output:

[0938] Emotional data (e.g., "happiness")

[0939] Specific behavior:

[0940] If the user is smiling, the emotion engine will parse it as "happy" and generate the data in the following format:

[0941] json

[0942] {

[0943] "Emotion": "Happiness"

[0944] }

[0945] Step 6: Sending Emotion Data

[0946] explanation:

[0947] The device transmits the analyzed emotion data to the server.

[0948] input:

[0949] Emotional Data

[0950] output:

[0951] Emotion data sent to the server

[0952] Step 7: Invoke the generative AI model

[0953] explanation:

[0954] The server calls the generative AI model based on the received user information and emotion data.

[0955] input:

[0956] User information and emotional data

[0957] output:

[0958] Executing a generative AI model by inputting a prompt

[0959] Step 8: Generate Avatar Images

[0960] explanation:

[0961] The generative AI model generates an avatar image based on the prompt text.

[0962] input:

[0963] Prompt sentence, user information, emotion data

[0964] output:

[0965] Generated avatar image

[0966] Specific behavior:

[0967] Enter the following prompt into the generative AI model:

[0968] "Generate the most suitable avatar based on the information (name, age, hobbies, gender) and emotional data (happiness, sadness, anger, etc.) entered by the user."

[0969] Step 9: Adding Avatar Ability Scores

[0970] explanation:

[0971] The server assigns the generated avatar ability values ​​such as "Knowledge 85," "Concentration 90," and "Happiness 95."

[0972] input:

[0973] Generated avatar image

[0974] output:

[0975] Avatar with ability scores

[0976] Step 10: Choose your avatar and opponent

[0977] explanation:

[0978] The user selects a generated avatar and chooses an opponent from the match list.

[0979] input:

[0980] Avatar with ability scores

[0981] output:

[0982] Selected Opponents

[0983] Specific behavior:

[0984] The user uses the generated avatar to select "User B" as an opponent.

[0985] Step 11: Send Opponent Information

[0986] explanation:

[0987] The terminal transmits information about the opponent selected by the user to the server.

[0988] input:

[0989] Opponent Information

[0990] output:

[0991] Opponent information sent to the server

[0992] Specific behavior:

[0993] The device sends the following data to the server:

[0994] json

[0995] {

[0996] "Opponent": "User B"

[0997] }

[0998] Step 12: Run a match simulation

[0999] explanation:

[1000] The server receives information about the opponent, compares the ability values ​​and skills of both avatars, and simulates the match.

[1001] input:

[1002] Avatar ability scores and opponent information

[1003] output:

[1004] Battle simulation results

[1005] Step 13: Generate and send match results

[1006] explanation:

[1007] The server generates the results of the battle simulation in JSON format and sends them to the device.

[1008] input:

[1009] Battle simulation results

[1010] output:

[1011] Match results in JSON format

[1012] Specific behavior:

[1013] The server generates the result: "User A's attack was effective and caused a lot of damage to User B. User A wins."

[1014] Step 14: Viewing Match Results

[1015] explanation:

[1016] The terminal displays the received match results to the user and notifies the user, such as "User A won."

[1017] input:

[1018] Match results in JSON format

[1019] output:

[1020] Results displayed to the user

[1021] Specific behavior:

[1022] The device displays the message "User A has won" to the user.

[1023] The above is the processing flow and specific steps of this system's program.

[1024] (Application example 2)

[1025] 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."

[1026] Conventional avatar generation systems rely solely on user information, making it difficult to generate personalized avatars that reflect the user's real-time emotional state. Furthermore, in virtual shopping experiences, they are unable to recommend products based on the user's emotions. Therefore, there is a need for a method to improve the quality of the shopping experience.

[1027] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring information such as the name, age, hobbies, and gender input by the user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for adjusting the avatar's ability values ​​and skills using an emotion engine that analyzes the user's emotions, means for displaying the avatar image, its ability values, and skills to the user, means for conducting a battle with other users, means for displaying the battle results, and means for recommending products in a virtual store based on the user's emotions. This makes it possible to generate an avatar that reflects the user's emotional state, improving the quality of the battle and shopping experience.

[1028] "User information" is information about a user's personal information, such as the user's name, age, hobbies, and gender, that is obtained by the application.

[1029] An "emotion engine" refers to technology or software that analyzes a user's facial expressions and behavior to detect their emotional state.

[1030] "Generative AI model" refers to an artificial intelligence algorithm that generates high-quality avatar images based on user information and emotional data.

[1031] "Avatar image" refers to a character image that reflects the user's characteristics and is generated by a generative AI model.

[1032] "Ability scores" are numerical representations of specific characteristics or status given to an avatar.

[1033] "Skills" refer to specific techniques or abilities that an avatar possesses and are used in battles and other actions.

[1034] "Virtual Store" refers to a virtual store where users can browse and purchase products via the Internet.

[1035] "Product recommendation" refers to suggesting appropriate products to a user based on the user's past behavior and current emotional state.

[1036] "Competition" refers to an activity in which generated avatars compete against each other in simulation or real time.

[1037] "Match results" refers to the information on victory or defeat and results that is displayed after avatars have competed against each other.

[1038] In this invention, a system is constructed that generates an avatar image and its ability values ​​and skills based on information and emotional state input by a user, and uses these to provide a personalized shopping experience in a virtual store.

[1039] First, the device acquires information such as the user's name, age, hobbies, and gender, which is then converted into JSON format and sent to the server.

[1040] The device captures the user's facial expressions through the camera. The emotion engine analyzes the user's emotions from the captured facial expressions and generates emotion data such as "happiness" or "sadness." This emotion data is also sent to the server.

[1041] The server receives user information and emotion data sent from the device. Using this information, the server invokes a generative AI model to generate an avatar image that reflects the user's characteristics. The generative AI model uses technologies such as Stable Diffusion and Midjourney.

[1042] The generated avatar image is returned to the server, and the avatar is given ability scores and skills such as "knowledge" and "concentration." This allows the ability scores to be adjusted according to the user's emotions.

[1043] Next, the user shops in the virtual store through the generated avatar. The server uses the user's emotional data to recommend appropriate products. This product recommendation is also performed by the server, providing the user with an optimal shopping experience.

[1044] For example, if a user enters information such as "Hanako Sato, 25 years old, reading, female" and smiles at the camera, the emotion engine will interpret this as "happiness." The generative AI model will generate an avatar with high knowledge and concentration, and a positive expression. This avatar will be given ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[1045] The system of this invention makes it possible to generate an avatar that reflects the user's emotional state and to recommend products based on that avatar, thereby improving the quality of the shopping experience in a virtual store.

[1046] Examples of prompts are:

[1047] "Create an avatar based on the following user information: {'Name': 'Hanako Sato', 'Age': 25, 'Hobbies': 'Reading', 'Gender': 'Female'}, Emotion: 'Happiness'. Give the avatar a costume that is easy to read and the ability scores of Knowledge 85, Concentration 90, and Happiness 95."

[1048] By inputting this prompt into a generative AI model, an avatar that best suits the user can be created.

[1049] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1050] Step 1:

[1051] The user inputs information such as name, age, hobbies, and gender into the device. The input data is converted to JSON format by the device. This data is sent to the server as user information. The input here is the user's personal information, and the output is user information in JSON format.

[1052] Step 2:

[1053] The device's camera captures the user's facial expression. The captured image data is sent to the emotion engine. The emotion engine analyzes the image data and recognizes the user's emotion. The input in this step is the image data, and the output is the analyzed emotion data.

[1054] Step 3:

[1055] The device transmits the captured emotion data to the server, which receives the transmitted user information and emotion data and integrates this data. The input is the user information and emotion data, and the output is the integrated dataset.

[1056] Step 4:

[1057] The server uses the integrated dataset to call the generative AI model to generate a prompt. The generated prompt sentence is input to the AI ​​model to generate an avatar image. The input is the prompt sentence, and the output is the generated avatar image.

[1058] Step 5:

[1059] The server receives the generated avatar image and assigns appropriate ability scores and skills to the avatar. These ability scores and skills are determined based on the user's personal information and emotional data. The input is the avatar image and user data, and the output is an avatar with the assigned ability scores and skills.

[1060] Step 6:

[1061] The server sends an avatar with assigned ability scores and skills to the device. The device displays this avatar to the user, who can then customize it. The input is the avatar with assigned ability scores and skills, and the output is the avatar displayed to the user.

[1062] Step 7:

[1063] The user receives product recommendations in a virtual store using an avatar. The server recommends optimal products based on the user's emotional data. The input is the emotional data and the avatar, and the output is a list of recommended products.

[1064] Step 8:

[1065] The user browses and purchases the recommended products in the virtual store. The purchase data is sent to the server, which then provides the products to the user. The input is a list of recommended products, and the output is information about the purchased products.

[1066] This allows users to enjoy a more personalized shopping experience through avatars that reflect their emotional state.

[1067] 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.

[1068] 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.

[1069] 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.

[1070] [Third embodiment]

[1071] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1072] 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.

[1073] 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).

[1074] 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.

[1075] 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.

[1076] 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).

[1077] 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.

[1078] 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.

[1079] 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.

[1080] 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.

[1081] 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.

[1082] 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."

[1083] MODE FOR CARRYING OUT THE INVENTION

[1084] This invention is a system that uses a generative AI model to automatically generate an avatar image based on information entered by a user and assigns ability scores and skills appropriate to the avatar. Specific embodiments of the system and program processing are described here.

[1085] Basic system configuration

[1086] This system is broadly composed of the following three modules:

[1087] 1. User information input module

[1088] 2. Avatar Generation Module

[1089] 3. Game Battle Module

[1090] User information input module

[1091] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[1092] Avatar Generation Module

[1093] The server receives user information sent from the device. Based on this information, the server invokes a generative AI model to generate an avatar image. The generative AI model generates the avatar image taking into account the user's characteristics such as age, gender, and hobbies.

[1094] For example, if a user's hobby is "reading," the generative AI model will create an avatar with high knowledge and concentration. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "Knowledge 85" and "Concentration 90."

[1095] Game Battle Module

[1096] The user can select a generated avatar and choose an opponent. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability values ​​and skills of both avatars, and simulates the battle. The simulation results are generated as a log in the form of, for example, "User A's attack was effective and caused great damage to User B."

[1097] Finally, the server generates the match results and sends them to the device. The device displays the received match results to the user, notifying them, for example, "User A won."

[1098] In this way, this system allows users to easily input their own information and intuitively generate an original avatar using a generative AI model. They can then use that avatar to compete against other users and enjoy the results. This allows users to enjoy a sophisticated gaming experience without any programming knowledge.

[1099] The processing flow will be explained below.

[1100] Step 1:

[1101] The user enters information such as name, age, hobbies, and gender into the application's input form. The user enters the required data into the form and presses the "Submit" button.

[1102] Step 2:

[1103] The terminal receives the information entered by the user, converts it into JSON format, and sends it to the server as an HTTP request.

[1104] Step 3:

[1105] The server receives the user information in JSON format sent from the device. It receives the HTTP request through the API endpoint, parses the JSON data, and converts it into an internal data structure.

[1106] Step 4:

[1107] The server calls the generative AI model based on the received user information, and passes the user information to the generative AI model as a parameter.

[1108] Step 5:

[1109] The generative AI model analyzes the input user information and generates an avatar image based on characteristics such as age, gender, and hobbies. The generated avatar image is then returned to the server.

[1110] Step 6:

[1111] The server receives the generated avatar image and assigns the corresponding ability scores and skills to the avatar image. These ability scores and skills are calculated based on predefined rules.

[1112] Step 7:

[1113] The server sends avatar information, including assigned ability values ​​and skills, to the device. The avatar image and ability value / skill data are then collected and returned to the device in JSON format.

