System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to input a color and an image; means including generative artificial intelligence for generating a design based on the input color and image; means for displaying the generated design; means for receiving a selection of the generated design and feedback; and means for recording the feedback and reflecting the feedback on a next design generation.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] Nail art is an important way to express one's individuality and mood, and the variety of designs is extremely wide. However, it takes time and effort to come up with a new design that suits oneself every month, and it is particularly difficult to create an original design that is unique to oneself. Furthermore, conventional systems that only provide general design ideas cannot fully respond to the user's preferences. It is desirable to provide a system that solves these issues and allows users to easily enjoy new nail designs. [Means for solving the problem]

[0005] To solve the above problems, the present invention proposes the following means. The present invention provides a system including a means for a user to input a color and an image, a means including a generation artificial intelligence that generates a design based on the input color and image, a means for displaying the generated design, a means for accepting selections and feedback on the generated design, and a means for recording the feedback and reflecting it in the next design generation. Furthermore, the generation artificial intelligence generates personalized designs based on the user's past selections and preferences, allowing the user to always receive new nail designs that are tailored to them. Furthermore, the design generation means generates and suggests multiple design proposals to the user, allowing the user to choose their favorite design from a wide range of options.

[0006] "User" refers to the individual or end user who utilizes the system to input, review, select, and provide feedback on nail designs.

[0007] "Color" refers to the specific shade or hue used as the base or decoration of the nail design, as input by the user.

[0008] "Image" refers to the specific concept or vision of the nail design theme, motif, or decoration entered by the user.

[0009] "Means" refers to the combination of elements, components, software and hardware required for the system to perform a specific function.

[0010] "Design" refers to the specific shape and pattern of nail art generated by artificial intelligence based on the colors and images input by the user.

[0011] "Generative AI" refers to algorithms and machine learning models that analyze user input data and automatically generate nail designs.

[0012] "Display" refers to an interface that allows the user to visually check the generated nail design proposal.

[0013] "Selection" refers to the act of a user choosing their preferred nail design from multiple proposed nail design ideas.

[0014] "Feedback" refers to the user's evaluation and impressions of the design they selected, as well as additional information to be reflected in future design generation.

[0015] "Recording" refers to the act of storing user feedback and preferences in a database and using them as reference for future design generation. [Brief explanation of the drawings]

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

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

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

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

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

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

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

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

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

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

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0037] This invention is a system in which a generation AI (artificial intelligence) automatically generates nail designs based on the colors and images input by the user, proposes them to the user, and receives feedback to improve the proposals from the next time onwards. Specific embodiments of this system are described below.

[0038] Program processing overview

[0039] User Input and Data Submission

[0040] The user first launches the system's terminal application and inputs their preferred color and design image. For example, if the user inputs "blue" and "stars" as their preferred color and design image, the terminal will acquire this information, convert it into a data packet, and send it to the server.

[0041] Nail design generation

[0042] The server analyzes the user's input data received from the device and activates the AI ​​generator, which generates multiple nail design ideas based on the analyzed colors and design image. For example, there are designs based on a blue base and a star motif, a design with stars on a blue and white gradient, and a design with silver stars on a blue background.

[0043] Personalized suggestions

[0044] The AI ​​then references the user's past preference data and generates a more personalized design based on this. If the user has previously selected a "night sky motif" design, the AI ​​will also take this into account when generating a design.

[0045] Send and view your designs

[0046] The generated nail design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data and displays multiple design proposals on the interface. The user can visually check these proposed designs.

[0047] User Choice and Feedback

[0048] The user selects the nail design they like best from the proposed options. Along with their selection, the user also inputs feedback, such as their evaluation and thoughts on the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0049] Recording feedback and incorporating it into the next session

[0050] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0051] Specific examples

[0052] For example, if a user inputs a design with the theme of "blue" and "stars," the AI ​​will generate a design that combines blue and silver stars, or a design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will use that information to generate a more detailed nail design with a night sky motif. This allows users to always enjoy new nail designs that suit their tastes.

[0053] This system allows users to easily try out new nail designs, saving time and effort while providing an original design experience that suits their individual tastes.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] The user launches the nail app and is presented with an interface to input their preferred color (e.g., "blue") and design image (e.g., "star"). The user enters this information and presses the send button.

[0057] Step 2:

[0058] The terminal receives the user's input data (color and design image), converts it into a data packet, and sends the converted data packet to the server.

[0059] Step 3:

[0060] The server receives user input data from the device, records it in a database, analyzes the data, and uses it as input for the generation AI.

[0061] Step 4:

[0062] The AI ​​then generates multiple nail design ideas based on the analyzed colors and design image, such as a blue-based star-shaped design or a blue and white gradient with stars.

[0063] Step 5:

[0064] The server converts the generated nail design proposal back into a data packet and transmits it to the terminal.

[0065] Step 6:

[0066] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually confirm these design proposals.

[0067] Step 7:

[0068] The user selects the design they like best from the displayed nail design suggestions, and along with their selection, they can enter their evaluation and thoughts on the design, as well as any requests they would like to have reflected in the next design generation, as feedback.

[0069] Step 8:

[0070] The terminal obtains the user's selection and feedback data, converts it into a data packet, and sends the converted data packet to the server.

[0071] Step 9:

[0072] The server analyzes the received feedback data and updates the user preference database. The updated data is reflected in subsequent design generation, resulting in more personalized design suggestions.

[0073] Example 1

[0074] 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."

[0075] Conventional nail design generation systems have difficulty efficiently generating designs that match the user's preferences. In addition, they lack the mechanism for incorporating user feedback into the next design generation, which makes it difficult to provide personalized suggestions.

[0076] 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.

[0077] In this invention, the server includes means for a user to input a color and an image, means including a generation artificial intelligence that generates a prompt sentence based on the input color and image and generates a plurality of design proposals, means for displaying the generated designs, means for accepting selection and feedback on the generated designs, and means for recording the feedback and reflecting it in the next design generation. This enables efficient design generation based on the user's preferences and personalized proposals by reflecting the feedback in the next design proposal.

[0078] A "user" is a person who uses the system's terminal application to input their preferred colors and design images, and select and evaluate the generated nail designs.

[0079] "Color" refers to the color information that forms the basis of the nail design that the user inputs into the system.

[0080] An "image" is a visual concept of a nail design motif or theme that a user inputs into the system.

[0081] A "prompt sentence" is a text-based input sentence that instructs the generative AI model to generate a design based on the colors and images entered by the user.

[0082] A "generative AI model" is an artificial intelligence algorithm that generates multiple nail design ideas based on user input data.

[0083] A "data packet" is a data format for efficiently transferring user input information and generated design data.

[0084] The "preference database" is a database that stores information on users' past choices and feedback and reflects this information in the next design generation.

[0085] "Feedback" refers to response information such as evaluations, impressions, and requests made by users regarding the generated design.

[0086] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, proposes them to the user, and receives feedback to improve the proposals for the next time and thereafter. Specific embodiments of this system are described below.

[0087] First, the user launches the system's terminal application. The terminal displays an input form for entering color and design image through the user interface. For example, the user enters "blue" and "stars" as their preferred color and design image. The terminal acquires this input information, converts it into a JSON-formatted data packet, and sends the data packet to the server.

[0088] The server analyzes the received data packet and extracts the color and design image specified by the user. Then, the server generates a prompt based on the analyzed data. For example, it generates a text prompt such as, "The color entered by the user is blue, and the design image is a star. Please generate a nail design."

[0089] Using the generated prompt, the server launches a generative AI model (e.g., OpenAI's GPT-3) to generate multiple nail design ideas. The generative AI model follows the prompt and outputs multiple design ideas, such as a design that combines blue and silver stars, or a design with stars arranged on a blue and white gradient.

[0090] The server also references the user's past preference data to generate personalized designs that take the user's preferences into account. If the user previously selected a "night sky motif" design, a night sky-themed design will also be generated based on that information.

[0091] The generated design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data and displays multiple design proposals on the user interface. For example, each design proposal is displayed as a thumbnail image in a 2-column by 2-row grid format.

[0092] The user selects the nail design they like best from the proposed options. Along with their selection, they can input feedback such as their evaluation and impressions of the design, as well as requests they would like reflected in the next design generation. The device converts this feedback information into data packets and sends them to the server.

[0093] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for the next design generation, resulting in more personalized design suggestions. This process allows users to easily try out new nail designs, saving time and effort while providing an original design experience tailored to their individual tastes.

[0094] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0095] Step 1: User Input and Data Submission

[0096] The user launches the system's terminal application and inputs their preferred color and design image. The input data, such as "blue" and "star," is converted into a JSON-formatted data packet by the terminal. The terminal then sends the generated data packet to the server. The input is the user's color and design image, and the output is the data sent to the server.

[0097] Step 2: Receiving and analyzing data on the server

[0098] The server receives a data packet sent from the terminal. For example, if the received data packet is {"color": "blue", "design": "star"}, the server analyzes the data packet and extracts the color "blue" and the design "star". This is the analysis of the input data, and the output is the analysis result.

[0099] Step 3: Generate prompts and launch the AI ​​model

[0100] The server generates a prompt based on the analyzed color and design image. For example, the generated prompt might be, "The color entered by the user is blue, and the design image is a star. Please generate a nail design." The server then inputs this prompt into a generative AI model (e.g., OpenAI's GPT-3) to generate nail design suggestions. The input is the prompt, and the output is the generated design suggestions.

[0101] Step 4: Personalized offers

[0102] In addition to the generated nail design suggestions, the server also references the user's past preference data. Based on this, the generative AI model also generates more personalized design suggestions. For example, if a user previously selected a "night sky motif" design, a design based on this information will also be added. The input is past preference data, and the output is personalized design suggestions.

[0103] Step 5: Send and view your design

[0104] The server converts the generated design proposals into data packets and sends them to the terminal. The terminal analyzes the received design data and displays multiple design proposals on a user interface, for example, displaying each design proposal as a thumbnail in a 2-column by 2-row grid format. The input is the design proposal data packets, and the output is a visual display for the user.

[0105] Step 6: User selection and feedback

[0106] The user selects one of the displayed design proposals and enters their evaluation and feedback on that design. The device converts this feedback into a data packet and sends it back to the server. The input is the user's selection and feedback, and the output is the data sent to the server.

[0107] Step 7: Record feedback and incorporate it next time

[0108] The server analyzes the received feedback data and updates the user preference database. The updated data is used as a reference in the next design generation, and more personalized proposals are made. The input is the feedback data, and the output is the updated preference database. This step enables the system to more accurately meet user needs by integrating the user's design preference information.

[0109] (Application Example 1)

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

[0111] Existing nail design proposal systems only generate temporary designs based on the colors and images input by users, and the problem is that no specific proposals that can be utilized in salon treatments are made. Furthermore, since the communication means between users and service providers (nail salon staff) are limited, personalized design proposals are not fully made. As a result, it is difficult to improve user satisfaction, and there is no guarantee that the quality of the service will be maintained uniformly.

[0112] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0113] In this invention, the server includes means for a user to input a color and an image, means including a generation artificial intelligence that generates a design based on the input color and image, means for displaying the generated design, means for accepting selections and feedback on the generated design, means for recording the feedback and reflecting it in the next design generation, means for generating design proposals based on the user's preferences in advance and sharing them with a service provider, and means for the service provider to review the design proposals and make personalized suggestions to the user, thereby enabling more effective communication between the user and the service provider and providing personalized services.

[0114] "User" refers to an individual who uses the system to input colors and design ideas and receive design proposals. It may also refer to a customer of a nail salon.

[0115] "Means for inputting colors and images" refers to an interface (e.g., a touch screen or voice input) that a user uses to input their preferred colors and design images.

[0116] "Generative AI" refers to AI technology that automatically generates designs based on input color and image information. Examples include generative AI models such as DALL-E and StyleGAN.

[0117] "Means for displaying the design" refers to a display or screen for visually presenting the generated nail design to the user.

[0118] "Means for selecting designs and receiving feedback" refers to an interface that allows users to select their preferred design from the proposed designs and input their evaluation of the design and requests for improvement.

[0119] "Means for recording feedback and reflecting it in the next design generation" refers to a system in which feedback information obtained from users is stored in a database and used in generating designs from the next time onwards.

[0120] "Service provider" refers to professionals who provide nail design installation services to users, such as nail salon staff and hairdressers.

[0121] "Means for generating design proposals in advance based on user preferences and sharing them with service providers" refers to a communication means for preparing design proposals in advance based on user input information and making them available for service providers to view.

[0122] "Means for making personalized suggestions" refers to a system or interface that allows a service provider to present optimal design proposals based on a user's individual preferences and past selection data.

[0123] This invention provides a system that automatically generates nail designs based on the colors and design image input by the user, proposes them to the user and service providers (such as nail salon staff), collects feedback, and reflects it in future proposals. Specific embodiments of this system are described below.

[0124] System configuration

[0125] The system mainly consists of the following hardware and software components:

[0126] 1. User Interface (UI):

[0127] Smartphone: A device that allows users to input color and design images.

[0128] Application (app): Software that allows users to input, review, and provide feedback on colors and design images.

[0129] 2. Server:

[0130] Cloud server: Receives, processes, and stores data.

[0131] Generative AI models: Generate nail designs based on user input. Examples include models such as DALL-E and StyleGAN.

[0132] Database: Stores user preferences and feedback information and uses it for the next design generation. For example, AWS RDS is used.

[0133] 3. Service Provider Interface:

[0134] Tablet or desktop PC: A device for salon staff to review design ideas based on customer preferences and feedback.

[0135] Application: Software that allows staff to review design proposals and make suggestions to users as needed.

[0136] Processing flow

[0137] 1. User input:

[0138] Users start the app and input their preferred colors and design image, for example, selecting elements such as "blue" or "stars" as their preferences.

[0139] 2. Data transmission:

[0140] The entered data is sent to the cloud server via the application.

[0141] 3. Design generation:

[0142] The server uses a generative AI model to generate multiple nail design ideas based on the input information.

[0143] The generated design proposals are sent back to the user's app in JSON format.

[0144] 4. Design Proposal:

[0145] The design proposals generated by the user's application are visually displayed, and the user can select the design they prefer.

[0146] The selected design proposal and feedback are sent back to the server.

[0147] 5. Sharing with Service Providers:

[0148] User preferences and feedback are also shared with the service provider's interface, allowing staff to make suggestions based on the user's preferences and feedback in advance.

[0149] 6. Record feedback and incorporate it into your next proposal:

[0150] The server records user feedback in a database and uses this information in the next design generation.

[0151] Specific examples

[0152] For example, if a user inputs a design based on the themes of "blue" and "stars," the generation AI will generate a design using prompts like the following:

[0153] Prompt: Use a generative AI model to generate a nail design based on the following criteria:

[0154] conditions:

[0155] Basic color: blue

[0156] Design image: Star

[0157] Past feedback: Users tend to prefer designs with a night sky theme

[0158] Based on this prompt, the generative AI will generate a nail design that matches the user's preferences and suggest it to the user and service provider, thereby realizing personalized, high-quality service provision.

[0159] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0160] Step 1:

[0161] A user launches a smartphone application and inputs their preferred color (e.g., "blue") and design image (e.g., "star"). The input information is obtained in text or image format. This information is converted into a JSON-formatted data packet for the next processing step.

[0162] Step 2:

[0163] The device sends the generated JSON data packet to a cloud server, which receives it and parses it as input to launch a generative AI model (e.g., DALL-E).

[0164] Step 3:

[0165] Based on the analyzed data, the server generates a prompt to generate the nail design requested by the user. For example, the prompt might be in the form of "Base color is blue, design image is stars, and based on past feedback, create a design with a night sky theme." The generative AI model uses this prompt to generate multiple nail design candidates.

[0166] Step 4:

[0167] The server then packets the generated nail design ideas in JSON format and resends them to the user's device. The user's application visually displays the received design ideas and arranges them in a format that the user can view.

[0168] Step 5:

[0169] The user selects the design they like from the presented options. Along with the selected design, they enter their feedback (e.g., their rating of the design and their requests for the next design) into the application. The feedback information is then converted back into a JSON-formatted data packet.

[0170] Step 6:

[0171] The device sends the feedback information entered by the user to the cloud server, which analyzes the received feedback and records it in a database, which is used to update the user preference database.

[0172] Step 7:

[0173] The server prepares data to be used for subsequent design generation based on the updated preference database. Service providers (nail salon staff) can also use a dedicated application to view design suggestions based on the user's preferences and feedback.

[0174] Step 8:

[0175] The service provider uses a tablet or desktop application to check the design ideas and feedback information selected by the user, and then proposes and performs a personalized nail design. This allows the user to find out which design best suits their preferences before visiting the salon.

[0176] Through this series of processes, users can easily receive personalized nail designs that suit their preferences, and service providers can use this information to provide high-quality services.

[0177] 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.

[0178] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and further recognizes the user's emotional state to make personalized suggestions. An embodiment of this system will be described in detail below.

[0179] Program processing overview

[0180] User Input and Emotion Recognition

[0181] When a user launches the nail app, an interface appears. The user inputs their preferred color (e.g., "blue") and design image (e.g., "star"). The emotion engine then analyzes the user's facial expressions and voice to recognize their emotional state. For example, it recognizes that the user is relaxed.

[0182] Data transmission and analysis

[0183] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), converting them into data packets, which are then sent to the server.

[0184] Nail design generation

[0185] The server analyzes the data packets received from the device and uses them as input for the generation AI. The generation AI generates multiple nail design proposals based on the user's specified colors and design image, as well as the analysis results of the emotion engine. For example, it could create a star-shaped design with a calm atmosphere based on blue, matching a relaxed emotional state.

[0186] Personalized suggestions

[0187] The generative AI also references the user's past preference data to generate more personalized designs. For example, it can generate a calming design with a starry sky motif, taking into account the user's past choice of "night sky motif" design and their current relaxed emotional state.

[0188] Send and view your designs

[0189] The generated nail design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data packets and displays multiple design proposals on the interface, allowing the user to visually check these design proposals.

[0190] User Choice and Feedback

[0191] The user selects the nail design they like best from the displayed options. Along with their selection, the user also enters feedback, such as their evaluation and thoughts on the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0192] Recording feedback and incorporating it into the next session

[0193] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0194] Specific examples

[0195] For example, if a user inputs the theme "blue" and "stars" and the emotion engine recognizes this as "relaxing," the AI ​​will generate a calming design combining blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will generate a nail design with a more detailed night sky motif based on that information. This allows users to always enjoy new nail designs that suit their tastes.

[0196] The system allows users to easily try out new nail designs, saving time and effort while providing an original design experience that suits their individual tastes and emotional state at the time.

[0197] The processing flow will be explained below.

[0198] Step 1:

[0199] The user launches the nail app and is presented with an interface where they can input their preferred color (e.g., "blue") and design image (e.g., "star"). The user inputs this information.

[0200] Step 2:

[0201] The emotion engine works by analyzing the user's facial expressions and voice, and as a result, it recognizes the user's emotional state (e.g., relaxed).

[0202] Step 3:

[0203] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), converting them into data packets, which are then sent to the server.

[0204] Step 4:

[0205] The server analyzes the data packets received from the device and uses them as input for the generation AI based on the user's specified colors, design image, and emotional state.

[0206] Step 5:

[0207] The AI ​​then generates multiple nail design ideas based on the analyzed data, for example, a star-shaped design with a blue base and a calming atmosphere that matches a relaxed emotional state.

[0208] Step 6:

[0209] The AI ​​will refer to a database of the user's past preferences, for example, by taking into account the user's past choice of "night sky motif" design and their current feeling of relaxation, and generate a design using a more detailed night sky motif.

[0210] Step 7:

[0211] The server converts the generated nail design proposal into a data packet and transmits it to the terminal.

[0212] Step 8:

[0213] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually confirm these design proposals.

[0214] Step 9:

[0215] The user selects the design they like best from the displayed nail design suggestions, and along with their selection, they can enter their evaluation and thoughts on the design, as well as any requests they would like to have reflected in the next design generation, as feedback.

[0216] Step 10:

[0217] The terminal obtains the user's selection and feedback data, converts it into a data packet, and sends the data packet to the server.

[0218] Step 11:

[0219] The server analyzes the received feedback data and updates the user preference database. The updated data is reflected in subsequent design generation, resulting in more personalized design suggestions.

[0220] This allows the system to provide original nail designs that match the user's preferences and current emotional state.

[0221] Example 2

[0222] 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."

[0223] Conventional nail design generation systems are unable to propose designs that take into account the user's emotional state, making it difficult to increase user satisfaction. Furthermore, there is a lack of a means to effectively utilize past preference data to generate personalized designs. Therefore, there is a need for a system that can propose optimal designs for each individual user.

[0224] 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.

[0225] In this invention, the server includes a means for the user to input colors and images, a means for analyzing the user's facial expressions and voice to recognize the emotional state, and a means including a generation artificial intelligence that generates designs based on the input colors and images and the analyzed emotional state, thereby making it possible to automatically generate personalized nail designs according to the user's emotional state.

[0226] "User" means an individual who utilizes the system to input colors and images to generate nail designs, and provides selections and feedback on the generated designs.

[0227] "Color" is a visual element that forms the basis or accent of the design entered by the user, and is a basic element that makes up the appearance of a nail design.

[0228] An "image" is a visual element that serves as the theme or motif of a design entered by the user, and constitutes the specific shape or pattern of the nail design.

[0229] "Emotional state" refers to a psychological state that is recognized by analyzing the user's facial expressions and voice, and represents emotions such as relaxation or excitement.

[0230] "Generative AI" refers to advanced algorithms and models that automatically generate nail designs based on input data.

[0231] The "display means" refers to an interface or device that allows the user to visually check the generated nail design.

[0232] "Feedback" refers to information such as the user's evaluation and impressions of the design they selected, and requests they would like to reflect in the next design generation.

[0233] A "data packet" is a unit of digital data that compiles information such as a user's input data, emotional state, and generated design.

[0234] A "server" is a computer system that receives, analyzes, and stores data sent by users.

[0235] "Terminal" means a device on which a user enters input and displays a design, including a smartphone or tablet.

[0236] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and further recognizes the user's emotional state to make personalized suggestions. An embodiment of this system will be described in detail below.

[0237] User Input and Emotion Recognition

[0238] When the device launches the nail application, a user interface is displayed. The user inputs their preferred color (e.g., "blue") and design image (e.g., "star"). Furthermore, the device incorporates an emotion engine (e.g., facial expression recognition API and voice analysis API) that analyzes the user's facial expressions and voice to recognize their emotional state. For example, it can recognize that the user is relaxed.

[0239] Data transmission and analysis

[0240] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), and generates a data packet that combines these data. The generated data packet is then sent to a server via the Internet.

[0241] Nail design generation

[0242] The server analyzes the received data packets and generates a nail design using a generative AI model (e.g., a large-scale language model). This generative AI generates multiple nail design proposals based on the user's specified color "blue," the design image "star," and the recognized emotional state "relaxed." For example, it creates a design with a blue base and a calm star motif that matches the relaxed emotional state.

[0243] Personalized suggestions

[0244] The generative AI can also refer to the user's past preference data to generate more personalized designs. For example, it can generate a design with a starry sky motif by taking into account the user's previous choice of a "night sky motif" design and their current relaxed emotional state.

[0245] Send and view your designs

[0246] The generated nail design proposals are converted back into data packets and sent from the server to the terminal. The terminal analyzes the received design data packets and displays multiple design proposals on the user interface. The user can visually check these design proposals.

[0247] User Choice and Feedback

[0248] The user selects the nail design they like best from the displayed options. Along with their selection, the user also enters feedback, such as their rating and impressions of the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0249] Recording feedback and incorporating it into the next session

[0250] The server analyzes the received feedback data and updates the user preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0251] Specific examples

[0252] For example, if a user inputs the themes "blue" and "stars" and the emotion engine recognizes this as "relaxing," the AI ​​will generate a calming design combining blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will use that information to generate a more detailed nail design with a night sky motif.

[0253] Prompt Sentence Examples

[0254] Here are some examples of prompts for generative AI models:

[0255] User entered color: Blue

[0256] User-entered design image: Star

[0257] User's emotional state: Relaxed

[0258] Example output of generated nail design:

[0259] A gentle star-shaped motif design based on blue

[0260] A relaxing design with stars arranged on a blue and white gradient

[0261] Design based on the night sky motif

[0262] This system allows users to easily enjoy new nail designs that suit their individual tastes and emotional state.

[0263] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0264] Step 1:

[0265] When a user launches the nail app, a user interface appears on the device, where the user inputs their preferred color (e.g., "blue") and design image (e.g., "star") into the interface.

[0266] Specific behavior:

[0267] The user enters "blue" and "star" into the input fields and presses the Next button.

[0268] Input: User-entered color "blue" and design image "star"

[0269] Output: Data for the color "blue" and the design image "star"

[0270] Step 2:

[0271] The emotion engine built into the device analyzes the user's facial expressions and voice to recognize their emotional state (e.g., relaxed).

[0272] Specific behavior:

[0273] The device activates the camera and captures the user's face.

[0274] Turn on the microphone and record your voice.

[0275] These data are sent to the emotion engine to obtain emotion analysis results.

[0276] Input: User's facial expression and voice data

[0277] Output: User's emotional state (e.g., relaxed)

[0278] Step 3:

[0279] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), and generates a data packet that integrates these data. The generated data packet is then sent to the server.

[0280] Specific behavior:

[0281] The color "blue", the design image "star", and the emotional state "relaxed" are packaged into a JSON format data packet.

[0282] Send the data packet to the server via HTTPS.

[0283] Input: Color "blue", design image "star", emotional state "relaxed"

[0284] Output: JSON formatted data packet

[0285] Step 4:

[0286] The server analyzes the received data packets and uses them as input to a generative AI model (e.g., a large-scale language model), which generates multiple nail design ideas based on the input data.

[0287] Specific behavior:

[0288] The server analyzes the data packet and sends "blue," "stars," and "relax" as input parameters to the generative AI model.

[0289] The generative AI generates nail design ideas and saves them in JSON format.

[0290] Input: Data packet (color "blue", design image "star", emotional state "relaxed")

[0291] Output: Generated nail design ideas (JSON format)

[0292] Step 5:

[0293] The server adds past user preference data to the generated nail design proposals to generate a personalized design.

[0294] Specific behavior:

[0295] The server retrieves the user's past preference data (e.g., "night sky motif") from a database.

[0296] Based on past preference data, it is fed back into a generative AI model to generate a personalized design.

[0297] Input: Generated nail design ideas, past preference data

[0298] Output: Personalized nail design ideas

[0299] Step 6:

[0300] The server sends the generated personalized design proposals to the terminal, which analyzes the received design data packets and displays multiple design proposals on the interface.

[0301] Specific behavior:

[0302] The generated design proposal is converted into a JSON format data packet.

[0303] Send the data packet to the device via HTTPS.

[0304] The device analyzes the data packets and displays multiple design proposals.

[0305] Input: JSON formatted design data packet

[0306] Output: User interface showing the proposed design

[0307] Step 7:

[0308] The user selects the design they like best from the displayed proposals and enters feedback into the device, including their rating, impressions, and requests for what they would like to see reflected in the next design generation. The device then converts this information into a data packet and sends it back to the server.

[0309] Specific behavior:

[0310] The user selects one of the design options displayed.

[0311] Enter your evaluation, comments, and requests in the feedback form and press the submit button.

[0312] The terminal assembles the feedback information into a data packet and transmits it to the server.

[0313] Input: User selection results, ratings, impressions, requests

[0314] Output: Feedback data packet

[0315] Step 8:

[0316] The server analyzes the received feedback data and updates the user preference database, which is then used to generate the next design.

[0317] Specific behavior:

[0318] The server analyzes the feedback data and updates the preference database.

[0319] Save the updated data to the database.

[0320] The next time you generate a design, this data will be referenced to provide more personalized suggestions.

[0321] Input: Feedback data packet

[0322] Output: Updated preference database

[0323] (Application example 2)

[0324] 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."

[0325] Many conventional nail design generation systems generate designs based on the user's color and design preferences, but do not support personalization that takes into account the user's emotional state or in-store usage. This makes it difficult for users to obtain a design that matches their current emotions and circumstances. Furthermore, real-time design suggestions in-store and improved user satisfaction have not been fully realized.

[0326] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the emotional state of the user, means for personalizing the design based on the analyzed emotional state, and means for recognizing the face of the user at the physical store and visualizing the design generated in real time. This makes it possible to generate personalized nail designs in real time, taking into account the emotional state of the user and usage at the physical store.

[0327] "User" refers to an individual who utilizes the system to input colors and designs and select generated designs.

[0328] "Colors and Images" refers to the preferred colors and specific design themes that the user inputs into the system.

[0329] "Generative AI" refers to AI technology that generates new designs based on colors and images entered by the user.

[0330] "Generated design" refers to a nail design idea created by generative artificial intelligence.

[0331] "Means for displaying" refers to a device or software interface for visually presenting the generated design to a user.

[0332] "Means for selection and feedback" refers to a mechanism that allows users to select the best design from the generated designs and provide feedback.

[0333] "Means for analyzing emotional state" refers to technology that analyzes data such as the user's facial expressions and voice to understand their emotional state at that time.

[0334] "Personalization tools" refers to mechanisms that optimize the design for each individual user based on the user's emotional state.

[0335] "Facial recognition" refers to technology used to detect a user's facial features and identify individual users.

[0336] "Means for visualizing the generated design in real time" refers to technologies and devices that allow the generated design to be instantly shown to the user.

[0337] "Means for recording feedback and reflecting it in the next design generation" refers to a system in which evaluations and opinions obtained from users are stored in a database and reflected in the design generation process from the next time onwards.

[0338] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and then recognizes the user's emotional state to make personalized suggestions. This system has the following configuration and processing steps.

[0339] Hardware and Software Configuration

[0340] The system includes a user-operated device (smartphone, tablet, or head-mounted display) and a server-based generative AI and database. It uses a camera and microphone for emotion recognition, OpenCV and DeepFace libraries for facial recognition and emotion analysis, and OpenAI's GPT-3 for generating nail designs.

[0341] Processing flow

[0342] 1. User Input and Emotion Recognition

[0343] The user launches the application using a device (e.g., a smartphone) and inputs the desired color and image. For example, the user inputs the theme "blue" and "stars." The application then analyzes the user's face and voice in real time using a camera and microphone to recognize their emotional state. In this example, the application recognizes that the user is relaxed.

[0344] 2. Data transmission and analysis

[0345] The device receives the color and image data entered by the user, as well as the emotion data analyzed by the emotion recognition engine, and transmits this data to the server. The data is first converted into data packets.

[0346] 3. Nail design generation

[0347] The server analyzes the received data packets and uses them as input for the generative AI (OpenAI GPT-3). The generative AI generates multiple nail design ideas based on the user's specified colors and images, as well as the analysis results of an emotion recognition engine. For example, it can generate a calming nail design combining blue and silver stars, or a design with stars arranged on a blue and white gradient.

[0348] 4. Personalized recommendations

[0349] The AI ​​also references the user's past preference data to generate more personalized designs. For example, it creates a calming nail design with a starry sky motif, taking into account the user's past choice of "night sky motif" design and their current emotional state of relaxation.

[0350] 5. Submit and display your design

[0351] The generated nail design proposals are converted into data packets and sent from the server to the terminal. The terminal analyzes the received design data packets and displays multiple design proposals on the interface. The user can visually check these design proposals.