[1114] Step 8:

[1115] The device displays the avatar information received from the server, allowing users to visually check their own avatar image, as well as their ability scores and skills.

[1116] Step 9:

[1117] The user selects their own avatar and chooses an opponent from the match list. After selecting an opponent, the user presses the "Challenge" button.

[1118] Step 10:

[1119] The device sends information about the selected opponent to the server, including the avatar IDs and user IDs of both players, in JSON format.

[1120] Step 11:

[1121] The server receives the matching information and simulates the battle, comparing the ability values ​​and skills of the avatars of both players and simulating the battle based on a predefined algorithm.

[1122] Step 12:

[1123] The server generates the match results, creating a match log with details such as "User A's attack was effective and caused a lot of damage to User B." It also generates the final victory or defeat result.

[1124] Step 13:

[1125] The server sends the generated match results to the device, formats the results in JSON format, and returns them to the device as an HTTP response.

[1126] Step 14:

[1127] The terminal displays the received match results to the user, who can receive a notification such as "User A won."

[1128] Example 1

[1129] 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."

[1130] Conventional avatar generation systems have had problems in that it is difficult to generate a unique avatar image based on information entered by the user and to assign appropriate ability scores and skills to that avatar. Furthermore, when playing against other users using the generated avatar, it is difficult to display the results of the match in real time.

[1131] 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.

[1132] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for converting the acquired information into a data format and transmitting the data to the server, means for analyzing the information received by the server, means for generating an avatar image by calling a generation AI model based on the analyzed information, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for displaying the avatar image, its ability values, and skills to the user, means for the user to select an opponent, means for transmitting information about the selected opponent to the server, means for the server to receive the opponent information and perform a battle simulation, and means for generating and displaying the battle results. This allows intuitive and attractive avatar images to be generated based on user information, and enables users to enjoy battles with other users in real time using the avatars.

[1133] In this invention, the term "user" refers to a person who uses the system.

[1134] "Terminal" refers to a device that a user inputs information into and communicates with a server. Examples include smartphones and personal computers.

[1135] "Server" refers to a high-performance computer or cloud service that performs central processing such as receiving and analyzing data, calling generative AI models, and conducting battle simulations.

[1136] "Generative AI models" refer to artificial intelligence models that generate avatar images based on user information. Examples include DALL-E and GPT-4.

[1137] "Prompt sentence" refers to the instruction sentence provided to the generative AI model when generating an avatar image.

[1138] "Avatar image" refers to an image of a virtual person or character generated by a generative AI model based on user information.

[1139] "Ability scores" refer to the numerical characteristics or skills given to an avatar, such as knowledge or concentration.

[1140] "Skills" refer to specific abilities or special techniques given to an avatar.

[1141] "Battle simulation" refers to the process of comparing the ability scores and skills of avatars selected by multiple users and virtually competing against each other.

[1142] "Match result" refers to the win / loss between users and other result information generated as a result of the match simulation.

[1143] "Means of obtaining information" refers to the function of the system receiving information such as name, age, hobbies, and gender entered by the user.

[1144] "Means for transmitting information" refers to the function of transferring acquired information to a server via a network.

[1145] "Means for receiving information" refers to the function of the server to receive information sent from the terminal.

[1146] "Means for parsing information" refers to the process by which the server breaks down and understands the user information it receives into individual data elements.

[1147] "Means for generating images" refers to the process of using a generative AI model to create an avatar image based on user information.

[1148] "Means for receiving images" refers to the function by which the server receives avatar images generated from the generative AI model.

[1149] "Means of assigning ability values ​​and skills" refers to the process of assigning specific characteristics and special moves to the generated avatar image.

[1150] "Means for displaying images" refers to the function of displaying the generated avatar image and its ability values ​​and skills on the user's device.

[1151] "Means for selecting an opponent" refers to a function that allows a user to select another user's avatar and designate it as an opponent.

[1152] "Means for transmitting opponent information" refers to a function for transmitting information about a selected opponent to the server.

[1153] "Means for performing battle simulation" refers to a function for conducting a virtual battle by comparing the ability values ​​and skills of each avatar based on the opponent information received by the server.

[1154] The "means for generating a match result" refers to a process for compiling information such as wins and losses between users based on the results of the match simulation.

[1155] "Means for displaying battle results" refers to a function for displaying the generated battle results on the user's terminal.

[1156] MODE FOR CARRYING OUT THE INVENTION

[1157] This system uses a generative AI model to automatically generate an avatar image based on information entered by the user, and assigns appropriate ability scores and skills to the avatar.It also has the ability to use the generated avatar to compete against other users and display the results of the competition in real time.

[1158] Basic system configuration

[1159] This system is broadly composed of the following three modules:

[1160] 1. User information input module

[1161] 2. Avatar Generation Module

[1162] 3. Game Battle Module

[1163] User information input module

[1164] The user enters information such as name, age, hobbies, and gender into the application's input form. For example, if the user enters "Hanako Sato, 25 years old, reading, female," each piece of information is entered appropriately into the form.

[1165] The device receives the information entered by the user and converts it into JSON format. For example, the input information is converted into the format {"name":"Hanako Sato","age":25,"hobby":"reading","gender":"female"}. Then, this JSON data is sent to the server.

[1166] Avatar Generation Module

[1167] The server receives and analyzes the JSON data sent from the device, identifying individual information (name, age, hobbies, gender).

[1168] The server calls a generative AI model (e.g., DALL-E or GPT-4) based on the analyzed information. The prompt used here is in the format, "Hanako Sato is 25 years old, female, and her hobby is reading. Please generate an avatar image that shows high knowledge and concentration based on this information."

[1169] The generative AI model generates an avatar image based on this prompt. After the generated avatar image is returned to the server, the server assigns the avatar ability scores and skills, such as "Knowledge 85" and "Concentration 90."

[1170] Game Battle Module

[1171] The user can select the generated avatar and choose an opponent. For example, if the user selects "Yamada Taro" from among the other candidates, the selection is complete.

[1172] The device sends information about the opponent selected by the user to the server. For example, information such as "Yamada Taro, ability values: Strength 75, Defense 60" is sent.

[1173] The server receives information about the opponent and performs a battle simulation along with the avatar information to compare. For example, the server compares User A's avatar (Knowledge 85, Concentration 90) with User B's avatar (Strength 75, Defense 60) and generates a simulation result. As a result of the battle simulation, a log is generated stating, for example, "User A's attack was effective and caused great damage to User B," and the result is "User A won."

[1174] The device receives the match result sent from the server and notifies the user. For example, it displays a message to the user saying "User A won."

[1175] The specific hardware and software used

[1176] Terminal: A device such as a smartphone or PC that inputs user information and communicates with the server.

[1177] Server: A high-performance computer or cloud service (e.g., AWS, Google Cloud) used for processing information and calling generative AI models.

[1178] Generative AI models: Uses generative AI models such as DALL-E and GPT-4.

[1179] This system allows users to intuitively create original avatars and enjoy playing against other users using those avatars. Using a generative AI model, it is possible to automatically generate avatars with rich individuality and appropriate ability scores and skills, and provides an advanced gaming experience through real-time battle simulations and results displays.

[1180] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1181] System program processing flow

[1182] Step 1:

[1183] The user enters information such as name, age, hobbies, and gender into the application's input form. For example, the user might enter "Hanako Sato, 25 years old, reading, female." The application receives this information and this becomes input.

[1184] Step 2:

[1185] The device receives the information entered by the user and converts it into JSON format. For example, the input information is converted into data such as {"name":"Hanako Sato","age":25,"hobby":"reading","gender":"female"}. This is then sent to the server as output.

[1186] Step 3:

[1187] The server receives the JSON data sent from the device. The received data is analyzed to identify individual information such as name, age, hobbies, and gender. The analysis results are output.

[1188] Step 4:

[1189] The server calls a generative AI model (e.g., DALL-E, GPT-4) based on the analyzed information. The prompt used at this time is in the form of, "Hanako Sato is 25 years old, female, and her hobby is reading. Please generate an avatar image that shows high knowledge and concentration based on this information." Sending this prompt to the generative AI model is the input, and the generation of an avatar image from the generative AI model is the output.

[1190] Step 5:

[1191] When the generated avatar image is returned to the server, the server assigns the avatar ability values ​​and skills, such as "Knowledge 85" and "Concentration 90." These ability values ​​and skills are stored in a database. This assigned information becomes the output.

[1192] Step 6:

[1193] The user selects an avatar created on the application and decides on an opponent. For example, they select "Yamada Taro." This opponent information is input.

[1194] Step 7:

[1195] The terminal sends information about the opponent selected by the user to the server. For example, the output would be "Yamada Taro, ability values: Strength 75, Defense 60."

[1196] Step 8:

[1197] The server receives information about the opponent and performs a battle simulation along with the avatar information of the opponent to be compared. In this battle, the server compares the ability values ​​and skills of User A's avatar with User B's avatar. The winner is determined based on this comparison. For example, a log such as "User A's attack was effective and caused great damage to User B" is generated.

[1198] Step 9:

[1199] The server generates a battle log based on the results of the battle simulation. The generated battle result, for example, "User A won," is output.

[1200] Step 10:

[1201] The terminal receives the match result sent from the server and displays it to the user. For example, it displays a message saying "User A won." This is the final output.

[1202] Through this series of processes, users can generate unique avatars based on input information and enjoy the results of matches against other users through battle simulations. By using a generative AI model, we can provide users with an intuitive and engaging gaming experience.

[1203] (Application example 1)

[1204] 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."

[1205] Conventional avatar generation systems were limited to avatar generation based on user information and battle simulations, limiting the means by which users could engage in virtual experiences using their own avatars. Furthermore, the user experience was not sufficiently enhanced, as no real-time try-on experience was provided in a virtual store. This meant that users were unable to try on items before purchasing, which was one of the reasons for the decline in purchasing motivation.

[1206] 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.

[1207] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for displaying the avatar image, its ability values, and skills to the user, means for conducting a match with another user, means for displaying the match results, means for conducting a virtual try-on based on the generated avatar image, and means for displaying the results of the virtual try-on. This allows users to virtually try on clothes using their own avatar in real time, thereby increasing purchasing motivation and improving the user experience.

[1208] The "user information input module" is a means for acquiring information such as name, age, hobbies, and gender input by the user.

[1209] A "server" is a central device that receives information sent by users and performs different processing based on it.

[1210] A "generative AI model" is an artificial intelligence model that generates avatar images based on user information.

[1211] An "avatar" is a virtual persona or character that is generated based on information entered by a user.

[1212] "Ability scores" are numerical representations of specific skills and characteristics given to an avatar.

[1213] "Skills" represent specific abilities or techniques that an avatar possesses.

[1214] "Virtual try-on" is a feature that allows you to try on items such as clothes and accessories on a virtual avatar.

[1215] "Virtual try-on results" are results that display the appearance and feedback of the item tried on by the avatar.

[1216] The "game battle module" is a means for a user to use a generated avatar to battle other users in a virtual space.

[1217] "Battle simulation" is the process of comparing the ability values ​​and skills of avatars and calculating the results of a hypothetical battle.

[1218] "Displaying battle results" is a means for providing the results of the battle simulation to the user.

[1219] The present invention is a system that uses a generative AI model to automatically create an avatar image based on information entered by a user and assigns appropriate ability scores and skills to the avatar. Furthermore, the system is equipped with a function that provides a fitting experience in a virtual store. Specific examples are described below.

[1220] Basic system configuration

[1221] This system mainly utilizes the following modules, hardware, and software.

[1222] 1. User information input module:

[1223] The user uses the device to input information such as name, age, hobbies, and gender. The input information is acquired by the device, converted into JSON format, and sent to the server.