[0352] Specific examples

[0353] For example, if a user inputs the themes "blue" and "stars" and the emotion engine recognizes this as relaxing, the generative AI will generate a prompt like this:

[0354] "Create a nail design with a blue and star theme that matches your relaxed mood."

[0355] In response to this prompt, the AI ​​will generate a calming design that combines blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Additionally, if the user has previously chosen a nail design with a "night sky" theme, the AI ​​will consider a more detailed design using a night sky motif.

[0356] This system allows users to easily try out personalized nail designs that match their emotional state and preferences at any given time, and since designs are generated and visualized in real time, it is also suitable for use in brick-and-mortar stores.

[0357] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0358] Step 1:

[0359] A user starts an application using a device (e.g., a smartphone). The user inputs the desired color and image. In this case, the input color is "blue" and the input image is "star." This information is saved on the device as user-input data.

[0360] Input: Color and image data (e.g. "blue", "star")

[0361] Output: User input data

[0362] Step 2:

[0363] The device uses the camera and microphone to analyze the user's face and voice in real time to recognize their emotional state. Here, OpenCV and DeepFace libraries are used for facial recognition and emotional analysis. The emotional state is recognized as "relaxed."

[0364] Input: User's face and voice data

[0365] Output: Emotional state data (e.g., "Relaxed")

[0366] Step 3:

[0367] The terminal takes the user's input data (color and image) and emotional state data and converts them into data packets, which are then sent to the server.

[0368] Input: User input data and emotional state data

[0369] Output: Data packet (containing user input data and emotional state data)

[0370] Step 4:

[0371] The server analyzes the received data packets and uses them as input for the generation AI. Here, OpenAI's GPT-3 is used to generate prompts and generate multiple nail design ideas. For example, the prompt generated is, "Generate a nail design with a blue and star theme that matches the relaxed emotion."

[0372] Input: Data packet (contains user input data and emotional state data)

[0373] Output: Multiple nail design ideas

[0374] Step 5:

[0375] The server converts the generated nail design proposal into a data packet and transmits it again to the terminal.

[0376] Input: Multiple nail design ideas

[0377] Output: Design Data Packet

[0378] Step 6:

[0379] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually check these design proposals.

[0380] Input: Design Data Packet

[0381] Output: Multiple design ideas displayed on the interface

[0382] Step 7:

[0383] The user selects the nail design they like best from the displayed options and enters feedback such as their evaluation and thoughts on the design, requests for the next design, etc. The device then converts this feedback back into a data packet and sends it to the server.

[0384] Input: User selections and feedback

[0385] Output: Feedback data packet

[0386] Step 8:

[0387] The server analyzes the received feedback data and updates the user preference database, which is used as a reference for subsequent design generation.

[0388] Input: Feedback data packet

[0389] Output: Updated preference database

[0390] Through these steps, users can easily try out personalized nail designs that suit their emotional state and preferences at any given time. Furthermore, since designs are generated and visualized in real time, the system is suitable for use in brick-and-mortar stores.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] [Second embodiment]

[0395] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0396] 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.

[0397] 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).

[0398] 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.

[0399] 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.

[0400] 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).

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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."

[0407] This invention is a system in which a generation AI (artificial intelligence) automatically generates nail designs based on the colors and images input by the user, proposes them to the user, and receives feedback to improve the proposals from the next time onwards. Specific embodiments of this system are described below.

[0408] Program processing overview

[0409] User Input and Data Submission

[0410] The user first launches the system's terminal application and inputs their preferred color and design image. For example, if the user inputs "blue" and "stars" as their preferred color and design image, the terminal will acquire this information, convert it into a data packet, and send it to the server.

[0411] Nail design generation

[0412] The server analyzes the user's input data received from the device and activates the AI ​​generator, which generates multiple nail design ideas based on the analyzed colors and design image. For example, there are designs based on a blue base and a star motif, a design with stars on a blue and white gradient, and a design with silver stars on a blue background.

[0413] Personalized suggestions

[0414] The AI ​​then references the user's past preference data and generates a more personalized design based on this. If the user has previously selected a "night sky motif" design, the AI ​​will also take this into account when generating a design.

[0415] Send and view your designs

[0416] The generated nail design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data and displays multiple design proposals on the interface. The user can visually check these proposed designs.

[0417] User Choice and Feedback

[0418] The user selects the nail design they like best from the proposed options. Along with their selection, the user also inputs feedback, such as their evaluation and thoughts on the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0419] Recording feedback and incorporating it into the next session

[0420] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0421] Specific examples

[0422] For example, if a user inputs a design with the theme of "blue" and "stars," the AI ​​will generate a design that combines blue and silver stars, or a design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will use that information to generate a more detailed nail design with a night sky motif. This allows users to always enjoy new nail designs that suit their tastes.

[0423] This system allows users to easily try out new nail designs, saving time and effort while providing an original design experience that suits their individual tastes.

[0424] The processing flow will be explained below.

[0425] Step 1:

[0426] The user launches the nail app and is presented with an interface to input their preferred color (e.g., "blue") and design image (e.g., "star"). The user enters this information and presses the send button.

[0427] Step 2:

[0428] The terminal receives the user's input data (color and design image), converts it into a data packet, and sends the converted data packet to the server.

[0429] Step 3:

[0430] The server receives user input data from the device, records it in a database, analyzes the data, and uses it as input for the generation AI.

[0431] Step 4:

[0432] The AI ​​then generates multiple nail design ideas based on the analyzed colors and design image, such as a blue-based star-shaped design or a blue and white gradient with stars.

[0433] Step 5:

[0434] The server converts the generated nail design proposal back into a data packet and transmits it to the terminal.

[0435] Step 6:

[0436] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually confirm these design proposals.

[0437] Step 7:

[0438] The user selects the design they like best from the displayed nail design suggestions, and along with their selection, they can enter their evaluation and thoughts on the design, as well as any requests they would like to have reflected in the next design generation, as feedback.

[0439] Step 8:

[0440] The terminal obtains the user's selection and feedback data, converts it into a data packet, and sends the converted data packet to the server.

[0441] Step 9:

[0442] The server analyzes the received feedback data and updates the user preference database. The updated data is reflected in subsequent design generation, resulting in more personalized design suggestions.

[0443] Example 1

[0444] 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."

[0445] Conventional nail design generation systems have difficulty efficiently generating designs that match the user's preferences. In addition, they lack the mechanism for incorporating user feedback into the next design generation, which makes it difficult to provide personalized suggestions.

[0446] 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.

[0447] In this invention, the server includes means for a user to input a color and an image, means including a generation artificial intelligence that generates a prompt sentence based on the input color and image and generates a plurality of design proposals, means for displaying the generated designs, means for accepting selection and feedback on the generated designs, and means for recording the feedback and reflecting it in the next design generation. This enables efficient design generation based on the user's preferences and personalized proposals by reflecting the feedback in the next design proposal.

[0448] A "user" is a person who uses the system's terminal application to input their preferred colors and design images, and select and evaluate the generated nail designs.

[0449] "Color" refers to the color information that forms the basis of the nail design that the user inputs into the system.

[0450] An "image" is a visual concept of a nail design motif or theme that a user inputs into the system.

[0451] A "prompt sentence" is a text-based input sentence that instructs the generative AI model to generate a design based on the colors and images entered by the user.

[0452] A "generative AI model" is an artificial intelligence algorithm that generates multiple nail design ideas based on user input data.

[0453] A "data packet" is a data format for efficiently transferring user input information and generated design data.

[0454] The "preference database" is a database that stores information on users' past choices and feedback and reflects this information in the next design generation.

[0455] "Feedback" refers to response information such as evaluations, impressions, and requests made by users regarding the generated design.

[0456] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, proposes them to the user, and receives feedback to improve the proposals for the next time and thereafter. Specific embodiments of this system are described below.

[0457] First, the user launches the system's terminal application. The terminal displays an input form for entering color and design image through the user interface. For example, the user enters "blue" and "stars" as their preferred color and design image. The terminal acquires this input information, converts it into a JSON-formatted data packet, and sends the data packet to the server.

[0458] The server analyzes the received data packet and extracts the color and design image specified by the user. Then, the server generates a prompt based on the analyzed data. For example, it generates a text prompt such as, "The color entered by the user is blue, and the design image is a star. Please generate a nail design."

[0459] Using the generated prompt, the server launches a generative AI model (e.g., OpenAI's GPT-3) to generate multiple nail design ideas. The generative AI model follows the prompt and outputs multiple design ideas, such as a design that combines blue and silver stars, or a design with stars arranged on a blue and white gradient.

[0460] The server also references the user's past preference data to generate personalized designs that take the user's preferences into account. If the user previously selected a "night sky motif" design, a night sky-themed design will also be generated based on that information.

[0461] The generated design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data and displays multiple design proposals on the user interface. For example, each design proposal is displayed as a thumbnail image in a 2-column by 2-row grid format.

[0462] The user selects the nail design they like best from the proposed options. Along with their selection, they can input feedback such as their evaluation and impressions of the design, as well as requests they would like reflected in the next design generation. The device converts this feedback information into data packets and sends them to the server.

[0463] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for the next design generation, resulting in more personalized design suggestions. This process allows users to easily try out new nail designs, saving time and effort while providing an original design experience tailored to their individual tastes.

[0464] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0465] Step 1: User Input and Data Submission

[0466] The user launches the system's terminal application and inputs their preferred color and design image. The input data, such as "blue" and "star," is converted into a JSON-formatted data packet by the terminal. The terminal then sends the generated data packet to the server. The input is the user's color and design image, and the output is the data sent to the server.

[0467] Step 2: Receiving and analyzing data on the server

[0468] The server receives a data packet sent from the terminal. For example, if the received data packet is {"color": "blue", "design": "star"}, the server analyzes the data packet and extracts the color "blue" and the design "star". This is the analysis of the input data, and the output is the analysis result.

[0469] Step 3: Generate prompts and launch the AI ​​model

[0470] The server generates a prompt based on the analyzed color and design image. For example, the generated prompt might be, "The color entered by the user is blue, and the design image is a star. Please generate a nail design." The server then inputs this prompt into a generative AI model (e.g., OpenAI's GPT-3) to generate nail design suggestions. The input is the prompt, and the output is the generated design suggestions.

[0471] Step 4: Personalized offers

[0472] In addition to the generated nail design suggestions, the server also references the user's past preference data. Based on this, the generative AI model also generates more personalized design suggestions. For example, if a user previously selected a "night sky motif" design, a design based on this information will also be added. The input is past preference data, and the output is personalized design suggestions.

[0473] Step 5: Send and view your design

[0474] The server converts the generated design proposals into data packets and sends them to the terminal. The terminal analyzes the received design data and displays multiple design proposals on a user interface, for example, displaying each design proposal as a thumbnail in a 2-column by 2-row grid format. The input is the design proposal data packets, and the output is a visual display for the user.

[0475] Step 6: User selection and feedback

[0476] The user selects one of the displayed design proposals and enters their evaluation and feedback on that design. The device converts this feedback into a data packet and sends it back to the server. The input is the user's selection and feedback, and the output is the data sent to the server.

[0477] Step 7: Recording of Feedback and Reflection in the Next Round

[0478] The server analyzes the received feedback data and updates the user preference database. The updated data is used as a reference in the next design generation, and more personalized proposals are made. The input is the feedback data, and the output is the updated preference database. This step enables the system to more accurately meet user needs by integrating the user's design preference information.

[0479] (Application Example 1)

[0480] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0481] The existing nail design proposal system only generates temporary designs based on the colors and images input by the user, and there is a problem that specific proposals that can be used in salon treatments are not made. Furthermore, since the communication means between the user and the service provider (nail salon staff) are limited, personalized design proposals are not sufficiently made. As a result, it is difficult to improve user satisfaction, and there is no guarantee that the quality of the service will be uniformly maintained.

[0482] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0483] In this invention, the server includes means for a user to input a color and an image, means including a generation artificial intelligence that generates a design based on the input color and image, means for displaying the generated design, means for accepting selections and feedback on the generated design, means for recording the feedback and reflecting it in the next design generation, means for generating design proposals based on the user's preferences in advance and sharing them with a service provider, and means for the service provider to review the design proposals and make personalized suggestions to the user, thereby enabling more effective communication between the user and the service provider and providing personalized services.

[0484] "User" refers to an individual who uses the system to input colors and design ideas and receive design proposals. It may also refer to a customer of a nail salon.

[0485] "Means for inputting colors and images" refers to an interface (e.g., a touch screen or voice input) that a user uses to input their preferred colors and design images.

[0486] "Generative AI" refers to AI technology that automatically generates designs based on input color and image information. Examples include generative AI models such as DALL-E and StyleGAN.

[0487] "Means for displaying the design" refers to a display or screen for visually presenting the generated nail design to the user.

[0488] "Means for selecting designs and receiving feedback" refers to an interface that allows users to select their preferred design from the proposed designs and input their evaluation of the design and requests for improvement.

[0489] "Means for recording feedback and reflecting it in the next design generation" refers to a system in which feedback information obtained from users is stored in a database and used in generating designs from the next time onwards.

[0490] "Service provider" refers to professionals who provide nail design installation services to users, such as nail salon staff and hairdressers.

[0491] "Means for generating design proposals in advance based on user preferences and sharing them with service providers" refers to a communication means for preparing design proposals in advance based on user input information and making them available for service providers to view.

[0492] "Means for making personalized suggestions" refers to a system or interface that allows a service provider to present optimal design proposals based on a user's individual preferences and past selection data.

[0493] This invention provides a system that automatically generates nail designs based on the colors and design image input by the user, proposes them to the user and service providers (such as nail salon staff), collects feedback, and reflects it in future proposals. Specific embodiments of this system are described below.

[0494] System configuration

[0495] The system mainly consists of the following hardware and software components:

[0496] 1. User Interface (UI):

[0497] Smartphone: A device that allows users to input color and design images.

[0498] Application (app): Software that allows users to input, review, and provide feedback on colors and design images.

[0499] 2. Server:

[0500] Cloud server: Receives, processes, and stores data.

[0501] Generative AI models: Generate nail designs based on user input. Examples include models such as DALL-E and StyleGAN.

[0502] Database: Stores user preferences and feedback information and uses it for the next design generation. For example, AWS RDS is used.

[0503] 3. Service Provider Interface:

[0504] Tablet or desktop PC: A device for salon staff to review design ideas based on customer preferences and feedback.

[0505] Application: Software that allows staff to review design proposals and make suggestions to users as needed.

[0506] Processing flow

[0507] 1. User input:

[0508] Users start the app and input their preferred colors and design image, for example, selecting elements such as "blue" or "stars" as their preferences.

[0509] 2. Data transmission:

[0510] The entered data is sent to the cloud server via the application.

[0511] 3. Design generation:

[0512] The server uses a generative AI model to generate multiple nail design ideas based on the input information.

[0513] The generated design proposals are sent back to the user's app in JSON format.

[0514] 4. Design Proposal:

[0515] The design proposals generated by the user's application are visually displayed, and the user can select the design they prefer.

[0516] The selected design proposal and feedback are sent back to the server.

[0517] 5. Sharing with Service Providers:

[0518] User preferences and feedback are also shared with the service provider's interface, allowing staff to make suggestions based on the user's preferences and feedback in advance.

[0519] 6. Record feedback and incorporate it into your next proposal:

[0520] The server records user feedback in a database and uses this information in the next design generation.

[0521] Specific examples

[0522] For example, if a user inputs a design based on the themes of "blue" and "stars," the generation AI will generate a design using prompts like the following:

[0523] Prompt: Use a generative AI model to generate a nail design based on the following criteria:

[0524] conditions:

[0525] Basic color: blue

[0526] Design image: Star

[0527] Past feedback: Users tend to prefer designs with a night sky theme

[0528] Based on this prompt, the generative AI will generate a nail design that matches the user's preferences and suggest it to the user and service provider, thereby realizing personalized, high-quality service provision.

[0529] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0530] Step 1:

[0531] A user launches a smartphone application and inputs their preferred color (e.g., "blue") and design image (e.g., "star"). The input information is obtained in text or image format. This information is converted into a JSON-formatted data packet for the next processing step.

[0532] Step 2:

[0533] The device sends the generated JSON data packet to a cloud server, which receives it and parses it as input to launch a generative AI model (e.g., DALL-E).

[0534] Step 3:

[0535] Based on the analyzed data, the server generates a prompt to generate the nail design requested by the user. For example, the prompt might be in the form of "Base color is blue, design image is stars, and based on past feedback, create a design with a night sky theme." The generative AI model uses this prompt to generate multiple nail design candidates.

[0536] Step 4:

[0537] The server then packets the generated nail design ideas in JSON format and resends them to the user's device. The user's application visually displays the received design ideas and arranges them in a format that the user can view.

[0538] Step 5:

[0539] The user selects the design they like from the presented options. Along with the selected design, they enter their feedback (e.g., their rating of the design and their requests for the next design) into the application. The feedback information is then converted back into a JSON-formatted data packet.

[0540] Step 6:

[0541] The device sends the feedback information entered by the user to the cloud server, which analyzes the received feedback and records it in a database, which is used to update the user preference database.

[0542] Step 7:

[0543] The server prepares data to be used for subsequent design generation based on the updated preference database. Service providers (nail salon staff) can also use a dedicated application to view design suggestions based on the user's preferences and feedback.

[0544] Step 8:

[0545] The service provider uses a tablet or desktop application to check the design ideas and feedback information selected by the user, and then proposes and performs a personalized nail design. This allows the user to find out which design best suits their preferences before visiting the salon.

[0546] Through this series of processes, users can easily receive personalized nail designs that suit their preferences, and service providers can use this information to provide high-quality services.

[0547] 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.

[0548] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and further recognizes the user's emotional state to make personalized suggestions. An embodiment of this system will be described in detail below.

[0549] Program processing overview

[0550] User Input and Emotion Recognition

[0551] When a user launches the nail app, an interface appears. The user inputs their preferred color (e.g., "blue") and design image (e.g., "star"). The emotion engine then analyzes the user's facial expressions and voice to recognize their emotional state. For example, it recognizes that the user is relaxed.

[0552] Data transmission and analysis

[0553] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), converting them into data packets, which are then sent to the server.

[0554] Nail design generation

[0555] The server analyzes the data packets received from the device and uses them as input for the generation AI. The generation AI generates multiple nail design proposals based on the user's specified colors and design image, as well as the analysis results of the emotion engine. For example, it could create a star-shaped design with a calm atmosphere based on blue, matching a relaxed emotional state.

[0556] Personalized suggestions

[0557] The generative AI also references the user's past preference data to generate more personalized designs. For example, it can generate a calming design with a starry sky motif, taking into account the user's past choice of "night sky motif" design and their current relaxed emotional state.

[0558] Send and view your designs

[0559] The generated nail design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data packets and displays multiple design proposals on the interface, allowing the user to visually check these design proposals.

[0560] User Choice and Feedback

[0561] The user selects the nail design they like best from the displayed options. Along with their selection, the user also enters feedback, such as their evaluation and thoughts on the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0562] Recording feedback and incorporating it into the next session

[0563] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0564] Specific examples

[0565] For example, if a user inputs the theme "blue" and "stars" and the emotion engine recognizes this as "relaxing," the AI ​​will generate a calming design combining blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will generate a nail design with a more detailed night sky motif based on that information. This allows users to always enjoy new nail designs that suit their tastes.

[0566] The system allows users to easily try out new nail designs, saving time and effort while providing an original design experience that suits their individual tastes and emotional state at the time.

[0567] The processing flow will be explained below.

[0568] Step 1:

[0569] The user launches the nail app and is presented with an interface where they can input their preferred color (e.g., "blue") and design image (e.g., "star"). The user inputs this information.

[0570] Step 2:

[0571] The emotion engine works by analyzing the user's facial expressions and voice, and as a result, it recognizes the user's emotional state (e.g., relaxed).

[0572] Step 3:

[0573] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), converting them into data packets, which are then sent to the server.

[0574] Step 4:

[0575] The server analyzes the data packets received from the device and uses them as input for the generation AI based on the user's specified colors, design image, and emotional state.

[0576] Step 5:

[0577] The AI ​​then generates multiple nail design ideas based on the analyzed data, for example, a star-shaped design with a blue base and a calming atmosphere that matches a relaxed emotional state.

[0578] Step 6:

[0579] The AI ​​will refer to a database of the user's past preferences, for example, by taking into account the user's past choice of "night sky motif" design and their current feeling of relaxation, and generate a design using a more detailed night sky motif.

[0580] Step 7:

[0581] The server converts the generated nail design proposal into a data packet and transmits it to the terminal.

[0582] Step 8:

[0583] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually confirm these design proposals.

[0584] Step 9:

[0585] The user selects the design they like best from the displayed nail design suggestions, and along with their selection, they can enter their evaluation and thoughts on the design, as well as any requests they would like to have reflected in the next design generation, as feedback.

[0586] Step 10:

[0587] The terminal obtains the user's selection and feedback data, converts it into a data packet, and sends the data packet to the server.

[0588] Step 11:

[0589] The server analyzes the received feedback data and updates the user preference database. The updated data is reflected in subsequent design generation, resulting in more personalized design suggestions.

[0590] This allows the system to provide original nail designs that match the user's preferences and current emotional state.

[0591] Example 2

[0592] 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."

[0593] Conventional nail design generation systems are unable to propose designs that take into account the user's emotional state, making it difficult to increase user satisfaction. Furthermore, there is a lack of a means to effectively utilize past preference data to generate personalized designs. Therefore, there is a need for a system that can propose optimal designs for each individual user.

[0594] 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.

[0595] In this invention, the server includes a means for the user to input colors and images, a means for analyzing the user's facial expressions and voice to recognize the emotional state, and a means including a generation artificial intelligence that generates designs based on the input colors and images and the analyzed emotional state, thereby making it possible to automatically generate personalized nail designs according to the user's emotional state.

[0596] "User" means an individual who utilizes the system to input colors and images to generate nail designs, and provides selections and feedback on the generated designs.

[0597] "Color" is a visual element that forms the basis or accent of the design entered by the user, and is a basic element that makes up the appearance of a nail design.

[0598] An "image" is a visual element that serves as the theme or motif of a design entered by the user, and constitutes the specific shape or pattern of the nail design.

[0599] "Emotional state" refers to a psychological state that is recognized by analyzing the user's facial expressions and voice, and represents emotions such as relaxation or excitement.

[0600] "Generative AI" refers to advanced algorithms and models that automatically generate nail designs based on input data.

[0601] The "display means" refers to an interface or device that allows the user to visually check the generated nail design.

[0602] "Feedback" refers to information such as the user's evaluation and impressions of the design they selected, and requests they would like to reflect in the next design generation.

[0603] A "data packet" is a unit of digital data that compiles information such as a user's input data, emotional state, and generated design.

[0604] A "server" is a computer system that receives, analyzes, and stores data sent by users.

[0605] "Terminal" means a device on which a user enters input and displays a design, including a smartphone or tablet.

[0606] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and further recognizes the user's emotional state to make personalized suggestions. An embodiment of this system will be described in detail below.

[0607] User Input and Emotion Recognition

[0608] When the device launches the nail application, a user interface is displayed. The user inputs their preferred color (e.g., "blue") and design image (e.g., "star"). Furthermore, the device incorporates an emotion engine (e.g., facial expression recognition API and voice analysis API) that analyzes the user's facial expressions and voice to recognize their emotional state. For example, it can recognize that the user is relaxed.

[0609] Data transmission and analysis

[0610] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), and generates a data packet that combines these data. The generated data packet is then sent to a server via the Internet.

[0611] Nail design generation

[0612] The server analyzes the received data packets and generates a nail design using a generative AI model (e.g., a large-scale language model). This generative AI generates multiple nail design proposals based on the user's specified color "blue," the design image "star," and the recognized emotional state "relaxed." For example, it creates a design with a blue base and a calm star motif that matches the relaxed emotional state.

[0613] Personalized suggestions

[0614] The generative AI can also refer to the user's past preference data to generate more personalized designs. For example, it can generate a design with a starry sky motif by taking into account the user's previous choice of a "night sky motif" design and their current relaxed emotional state.

[0615] Send and view your designs

[0616] The generated nail design proposals are converted back into data packets and sent from the server to the terminal. The terminal analyzes the received design data packets and displays multiple design proposals on the user interface. The user can visually check these design proposals.

[0617] User Choice and Feedback

[0618] The user selects the nail design they like best from the displayed options. Along with their selection, the user also enters feedback, such as their rating and impressions of the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0619] Recording feedback and incorporating it into the next session

[0620] The server analyzes the received feedback data and updates the user preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0621] Specific examples

[0622] For example, if a user inputs the themes "blue" and "stars" and the emotion engine recognizes this as "relaxing," the AI ​​will generate a calming design combining blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will use that information to generate a more detailed nail design with a night sky motif.

[0623] Prompt Sentence Examples

[0624] Here are some examples of prompts for generative AI models:

[0625] User entered color: Blue

[0626] User-entered design image: Star

[0627] User's emotional state: Relaxed

[0628] Example output of generated nail design:

[0629] A gentle star-shaped motif design based on blue

[0630] A relaxing design with stars arranged on a blue and white gradient

[0631] Design based on the night sky motif

[0632] This system allows users to easily enjoy new nail designs that suit their individual tastes and emotional state.

[0633] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0634] Step 1:

[0635] When a user launches the nail app, a user interface appears on the device, where the user inputs their preferred color (e.g., "blue") and design image (e.g., "star") into the interface.

[0636] Specific behavior:

[0637] The user enters "blue" and "star" into the input fields and presses the Next button.

[0638] Input: User-entered color "blue" and design image "star"

[0639] Output: Data for the color "blue" and the design image "star"

[0640] Step 2:

[0641] The emotion engine built into the device analyzes the user's facial expressions and voice to recognize their emotional state (e.g., relaxed).

[0642] Specific behavior:

[0643] The device activates the camera and captures the user's face.

[0644] Turn on the microphone and record your voice.

[0645] These data are sent to the emotion engine to obtain emotion analysis results.

[0646] Input: User's facial expression and voice data

[0647] Output: User's emotional state (e.g., relaxed)

[0648] Step 3:

[0649] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), and generates a data packet that integrates these data. The generated data packet is then sent to the server.

[0650] Specific behavior:

[0651] The color "blue", the design image "star", and the emotional state "relaxed" are packaged into a JSON format data packet.

[0652] Send the data packet to the server via HTTPS.

[0653] Input: Color "blue", design image "star", emotional state "relaxed"

[0654] Output: JSON formatted data packet

[0655] Step 4:

[0656] The server analyzes the received data packets and uses them as input to a generative AI model (e.g., a large-scale language model), which generates multiple nail design ideas based on the input data.

[0657] Specific behavior:

[0658] The server analyzes the data packet and sends "blue," "stars," and "relax" as input parameters to the generative AI model.

[0659] The generative AI generates nail design ideas and saves them in JSON format.

[0660] Input: Data packet (color "blue", design image "star", emotional state "relaxed")

[0661] Output: Generated nail design ideas (JSON format)

[0662] Step 5:

[0663] The server adds past user preference data to the generated nail design proposals to generate a personalized design.

[0664] Specific behavior:

[0665] The server retrieves the user's past preference data (e.g., "night sky motif") from a database.

[0666] Based on past preference data, it is fed back into a generative AI model to generate a personalized design.

[0667] Input: Generated nail design ideas, past preference data

[0668] Output: Personalized nail design ideas

[0669] Step 6:

[0670] The server sends the generated personalized design proposals to the terminal, which analyzes the received design data packets and displays multiple design proposals on the interface.

[0671] Specific behavior:

[0672] The generated design proposal is converted into a JSON format data packet.

[0673] Send the data packet to the device via HTTPS.

[0674] The device analyzes the data packets and displays multiple design proposals.

[0675] Input: JSON formatted design data packet

[0676] Output: User interface showing the proposed design

[0677] Step 7:

[0678] The user selects the design they like best from the displayed proposals and enters feedback into the device, including their rating, impressions, and requests for what they would like to see reflected in the next design generation. The device then converts this information into a data packet and sends it back to the server.

[0679] Specific behavior:

[0680] The user selects one of the design options displayed.

[0681] Enter your evaluation, comments, and requests in the feedback form and press the submit button.

[0682] The terminal assembles the feedback information into a data packet and transmits it to the server.

[0683] Input: User selection results, ratings, impressions, requests

[0684] Output: Feedback data packet

[0685] Step 8:

[0686] The server analyzes the received feedback data and updates the user preference database, which is then used to generate the next design.

[0687] Specific behavior:

[0688] The server analyzes the feedback data and updates the preference database.

[0689] Save the updated data to the database.

[0690] The next time you generate a design, this data will be referenced to provide more personalized suggestions.

[0691] Input: Feedback data packet

[0692] Output: Updated preference database

[0693] (Application example 2)

[0694] 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."

[0695] Many conventional nail design generation systems generate designs based on the user's color and design preferences, but do not support personalization that takes into account the user's emotional state or in-store usage. This makes it difficult for users to obtain a design that matches their current emotions and circumstances. Furthermore, real-time design suggestions in-store and improved user satisfaction have not been fully realized.

[0696] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the emotional state of the user, means for personalizing the design based on the analyzed emotional state, and means for recognizing the face of the user at the physical store and visualizing the design generated in real time. This makes it possible to generate personalized nail designs in real time, taking into account the emotional state of the user and usage at the physical store.

[0697] "User" refers to an individual who utilizes the system to input colors and designs and select generated designs.

[0698] "Colors and Images" refers to the preferred colors and specific design themes that the user inputs into the system.

[0699] "Generative AI" refers to AI technology that generates new designs based on colors and images entered by the user.

[0700] "Generated design" refers to a nail design idea created by generative artificial intelligence.

[0701] "Means for displaying" refers to a device or software interface for visually presenting the generated design to a user.

[0702] "Means for selection and feedback" refers to a mechanism that allows users to select the best design from the generated designs and provide feedback.

[0703] "Means for analyzing emotional state" refers to technology that analyzes data such as the user's facial expressions and voice to understand their emotional state at that time.

[0704] "Personalization tools" refers to mechanisms that optimize the design for each individual user based on the user's emotional state.

[0705] "Facial recognition" refers to technology used to detect a user's facial features and identify individual users.

[0706] "Means for visualizing the generated design in real time" refers to technologies and devices that allow the generated design to be instantly shown to the user.

[0707] "Means for recording feedback and reflecting it in the next design generation" refers to a system in which evaluations and opinions obtained from users are stored in a database and reflected in the design generation process from the next time onwards.

[0708] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and then recognizes the user's emotional state to make personalized suggestions. This system has the following configuration and processing steps.

[0709] Hardware and Software Configuration

[0710] The system includes a user-operated device (smartphone, tablet, or head-mounted display) and a server-based generative AI and database. It uses a camera and microphone for emotion recognition, OpenCV and DeepFace libraries for facial recognition and emotion analysis, and OpenAI's GPT-3 for generating nail designs.

[0711] Processing flow

[0712] 1. User Input and Emotion Recognition

[0713] The user launches the application using a device (e.g., a smartphone) and inputs the desired color and image. For example, the user inputs the theme "blue" and "stars." The application then analyzes the user's face and voice in real time using a camera and microphone to recognize their emotional state. In this example, the application recognizes that the user is relaxed.