[1224] 2. Generative AI Model:

[1225] The server receives the information sent from the device and generates an avatar image based on that information. The generative AI model generates the avatar image taking into account the user's characteristics such as age, gender, and hobbies. For example, if a user's hobby is "reading," it creates an avatar that is highly knowledgeable and focused.

[1226] 3. Attributes and Skills:

[1227] The generated avatar image is returned to the server, which then assigns the avatar ability values ​​such as "Knowledge 85" and "Concentration 90."

[1228] 4. Virtual Try-on Module:

[1229] Users can try on clothes and accessories in a virtual store using the generated avatar, using virtual avatar generation libraries such as MakeHuman and Unity to simulate the try-on experience in real time.

[1230] 5. Try-on result display:

[1231] The results of the virtual try-on are sent from the server to the device and displayed to the user, providing specific feedback such as "I tried on the red dress and it looks great on me."

[1232] Example

[1233] 1. Example user input:

[1234] Name: Hanako Sato

[1235] Age: 25

[1236] Hobbies: Reading

[1237] Gender: Female

[1238] 2. Avatar generation example:

[1239] A generative AI model creates an avatar with enhanced knowledge and focus, trying on muted shirts and black-framed glasses that match the user's hobbies.

[1240] 3. Virtual try-on example:

[1241] The user selects a red dress and has the avatar try it on. As a result, the server generates feedback such as "This dress looks great on you" and sends it to the terminal.

[1242] Example prompt sentence:

[1243] Name: Hanako Sato

[1244] Age: 25

[1245] Hobbies: Reading

[1246] Gender: Female

[1247] Avatar characteristics: Appearance of knowledgeable and focused, clothing that reflects reading

[1248] This allows users to have a more personalized virtual try-on experience based on their own personal information. It is also possible for the generated avatar to compete against other users, and the system is expected to be applicable to a variety of scenarios.

[1249] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1250] Step 1:

[1251] The user enters information such as name, age, hobbies, and gender using a device such as a smartphone or computer. The entered information is converted into JSON format.

[1252] Input: Name, age, hobbies, gender

[1253] Output: User information in JSON format

[1254] Example: A user enters "Hanako Sato, 25 years old, reading, female", which is converted to JSON format as {'name': 'Hanako Sato', 'age': 25, 'hobby': 'reading', 'gender': 'female'}.

[1255] Step 2:

[1256] The terminal sends the acquired user information in JSON format to the server.

[1257] Input: JSON data of user information

[1258] Output: Send data to the server

[1259] Example: JSON data containing user information is sent from the terminal to the server via a POST request.

[1260] Step 3:

[1261] The server calls a generative AI model based on the received user information and generates an avatar image.

[1262] Input: User information in JSON format

[1263] Output: Generated avatar image

[1264] Example: The server passes user information in JSON format to the generative AI model, and asks it to generate an avatar image. For example, the generative AI model creates a female avatar whose hobby is reading.

[1265] Step 4:

[1266] The server receives the avatar image generated by the generative AI model and assigns the avatar ability values ​​such as "Knowledge 85" and "Concentration 90."

[1267] Input: Generated avatar image

[1268] Output: Avatar image with ability scores

[1269] Example: The generated avatar image is assigned specific numerical values ​​such as knowledge and concentration.

[1270] Step 5:

[1271] The server transmits the generated avatar image, its ability values, and skills to the terminal, which then displays them to the user.

[1272] Input: Avatar image with ability values

[1273] Output: Display of avatar image and ability scores to the user

[1274] Example: The device displays the avatar image and ability values ​​received from the server on the screen.

[1275] Step 6:

[1276] Using the generated avatar, users can try on clothes and accessories in a virtual store.

[1277] Input: Generated avatar image

[1278] Output: Simulation results for virtual try-on

[1279] Example: You can have your avatar try on a red dress to see how it looks.

[1280] Step 7:

[1281] The server transmits the results of the virtual try-on to the terminal, which then displays the results to the user.

[1282] Input: Virtual try-on simulation results

[1283] Output: Display of fitting results to the user

[1284] Example: A user is shown a rating that a red dress looks good on the avatar.

[1285] Step 8:

[1286] When a user wishes to compete against another user, the server compares the ability values ​​and skills of the avatars of both users and simulates a battle.

[1287] Input: Opponent information, avatar ability values, skills

[1288] Output: Match result log

[1289] Example: User A's avatar plays against User B's avatar, and the result is generated as a log in the format "User A won."

[1290] Step 9:

[1291] The server transmits the results of the match to the terminal, and the terminal displays the results to the user.

[1292] Input: Match result log

[1293] Output: Display the match result to the user

[1294] Example: The match result "User A won" is displayed on the screen.

[1295] 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.

[1296] MODE FOR CARRYING OUT THE INVENTION

[1297] This invention is a system that uses a generative AI model to generate an avatar image based on information entered by a user and assigns ability scores and skills appropriate to the avatar. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to generate an avatar and adjust ability scores according to the user's emotional state. A specific embodiment of this system and the program processing are described below.

[1298] Basic system configuration

[1299] This system is broadly composed of the following modules:

[1300] 1. User information input module

[1301] 2. Emotion Engine Module

[1302] 3. Avatar Generation Module

[1303] 4. Game Battle Module

[1304] User information input module

[1305] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[1306] Emotion Engine Module

[1307] The device is equipped with a camera that captures the user's facial expressions in real time. The emotion engine module analyzes the user's emotions from the captured facial expressions. The information entered by the user and the emotion data obtained from the facial expressions are sent to the server. For example, if the user is smiling, the emotion engine analyzes it as "happiness" and sends the data to the server.

[1308] Avatar Generation Module

[1309] The server receives user information and emotion data sent from the device. Based on this information, it calls a generative AI model to generate an avatar image. The generative AI model generates the avatar image by taking into account the user's characteristics such as age, gender, hobbies, and emotions.

[1310] For example, if a user's hobby is "reading" and emotional data of "happiness" is sent, the generative AI model will create an avatar with high knowledge and concentration, and a positive facial expression. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[1311] Game Battle Module

[1312] The user can select a generated avatar and choose an opponent from the match list. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability scores and skills of both avatars, and simulates a match.

[1313] The simulation results are generated in the form of, for example, "User A's attack was effective and caused great damage to User B." Finally, the server generates the match results and sends them to the device. The device then displays the received match results to the user, notifying them, for example, "User A won."

[1314] This system allows users to create avatars that reflect their own emotional state and enjoy playing against other users. By combining it with an emotion engine, it is possible to provide a more realistic gaming experience in which the user's emotional state affects the game experience.

[1315] The processing flow will be explained below.

[1316] Step 1:

[1317] The user enters information such as name, age, hobbies, and gender into the application's input form. The user enters the required data into the form and presses the "Submit" button.

[1318] Step 2:

[1319] The terminal acquires the information entered by the user, converts it into JSON format, and sends it to the server as an HTTP request.

[1320] Step 3:

[1321] The camera on the device captures the user's facial expressions in real time and sends the captured images to the emotion engine.

[1322] Step 4:

[1323] The emotion engine analyzes the captured facial images to identify the user's emotional state. For example, a smile might be interpreted as "happiness," while a crease in the brow might be interpreted as "anger." The emotion data is then sent back to the device.

[1324] Step 5:

[1325] The device acquires the analyzed emotion data and sends it along with the user information to the server, where it is converted back into JSON format.

[1326] Step 6:

[1327] The server receives user information and emotion data in JSON format sent from the device, receives HTTP requests through the API endpoint, and converts the data into an internal data structure.

[1328] Step 7:

[1329] The server calls the generative AI model based on the received information, and passes the user information and emotion data to the generative AI model as parameters.

[1330] Step 8:

[1331] The generative AI model analyzes the input user information and emotional data and generates an avatar image based on this. For example, if a user's hobby is "reading" and the emotional data is "happiness," the model will create an avatar image that shows high knowledge and concentration, as well as a positive expression. The generated avatar image is then returned to the server.

[1332] Step 9:

[1333] The server receives the generated avatar image and assigns the corresponding ability scores and skills to the avatar image. These ability scores and skills are determined based on the user's hobbies and emotional data. For example, the avatar may be assigned "knowledge 85," "concentration 90," or "happiness 95."

[1334] Step 10:

[1335] The server sends avatar information, including assigned ability values ​​and skills, to the device. The avatar image and ability value / skill data are then collected and returned to the device in JSON format.

[1336] Step 11:

[1337] The terminal displays the avatar information received from the server to the user, who can visually check their own avatar image, its ability scores, and skills.

[1338] Step 12:

[1339] The user selects their own avatar and chooses an opponent from the match list. After selecting an opponent, the user presses the "Challenge" button.

[1340] Step 13:

[1341] The device sends information about the selected opponent to the server, including the avatar IDs and user IDs of both players, in JSON format.

[1342] Step 14:

[1343] The server receives the matching information and simulates the battle, comparing the ability values ​​and skills of the avatars of both players and simulating the battle based on a predefined algorithm.

[1344] Step 15:

[1345] The server generates the match results, creating a match log with details such as "User A's attack was effective and caused a lot of damage to User B," and then generates the final winner / loser result.

[1346] Step 16:

[1347] The server sends the generated match results to the device, formats the results in JSON format, and returns them to the device as an HTTP response.

[1348] Step 17:

[1349] The terminal displays the received match results to the user, who can receive a notification such as "User A won."

[1350] Example 2

[1351] 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."

[1352] Conventional systems could generate avatars based on basic information entered by the user (such as name, age, hobbies, and gender) and assign ability scores and skills, but they had the problem of not being able to generate avatars that reflected the user's emotional state or adjust ability scores. As a result, the user's emotional state was not reflected in the game experience, making it difficult to provide a more realistic feel.

[1353] 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.

[1354] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability scores and skills corresponding to the avatar image, means for displaying the avatar image, its ability scores, and skills to the user, means for capturing the user's facial expression, means for analyzing emotional data from the captured facial expression, means for transmitting the analyzed emotional data to the server, means for adjusting the ability scores and skills using the emotional data, means for conducting a match against another user, and means for displaying the match results. This enables the generation of an avatar and the adjustment of ability scores to reflect the user's emotional state, providing a more realistic experience.

[1355] "User information" refers to basic personal information such as name, age, hobbies, and gender that a user enters into an application.

[1356] A "terminal" is a device used by a user, and is a device for inputting and capturing information and transmitting and receiving data.

[1357] A "server" is a computer system that receives and processes data sent from a terminal.

[1358] A "generative AI model" is an artificial intelligence model for generating avatar images based on user information and emotional data.

[1359] An "avatar image" is visual data of a virtual character that represents a user and is created by a generative AI model.

[1360] "Ability score" is a numerical evaluation of a status given to an avatar, such as knowledge, concentration, happiness, etc.

[1361] A "skill" is an element that indicates a specific action or ability that is given to an avatar.

[1362] The "emotion engine module" is a software module that analyzes the user's facial expressions and identifies emotion data.

[1363] "Emotion data" is data that indicates the user's emotional state analyzed by the emotion engine module.

[1364] "Battle" means that the generated avatars virtually compete against each other based on their skills and ability values.

[1365] "Match results" refers to the result data such as win / loss and damage obtained from the match simulation.

[1366] This invention is a system that uses a generative AI model to generate an avatar image based on information and emotional data entered by a user, and assigns ability scores and skills appropriate to the avatar. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to generate an avatar and adjust its ability scores according to the user's emotional state. Specific embodiments of the invention are described in detail below.

[1367] Basic system configuration

[1368] This system is broadly composed of the following modules:

[1369] 1. User information input module

[1370] 2. Emotion Engine Module

[1371] 3. Avatar Generation Module

[1372] 4. Game Battle Module

[1373] User information input module

[1374] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[1375] Emotion Engine Module

[1376] The device is equipped with a camera that captures the user's facial expressions in real time. The emotion engine module analyzes the user's emotions from the captured facial expressions. The information entered by the user and the emotion data obtained from the facial expressions are sent to the server. For example, if the user is smiling, the emotion engine analyzes it as "happiness" and sends the data to the server.