[0714] 2. Data transmission and analysis

[0715] The device receives the color and image data entered by the user, as well as the emotion data analyzed by the emotion recognition engine, and transmits this data to the server. The data is first converted into data packets.

[0716] 3. Nail design generation

[0717] The server analyzes the received data packets and uses them as input for the generative AI (OpenAI GPT-3). The generative AI generates multiple nail design ideas based on the user's specified colors and images, as well as the analysis results of an emotion recognition engine. For example, it can generate a calming nail design combining blue and silver stars, or a design with stars arranged on a blue and white gradient.

[0718] 4. Personalized recommendations

[0719] The AI ​​also references the user's past preference data to generate more personalized designs. For example, it creates a calming nail design with a starry sky motif, taking into account the user's past choice of "night sky motif" design and their current emotional state of relaxation.

[0720] 5. Submit and display your design

[0721] The generated nail design proposals are converted into data packets and sent from the server to the terminal. The terminal analyzes the received design data packets and displays multiple design proposals on the interface. The user can visually check these design proposals.

[0722] Specific examples

[0723] For example, if a user inputs the themes "blue" and "stars" and the emotion engine recognizes this as relaxing, the generative AI will generate a prompt like this:

[0724] "Create a nail design with a blue and star theme that matches your relaxed mood."

[0725] In response to this prompt, the AI ​​will generate a calming design that combines blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Additionally, if the user has previously chosen a nail design with a "night sky" theme, the AI ​​will consider a more detailed design using a night sky motif.

[0726] This system allows users to easily try out personalized nail designs that match their emotional state and preferences at any given time, and since designs are generated and visualized in real time, it is also suitable for use in brick-and-mortar stores.

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

[0728] Step 1:

[0729] A user starts an application using a device (e.g., a smartphone). The user inputs the desired color and image. In this case, the input color is "blue" and the input image is "star." This information is saved on the device as user-input data.

[0730] Input: Color and image data (e.g. "blue", "star")

[0731] Output: User input data

[0732] Step 2:

[0733] The device uses the camera and microphone to analyze the user's face and voice in real time to recognize their emotional state. Here, OpenCV and DeepFace libraries are used for facial recognition and emotional analysis. The emotional state is recognized as "relaxed."

[0734] Input: User's face and voice data

[0735] Output: Emotional state data (e.g., "Relaxed")

[0736] Step 3:

[0737] The terminal takes the user's input data (color and image) and emotional state data and converts them into data packets, which are then sent to the server.

[0738] Input: User input data and emotional state data

[0739] Output: Data packet (containing user input data and emotional state data)

[0740] Step 4:

[0741] The server analyzes the received data packets and uses them as input for the generation AI. Here, OpenAI's GPT-3 is used to generate prompts and generate multiple nail design ideas. For example, the prompt generated is, "Generate a nail design with a blue and star theme that matches the relaxed emotion."

[0742] Input: Data packet (contains user input data and emotional state data)

[0743] Output: Multiple nail design ideas

[0744] Step 5:

[0745] The server converts the generated nail design proposal into a data packet and transmits it again to the terminal.

[0746] Input: Multiple nail design ideas

[0747] Output: Design Data Packet

[0748] Step 6:

[0749] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually check these design proposals.

[0750] Input: Design Data Packet

[0751] Output: Multiple design ideas displayed on the interface

[0752] Step 7:

[0753] The user selects the nail design they like best from the displayed options and enters feedback such as their evaluation and thoughts on the design, requests for the next design, etc. The device then converts this feedback back into a data packet and sends it to the server.

[0754] Input: User selections and feedback

[0755] Output: Feedback data packet

[0756] Step 8:

[0757] The server analyzes the received feedback data and updates the user preference database, which is used as a reference for subsequent design generation.

[0758] Input: Feedback data packet

[0759] Output: Updated preference database

[0760] Through these steps, users can easily try out personalized nail designs that suit their emotional state and preferences at any given time. Furthermore, since designs are generated and visualized in real time, the system is suitable for use in brick-and-mortar stores.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] [Third embodiment]

[0765] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0766] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0767] 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).

[0768] 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.

[0769] 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.

[0770] 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).

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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."

[0777] This invention is a system in which a generation AI (artificial intelligence) automatically generates nail designs based on the colors and images input by the user, proposes them to the user, and receives feedback to improve the proposals from the next time onwards. Specific embodiments of this system are described below.

[0778] Program processing overview

[0779] User Input and Data Submission

[0780] The user first launches the system's terminal application and inputs their preferred color and design image. For example, if the user inputs "blue" and "stars" as their preferred color and design image, the terminal will acquire this information, convert it into a data packet, and send it to the server.

[0781] Nail design generation

[0782] The server analyzes the user's input data received from the device and activates the AI ​​generator, which generates multiple nail design ideas based on the analyzed colors and design image. For example, there are designs based on a blue base and a star motif, a design with stars on a blue and white gradient, and a design with silver stars on a blue background.

[0783] Personalized suggestions

[0784] The AI ​​then references the user's past preference data and generates a more personalized design based on this. If the user has previously selected a "night sky motif" design, the AI ​​will also take this into account when generating a design.

[0785] Send and view your designs

[0786] The generated nail design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data and displays multiple design proposals on the interface. The user can visually check these proposed designs.

[0787] User Choice and Feedback

[0788] The user selects the nail design they like best from the proposed options. Along with their selection, the user also inputs feedback, such as their evaluation and thoughts on the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0789] Recording feedback and incorporating it into the next session

[0790] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0791] Specific examples

[0792] For example, if a user inputs a design with the theme of "blue" and "stars," the AI ​​will generate a design that combines blue and silver stars, or a design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will use that information to generate a more detailed nail design with a night sky motif. This allows users to always enjoy new nail designs that suit their tastes.

[0793] This system allows users to easily try out new nail designs, saving time and effort while providing an original design experience that suits their individual tastes.

[0794] The processing flow will be explained below.

[0795] Step 1:

[0796] The user launches the nail app and is presented with an interface to input their preferred color (e.g., "blue") and design image (e.g., "star"). The user enters this information and presses the send button.

[0797] Step 2:

[0798] The terminal receives the user's input data (color and design image), converts it into a data packet, and sends the converted data packet to the server.

[0799] Step 3:

[0800] The server receives user input data from the device, records it in a database, analyzes the data, and uses it as input for the generation AI.

[0801] Step 4:

[0802] The AI ​​then generates multiple nail design ideas based on the analyzed colors and design image, such as a blue-based star-shaped design or a blue and white gradient with stars.

[0803] Step 5:

[0804] The server converts the generated nail design proposal back into a data packet and transmits it to the terminal.

[0805] Step 6:

[0806] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually confirm these design proposals.

[0807] Step 7:

[0808] The user selects the design they like best from the displayed nail design suggestions, and along with their selection, they can enter their evaluation and thoughts on the design, as well as any requests they would like to have reflected in the next design generation, as feedback.

[0809] Step 8:

[0810] The terminal obtains the user's selection and feedback data, converts it into a data packet, and sends the converted data packet to the server.

[0811] Step 9:

[0812] The server analyzes the received feedback data and updates the user preference database. The updated data is reflected in subsequent design generation, resulting in more personalized design suggestions.

[0813] Example 1

[0814] 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."

[0815] Conventional nail design generation systems have difficulty efficiently generating designs that match the user's preferences. In addition, they lack the mechanism for incorporating user feedback into the next design generation, which makes it difficult to provide personalized suggestions.

[0816] 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.

[0817] In this invention, the server includes means for a user to input a color and an image, means including a generation artificial intelligence that generates a prompt sentence based on the input color and image and generates a plurality of design proposals, means for displaying the generated designs, means for accepting selection and feedback on the generated designs, and means for recording the feedback and reflecting it in the next design generation. This enables efficient design generation based on the user's preferences and personalized proposals by reflecting the feedback in the next design proposal.

[0818] A "user" is a person who uses the system's terminal application to input their preferred colors and design images, and select and evaluate the generated nail designs.

[0819] "Color" refers to the color information that forms the basis of the nail design that the user inputs into the system.

[0820] An "image" is a visual concept of a nail design motif or theme that a user inputs into the system.

[0821] A "prompt sentence" is a text-based input sentence that instructs the generative AI model to generate a design based on the colors and images entered by the user.

[0822] A "generative AI model" is an artificial intelligence algorithm that generates multiple nail design ideas based on user input data.

[0823] A "data packet" is a data format for efficiently transferring user input information and generated design data.

[0824] The "preference database" is a database that stores information on users' past choices and feedback and reflects this information in the next design generation.

[0825] "Feedback" refers to response information such as evaluations, impressions, and requests made by users regarding the generated design.

[0826] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, proposes them to the user, and receives feedback to improve the proposals for the next time and thereafter. Specific embodiments of this system are described below.

[0827] First, the user launches the system's terminal application. The terminal displays an input form for entering color and design image through the user interface. For example, the user enters "blue" and "stars" as their preferred color and design image. The terminal acquires this input information, converts it into a JSON-formatted data packet, and sends the data packet to the server.

[0828] The server analyzes the received data packet and extracts the color and design image specified by the user. Then, the server generates a prompt based on the analyzed data. For example, it generates a text prompt such as, "The color entered by the user is blue, and the design image is a star. Please generate a nail design."

[0829] Using the generated prompt, the server launches a generative AI model (e.g., OpenAI's GPT-3) to generate multiple nail design ideas. The generative AI model follows the prompt and outputs multiple design ideas, such as a design that combines blue and silver stars, or a design with stars arranged on a blue and white gradient.

[0830] The server also references the user's past preference data to generate personalized designs that take the user's preferences into account. If the user previously selected a "night sky motif" design, a night sky-themed design will also be generated based on that information.

[0831] The generated design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data and displays multiple design proposals on the user interface. For example, each design proposal is displayed as a thumbnail image in a 2-column by 2-row grid format.

[0832] The user selects the nail design they like best from the proposed options. Along with their selection, they can input feedback such as their evaluation and impressions of the design, as well as requests they would like reflected in the next design generation. The device converts this feedback information into data packets and sends them to the server.

[0833] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for the next design generation, resulting in more personalized design suggestions. This process allows users to easily try out new nail designs, saving time and effort while providing an original design experience tailored to their individual tastes.

[0834] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0835] Step 1: User Input and Data Submission

[0836] The user launches the system's terminal application and inputs their preferred color and design image. The input data, such as "blue" and "star," is converted into a JSON-formatted data packet by the terminal. The terminal then sends the generated data packet to the server. The input is the user's color and design image, and the output is the data sent to the server.

[0837] Step 2: Receiving and analyzing data on the server

[0838] The server receives a data packet sent from the terminal. For example, if the received data packet is {"color": "blue", "design": "star"}, the server analyzes the data packet and extracts the color "blue" and the design "star". This is the analysis of the input data, and the output is the analysis result.

[0839] Step 3: Generate prompts and launch the AI ​​model

[0840] The server generates a prompt based on the analyzed color and design image. For example, the generated prompt might be, "The color entered by the user is blue, and the design image is a star. Please generate a nail design." The server then inputs this prompt into a generative AI model (e.g., OpenAI's GPT-3) to generate nail design suggestions. The input is the prompt, and the output is the generated design suggestions.

[0841] Step 4: Personalized offers

[0842] In addition to the generated nail design suggestions, the server also references the user's past preference data. Based on this, the generative AI model also generates more personalized design suggestions. For example, if a user previously selected a "night sky motif" design, a design based on this information will also be added. The input is past preference data, and the output is personalized design suggestions.

[0843] Step 5: Send and view your design

[0844] The server converts the generated design proposals into data packets and sends them to the terminal. The terminal analyzes the received design data and displays multiple design proposals on a user interface, for example, displaying each design proposal as a thumbnail in a 2-column by 2-row grid format. The input is the design proposal data packets, and the output is a visual display for the user.

[0845] Step 6: User selection and feedback

[0846] The user selects one of the displayed design proposals and enters their evaluation and feedback on that design. The device converts this feedback into a data packet and sends it back to the server. The input is the user's selection and feedback, and the output is the data sent to the server.

[0847] Step 7: Recording of Feedback and Reflection in the Next Round

[0848] The server analyzes the received feedback data and updates the user preference database. The updated data is used as a reference in the next design generation, and more personalized proposals are made. The input is the feedback data, and the output is the updated preference database. This step enables the system to more accurately meet user needs by integrating the user's design preference information.

[0849] (Application Example 1)

[0850] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the headset-type terminal 314 is referred to as the "terminal".

[0851] The existing nail design proposal system only generates temporary designs based on the colors and images input by the user, and there is no problem that specific proposals that can be used in salon treatments are not made. Furthermore, since the communication means between the user and the service provider (nail salon staff) are limited, personalized design proposals are not sufficiently made. As a result, it is difficult to improve user satisfaction, and there is no guarantee that the quality of the service is maintained uniformly.

[0852] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0853] In this invention, the server includes means for a user to input a color and an image, means including a generation artificial intelligence that generates a design based on the input color and image, means for displaying the generated design, means for accepting selections and feedback on the generated design, means for recording the feedback and reflecting it in the next design generation, means for generating design proposals based on the user's preferences in advance and sharing them with a service provider, and means for the service provider to review the design proposals and make personalized suggestions to the user, thereby enabling more effective communication between the user and the service provider and providing personalized services.

[0854] "User" refers to an individual who uses the system to input colors and design ideas and receive design proposals. It may also refer to a customer of a nail salon.

[0855] "Means for inputting colors and images" refers to an interface (e.g., a touch screen or voice input) that a user uses to input their preferred colors and design images.

[0856] "Generative AI" refers to AI technology that automatically generates designs based on input color and image information. Examples include generative AI models such as DALL-E and StyleGAN.

[0857] "Means for displaying the design" refers to a display or screen for visually presenting the generated nail design to the user.

[0858] "Means for selecting designs and receiving feedback" refers to an interface that allows users to select their preferred design from the proposed designs and input their evaluation of the design and requests for improvement.

[0859] "Means for recording feedback and reflecting it in the next design generation" refers to a system in which feedback information obtained from users is stored in a database and used in generating designs from the next time onwards.

[0860] "Service provider" refers to professionals who provide nail design installation services to users, such as nail salon staff and hairdressers.

[0861] "Means for generating design proposals in advance based on user preferences and sharing them with service providers" refers to a communication means for preparing design proposals in advance based on user input information and making them available for service providers to view.

[0862] "Means for making personalized suggestions" refers to a system or interface that allows a service provider to present optimal design proposals based on a user's individual preferences and past selection data.

[0863] This invention provides a system that automatically generates nail designs based on the colors and design image input by the user, proposes them to the user and service providers (such as nail salon staff), collects feedback, and reflects it in future proposals. Specific embodiments of this system are described below.

[0864] System configuration

[0865] The system mainly consists of the following hardware and software components:

[0866] 1. User Interface (UI):

[0867] Smartphone: A device that allows users to input color and design images.

[0868] Application (app): Software that allows users to input, review, and provide feedback on colors and design images.

[0869] 2. Server:

[0870] Cloud server: Receives, processes, and stores data.

[0871] Generative AI models: Generate nail designs based on user input. Examples include models such as DALL-E and StyleGAN.

[0872] Database: Stores user preferences and feedback information and uses it for the next design generation. For example, AWS RDS is used.

[0873] 3. Service Provider Interface:

[0874] Tablet or desktop PC: A device for salon staff to review design ideas based on customer preferences and feedback.

[0875] Application: Software that allows staff to review design proposals and make suggestions to users as needed.

[0876] Processing flow

[0877] 1. User input:

[0878] Users start the app and input their preferred colors and design image, for example, selecting elements such as "blue" or "stars" as their preferences.

[0879] 2. Data transmission:

[0880] The entered data is sent to the cloud server via the application.

[0881] 3. Design generation:

[0882] The server uses a generative AI model to generate multiple nail design ideas based on the input information.

[0883] The generated design proposals are sent back to the user's app in JSON format.

[0884] 4. Design Proposal:

[0885] The design proposals generated by the user's application are visually displayed, and the user can select the design they prefer.

[0886] The selected design proposal and feedback are sent back to the server.

[0887] 5. Sharing with Service Providers:

[0888] User preferences and feedback are also shared with the service provider's interface, allowing staff to make suggestions based on the user's preferences and feedback in advance.

[0889] 6. Record feedback and incorporate it into your next proposal:

[0890] The server records user feedback in a database and uses this information in the next design generation.

[0891] Specific examples

[0892] For example, if a user inputs a design based on the themes of "blue" and "stars," the generation AI will generate a design using prompts like the following:

[0893] Prompt: Use a generative AI model to generate a nail design based on the following criteria:

[0894] conditions:

[0895] Basic color: blue

[0896] Design image: Star

[0897] Past feedback: Users tend to prefer designs with a night sky theme

[0898] Based on this prompt, the generative AI will generate a nail design that matches the user's preferences and suggest it to the user and service provider, thereby realizing personalized, high-quality service provision.

[0899] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0900] Step 1:

[0901] A user launches a smartphone application and inputs their preferred color (e.g., "blue") and design image (e.g., "star"). The input information is obtained in text or image format. This information is converted into a JSON-formatted data packet for the next processing step.

[0902] Step 2:

[0903] The device sends the generated JSON data packet to a cloud server, which receives it and parses it as input to launch a generative AI model (e.g., DALL-E).

[0904] Step 3:

[0905] Based on the analyzed data, the server generates a prompt to generate the nail design requested by the user. For example, the prompt might be in the form of "Base color is blue, design image is stars, and based on past feedback, create a design with a night sky theme." The generative AI model uses this prompt to generate multiple nail design candidates.

[0906] Step 4:

[0907] The server then packets the generated nail design ideas in JSON format and resends them to the user's device. The user's application visually displays the received design ideas and arranges them in a format that the user can view.

[0908] Step 5:

[0909] The user selects the design they like from the presented options. Along with the selected design, they enter their feedback (e.g., their rating of the design and their requests for the next design) into the application. The feedback information is then converted back into a JSON-formatted data packet.

[0910] Step 6:

[0911] The device sends the feedback information entered by the user to the cloud server, which analyzes the received feedback and records it in a database, which is used to update the user preference database.

[0912] Step 7:

[0913] The server prepares data to be used for subsequent design generation based on the updated preference database. Service providers (nail salon staff) can also use a dedicated application to view design suggestions based on the user's preferences and feedback.

[0914] Step 8:

[0915] The service provider uses a tablet or desktop application to check the design ideas and feedback information selected by the user, and then proposes and performs a personalized nail design. This allows the user to find out which design best suits their preferences before visiting the salon.

[0916] Through this series of processes, users can easily receive personalized nail designs that suit their preferences, and service providers can use this information to provide high-quality services.

[0917] 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.

[0918] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and further recognizes the user's emotional state to make personalized suggestions. An embodiment of this system will be described in detail below.

[0919] Program processing overview

[0920] User Input and Emotion Recognition

[0921] When a user launches the nail app, an interface appears. The user inputs their preferred color (e.g., "blue") and design image (e.g., "star"). The emotion engine then analyzes the user's facial expressions and voice to recognize their emotional state. For example, it recognizes that the user is relaxed.

[0922] Data transmission and analysis

[0923] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), converting them into data packets, which are then sent to the server.

[0924] Nail design generation

[0925] The server analyzes the data packets received from the device and uses them as input for the generation AI. The generation AI generates multiple nail design proposals based on the user's specified colors and design image, as well as the analysis results of the emotion engine. For example, it could create a star-shaped design with a calm atmosphere based on blue, matching a relaxed emotional state.

[0926] Personalized suggestions

[0927] The generative AI also references the user's past preference data to generate more personalized designs. For example, it can generate a calming design with a starry sky motif, taking into account the user's past choice of "night sky motif" design and their current relaxed emotional state.

[0928] Send and view your designs

[0929] The generated nail design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data packets and displays multiple design proposals on the interface, allowing the user to visually check these design proposals.

[0930] User Choice and Feedback

[0931] The user selects the nail design they like best from the displayed options. Along with their selection, the user also enters feedback, such as their evaluation and thoughts on the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0932] Recording feedback and incorporating it into the next session

[0933] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0934] Specific examples

[0935] For example, if a user inputs the theme "blue" and "stars" and the emotion engine recognizes this as "relaxing," the AI ​​will generate a calming design combining blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will generate a nail design with a more detailed night sky motif based on that information. This allows users to always enjoy new nail designs that suit their tastes.

[0936] The system allows users to easily try out new nail designs, saving time and effort while providing an original design experience that suits their individual tastes and emotional state at the time.

[0937] The processing flow will be explained below.

[0938] Step 1:

[0939] The user launches the nail app and is presented with an interface where they can input their preferred color (e.g., "blue") and design image (e.g., "star"). The user inputs this information.

[0940] Step 2:

[0941] The emotion engine works by analyzing the user's facial expressions and voice, and as a result, it recognizes the user's emotional state (e.g., relaxed).

[0942] Step 3:

[0943] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), converting them into data packets, which are then sent to the server.

[0944] Step 4:

[0945] The server analyzes the data packets received from the device and uses them as input for the generation AI based on the user's specified colors, design image, and emotional state.

[0946] Step 5:

[0947] The AI ​​then generates multiple nail design ideas based on the analyzed data, for example, a star-shaped design with a blue base and a calming atmosphere that matches a relaxed emotional state.

[0948] Step 6:

[0949] The AI ​​will refer to a database of the user's past preferences, for example, by taking into account the user's past choice of "night sky motif" design and their current feeling of relaxation, and generate a design using a more detailed night sky motif.

[0950] Step 7:

[0951] The server converts the generated nail design proposal into a data packet and transmits it to the terminal.

[0952] Step 8:

[0953] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually confirm these design proposals.

[0954] Step 9:

[0955] The user selects the design they like best from the displayed nail design suggestions, and along with their selection, they can enter their evaluation and thoughts on the design, as well as any requests they would like to have reflected in the next design generation, as feedback.

[0956] Step 10:

[0957] The terminal obtains the user's selection and feedback data, converts it into a data packet, and sends the data packet to the server.

[0958] Step 11:

[0959] The server analyzes the received feedback data and updates the user preference database. The updated data is reflected in subsequent design generation, resulting in more personalized design suggestions.

[0960] This allows the system to provide original nail designs that match the user's preferences and current emotional state.

[0961] Example 2

[0962] 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."

[0963] Conventional nail design generation systems are unable to propose designs that take into account the user's emotional state, making it difficult to increase user satisfaction. Furthermore, there is a lack of a means to effectively utilize past preference data to generate personalized designs. Therefore, there is a need for a system that can propose optimal designs for each individual user.

[0964] 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.

[0965] In this invention, the server includes a means for the user to input colors and images, a means for analyzing the user's facial expressions and voice to recognize the emotional state, and a means including a generation artificial intelligence that generates designs based on the input colors and images and the analyzed emotional state, thereby making it possible to automatically generate personalized nail designs according to the user's emotional state.

[0966] "User" means an individual who utilizes the system to input colors and images to generate nail designs, and provides selections and feedback on the generated designs.

[0967] "Color" is a visual element that forms the basis or accent of the design entered by the user, and is a basic element that makes up the appearance of a nail design.

[0968] An "image" is a visual element that serves as the theme or motif of a design entered by the user, and constitutes the specific shape or pattern of the nail design.

[0969] "Emotional state" refers to a psychological state that is recognized by analyzing the user's facial expressions and voice, and represents emotions such as relaxation or excitement.

[0970] "Generative AI" refers to advanced algorithms and models that automatically generate nail designs based on input data.

[0971] The "display means" refers to an interface or device that allows the user to visually check the generated nail design.

[0972] "Feedback" refers to information such as the user's evaluation and impressions of the design they selected, and requests they would like to reflect in the next design generation.

[0973] A "data packet" is a unit of digital data that compiles information such as a user's input data, emotional state, and generated design.

[0974] A "server" is a computer system that receives, analyzes, and stores data sent by users.

[0975] "Terminal" means a device on which a user enters input and displays a design, including a smartphone or tablet.

[0976] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and further recognizes the user's emotional state to make personalized suggestions. An embodiment of this system will be described in detail below.

[0977] User Input and Emotion Recognition

[0978] When the device launches the nail application, a user interface is displayed. The user inputs their preferred color (e.g., "blue") and design image (e.g., "star"). Furthermore, the device incorporates an emotion engine (e.g., facial expression recognition API and voice analysis API) that analyzes the user's facial expressions and voice to recognize their emotional state. For example, it can recognize that the user is relaxed.

[0979] Data transmission and analysis

[0980] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), and generates a data packet that combines these data. The generated data packet is then sent to a server via the Internet.

[0981] Nail design generation

[0982] The server analyzes the received data packets and generates a nail design using a generative AI model (e.g., a large-scale language model). This generative AI generates multiple nail design proposals based on the user's specified color "blue," the design image "star," and the recognized emotional state "relaxed." For example, it creates a design with a blue base and a calm star motif that matches the relaxed emotional state.

[0983] Personalized suggestions

[0984] The generative AI can also refer to the user's past preference data to generate more personalized designs. For example, it can generate a design with a starry sky motif by taking into account the user's previous choice of a "night sky motif" design and their current relaxed emotional state.

[0985] Send and view your designs

[0986] The generated nail design proposals are converted back into data packets and sent from the server to the terminal. The terminal analyzes the received design data packets and displays multiple design proposals on the user interface. The user can visually check these design proposals.

[0987] User Choice and Feedback

[0988] The user selects the nail design they like best from the displayed options. Along with their selection, the user also enters feedback, such as their rating and impressions of the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[0989] Recording feedback and incorporating it into the next session

[0990] The server analyzes the received feedback data and updates the user preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[0991] Specific examples

[0992] For example, if a user inputs the themes "blue" and "stars" and the emotion engine recognizes this as "relaxing," the AI ​​will generate a calming design combining blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will use that information to generate a more detailed nail design with a night sky motif.

[0993] Prompt Sentence Examples

[0994] Here are some examples of prompts for generative AI models:

[0995] User entered color: Blue

[0996] User-entered design image: Star

[0997] User's emotional state: Relaxed

[0998] Example output of generated nail design:

[0999] A gentle star-shaped motif design based on blue

[1000] A relaxing design with stars arranged on a blue and white gradient

[1001] Design based on the night sky motif

[1002] This system allows users to easily enjoy new nail designs that suit their individual tastes and emotional state.

[1003] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1004] Step 1:

[1005] When a user launches the nail app, a user interface appears on the device, where the user inputs their preferred color (e.g., "blue") and design image (e.g., "star") into the interface.

[1006] Specific behavior:

[1007] The user enters "blue" and "star" into the input fields and presses the Next button.

[1008] Input: User-entered color "blue" and design image "star"

[1009] Output: Data for the color "blue" and the design image "star"

[1010] Step 2:

[1011] The emotion engine built into the device analyzes the user's facial expressions and voice to recognize their emotional state (e.g., relaxed).

[1012] Specific behavior:

[1013] The device activates the camera and captures the user's face.

[1014] Turn on the microphone and record your voice.

[1015] These data are sent to the emotion engine to obtain emotion analysis results.

[1016] Input: User's facial expression and voice data

[1017] Output: User's emotional state (e.g., relaxed)

[1018] Step 3:

[1019] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), and generates a data packet that integrates these data. The generated data packet is then sent to the server.

[1020] Specific behavior:

[1021] The color "blue", the design image "star", and the emotional state "relaxed" are packaged into a JSON format data packet.

[1022] Send the data packet to the server via HTTPS.

[1023] Input: Color "blue", design image "star", emotional state "relaxed"

[1024] Output: JSON formatted data packet

[1025] Step 4:

[1026] The server analyzes the received data packets and uses them as input to a generative AI model (e.g., a large-scale language model), which generates multiple nail design ideas based on the input data.

[1027] Specific behavior:

[1028] The server analyzes the data packet and sends "blue," "stars," and "relax" as input parameters to the generative AI model.

[1029] The generative AI generates nail design ideas and saves them in JSON format.

[1030] Input: Data packet (color "blue", design image "star", emotional state "relaxed")

[1031] Output: Generated nail design ideas (JSON format)

[1032] Step 5:

[1033] The server adds past user preference data to the generated nail design proposals to generate a personalized design.

[1034] Specific behavior:

[1035] The server retrieves the user's past preference data (e.g., "night sky motif") from a database.

[1036] Based on past preference data, it is fed back into a generative AI model to generate a personalized design.

[1037] Input: Generated nail design ideas, past preference data

[1038] Output: Personalized nail design ideas

[1039] Step 6:

[1040] The server sends the generated personalized design proposals to the terminal, which analyzes the received design data packets and displays multiple design proposals on the interface.

[1041] Specific behavior:

[1042] The generated design proposal is converted into a JSON format data packet.

[1043] Send the data packet to the device via HTTPS.

[1044] The device analyzes the data packets and displays multiple design proposals.

[1045] Input: JSON formatted design data packet

[1046] Output: User interface showing the proposed design

[1047] Step 7:

[1048] The user selects the design they like best from the displayed proposals and enters feedback into the device, including their rating, impressions, and requests for what they would like to see reflected in the next design generation. The device then converts this information into a data packet and sends it back to the server.

[1049] Specific behavior:

[1050] The user selects one of the design options displayed.

[1051] Enter your evaluation, comments, and requests in the feedback form and press the submit button.

[1052] The terminal assembles the feedback information into a data packet and transmits it to the server.

[1053] Input: User selection results, ratings, impressions, requests

[1054] Output: Feedback data packet

[1055] Step 8:

[1056] The server analyzes the received feedback data and updates the user preference database, which is then used to generate the next design.

[1057] Specific behavior:

[1058] The server analyzes the feedback data and updates the preference database.

[1059] Save the updated data to the database.

[1060] The next time you generate a design, this data will be referenced to provide more personalized suggestions.

[1061] Input: Feedback data packet

[1062] Output: Updated preference database

[1063] (Application example 2)

[1064] 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."

[1065] Many conventional nail design generation systems generate designs based on the user's color and design preferences, but do not support personalization that takes into account the user's emotional state or in-store usage. This makes it difficult for users to obtain a design that matches their current emotions and circumstances. Furthermore, real-time design suggestions in-store and improved user satisfaction have not been fully realized.

[1066] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the emotional state of the user, means for personalizing the design based on the analyzed emotional state, and means for recognizing the face of the user at the physical store and visualizing the design generated in real time. This makes it possible to generate personalized nail designs in real time, taking into account the emotional state of the user and usage at the physical store.

[1067] "User" refers to an individual who utilizes the system to input colors and designs and select generated designs.

[1068] "Colors and Images" refers to the preferred colors and specific design themes that the user inputs into the system.

[1069] "Generative AI" refers to AI technology that generates new designs based on colors and images entered by the user.

[1070] "Generated design" refers to a nail design idea created by generative artificial intelligence.

[1071] "Means for displaying" refers to a device or software interface for visually presenting the generated design to a user.

[1072] "Means for selection and feedback" refers to a mechanism that allows users to select the best design from the generated designs and provide feedback.

[1073] "Means for analyzing emotional state" refers to technology that analyzes data such as the user's facial expressions and voice to understand their emotional state at that time.

[1074] "Personalization tools" refers to mechanisms that optimize the design for each individual user based on the user's emotional state.

[1075] "Facial recognition" refers to technology used to detect a user's facial features and identify individual users.