[1377] Avatar Generation Module

[1378] The server receives user information and emotion data sent from the device. Based on this information, it calls a generative AI model to generate an avatar image. The generative AI model generates the avatar image by taking into account the user's characteristics such as age, gender, hobbies, and emotions.

[1379] For example, if a user's hobby is "reading" and emotional data of "happiness" is sent, the generative AI model will create an avatar with high knowledge and concentration, and a positive facial expression. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[1380] Game Battle Module

[1381] The user can select a generated avatar and choose an opponent from the match list. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability scores and skills of both avatars, and simulates a match.

[1382] The simulation results are generated in the form of, for example, "User A's attack was effective and caused great damage to User B." Finally, the server generates the match results and sends them to the device. The device then displays the received match results to the user, notifying them, for example, "User A won."

[1383] Specific examples

[1384] The user enters the following information:

[1385] Name: Hanako Sato

[1386] Age: 25

[1387] Hobbies: Reading

[1388] Gender: Female

[1389] The device converts this to JSON format and sends it to the server:

[1390] json

[1391] {

[1392] "Name": "Hanako Sato",

[1393] "age": "25 years old",

[1394] "Hobbies": "Reading",

[1395] "Gender": "Female"

[1396] }

[1397] Next, the user's smiling expression is captured by the device's camera. The emotion engine analyzes this expression and determines it as "happy." This data is also sent to the server:

[1398] json

[1399] {

[1400] "Emotion": "Happiness"

[1401] }

[1402] The server then calls the generative AI model based on the received data and generates an avatar, which is given knowledge of 85, concentration of 90, and happiness of 95.

[1403] When the user selects "User B" as their opponent, the device sends the following data to the server:

[1404] json

[1405] {

[1406] "Opponent": "User B"

[1407] }

[1408] The server performs a battle simulation, generates the results, and sends them to the device. The device then displays the results to the user, saying "User A won."

[1409] Prompt Sentence Examples

[1410] Here are some example prompts to input to a generative AI model:

[1411] "Generate the most suitable avatar based on the information (name, age, hobbies, gender) and emotional data (happiness, sadness, anger, etc.) entered by the user."

[1412] This system allows users to create avatars that reflect their own emotions and compete against other users. By utilizing the emotion engine, the user's emotional state directly affects the game experience, providing a greater sense of realism.

[1413] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1414] System processing flow

[1415] Step 1: Enter your user information

[1416] explanation:

[1417] The user enters basic information such as name, age, hobbies, and gender into the application's input form.

[1418] input:

[1419] User information such as name, age, hobbies, and gender

[1420] output:

[1421] User-entered information

[1422] Step 2: Convert and send information

[1423] explanation:

[1424] The terminal acquires the information entered by the user, converts it into JSON format, and sends it to the server.

[1425] input:

[1426] User-entered information

[1427] output:

[1428] User information in JSON format

[1429] Specific behavior:

[1430] Convert the input "Hanako Sato, 25 years old, reading, female" into the following JSON format on the terminal:

[1431] json

[1432] {

[1433] "Name": "Hanako Sato",

[1434] "age": "25 years old",

[1435] "Hobbies": "Reading",

[1436] "Gender": "Female"

[1437] }

[1438] This data is sent to the server.

[1439] Step 3: Receiving and parsing by the server

[1440] explanation:

[1441] The server receives the user information in JSON format sent from the terminal.

[1442] input:

[1443] User information in JSON format

[1444] output:

[1445] User information analysis results

[1446] Step 4: Capture facial expressions

[1447] explanation:

[1448] The camera on the device captures the user's facial expressions in real time.

[1449] input:

[1450] User's facial expression

[1451] output:

[1452] Captured facial expression image data

[1453] Step 5: Analyze the sentiment data

[1454] explanation:

[1455] An emotion engine module analyzes the captured facial expressions and generates emotion data for the user.

[1456] input:

[1457] Facial image data

[1458] output:

[1459] Emotional data (e.g., "happiness")

[1460] Specific behavior:

[1461] If the user is smiling, the emotion engine will parse it as "happy" and generate the data in the following format:

[1462] json

[1463] {

[1464] "Emotion": "Happiness"

[1465] }

[1466] Step 6: Sending Emotion Data

[1467] explanation:

[1468] The device transmits the analyzed emotion data to the server.

[1469] input:

[1470] Emotional Data

[1471] output:

[1472] Emotion data sent to the server

[1473] Step 7: Invoke the generative AI model

[1474] explanation:

[1475] The server calls the generative AI model based on the received user information and emotion data.

[1476] input:

[1477] User information and emotional data

[1478] output:

[1479] Executing a generative AI model by inputting a prompt

[1480] Step 8: Generate Avatar Images

[1481] explanation:

[1482] The generative AI model generates an avatar image based on the prompt text.

[1483] input:

[1484] Prompt sentence, user information, emotion data

[1485] output:

[1486] Generated avatar image

[1487] Specific behavior:

[1488] Enter the following prompt into the generative AI model:

[1489] "Generate the most suitable avatar based on the information (name, age, hobbies, gender) and emotional data (happiness, sadness, anger, etc.) entered by the user."

[1490] Step 9: Adding Avatar Ability Scores

[1491] explanation:

[1492] The server assigns the generated avatar ability values ​​such as "Knowledge 85," "Concentration 90," and "Happiness 95."

[1493] input:

[1494] Generated avatar image

[1495] output:

[1496] Avatar with ability scores

[1497] Step 10: Choose your avatar and opponent

[1498] explanation:

[1499] The user selects a generated avatar and chooses an opponent from the match list.

[1500] input:

[1501] Avatar with ability scores

[1502] output:

[1503] Selected Opponents

[1504] Specific behavior:

[1505] The user uses the generated avatar to select "User B" as an opponent.

[1506] Step 11: Send Opponent Information

[1507] explanation:

[1508] The terminal transmits information about the opponent selected by the user to the server.

[1509] input:

[1510] Opponent Information

[1511] output:

[1512] Opponent information sent to the server

[1513] Specific behavior:

[1514] The device sends the following data to the server:

[1515] json

[1516] {

[1517] "Opponent": "User B"

[1518] }

[1519] Step 12: Run a match simulation

[1520] explanation:

[1521] The server receives information about the opponent, compares the ability values ​​and skills of both avatars, and simulates the match.

[1522] input:

[1523] Avatar ability scores and opponent information

[1524] output:

[1525] Battle simulation results

[1526] Step 13: Generate and send match results

[1527] explanation:

[1528] The server generates the results of the battle simulation in JSON format and sends them to the device.

[1529] input:

[1530] Battle simulation results

[1531] output:

[1532] Match results in JSON format

[1533] Specific behavior:

[1534] The server generates the result: "User A's attack was effective and caused a lot of damage to User B. User A wins."

[1535] Step 14: Viewing Match Results

[1536] explanation:

[1537] The terminal displays the received match results to the user and notifies the user, such as "User A won."

[1538] input:

[1539] Match results in JSON format

[1540] output:

[1541] Results displayed to the user

[1542] Specific behavior:

[1543] The device displays the message "User A has won" to the user.

[1544] The above is the processing flow and specific steps of this system's program.

[1545] (Application example 2)

[1546] 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."

[1547] Conventional avatar generation systems rely solely on user information, making it difficult to generate personalized avatars that reflect the user's real-time emotional state. Furthermore, in virtual shopping experiences, they are unable to recommend products based on the user's emotions. Therefore, there is a need for a method to improve the quality of the shopping experience.

[1548] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring information such as the name, age, hobbies, and gender input by the user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for adjusting the avatar's ability values ​​and skills using an emotion engine that analyzes the user's emotions, means for displaying the avatar image, its ability values, and skills to the user, means for conducting a battle with other users, means for displaying the battle results, and means for recommending products in a virtual store based on the user's emotions. This makes it possible to generate an avatar that reflects the user's emotional state, improving the quality of the battle and shopping experience.

[1549] "User information" is information about a user's personal information, such as the user's name, age, hobbies, and gender, that is obtained by the application.

[1550] An "emotion engine" refers to technology or software that analyzes a user's facial expressions and behavior to detect their emotional state.

[1551] "Generative AI model" refers to an artificial intelligence algorithm that generates high-quality avatar images based on user information and emotional data.

[1552] "Avatar image" refers to a character image that reflects the user's characteristics and is generated by a generative AI model.

[1553] "Ability scores" are numerical representations of specific characteristics or status given to an avatar.

[1554] "Skills" refer to specific techniques or abilities that an avatar possesses and are used in battles and other actions.

[1555] "Virtual Store" refers to a virtual store where users can browse and purchase products via the Internet.

[1556] "Product recommendation" refers to suggesting appropriate products to a user based on the user's past behavior and current emotional state.

[1557] "Competition" refers to an activity in which generated avatars compete against each other in simulation or real time.

[1558] "Match results" refers to the information on victory or defeat and results that is displayed after avatars have competed against each other.

[1559] In this invention, a system is constructed that generates an avatar image and its ability values ​​and skills based on information and emotional state input by a user, and uses these to provide a personalized shopping experience in a virtual store.

[1560] First, the device acquires information such as the user's name, age, hobbies, and gender, which is then converted into JSON format and sent to the server.

[1561] The device captures the user's facial expressions through the camera. The emotion engine analyzes the user's emotions from the captured facial expressions and generates emotion data such as "happiness" or "sadness." This emotion data is also sent to the server.

[1562] The server receives user information and emotion data sent from the device. Using this information, the server invokes a generative AI model to generate an avatar image that reflects the user's characteristics. The generative AI model uses technologies such as Stable Diffusion and Midjourney.

[1563] The generated avatar image is returned to the server, and the avatar is given ability scores and skills such as "knowledge" and "concentration." This allows the ability scores to be adjusted according to the user's emotions.

[1564] Next, the user shops in the virtual store through the generated avatar. The server uses the user's emotional data to recommend appropriate products. This product recommendation is also performed by the server, providing the user with an optimal shopping experience.

[1565] For example, if a user enters information such as "Hanako Sato, 25 years old, reading, female" and smiles at the camera, the emotion engine will interpret this as "happiness." The generative AI model will generate an avatar with high knowledge and concentration, and a positive expression. This avatar will be given ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[1566] The system of this invention makes it possible to generate an avatar that reflects the user's emotional state and to recommend products based on that avatar, thereby improving the quality of the shopping experience in a virtual store.

[1567] Examples of prompts are:

[1568] "Create an avatar based on the following user information: {'Name': 'Hanako Sato', 'Age': 25, 'Hobbies': 'Reading', 'Gender': 'Female'}, Emotion: 'Happiness'. Give the avatar a costume that is easy to read and the ability scores of Knowledge 85, Concentration 90, and Happiness 95."

[1569] By inputting this prompt into a generative AI model, an avatar that best suits the user can be created.

[1570] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1571] Step 1:

[1572] The user inputs information such as name, age, hobbies, and gender into the device. The input data is converted to JSON format by the device. This data is sent to the server as user information. The input here is the user's personal information, and the output is user information in JSON format.

[1573] Step 2:

[1574] The device's camera captures the user's facial expression. The captured image data is sent to the emotion engine. The emotion engine analyzes the image data and recognizes the user's emotion. The input in this step is the image data, and the output is the analyzed emotion data.

[1575] Step 3:

[1576] The device transmits the captured emotion data to the server, which receives the transmitted user information and emotion data and integrates this data. The input is the user information and emotion data, and the output is the integrated dataset.

[1577] Step 4:

[1578] The server uses the integrated dataset to call the generative AI model to generate a prompt. The generated prompt sentence is input to the AI ​​model to generate an avatar image. The input is the prompt sentence, and the output is the generated avatar image.

[1579] Step 5:

[1580] The server receives the generated avatar image and assigns appropriate ability scores and skills to the avatar. These ability scores and skills are determined based on the user's personal information and emotional data. The input is the avatar image and user data, and the output is an avatar with the assigned ability scores and skills.

[1581] Step 6:

[1582] The server sends an avatar with assigned ability scores and skills to the device. The device displays this avatar to the user, who can then customize it. The input is the avatar with assigned ability scores and skills, and the output is the avatar displayed to the user.

[1583] Step 7:

[1584] The user receives product recommendations in a virtual store using an avatar. The server recommends optimal products based on the user's emotional data. The input is the emotional data and the avatar, and the output is a list of recommended products.

[1585] Step 8:

[1586] The user browses and purchases the recommended products in the virtual store. The purchase data is sent to the server, which then provides the products to the user. The input is a list of recommended products, and the output is information about the purchased products.

[1587] This allows users to enjoy a more personalized shopping experience through avatars that reflect their emotional state.

[1588] 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.

[1589] 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.

[1590] 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.

[1591] [Fourth embodiment]

[1592] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1593] 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.

[1594] 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).

[1595] 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.

[1596] 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.

[1597] 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).

[1598] 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.

[1599] 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.

[1600] 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.

[1601] 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.

[1602] 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.

[1603] 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.

[1604] 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."

[1605] MODE FOR CARRYING OUT THE INVENTION

[1606] This invention is a system that uses a generative AI model to automatically generate an avatar image based on information entered by a user and assigns ability scores and skills appropriate to the avatar. Specific embodiments of the system and program processing are described here.

[1607] Basic system configuration

[1608] This system is broadly composed of the following three modules:

[1609] 1. User information input module

[1610] 2. Avatar Generation Module

[1611] 3. Game Battle Module

[1612] User information input module

[1613] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[1614] Avatar Generation Module

[1615] The server receives user information sent from the device. Based on this information, the server invokes a generative AI model to generate an avatar image. The generative AI model generates the avatar image taking into account the user's characteristics such as age, gender, and hobbies.

[1616] For example, if a user's hobby is "reading," the generative AI model will create an avatar with high knowledge and concentration. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "Knowledge 85" and "Concentration 90."

[1617] Game Battle Module

[1618] The user can select a generated avatar and choose an opponent. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability values ​​and skills of both avatars, and simulates the battle. The simulation results are generated as a log in the form of, for example, "User A's attack was effective and caused great damage to User B."

[1619] Finally, the server generates the match results and sends them to the device. The device displays the received match results to the user, notifying them, for example, "User A won."

[1620] In this way, this system allows users to easily input their own information and intuitively generate an original avatar using a generative AI model. They can then use that avatar to compete against other users and enjoy the results. This allows users to enjoy a sophisticated gaming experience without any programming knowledge.

[1621] The processing flow will be explained below.

[1622] Step 1:

[1623] The user enters information such as name, age, hobbies, and gender into the application's input form. The user enters the required data into the form and presses the "Submit" button.

[1624] Step 2:

[1625] The terminal receives the information entered by the user, converts it into JSON format, and sends it to the server as an HTTP request.

[1626] Step 3:

[1627] The server receives the user information in JSON format sent from the device. It receives the HTTP request through the API endpoint, parses the JSON data, and converts it into an internal data structure.

[1628] Step 4:

[1629] The server calls the generative AI model based on the received user information, and passes the user information to the generative AI model as a parameter.

[1630] Step 5:

[1631] The generative AI model analyzes the input user information and generates an avatar image based on characteristics such as age, gender, and hobbies. The generated avatar image is then returned to the server.

[1632] Step 6:

[1633] The server receives the generated avatar image and assigns the corresponding ability scores and skills to the avatar image. These ability scores and skills are calculated based on predefined rules.

[1634] Step 7:

[1635] The server sends avatar information, including assigned ability values ​​and skills, to the device. The avatar image and ability value / skill data are then collected and returned to the device in JSON format.

[1636] Step 8:

[1637] The device displays the avatar information received from the server, allowing users to visually check their own avatar image, as well as their ability scores and skills.

[1638] Step 9:

[1639] The user selects their own avatar and chooses an opponent from the match list. After selecting an opponent, the user presses the "Challenge" button.

[1640] Step 10:

[1641] The device sends information about the selected opponent to the server, including the avatar IDs and user IDs of both players, in JSON format.

[1642] Step 11:

[1643] The server receives the matching information and simulates the battle, comparing the ability values ​​and skills of the avatars of both players and simulating the battle based on a predefined algorithm.

[1644] Step 12:

[1645] The server generates the match results, creating a match log with details such as "User A's attack was effective and caused a lot of damage to User B." It also generates the final victory or defeat result.

[1646] Step 13:

[1647] The server sends the generated match results to the device, formats the results in JSON format, and returns them to the device as an HTTP response.

[1648] Step 14:

[1649] The terminal displays the received match results to the user, who can receive a notification such as "User A won."

[1650] Example 1

[1651] 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."

[1652] Conventional avatar generation systems have had problems in that it is difficult to generate a unique avatar image based on information entered by the user and to assign appropriate ability scores and skills to that avatar. Furthermore, when playing against other users using the generated avatar, it is difficult to display the results of the match in real time.

[1653] 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.

[1654] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for converting the acquired information into a data format and transmitting the data to the server, means for analyzing the information received by the server, means for generating an avatar image by calling a generation AI model based on the analyzed information, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for displaying the avatar image, its ability values, and skills to the user, means for the user to select an opponent, means for transmitting information about the selected opponent to the server, means for the server to receive the opponent information and perform a battle simulation, and means for generating and displaying the battle results. This allows intuitive and attractive avatar images to be generated based on user information, and enables users to enjoy battles with other users in real time using the avatars.

[1655] In this invention, the term "user" refers to a person who uses the system.

[1656] "Terminal" refers to a device that a user inputs information into and communicates with a server. Examples include smartphones and personal computers.

[1657] "Server" refers to a high-performance computer or cloud service that performs central processing such as receiving and analyzing data, calling generative AI models, and conducting battle simulations.

[1658] "Generative AI models" refer to artificial intelligence models that generate avatar images based on user information. Examples include DALL-E and GPT-4.

[1659] "Prompt sentence" refers to the instruction sentence provided to the generative AI model when generating an avatar image.

[1660] "Avatar image" refers to an image of a virtual person or character generated by a generative AI model based on user information.

[1661] "Ability scores" refer to the numerical characteristics or skills given to an avatar, such as knowledge or concentration.

[1662] "Skills" refer to specific abilities or special techniques given to an avatar.

[1663] "Battle simulation" refers to the process of comparing the ability scores and skills of avatars selected by multiple users and virtually competing against each other.

[1664] "Match result" refers to the win / loss between users and other result information generated as a result of the match simulation.

[1665] "Means of obtaining information" refers to the function of the system receiving information such as name, age, hobbies, and gender entered by the user.

[1666] "Means for transmitting information" refers to the function of transferring acquired information to a server via a network.

[1667] "Means for receiving information" refers to the function of the server to receive information sent from the terminal.

[1668] "Means for parsing information" refers to the process by which the server breaks down and understands the user information it receives into individual data elements.

[1669] "Means for generating images" refers to the process of using a generative AI model to create an avatar image based on user information.

[1670] "Means for receiving images" refers to the function by which the server receives avatar images generated from the generative AI model.

[1671] "Means of assigning ability values ​​and skills" refers to the process of assigning specific characteristics and special moves to the generated avatar image.

[1672] "Means for displaying images" refers to the function of displaying the generated avatar image and its ability values ​​and skills on the user's device.

[1673] "Means for selecting an opponent" refers to a function that allows a user to select another user's avatar and designate it as an opponent.

[1674] "Means for transmitting opponent information" refers to a function for transmitting information about a selected opponent to the server.

[1675] "Means for performing battle simulation" refers to a function for conducting a virtual battle by comparing the ability values ​​and skills of each avatar based on the opponent information received by the server.

[1676] The "means for generating a match result" refers to a process for compiling information such as wins and losses between users based on the results of the match simulation.

[1677] "Means for displaying battle results" refers to a function for displaying the generated battle results on the user's terminal.

[1678] MODE FOR CARRYING OUT THE INVENTION

[1679] This system uses a generative AI model to automatically generate an avatar image based on information entered by the user, and assigns appropriate ability scores and skills to the avatar.It also has the ability to use the generated avatar to compete against other users and display the results of the competition in real time.

[1680] Basic system configuration

[1681] This system is broadly composed of the following three modules:

[1682] 1. User information input module

[1683] 2. Avatar Generation Module

[1684] 3. Game Battle Module

[1685] User information input module

[1686] The user enters information such as name, age, hobbies, and gender into the application's input form. For example, if the user enters "Hanako Sato, 25 years old, reading, female," each piece of information is entered appropriately into the form.

[1687] The device receives the information entered by the user and converts it into JSON format. For example, the input information is converted into the format {"name":"Hanako Sato","age":25,"hobby":"reading","gender":"female"}. Then, this JSON data is sent to the server.

[1688] Avatar Generation Module

[1689] The server receives and analyzes the JSON data sent from the device, identifying individual information (name, age, hobbies, gender).

[1690] The server calls a generative AI model (e.g., DALL-E or GPT-4) based on the analyzed information. The prompt used here is in the format, "Hanako Sato is 25 years old, female, and her hobby is reading. Please generate an avatar image that shows high knowledge and concentration based on this information."

[1691] The generative AI model generates an avatar image based on this prompt. After the generated avatar image is returned to the server, the server assigns the avatar ability scores and skills, such as "Knowledge 85" and "Concentration 90."

[1692] Game Battle Module

[1693] The user can select the generated avatar and choose an opponent. For example, if the user selects "Yamada Taro" from among the other candidates, the selection is complete.

[1694] The device sends information about the opponent selected by the user to the server. For example, information such as "Yamada Taro, ability values: Strength 75, Defense 60" is sent.

[1695] The server receives information about the opponent and performs a battle simulation along with the avatar information to compare. For example, the server compares User A's avatar (Knowledge 85, Concentration 90) with User B's avatar (Strength 75, Defense 60) and generates a simulation result. As a result of the battle simulation, a log is generated stating, for example, "User A's attack was effective and caused great damage to User B," and the result is "User A won."

[1696] The device receives the match result sent from the server and notifies the user. For example, it displays a message to the user saying "User A won."

[1697] The specific hardware and software used

[1698] Terminal: A device such as a smartphone or PC that inputs user information and communicates with the server.

[1699] Server: A high-performance computer or cloud service (e.g., AWS, Google Cloud) used for processing information and calling generative AI models.

[1700] Generative AI models: Uses generative AI models such as DALL-E and GPT-4.

[1701] This system allows users to intuitively create original avatars and enjoy playing against other users using those avatars. Using a generative AI model, it is possible to automatically generate avatars with rich individuality and appropriate ability scores and skills, and provides an advanced gaming experience through real-time battle simulations and results displays.

[1702] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1703] System program processing flow

[1704] Step 1:

[1705] The user enters information such as name, age, hobbies, and gender into the application's input form. For example, the user might enter "Hanako Sato, 25 years old, reading, female." The application receives this information and this becomes input.

[1706] Step 2:

[1707] The device receives the information entered by the user and converts it into JSON format. For example, the input information is converted into data such as {"name":"Hanako Sato","age":25,"hobby":"reading","gender":"female"}. This is then sent to the server as output.

[1708] Step 3:

[1709] The server receives the JSON data sent from the device. The received data is analyzed to identify individual information such as name, age, hobbies, and gender. The analysis results are output.