[1076] "Means for visualizing the generated design in real time" refers to technologies and devices that allow the generated design to be instantly shown to the user.

[1077] "Means for recording feedback and reflecting it in the next design generation" refers to a system in which evaluations and opinions obtained from users are stored in a database and reflected in the design generation process from the next time onwards.

[1078] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and then recognizes the user's emotional state to make personalized suggestions. This system has the following configuration and processing steps.

[1079] Hardware and Software Configuration

[1080] The system includes a user-operated device (smartphone, tablet, or head-mounted display) and a server-based generative AI and database. It uses a camera and microphone for emotion recognition, OpenCV and DeepFace libraries for facial recognition and emotion analysis, and OpenAI's GPT-3 for generating nail designs.

[1081] Processing flow

[1082] 1. User Input and Emotion Recognition

[1083] The user launches the application using a device (e.g., a smartphone) and inputs the desired color and image. For example, the user inputs the theme "blue" and "stars." The application then analyzes the user's face and voice in real time using a camera and microphone to recognize their emotional state. In this example, the application recognizes that the user is relaxed.

[1084] 2. Data transmission and analysis

[1085] The device receives the color and image data entered by the user, as well as the emotion data analyzed by the emotion recognition engine, and transmits this data to the server. The data is first converted into data packets.

[1086] 3. Nail design generation

[1087] The server analyzes the received data packets and uses them as input for the generative AI (OpenAI GPT-3). The generative AI generates multiple nail design ideas based on the user's specified colors and images, as well as the analysis results of an emotion recognition engine. For example, it can generate a calming nail design combining blue and silver stars, or a design with stars arranged on a blue and white gradient.

[1088] 4. Personalized recommendations

[1089] The AI ​​also references the user's past preference data to generate more personalized designs. For example, it creates a calming nail design with a starry sky motif, taking into account the user's past choice of "night sky motif" design and their current emotional state of relaxation.

[1090] 5. Submit and display your design

[1091] The generated nail design proposals are converted into data packets and sent from the server to the terminal. The terminal analyzes the received design data packets and displays multiple design proposals on the interface. The user can visually check these design proposals.

[1092] Specific examples

[1093] For example, if a user inputs the themes "blue" and "stars" and the emotion engine recognizes this as relaxing, the generative AI will generate a prompt like this:

[1094] "Create a nail design with a blue and star theme that matches your relaxed mood."

[1095] In response to this prompt, the AI ​​will generate a calming design that combines blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Additionally, if the user has previously chosen a nail design with a "night sky" theme, the AI ​​will consider a more detailed design using a night sky motif.

[1096] This system allows users to easily try out personalized nail designs that match their emotional state and preferences at any given time, and since designs are generated and visualized in real time, it is also suitable for use in brick-and-mortar stores.

[1097] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1098] Step 1:

[1099] A user starts an application using a device (e.g., a smartphone). The user inputs the desired color and image. In this case, the input color is "blue" and the input image is "star." This information is saved on the device as user-input data.

[1100] Input: Color and image data (e.g. "blue", "star")

[1101] Output: User input data

[1102] Step 2:

[1103] The device uses the camera and microphone to analyze the user's face and voice in real time to recognize their emotional state. Here, OpenCV and DeepFace libraries are used for facial recognition and emotional analysis. The emotional state is recognized as "relaxed."

[1104] Input: User's face and voice data

[1105] Output: Emotional state data (e.g., "Relaxed")

[1106] Step 3:

[1107] The terminal takes the user's input data (color and image) and emotional state data and converts them into data packets, which are then sent to the server.

[1108] Input: User input data and emotional state data

[1109] Output: Data packet (containing user input data and emotional state data)

[1110] Step 4:

[1111] The server analyzes the received data packets and uses them as input for the generation AI. Here, OpenAI's GPT-3 is used to generate prompts and generate multiple nail design ideas. For example, the prompt generated is, "Generate a nail design with a blue and star theme that matches the relaxed emotion."

[1112] Input: Data packet (contains user input data and emotional state data)

[1113] Output: Multiple nail design ideas

[1114] Step 5:

[1115] The server converts the generated nail design proposal into a data packet and transmits it again to the terminal.

[1116] Input: Multiple nail design ideas

[1117] Output: Design Data Packet

[1118] Step 6:

[1119] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually check these design proposals.

[1120] Input: Design Data Packet

[1121] Output: Multiple design ideas displayed on the interface

[1122] Step 7:

[1123] The user selects the nail design they like best from the displayed options and enters feedback such as their evaluation and thoughts on the design, requests for the next design, etc. The device then converts this feedback back into a data packet and sends it to the server.

[1124] Input: User selections and feedback

[1125] Output: Feedback data packet

[1126] Step 8:

[1127] The server analyzes the received feedback data and updates the user preference database, which is used as a reference for subsequent design generation.

[1128] Input: Feedback data packet

[1129] Output: Updated preference database

[1130] Through these steps, users can easily try out personalized nail designs that suit their emotional state and preferences at any given time. Furthermore, since designs are generated and visualized in real time, the system is suitable for use in brick-and-mortar stores.

[1131] 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.

[1132] 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.

[1133] 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.

[1134] [Fourth embodiment]

[1135] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1136] 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.

[1137] 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).

[1138] 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.

[1139] 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.

[1140] 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).

[1141] 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.

[1142] 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.

[1143] 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.

[1144] 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.

[1145] 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.

[1146] 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.

[1147] 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."

[1148] This invention is a system in which a generation AI (artificial intelligence) automatically generates nail designs based on the colors and images input by the user, proposes them to the user, and receives feedback to improve the proposals from the next time onwards. Specific embodiments of this system are described below.

[1149] Program processing overview

[1150] User Input and Data Submission

[1151] The user first launches the system's terminal application and inputs their preferred color and design image. For example, if the user inputs "blue" and "stars" as their preferred color and design image, the terminal will acquire this information, convert it into a data packet, and send it to the server.

[1152] Nail design generation

[1153] The server analyzes the user's input data received from the device and activates the AI ​​generator, which generates multiple nail design ideas based on the analyzed colors and design image. For example, there are designs based on a blue base and a star motif, a design with stars on a blue and white gradient, and a design with silver stars on a blue background.

[1154] Personalized suggestions

[1155] The AI ​​then references the user's past preference data and generates a more personalized design based on this. If the user has previously selected a "night sky motif" design, the AI ​​will also take this into account when generating a design.

[1156] Send and view your designs

[1157] The generated nail design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data and displays multiple design proposals on the interface. The user can visually check these proposed designs.

[1158] User Choice and Feedback

[1159] The user selects the nail design they like best from the proposed options. Along with their selection, the user also inputs feedback, such as their evaluation and thoughts on the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[1160] Recording feedback and incorporating it into the next session

[1161] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[1162] Specific examples

[1163] For example, if a user inputs a design with the theme of "blue" and "stars," the AI ​​will generate a design that combines blue and silver stars, or a design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will use that information to generate a more detailed nail design with a night sky motif. This allows users to always enjoy new nail designs that suit their tastes.

[1164] This system allows users to easily try out new nail designs, saving time and effort while providing an original design experience that suits their individual tastes.

[1165] The processing flow will be explained below.

[1166] Step 1:

[1167] The user launches the nail app and is presented with an interface to input their preferred color (e.g., "blue") and design image (e.g., "star"). The user enters this information and presses the send button.

[1168] Step 2:

[1169] The terminal receives the user's input data (color and design image), converts it into a data packet, and sends the converted data packet to the server.

[1170] Step 3:

[1171] The server receives user input data from the device, records it in a database, analyzes the data, and uses it as input for the generation AI.

[1172] Step 4:

[1173] The AI ​​then generates multiple nail design ideas based on the analyzed colors and design image, such as a blue-based star-shaped design or a blue and white gradient with stars.

[1174] Step 5:

[1175] The server converts the generated nail design proposal back into a data packet and transmits it to the terminal.

[1176] Step 6:

[1177] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually confirm these design proposals.

[1178] Step 7:

[1179] The user selects the design they like best from the displayed nail design suggestions, and along with their selection, they can enter their evaluation and thoughts on the design, as well as any requests they would like to have reflected in the next design generation, as feedback.

[1180] Step 8:

[1181] The terminal obtains the user's selection and feedback data, converts it into a data packet, and sends the converted data packet to the server.

[1182] Step 9:

[1183] The server analyzes the received feedback data and updates the user preference database. The updated data is reflected in subsequent design generation, resulting in more personalized design suggestions.

[1184] Example 1

[1185] 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."

[1186] Conventional nail design generation systems have difficulty efficiently generating designs that match the user's preferences. In addition, they lack the mechanism for incorporating user feedback into the next design generation, which makes it difficult to provide personalized suggestions.

[1187] 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.

[1188] In this invention, the server includes means for a user to input a color and an image, means including a generation artificial intelligence that generates a prompt sentence based on the input color and image and generates a plurality of design proposals, means for displaying the generated designs, means for accepting selection and feedback on the generated designs, and means for recording the feedback and reflecting it in the next design generation. This enables efficient design generation based on the user's preferences and personalized proposals by reflecting the feedback in the next design proposal.

[1189] A "user" is a person who uses the system's terminal application to input their preferred colors and design images, and select and evaluate the generated nail designs.

[1190] "Color" refers to the color information that forms the basis of the nail design that the user inputs into the system.

[1191] An "image" is a visual concept of a nail design motif or theme that a user inputs into the system.

[1192] A "prompt sentence" is a text-based input sentence that instructs the generative AI model to generate a design based on the colors and images entered by the user.

[1193] A "generative AI model" is an artificial intelligence algorithm that generates multiple nail design ideas based on user input data.

[1194] A "data packet" is a data format for efficiently transferring user input information and generated design data.

[1195] The "preference database" is a database that stores information on users' past choices and feedback and reflects this information in the next design generation.

[1196] "Feedback" refers to response information such as evaluations, impressions, and requests made by users regarding the generated design.

[1197] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, proposes them to the user, and receives feedback to improve the proposals for the next time and thereafter. Specific embodiments of this system are described below.

[1198] First, the user launches the system's terminal application. The terminal displays an input form for entering color and design image through the user interface. For example, the user enters "blue" and "stars" as their preferred color and design image. The terminal acquires this input information, converts it into a JSON-formatted data packet, and sends the data packet to the server.

[1199] The server analyzes the received data packet and extracts the color and design image specified by the user. Then, the server generates a prompt based on the analyzed data. For example, it generates a text prompt such as, "The color entered by the user is blue, and the design image is a star. Please generate a nail design."

[1200] Using the generated prompt, the server launches a generative AI model (e.g., OpenAI's GPT-3) to generate multiple nail design ideas. The generative AI model follows the prompt and outputs multiple design ideas, such as a design that combines blue and silver stars, or a design with stars arranged on a blue and white gradient.

[1201] The server also references the user's past preference data to generate personalized designs that take the user's preferences into account. If the user previously selected a "night sky motif" design, a night sky-themed design will also be generated based on that information.

[1202] The generated design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data and displays multiple design proposals on the user interface. For example, each design proposal is displayed as a thumbnail image in a 2-column by 2-row grid format.

[1203] The user selects the nail design they like best from the proposed options. Along with their selection, they can input feedback such as their evaluation and impressions of the design, as well as requests they would like reflected in the next design generation. The device converts this feedback information into data packets and sends them to the server.

[1204] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for the next design generation, resulting in more personalized design suggestions. This process allows users to easily try out new nail designs, saving time and effort while providing an original design experience tailored to their individual tastes.

[1205] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1206] Step 1: User Input and Data Submission

[1207] The user launches the system's terminal application and inputs their preferred color and design image. The input data, such as "blue" and "star," is converted into a JSON-formatted data packet by the terminal. The terminal then sends the generated data packet to the server. The input is the user's color and design image, and the output is the data sent to the server.

[1208] Step 2: Receiving and analyzing data on the server

[1209] The server receives a data packet sent from the terminal. For example, if the received data packet is {"color": "blue", "design": "star"}, the server analyzes the data packet and extracts the color "blue" and the design "star". This is the analysis of the input data, and the output is the analysis result.

[1210] Step 3: Generate prompts and launch the AI ​​model

[1211] The server generates a prompt based on the analyzed color and design image. For example, the generated prompt might be, "The color entered by the user is blue, and the design image is a star. Please generate a nail design." The server then inputs this prompt into a generative AI model (e.g., OpenAI's GPT-3) to generate nail design suggestions. The input is the prompt, and the output is the generated design suggestions.

[1212] Step 4: Personalized offers

[1213] In addition to the generated nail design suggestions, the server also references the user's past preference data. Based on this, the generative AI model also generates more personalized design suggestions. For example, if a user previously selected a "night sky motif" design, a design based on this information will also be added. The input is past preference data, and the output is personalized design suggestions.

[1214] Step 5: Send and view your design

[1215] The server converts the generated design proposals into data packets and sends them to the terminal. The terminal analyzes the received design data and displays multiple design proposals on a user interface, for example, displaying each design proposal as a thumbnail in a 2-column by 2-row grid format. The input is the design proposal data packets, and the output is a visual display for the user.

[1216] Step 6: User selection and feedback

[1217] The user selects one of the displayed design proposals and enters their evaluation and feedback on that design. The device converts this feedback into a data packet and sends it back to the server. The input is the user's selection and feedback, and the output is the data sent to the server.

[1218] Step 7: Recording of Feedback and Reflection in the Next Round

[1219] The server analyzes the received feedback data and updates the user preference database. The updated data is used as a reference in the next design generation, and more personalized proposals are made. The input is the feedback data, and the output is the updated preference database. This step enables the system to more accurately meet user needs by integrating the user's design preference information.

[1220] (Application Example 1)

[1221] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the robot 414 is referred to as the "terminal".

[1222] The existing nail design proposal system only generates temporary designs based on the colors and images input by the user, and there is a problem that no specific proposals that can be utilized in salon treatments are made. Furthermore, since the communication means between the user and the service provider (nail salon staff) are limited, personalized design proposals are not sufficiently made. As a result, it is difficult to improve user satisfaction, and there is no guarantee that the quality of the service will be uniformly maintained.

[1223] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[1224] In this invention, the server includes means for a user to input a color and an image, means including a generation artificial intelligence that generates a design based on the input color and image, means for displaying the generated design, means for accepting selections and feedback on the generated design, means for recording the feedback and reflecting it in the next design generation, means for generating design proposals based on the user's preferences in advance and sharing them with a service provider, and means for the service provider to review the design proposals and make personalized suggestions to the user, thereby enabling more effective communication between the user and the service provider and providing personalized services.

[1225] "User" refers to an individual who uses the system to input colors and design ideas and receive design proposals. It may also refer to a customer of a nail salon.

[1226] "Means for inputting colors and images" refers to an interface (e.g., a touch screen or voice input) that a user uses to input their preferred colors and design images.

[1227] "Generative AI" refers to AI technology that automatically generates designs based on input color and image information. Examples include generative AI models such as DALL-E and StyleGAN.

[1228] "Means for displaying the design" refers to a display or screen for visually presenting the generated nail design to the user.

[1229] "Means for selecting designs and receiving feedback" refers to an interface that allows users to select their preferred design from the proposed designs and input their evaluation of the design and requests for improvement.

[1230] "Means for recording feedback and reflecting it in the next design generation" refers to a system in which feedback information obtained from users is stored in a database and used in generating designs from the next time onwards.

[1231] "Service provider" refers to professionals who provide nail design installation services to users, such as nail salon staff and hairdressers.

[1232] "Means for generating design proposals in advance based on user preferences and sharing them with service providers" refers to a communication means for preparing design proposals in advance based on user input information and making them available for service providers to view.

[1233] "Means for making personalized suggestions" refers to a system or interface that allows a service provider to present optimal design proposals based on a user's individual preferences and past selection data.