[1710] Step 4:

[1711] The server calls a generative AI model (e.g., DALL-E, GPT-4) based on the analyzed information. The prompt used at this time is in the form of, "Hanako Sato is 25 years old, female, and her hobby is reading. Please generate an avatar image that shows high knowledge and concentration based on this information." Sending this prompt to the generative AI model is the input, and the generation of an avatar image from the generative AI model is the output.

[1712] Step 5:

[1713] When the generated avatar image is returned to the server, the server assigns the avatar ability values ​​and skills, such as "Knowledge 85" and "Concentration 90." These ability values ​​and skills are stored in a database. This assigned information becomes the output.

[1714] Step 6:

[1715] The user selects an avatar created on the application and decides on an opponent. For example, they select "Yamada Taro." This opponent information is input.

[1716] Step 7:

[1717] The terminal sends information about the opponent selected by the user to the server. For example, the output would be "Yamada Taro, ability values: Strength 75, Defense 60."

[1718] Step 8:

[1719] The server receives information about the opponent and performs a battle simulation along with the avatar information of the opponent to be compared. In this battle, the server compares the ability values ​​and skills of User A's avatar with User B's avatar. The winner is determined based on this comparison. For example, a log such as "User A's attack was effective and caused great damage to User B" is generated.

[1720] Step 9:

[1721] The server generates a battle log based on the results of the battle simulation. The generated battle result, for example, "User A won," is output.

[1722] Step 10:

[1723] The terminal receives the match result sent from the server and displays it to the user. For example, it displays a message saying "User A won." This is the final output.

[1724] Through this series of processes, users can generate unique avatars based on input information and enjoy the results of matches against other users through battle simulations. By using a generative AI model, we can provide users with an intuitive and engaging gaming experience.

[1725] (Application example 1)

[1726] 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."

[1727] Conventional avatar generation systems were limited to avatar generation based on user information and battle simulations, limiting the means by which users could engage in virtual experiences using their own avatars. Furthermore, the user experience was not sufficiently enhanced, as no real-time try-on experience was provided in a virtual store. This meant that users were unable to try on items before purchasing, which was one of the reasons for the decline in purchasing motivation.

[1728] 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.

[1729] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for displaying the avatar image, its ability values, and skills to the user, means for conducting a match with another user, means for displaying the match results, means for conducting a virtual try-on based on the generated avatar image, and means for displaying the results of the virtual try-on. This allows users to virtually try on clothes using their own avatar in real time, thereby increasing purchasing motivation and improving the user experience.

[1730] The "user information input module" is a means for acquiring information such as name, age, hobbies, and gender input by the user.

[1731] A "server" is a central device that receives information sent by users and performs different processing based on it.

[1732] A "generative AI model" is an artificial intelligence model that generates avatar images based on user information.

[1733] An "avatar" is a virtual persona or character that is generated based on information entered by a user.

[1734] "Ability scores" are numerical representations of specific skills and characteristics given to an avatar.

[1735] "Skills" represent specific abilities or techniques that an avatar possesses.

[1736] "Virtual try-on" is a feature that allows you to try on items such as clothes and accessories on a virtual avatar.

[1737] "Virtual try-on results" are results that display the appearance and feedback of the item tried on by the avatar.

[1738] The "game battle module" is a means for a user to use a generated avatar to battle other users in a virtual space.

[1739] "Battle simulation" is the process of comparing the ability values ​​and skills of avatars and calculating the results of a hypothetical battle.

[1740] "Displaying battle results" is a means for providing the results of the battle simulation to the user.

[1741] The present invention is a system that uses a generative AI model to automatically create an avatar image based on information entered by a user and assigns appropriate ability scores and skills to the avatar. Furthermore, the system is equipped with a function that provides a fitting experience in a virtual store. Specific examples are described below.

[1742] Basic system configuration

[1743] This system mainly utilizes the following modules, hardware, and software.

[1744] 1. User information input module:

[1745] The user uses the device to input information such as name, age, hobbies, and gender. The input information is acquired by the device, converted into JSON format, and sent to the server.

[1746] 2. Generative AI Model:

[1747] The server receives the information sent from the device and generates an avatar image based on that information. The generative AI model generates the avatar image taking into account the user's characteristics such as age, gender, and hobbies. For example, if a user's hobby is "reading," it creates an avatar that is highly knowledgeable and focused.

[1748] 3. Attributes and Skills:

[1749] The generated avatar image is returned to the server, which then assigns the avatar ability values ​​such as "Knowledge 85" and "Concentration 90."

[1750] 4. Virtual Try-on Module:

[1751] Users can try on clothes and accessories in a virtual store using the generated avatar, using virtual avatar generation libraries such as MakeHuman and Unity to simulate the try-on experience in real time.

[1752] 5. Try-on result display:

[1753] The results of the virtual try-on are sent from the server to the device and displayed to the user, providing specific feedback such as "I tried on the red dress and it looks great on me."

[1754] Example

[1755] 1. Example user input:

[1756] Name: Hanako Sato

[1757] Age: 25

[1758] Hobbies: Reading

[1759] Gender: Female

[1760] 2. Avatar generation example:

[1761] A generative AI model creates an avatar with enhanced knowledge and focus, trying on muted shirts and black-framed glasses that match the user's hobbies.

[1762] 3. Virtual try-on example:

[1763] The user selects a red dress and has the avatar try it on. As a result, the server generates feedback such as "This dress looks great on you" and sends it to the terminal.

[1764] Example prompt sentence:

[1765] Name: Hanako Sato

[1766] Age: 25

[1767] Hobbies: Reading

[1768] Gender: Female

[1769] Avatar characteristics: Appearance of knowledgeable and focused, clothing that reflects reading

[1770] This allows users to have a more personalized virtual try-on experience based on their own personal information. It is also possible for the generated avatar to compete against other users, and the system is expected to be applicable to a variety of scenarios.

[1771] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1772] Step 1:

[1773] The user enters information such as name, age, hobbies, and gender using a device such as a smartphone or computer. The entered information is converted into JSON format.

[1774] Input: Name, age, hobbies, gender

[1775] Output: User information in JSON format

[1776] Example: A user enters "Hanako Sato, 25 years old, reading, female", which is converted to JSON format as {'name': 'Hanako Sato', 'age': 25, 'hobby': 'reading', 'gender': 'female'}.

[1777] Step 2:

[1778] The terminal sends the acquired user information in JSON format to the server.

[1779] Input: JSON data of user information

[1780] Output: Send data to the server

[1781] Example: JSON data containing user information is sent from the terminal to the server via a POST request.

[1782] Step 3:

[1783] The server calls a generative AI model based on the received user information and generates an avatar image.

[1784] Input: User information in JSON format

[1785] Output: Generated avatar image

[1786] Example: The server passes user information in JSON format to the generative AI model, and asks it to generate an avatar image. For example, the generative AI model creates a female avatar whose hobby is reading.

[1787] Step 4:

[1788] The server receives the avatar image generated by the generative AI model and assigns the avatar ability values ​​such as "Knowledge 85" and "Concentration 90."

[1789] Input: Generated avatar image

[1790] Output: Avatar image with ability scores

[1791] Example: The generated avatar image is assigned specific numerical values ​​such as knowledge and concentration.

[1792] Step 5:

[1793] The server transmits the generated avatar image, its ability values, and skills to the terminal, which then displays them to the user.

[1794] Input: Avatar image with ability values

[1795] Output: Display of avatar image and ability scores to the user

[1796] Example: The device displays the avatar image and ability values ​​received from the server on the screen.

[1797] Step 6:

[1798] Using the generated avatar, users can try on clothes and accessories in a virtual store.

[1799] Input: Generated avatar image

[1800] Output: Simulation results for virtual try-on

[1801] Example: You can have your avatar try on a red dress to see how it looks.

[1802] Step 7:

[1803] The server transmits the results of the virtual try-on to the terminal, which then displays the results to the user.

[1804] Input: Virtual try-on simulation results

[1805] Output: Display of fitting results to the user

[1806] Example: A user is shown a rating that a red dress looks good on the avatar.

[1807] Step 8:

[1808] When a user wishes to compete against another user, the server compares the ability values ​​and skills of the avatars of both users and simulates a battle.

[1809] Input: Opponent information, avatar ability values, skills

[1810] Output: Match result log

[1811] Example: User A's avatar plays against User B's avatar, and the result is generated as a log in the format "User A won."

[1812] Step 9:

[1813] The server transmits the results of the match to the terminal, and the terminal displays the results to the user.

[1814] Input: Match result log

[1815] Output: Display the match result to the user

[1816] Example: The match result "User A won" is displayed on the screen.

[1817] 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.

[1818] MODE FOR CARRYING OUT THE INVENTION

[1819] This invention is a system that uses a generative AI model to generate an avatar image based on information entered by a user and assigns ability scores and skills appropriate to the avatar. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to generate an avatar and adjust ability scores according to the user's emotional state. A specific embodiment of this system and the program processing are described below.

[1820] Basic system configuration

[1821] This system is broadly composed of the following modules:

[1822] 1. User information input module

[1823] 2. Emotion Engine Module

[1824] 3. Avatar Generation Module

[1825] 4. Game Battle Module

[1826] User information input module

[1827] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[1828] Emotion Engine Module

[1829] The device is equipped with a camera that captures the user's facial expressions in real time. The emotion engine module analyzes the user's emotions from the captured facial expressions. The information entered by the user and the emotion data obtained from the facial expressions are sent to the server. For example, if the user is smiling, the emotion engine analyzes it as "happiness" and sends the data to the server.

[1830] Avatar Generation Module

[1831] The server receives user information and emotion data sent from the device. Based on this information, it calls a generative AI model to generate an avatar image. The generative AI model generates the avatar image by taking into account the user's characteristics such as age, gender, hobbies, and emotions.

[1832] For example, if a user's hobby is "reading" and emotional data of "happiness" is sent, the generative AI model will create an avatar with high knowledge and concentration, and a positive facial expression. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[1833] Game Battle Module

[1834] The user can select a generated avatar and choose an opponent from the match list. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability scores and skills of both avatars, and simulates a match.

[1835] The simulation results are generated in the form of, for example, "User A's attack was effective and caused great damage to User B." Finally, the server generates the match results and sends them to the device. The device then displays the received match results to the user, notifying them, for example, "User A won."

[1836] This system allows users to create avatars that reflect their own emotional state and enjoy playing against other users. By combining it with an emotion engine, it is possible to provide a more realistic gaming experience in which the user's emotional state affects the game experience.

[1837] The processing flow will be explained below.

[1838] Step 1:

[1839] The user enters information such as name, age, hobbies, and gender into the application's input form. The user enters the required data into the form and presses the "Submit" button.

[1840] Step 2:

[1841] The terminal acquires the information entered by the user, converts it into JSON format, and sends it to the server as an HTTP request.

[1842] Step 3:

[1843] The camera on the device captures the user's facial expressions in real time and sends the captured images to the emotion engine.

[1844] Step 4:

[1845] The emotion engine analyzes the captured facial images to identify the user's emotional state. For example, a smile might be interpreted as "happiness," while a crease in the brow might be interpreted as "anger." The emotion data is then sent back to the device.

[1846] Step 5:

[1847] The device acquires the analyzed emotion data and sends it along with the user information to the server, where it is converted back into JSON format.

[1848] Step 6:

[1849] The server receives user information and emotion data in JSON format sent from the device, receives HTTP requests through the API endpoint, and converts the data into an internal data structure.

[1850] Step 7:

[1851] The server calls the generative AI model based on the received information, and passes the user information and emotion data to the generative AI model as parameters.

[1852] Step 8:

[1853] The generative AI model analyzes the input user information and emotional data and generates an avatar image based on this. For example, if a user's hobby is "reading" and the emotional data is "happiness," the model will create an avatar image that shows high knowledge and concentration, as well as a positive expression. The generated avatar image is then returned to the server.

[1854] Step 9:

[1855] The server receives the generated avatar image and assigns the corresponding ability scores and skills to the avatar image. These ability scores and skills are determined based on the user's hobbies and emotional data. For example, the avatar may be assigned "knowledge 85," "concentration 90," or "happiness 95."

[1856] Step 10:

[1857] The server sends avatar information, including assigned ability values ​​and skills, to the device. The avatar image and ability value / skill data are then collected and returned to the device in JSON format.

[1858] Step 11:

[1859] The terminal displays the avatar information received from the server to the user, who can visually check their own avatar image, its ability scores, and skills.

[1860] Step 12:

[1861] The user selects their own avatar and chooses an opponent from the match list. After selecting an opponent, the user presses the "Challenge" button.

[1862] Step 13:

[1863] The device sends information about the selected opponent to the server, including the avatar IDs and user IDs of both players, in JSON format.

[1864] Step 14:

[1865] The server receives the matching information and simulates the battle, comparing the ability values ​​and skills of the avatars of both players and simulating the battle based on a predefined algorithm.

[1866] Step 15:

[1867] The server generates the match results, creating a match log with details such as "User A's attack was effective and caused a lot of damage to User B," and then generates the final winner / loser result.

[1868] Step 16:

[1869] The server sends the generated match results to the device, formats the results in JSON format, and returns them to the device as an HTTP response.

[1870] Step 17:

[1871] The terminal displays the received match results to the user, who can receive a notification such as "User A won."

[1872] Example 2

[1873] 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."

[1874] Conventional systems could generate avatars based on basic information entered by the user (such as name, age, hobbies, and gender) and assign ability scores and skills, but they had the problem of not being able to generate avatars that reflected the user's emotional state or adjust ability scores. As a result, the user's emotional state was not reflected in the game experience, making it difficult to provide a more realistic feel.

[1875] 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.

[1876] In this invention, the server includes means for acquiring information such as name, age, hobbies, and gender input by a user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability scores and skills corresponding to the avatar image, means for displaying the avatar image, its ability scores, and skills to the user, means for capturing the user's facial expression, means for analyzing emotional data from the captured facial expression, means for transmitting the analyzed emotional data to the server, means for adjusting the ability scores and skills using the emotional data, means for conducting a match against another user, and means for displaying the match results. This enables the generation of an avatar and the adjustment of ability scores to reflect the user's emotional state, providing a more realistic experience.

[1877] "User information" refers to basic personal information such as name, age, hobbies, and gender that a user enters into an application.

[1878] A "terminal" is a device used by a user, and is a device for inputting and capturing information and transmitting and receiving data.

[1879] A "server" is a computer system that receives and processes data sent from a terminal.

[1880] A "generative AI model" is an artificial intelligence model for generating avatar images based on user information and emotional data.

[1881] An "avatar image" is visual data of a virtual character that represents a user and is created by a generative AI model.

[1882] "Ability score" is a numerical evaluation of a status given to an avatar, such as knowledge, concentration, happiness, etc.

[1883] A "skill" is an element that indicates a specific action or ability that is given to an avatar.

[1884] The "emotion engine module" is a software module that analyzes the user's facial expressions and identifies emotion data.

[1885] "Emotion data" is data that indicates the user's emotional state analyzed by the emotion engine module.

[1886] "Battle" means that the generated avatars virtually compete against each other based on their skills and ability values.

[1887] "Match results" refers to the result data such as win / loss and damage obtained from the match simulation.

[1888] This invention is a system that uses a generative AI model to generate an avatar image based on information and emotional data entered by a user, and assigns ability scores and skills appropriate to the avatar. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to generate an avatar and adjust its ability scores according to the user's emotional state. Specific embodiments of the invention are described in detail below.

[1889] Basic system configuration

[1890] This system is broadly composed of the following modules:

[1891] 1. User information input module

[1892] 2. Emotion Engine Module

[1893] 3. Avatar Generation Module

[1894] 4. Game Battle Module

[1895] User information input module

[1896] The user enters information such as name, age, hobbies, and gender into the application's input form. The device acquires this information, converts it into JSON format, and sends it to the server. For example, if a user enters "Hanako Sato, 25 years old, reading, female," the information is sent from the device to the server.

[1897] Emotion Engine Module

[1898] The device is equipped with a camera that captures the user's facial expressions in real time. The emotion engine module analyzes the user's emotions from the captured facial expressions. The information entered by the user and the emotion data obtained from the facial expressions are sent to the server. For example, if the user is smiling, the emotion engine analyzes it as "happiness" and sends the data to the server.

[1899] Avatar Generation Module

[1900] The server receives user information and emotion data sent from the device. Based on this information, it calls a generative AI model to generate an avatar image. The generative AI model generates the avatar image by taking into account the user's characteristics such as age, gender, hobbies, and emotions.

[1901] For example, if a user's hobby is "reading" and emotional data of "happiness" is sent, the generative AI model will create an avatar with high knowledge and concentration, and a positive facial expression. When the generated avatar image is returned to the server, the server will assign the avatar ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[1902] Game Battle Module

[1903] The user can select a generated avatar and choose an opponent from the match list. The device sends information about the opponent selected by the user to the server. The server receives the opponent information, compares the ability scores and skills of both avatars, and simulates a match.

[1904] The simulation results are generated in the form of, for example, "User A's attack was effective and caused great damage to User B." Finally, the server generates the match results and sends them to the device. The device then displays the received match results to the user, notifying them, for example, "User A won."

[1905] Specific examples

[1906] The user enters the following information:

[1907] Name: Hanako Sato

[1908] Age: 25

[1909] Hobbies: Reading

[1910] Gender: Female

[1911] The device converts this to JSON format and sends it to the server:

[1912] json

[1913] {

[1914] "Name": "Hanako Sato",

[1915] "age": "25 years old",

[1916] "Hobbies": "Reading",

[1917] "Gender": "Female"

[1918] }

[1919] Next, the user's smiling expression is captured by the device's camera. The emotion engine analyzes this expression and determines it as "happy." This data is also sent to the server:

[1920] json

[1921] {

[1922] "Emotion": "Happiness"

[1923] }

[1924] The server then calls the generative AI model based on the received data and generates an avatar, which is given knowledge of 85, concentration of 90, and happiness of 95.

[1925] When the user selects "User B" as their opponent, the device sends the following data to the server:

[1926] json

[1927] {

[1928] "Opponent": "User B"

[1929] }

[1930] The server performs a battle simulation, generates the results, and sends them to the device. The device then displays the results to the user, saying "User A won."

[1931] Prompt Sentence Examples

[1932] Here are some example prompts to input to a generative AI model:

[1933] "Generate the most suitable avatar based on the information (name, age, hobbies, gender) and emotional data (happiness, sadness, anger, etc.) entered by the user."

[1934] This system allows users to create avatars that reflect their own emotions and compete against other users. By utilizing the emotion engine, the user's emotional state directly affects the game experience, providing a greater sense of realism.

[1935] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1936] System processing flow

[1937] Step 1: Enter your user information

[1938] explanation:

[1939] The user enters basic information such as name, age, hobbies, and gender into the application's input form.

[1940] input:

[1941] User information such as name, age, hobbies, and gender

[1942] output:

[1943] User-entered information

[1944] Step 2: Convert and send information

[1945] explanation:

[1946] The terminal acquires the information entered by the user, converts it into JSON format, and sends it to the server.

[1947] input:

[1948] User-entered information

[1949] output:

[1950] User information in JSON format

[1951] Specific behavior:

[1952] Convert the input "Hanako Sato, 25 years old, reading, female" into the following JSON format on the terminal:

[1953] json

[1954] {

[1955] "Name": "Hanako Sato",

[1956] "age": "25 years old",

[1957] "Hobbies": "Reading",

[1958] "Gender": "Female"

[1959] }

[1960] This data is sent to the server.

[1961] Step 3: Receiving and parsing by the server

[1962] explanation:

[1963] The server receives the user information in JSON format sent from the terminal.

[1964] input:

[1965] User information in JSON format

[1966] output:

[1967] User information analysis results

[1968] Step 4: Capture facial expressions

[1969] explanation:

[1970] The camera on the device captures the user's facial expressions in real time.

[1971] input:

[1972] User's facial expression

[1973] output:

[1974] Captured facial expression image data

[1975] Step 5: Analyze the sentiment data

[1976] explanation:

[1977] An emotion engine module analyzes the captured facial expressions and generates emotion data for the user.

[1978] input:

[1979] Facial image data

[1980] output:

[1981] Emotional data (e.g., "happiness")

[1982] Specific behavior:

[1983] If the user is smiling, the emotion engine will parse it as "happy" and generate the data in the following format:

[1984] json

[1985] {

[1986] "Emotion": "Happiness"

[1987] }

[1988] Step 6: Sending Emotion Data

[1989] explanation:

[1990] The device transmits the analyzed emotion data to the server.

[1991] input:

[1992] Emotional Data

[1993] output:

[1994] Emotion data sent to the server

[1995] Step 7: Invoke the generative AI model

[1996] explanation:

[1997] The server calls the generative AI model based on the received user information and emotion data.

[1998] input:

[1999] User information and emotional data

[2000] output:

[2001] Executing a generative AI model by inputting a prompt

[2002] Step 8: Generate Avatar Images

[2003] explanation:

[2004] The generative AI model generates an avatar image based on the prompt text.

[2005] input:

[2006] Prompt sentence, user information, emotion data

[2007] output:

[2008] Generated avatar image

[2009] Specific behavior:

[2010] Enter the following prompt into the generative AI model:

[2011] "Generate the most suitable avatar based on the information (name, age, hobbies, gender) and emotional data (happiness, sadness, anger, etc.) entered by the user."

[2012] Step 9: Adding Avatar Ability Scores

[2013] explanation:

[2014] The server assigns the generated avatar ability values ​​such as "Knowledge 85," "Concentration 90," and "Happiness 95."

[2015] input:

[2016] Generated avatar image

[2017] output:

[2018] Avatar with ability scores

[2019] Step 10: Choose your avatar and opponent

[2020] explanation:

[2021] The user selects a generated avatar and chooses an opponent from the match list.

[2022] input:

[2023] Avatar with ability scores

[2024] output:

[2025] Selected Opponents

[2026] Specific behavior:

[2027] The user uses the generated avatar to select "User B" as an opponent.

[2028] Step 11: Send Opponent Information

[2029] explanation:

[2030] The terminal transmits information about the opponent selected by the user to the server.

[2031] input:

[2032] Opponent Information

[2033] output:

[2034] Opponent information sent to the server

[2035] Specific behavior:

[2036] The device sends the following data to the server:

[2037] json

[2038] {

[2039] "Opponent": "User B"

[2040] }

[2041] Step 12: Run a match simulation

[2042] explanation:

[2043] The server receives information about the opponent, compares the ability values ​​and skills of both avatars, and simulates the match.

[2044] input:

[2045] Avatar ability scores and opponent information

[2046] output:

[2047] Battle simulation results

[2048] Step 13: Generate and send match results

[2049] explanation:

[2050] The server generates the results of the battle simulation in JSON format and sends them to the device.

[2051] input:

[2052] Battle simulation results

[2053] output:

[2054] Match results in JSON format

[2055] Specific behavior:

[2056] The server generates the result: "User A's attack was effective and caused a lot of damage to User B. User A wins."

[2057] Step 14: Viewing Match Results

[2058] explanation:

[2059] The terminal displays the received match results to the user and notifies the user, such as "User A won."

[2060] input:

[2061] Match results in JSON format

[2062] output:

[2063] Results displayed to the user

[2064] Specific behavior:

[2065] The device displays the message "User A has won" to the user.

[2066] The above is the processing flow and specific steps of this system's program.

[2067] (Application example 2)

[2068] 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."

[2069] Conventional avatar generation systems rely solely on user information, making it difficult to generate personalized avatars that reflect the user's real-time emotional state. Furthermore, in virtual shopping experiences, they are unable to recommend products based on the user's emotions. Therefore, there is a need for a method to improve the quality of the shopping experience.

[2070] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring information such as the name, age, hobbies, and gender input by the user, means for transmitting the acquired information to the server, means for calling a generation AI model that generates an avatar image using the information received by the server, means for receiving the avatar image generated by the generation AI model, means for assigning ability values ​​and skills corresponding to the avatar image, means for adjusting the avatar's ability values ​​and skills using an emotion engine that analyzes the user's emotions, means for displaying the avatar image, its ability values, and skills to the user, means for conducting a battle with other users, means for displaying the battle results, and means for recommending products in a virtual store based on the user's emotions. This makes it possible to generate an avatar that reflects the user's emotional state, improving the quality of the battle and shopping experience.

[2071] "User information" is information about a user's personal information, such as the user's name, age, hobbies, and gender, that is obtained by the application.

[2072] An "emotion engine" refers to technology or software that analyzes a user's facial expressions and behavior to detect their emotional state.

[2073] "Generative AI model" refers to an artificial intelligence algorithm that generates high-quality avatar images based on user information and emotional data.

[2074] "Avatar image" refers to a character image that reflects the user's characteristics and is generated by a generative AI model.

[2075] "Ability scores" are numerical representations of specific characteristics or status given to an avatar.

[2076] "Skills" refer to specific techniques or abilities that an avatar possesses and are used in battles and other actions.

[2077] "Virtual Store" refers to a virtual store where users can browse and purchase products via the Internet.

[2078] "Product recommendation" refers to suggesting appropriate products to a user based on the user's past behavior and current emotional state.

[2079] "Competition" refers to an activity in which generated avatars compete against each other in simulation or real time.

[2080] "Match results" refers to the information on victory or defeat and results that is displayed after avatars have competed against each other.

[2081] In this invention, a system is constructed that generates an avatar image and its ability values ​​and skills based on information and emotional state input by a user, and uses these to provide a personalized shopping experience in a virtual store.

[2082] First, the device acquires information such as the user's name, age, hobbies, and gender, which is then converted into JSON format and sent to the server.

[2083] The device captures the user's facial expressions through the camera. The emotion engine analyzes the user's emotions from the captured facial expressions and generates emotion data such as "happiness" or "sadness." This emotion data is also sent to the server.

[2084] The server receives user information and emotion data sent from the device. Using this information, the server invokes a generative AI model to generate an avatar image that reflects the user's characteristics. The generative AI model uses technologies such as Stable Diffusion and Midjourney.

[2085] The generated avatar image is returned to the server, and the avatar is given ability scores and skills such as "knowledge" and "concentration." This allows the ability scores to be adjusted according to the user's emotions.

[2086] Next, the user shops in the virtual store through the generated avatar. The server uses the user's emotional data to recommend appropriate products. This product recommendation is also performed by the server, providing the user with an optimal shopping experience.

[2087] For example, if a user enters information such as "Hanako Sato, 25 years old, reading, female" and smiles at the camera, the emotion engine will interpret this as "happiness." The generative AI model will generate an avatar with high knowledge and concentration, and a positive expression. This avatar will be given ability scores such as "knowledge 85," "concentration 90," and "happiness 95."

[2088] The system of this invention makes it possible to generate an avatar that reflects the user's emotional state and to recommend products based on that avatar, thereby improving the quality of the shopping experience in a virtual store.

[2089] Examples of prompts are:

[2090] "Create an avatar based on the following user information: {'Name': 'Hanako Sato', 'Age': 25, 'Hobbies': 'Reading', 'Gender': 'Female'}, Emotion: 'Happiness'. Give the avatar a costume that is easy to read and the ability scores of Knowledge 85, Concentration 90, and Happiness 95."

[2091] By inputting this prompt into a generative AI model, an avatar that best suits the user can be created.

[2092] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2093] Step 1:

[2094] The user inputs information such as name, age, hobbies, and gender into the device. The input data is converted to JSON format by the device. This data is sent to the server as user information. The input here is the user's personal information, and the output is user information in JSON format.

[2095] Step 2:

[2096] The device's camera captures the user's facial expression. The captured image data is sent to the emotion engine. The emotion engine analyzes the image data and recognizes the user's emotion. The input in this step is the image data, and the output is the analyzed emotion data.

[2097] Step 3:

[2098] The device transmits the captured emotion data to the server, which receives the transmitted user information and emotion data and integrates this data. The input is the user information and emotion data, and the output is the integrated dataset.

[2099] Step 4:

[2100] The server uses the integrated dataset to call the generative AI model to generate a prompt. The generated prompt sentence is input to the AI ​​model to generate an avatar image. The input is the prompt sentence, and the output is the generated avatar image.

[2101] Step 5:

[2102] The server receives the generated avatar image and assigns appropriate ability scores and skills to the avatar. These ability scores and skills are determined based on the user's personal information and emotional data. The input is the avatar image and user data, and the output is an avatar with the assigned ability scores and skills.

[2103] Step 6:

[2104] The server sends an avatar with assigned ability scores and skills to the device. The device displays this avatar to the user, who can then customize it. The input is the avatar with assigned ability scores and skills, and the output is the avatar displayed to the user.

[2105] Step 7:

[2106] The user receives product recommendations in a virtual store using an avatar. The server recommends optimal products based on the user's emotional data. The input is the emotional data and the avatar, and the output is a list of recommended products.

[2107] Step 8:

[2108] The user browses and purchases the recommended products in the virtual store. The purchase data is sent to the server, which then provides the products to the user. The input is a list of recommended products, and the output is information about the purchased products.

[2109] This allows users to enjoy a more personalized shopping experience through avatars that reflect their emotional state.

[2110] 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.

[2111] 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.

[2112] 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.

[2113] 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.

[2114] 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.

[2115] 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.

[2116] 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).

[2117] 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.

[2118] 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."

[2119] 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.

[2120] 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).

[2121] 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.

[2122] 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.

[2123] 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.

[2124] 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.

[2125] 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.

[2126] 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.

[2127] 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.

[2128] 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.

[2129] 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.

[2130] 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.

[2131] The following is further disclosed regarding the above embodiment.

[2132] (Claim 1)

[2133] A means of acquiring information such as name, age, hobbies, and gender entered by the user;

[2134] means for transmitting the acquired information to a server;

[2135] A means for calling a generative AI model that generates an avatar image using the information received by the server;

[2136] means for receiving an avatar image generated by the generative AI model;

[2137] A means for assigning ability values ​​and skills corresponding to the avatar image;

[2138] means for displaying an avatar image and its ability values ​​and skills to a user;

[2139] A means for playing against other users;

[2140] a means for displaying the results of the match;

[2141] A system including:

[2142] (Claim 2)

[2143] The system of claim 1, wherein the generative AI model generates images based on user hobby information.

[2144] (Claim 3)

[2145] 2. The system according to claim 1, wherein the ability values ​​and skills are determined based on information input by the user.

[2146] "Example 1"

[2147] (Claim 1)

[2148] A means of acquiring information such as name, age, hobbies, and gender entered by the user;

[2149] means for converting the acquired information into a data format and transmitting the data to a server;

[2150] means for analyzing the received information by the server;

[2151] A means for generating an avatar image by calling a generative AI model based on the analyzed information;

[2152] means for receiving an avatar image generated by the generative AI model;

[2153] A means for assigning ability values ​​and skills corresponding to the avatar image;

[2154] means for displaying an avatar image and its ability values ​​and skills to a user;

[2155] a means for a user to select an opponent;

[2156] means for transmitting information of the selected opponent to a server;

[2157] a means for the server to receive opponent information and perform a battle simulation;

[2158] A means for generating and displaying a match result;

[2159] A system including:

[2160] (Claim 2)

[2161] The system of claim 1, wherein the generative AI model generates images based on user hobby information.

[2162] (Claim 3)

[2163] 2. The system according to claim 1, wherein the ability values ​​and skills are determined based on information input by the user.

[2164] "Application Example 1"

[2165] (Claim 1)

[2166] A means of acquiring information such as name, age, hobbies, and gender entered by the user;

[2167] means for transmitting the acquired information to a server;

[2168] A means for calling a generative AI model that generates an avatar image using the information received by the server;

[2169] means for receiving an avatar image generated by the generative AI model;

[2170] A means for assigning ability values ​​and skills corresponding to the avatar image;

[2171] means for displaying an avatar image and its ability values ​​and skills to a user;

[2172] A means for playing against other users;

[2173] a means for displaying the results of the match;

[2174] A means for performing virtual try-on based on the generated avatar image;

[2175] a means for displaying the results of the virtual try-on;

[2176] A system including:

[2177] (Claim 2)

[2178] The system of claim 1, wherein the generative AI model generates images based on user hobby information.

[2179] (Claim 3)

[2180] 2. The system according to claim 1, wherein the ability values ​​and skills are determined based on information input by the user.

[2181] "Example 2: Combining Emotion Engines"

[2182] (Claim 1)

[2183] A means of acquiring information such as name, age, hobbies, and gender entered by the user;

[2184] means for transmitting the acquired information to a server;

[2185] A means for calling a generative AI model that generates an avatar image using the information received by the server;

[2186] means for receiving an avatar image generated by the generative AI model;

[2187] A means for assigning ability values ​​and skills corresponding to the avatar image;

[2188] means for displaying an avatar image and its ability values ​​and skills to a user;

[2189] means for capturing a user's facial expression;

[2190] means for analyzing emotion data from the captured facial expressions;

[2191] means for transmitting the analyzed emotion data to a server;

[2192] A means of adjusting ability scores and skills using emotional data,

[2193] A means for playing against other users;

[2194] a means for displaying the results of the match;

[2195] A system including:

[2196] (Claim 2)

[2197] 2. The system of claim 1, wherein the generative AI model generates images based on a user's hobby information and emotion data.

[2198] (Claim 3)

[2199] 2. The system according to claim 1, wherein the ability values ​​and skills are determined based on user input information and emotion data.

[2200] "Application example 2 when combining emotion engines"

[2201] (Claim 1)

[2202] A means of acquiring information such as name, age, hobbies, and gender entered by the user;

[2203] means for transmitting the acquired information to a server;

[2204] A means for calling a generative AI model that generates an avatar image using the information received by the server;

[2205] means for receiving an avatar image generated by the generative AI model;

[2206] A means for assigning ability values ​​and skills corresponding to the avatar image;

[2207] A means for adjusting the avatar's ability values ​​and skills using an emotion engine that analyzes the user's emotions;

[2208] means for displaying an avatar image and its ability values ​​and skills to a user;

[2209] A means for playing against other users;

[2210] a means for displaying the results of the match;

[2211] A means for recommending products in a virtual store according to the user's emotions;

[2212] A system including:

[2213] (Claim 2)

[2214] The system of claim 1, wherein the generative AI model generates images based on user hobby information.

[2215] (Claim 3)

[2216] 2. The system according to claim 1, wherein the ability values ​​and skills are determined based on the user's input information and analyzed emotions. [Explanation of symbols]

[2217] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of acquiring information such as name, age, hobbies, and gender entered by the user; means for transmitting the acquired information to a server; A means for calling a generative AI model that generates an avatar image using the information received by the server; means for receiving an avatar image generated by the generative AI model; A means for assigning ability values ​​and skills corresponding to the avatar image; means for displaying an avatar image and its ability values ​​and skills to a user; A means for playing against other users; a means for displaying the results of the match; A system including:

2. The system of claim 1 , wherein the generative AI model generates images based on user hobby information.

3. 2. The system according to claim 1, wherein the ability values ​​and skills are determined based on information input by the user.

Images