[1234] This invention provides a system that automatically generates nail designs based on the colors and design image input by the user, proposes them to the user and service providers (such as nail salon staff), collects feedback, and reflects it in future proposals. Specific embodiments of this system are described below.

[1235] System configuration

[1236] The system mainly consists of the following hardware and software components:

[1237] 1. User Interface (UI):

[1238] Smartphone: A device that allows users to input color and design images.

[1239] Application (app): Software that allows users to input, review, and provide feedback on colors and design images.

[1240] 2. Server:

[1241] Cloud server: Receives, processes, and stores data.

[1242] Generative AI models: Generate nail designs based on user input. Examples include models such as DALL-E and StyleGAN.

[1243] Database: Stores user preferences and feedback information and uses it for the next design generation. For example, AWS RDS is used.

[1244] 3. Service Provider Interface:

[1245] Tablet or desktop PC: A device for salon staff to review design ideas based on customer preferences and feedback.

[1246] Application: Software that allows staff to review design proposals and make suggestions to users as needed.

[1247] Processing flow

[1248] 1. User input:

[1249] Users start the app and input their preferred colors and design image, for example, selecting elements such as "blue" or "stars" as their preferences.

[1250] 2. Data transmission:

[1251] The entered data is sent to the cloud server via the application.

[1252] 3. Design generation:

[1253] The server uses a generative AI model to generate multiple nail design ideas based on the input information.

[1254] The generated design proposals are sent back to the user's app in JSON format.

[1255] 4. Design Proposal:

[1256] The design proposals generated by the user's application are visually displayed, and the user can select the design they prefer.

[1257] The selected design proposal and feedback are sent back to the server.

[1258] 5. Sharing with Service Providers:

[1259] User preferences and feedback are also shared with the service provider's interface, allowing staff to make suggestions based on the user's preferences and feedback in advance.

[1260] 6. Record feedback and incorporate it into your next proposal:

[1261] The server records user feedback in a database and uses this information in the next design generation.

[1262] Specific examples

[1263] For example, if a user inputs a design based on the themes of "blue" and "stars," the generation AI will generate a design using prompts like the following:

[1264] Prompt: Use a generative AI model to generate a nail design based on the following criteria:

[1265] conditions:

[1266] Basic color: blue

[1267] Design image: Star

[1268] Past feedback: Users tend to prefer designs with a night sky theme

[1269] Based on this prompt, the generative AI will generate a nail design that matches the user's preferences and suggest it to the user and service provider, thereby realizing personalized, high-quality service provision.

[1270] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1271] Step 1:

[1272] A user launches a smartphone application and inputs their preferred color (e.g., "blue") and design image (e.g., "star"). The input information is obtained in text or image format. This information is converted into a JSON-formatted data packet for the next processing step.

[1273] Step 2:

[1274] The device sends the generated JSON data packet to a cloud server, which receives it and parses it as input to launch a generative AI model (e.g., DALL-E).

[1275] Step 3:

[1276] Based on the analyzed data, the server generates a prompt to generate the nail design requested by the user. For example, the prompt might be in the form of "Base color is blue, design image is stars, and based on past feedback, create a design with a night sky theme." The generative AI model uses this prompt to generate multiple nail design candidates.

[1277] Step 4:

[1278] The server then packets the generated nail design ideas in JSON format and resends them to the user's device. The user's application visually displays the received design ideas and arranges them in a format that the user can view.

[1279] Step 5:

[1280] The user selects the design they like from the presented options. Along with the selected design, they enter their feedback (e.g., their rating of the design and their requests for the next design) into the application. The feedback information is then converted back into a JSON-formatted data packet.

[1281] Step 6:

[1282] The device sends the feedback information entered by the user to the cloud server, which analyzes the received feedback and records it in a database, which is used to update the user preference database.

[1283] Step 7:

[1284] The server prepares data to be used for subsequent design generation based on the updated preference database. Service providers (nail salon staff) can also use a dedicated application to view design suggestions based on the user's preferences and feedback.

[1285] Step 8:

[1286] The service provider uses a tablet or desktop application to check the design ideas and feedback information selected by the user, and then proposes and performs a personalized nail design. This allows the user to find out which design best suits their preferences before visiting the salon.

[1287] Through this series of processes, users can easily receive personalized nail designs that suit their preferences, and service providers can use this information to provide high-quality services.

[1288] 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.

[1289] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and further recognizes the user's emotional state to make personalized suggestions. An embodiment of this system will be described in detail below.

[1290] Program processing overview

[1291] User Input and Emotion Recognition

[1292] When a user launches the nail app, an interface appears. The user inputs their preferred color (e.g., "blue") and design image (e.g., "star"). The emotion engine then analyzes the user's facial expressions and voice to recognize their emotional state. For example, it recognizes that the user is relaxed.

[1293] Data transmission and analysis

[1294] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), converting them into data packets, which are then sent to the server.

[1295] Nail design generation

[1296] The server analyzes the data packets received from the device and uses them as input for the generation AI. The generation AI generates multiple nail design proposals based on the user's specified colors and design image, as well as the analysis results of the emotion engine. For example, it could create a star-shaped design with a calm atmosphere based on blue, matching a relaxed emotional state.

[1297] Personalized suggestions

[1298] The generative AI also references the user's past preference data to generate more personalized designs. For example, it can generate a calming design with a starry sky motif, taking into account the user's past choice of "night sky motif" design and their current relaxed emotional state.

[1299] Send and view your designs

[1300] The generated nail design proposals are converted back into data packets and sent from the server to the device. The device analyzes the received design data packets and displays multiple design proposals on the interface, allowing the user to visually check these design proposals.

[1301] User Choice and Feedback

[1302] The user selects the nail design they like best from the displayed options. Along with their selection, the user also enters feedback, such as their evaluation and thoughts on the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[1303] Recording feedback and incorporating it into the next session

[1304] The server analyzes the received feedback data and updates the user's preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[1305] Specific examples

[1306] For example, if a user inputs the theme "blue" and "stars" and the emotion engine recognizes this as "relaxing," the AI ​​will generate a calming design combining blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will generate a nail design with a more detailed night sky motif based on that information. This allows users to always enjoy new nail designs that suit their tastes.

[1307] The system allows users to easily try out new nail designs, saving time and effort while providing an original design experience that suits their individual tastes and emotional state at the time.

[1308] The processing flow will be explained below.

[1309] Step 1:

[1310] The user launches the nail app and is presented with an interface where they can input their preferred color (e.g., "blue") and design image (e.g., "star"). The user inputs this information.

[1311] Step 2:

[1312] The emotion engine works by analyzing the user's facial expressions and voice, and as a result, it recognizes the user's emotional state (e.g., relaxed).

[1313] Step 3:

[1314] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), converting them into data packets, which are then sent to the server.

[1315] Step 4:

[1316] The server analyzes the data packets received from the device and uses them as input for the generation AI based on the user's specified colors, design image, and emotional state.

[1317] Step 5:

[1318] The AI ​​then generates multiple nail design ideas based on the analyzed data, for example, a star-shaped design with a blue base and a calming atmosphere that matches a relaxed emotional state.

[1319] Step 6:

[1320] The AI ​​will refer to a database of the user's past preferences, for example, by taking into account the user's past choice of "night sky motif" design and their current feeling of relaxation, and generate a design using a more detailed night sky motif.

[1321] Step 7:

[1322] The server converts the generated nail design proposal into a data packet and transmits it to the terminal.

[1323] Step 8:

[1324] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually confirm these design proposals.

[1325] Step 9:

[1326] The user selects the design they like best from the displayed nail design suggestions, and along with their selection, they can enter their evaluation and thoughts on the design, as well as any requests they would like to have reflected in the next design generation, as feedback.

[1327] Step 10:

[1328] The terminal obtains the user's selection and feedback data, converts it into a data packet, and sends the data packet to the server.

[1329] Step 11:

[1330] The server analyzes the received feedback data and updates the user preference database. The updated data is reflected in subsequent design generation, resulting in more personalized design suggestions.

[1331] This allows the system to provide original nail designs that match the user's preferences and current emotional state.

[1332] Example 2

[1333] 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."

[1334] Conventional nail design generation systems are unable to propose designs that take into account the user's emotional state, making it difficult to increase user satisfaction. Furthermore, there is a lack of a means to effectively utilize past preference data to generate personalized designs. Therefore, there is a need for a system that can propose optimal designs for each individual user.

[1335] 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.

[1336] In this invention, the server includes a means for the user to input colors and images, a means for analyzing the user's facial expressions and voice to recognize the emotional state, and a means including a generation artificial intelligence that generates designs based on the input colors and images and the analyzed emotional state, thereby making it possible to automatically generate personalized nail designs according to the user's emotional state.

[1337] "User" means an individual who utilizes the system to input colors and images to generate nail designs, and provides selections and feedback on the generated designs.

[1338] "Color" is a visual element that forms the basis or accent of the design entered by the user, and is a basic element that makes up the appearance of a nail design.

[1339] An "image" is a visual element that serves as the theme or motif of a design entered by the user, and constitutes the specific shape or pattern of the nail design.

[1340] "Emotional state" refers to a psychological state that is recognized by analyzing the user's facial expressions and voice, and represents emotions such as relaxation or excitement.

[1341] "Generative AI" refers to advanced algorithms and models that automatically generate nail designs based on input data.

[1342] The "display means" refers to an interface or device that allows the user to visually check the generated nail design.

[1343] "Feedback" refers to information such as the user's evaluation and impressions of the design they selected, and requests they would like to reflect in the next design generation.

[1344] A "data packet" is a unit of digital data that compiles information such as a user's input data, emotional state, and generated design.

[1345] A "server" is a computer system that receives, analyzes, and stores data sent by users.

[1346] "Terminal" means a device on which a user enters input and displays a design, including a smartphone or tablet.

[1347] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and further recognizes the user's emotional state to make personalized suggestions. An embodiment of this system will be described in detail below.

[1348] User Input and Emotion Recognition

[1349] When the device launches the nail application, a user interface is displayed. The user inputs their preferred color (e.g., "blue") and design image (e.g., "star"). Furthermore, the device incorporates an emotion engine (e.g., facial expression recognition API and voice analysis API) that analyzes the user's facial expressions and voice to recognize their emotional state. For example, it can recognize that the user is relaxed.

[1350] Data transmission and analysis

[1351] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), and generates a data packet that combines these data. The generated data packet is then sent to a server via the Internet.

[1352] Nail design generation

[1353] The server analyzes the received data packets and generates a nail design using a generative AI model (e.g., a large-scale language model). This generative AI generates multiple nail design proposals based on the user's specified color "blue," the design image "star," and the recognized emotional state "relaxed." For example, it creates a design with a blue base and a calm star motif that matches the relaxed emotional state.

[1354] Personalized suggestions

[1355] The generative AI can also refer to the user's past preference data to generate more personalized designs. For example, it can generate a design with a starry sky motif by taking into account the user's previous choice of a "night sky motif" design and their current relaxed emotional state.

[1356] Send and view your designs

[1357] The generated nail design proposals are converted back into data packets and sent from the server to the terminal. The terminal analyzes the received design data packets and displays multiple design proposals on the user interface. The user can visually check these design proposals.

[1358] User Choice and Feedback

[1359] The user selects the nail design they like best from the displayed options. Along with their selection, the user also enters feedback, such as their rating and impressions of the design, and any suggestions they would like to see reflected in the next design. This information is then converted back into a data packet and sent to the server.

[1360] Recording feedback and incorporating it into the next session

[1361] The server analyzes the received feedback data and updates the user preference database. This updated preference data is used as a reference for subsequent design generation, resulting in more personalized design suggestions.

[1362] Specific examples

[1363] For example, if a user inputs the themes "blue" and "stars" and the emotion engine recognizes this as "relaxing," the AI ​​will generate a calming design combining blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Furthermore, if a user previously selected the theme "night sky," the AI ​​will use that information to generate a more detailed nail design with a night sky motif.

[1364] Prompt Sentence Examples

[1365] Here are some examples of prompts for generative AI models:

[1366] User entered color: Blue

[1367] User-entered design image: Star

[1368] User's emotional state: Relaxed

[1369] Example output of generated nail design:

[1370] A gentle star-shaped motif design based on blue

[1371] A relaxing design with stars arranged on a blue and white gradient

[1372] Design based on the night sky motif

[1373] This system allows users to easily enjoy new nail designs that suit their individual tastes and emotional state.

[1374] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1375] Step 1:

[1376] When a user launches the nail app, a user interface appears on the device, where the user inputs their preferred color (e.g., "blue") and design image (e.g., "star") into the interface.

[1377] Specific behavior:

[1378] The user enters "blue" and "star" into the input fields and presses the Next button.

[1379] Input: User-entered color "blue" and design image "star"

[1380] Output: Data for the color "blue" and the design image "star"

[1381] Step 2:

[1382] The emotion engine built into the device analyzes the user's facial expressions and voice to recognize their emotional state (e.g., relaxed).

[1383] Specific behavior:

[1384] The device activates the camera and captures the user's face.

[1385] Turn on the microphone and record your voice.

[1386] These data are sent to the emotion engine to obtain emotion analysis results.

[1387] Input: User's facial expression and voice data

[1388] Output: User's emotional state (e.g., relaxed)

[1389] Step 3:

[1390] The device receives the user's input data (color and design image) and the emotion engine's analysis results (emotional state), and generates a data packet that integrates these data. The generated data packet is then sent to the server.

[1391] Specific behavior:

[1392] The color "blue", the design image "star", and the emotional state "relaxed" are packaged into a JSON format data packet.

[1393] Send the data packet to the server via HTTPS.

[1394] Input: Color "blue", design image "star", emotional state "relaxed"

[1395] Output: JSON formatted data packet

[1396] Step 4:

[1397] The server analyzes the received data packets and uses them as input to a generative AI model (e.g., a large-scale language model), which generates multiple nail design ideas based on the input data.

[1398] Specific behavior:

[1399] The server analyzes the data packet and sends "blue," "stars," and "relax" as input parameters to the generative AI model.

[1400] The generative AI generates nail design ideas and saves them in JSON format.

[1401] Input: Data packet (color "blue", design image "star", emotional state "relaxed")

[1402] Output: Generated nail design ideas (JSON format)

[1403] Step 5:

[1404] The server adds past user preference data to the generated nail design proposals to generate a personalized design.

[1405] Specific behavior:

[1406] The server retrieves the user's past preference data (e.g., "night sky motif") from a database.

[1407] Based on past preference data, it is fed back into a generative AI model to generate a personalized design.

[1408] Input: Generated nail design ideas, past preference data

[1409] Output: Personalized nail design ideas

[1410] Step 6:

[1411] The server sends the generated personalized design proposals to the terminal, which analyzes the received design data packets and displays multiple design proposals on the interface.

[1412] Specific behavior:

[1413] The generated design proposal is converted into a JSON format data packet.

[1414] Send the data packet to the device via HTTPS.

[1415] The device analyzes the data packets and displays multiple design proposals.

[1416] Input: JSON formatted design data packet

[1417] Output: User interface showing the proposed design

[1418] Step 7:

[1419] The user selects the design they like best from the displayed proposals and enters feedback into the device, including their rating, impressions, and requests for what they would like to see reflected in the next design generation. The device then converts this information into a data packet and sends it back to the server.

[1420] Specific behavior:

[1421] The user selects one of the design options displayed.

[1422] Enter your evaluation, comments, and requests in the feedback form and press the submit button.

[1423] The terminal assembles the feedback information into a data packet and transmits it to the server.

[1424] Input: User selection results, ratings, impressions, requests

[1425] Output: Feedback data packet

[1426] Step 8:

[1427] The server analyzes the received feedback data and updates the user preference database, which is then used to generate the next design.

[1428] Specific behavior:

[1429] The server analyzes the feedback data and updates the preference database.

[1430] Save the updated data to the database.

[1431] The next time you generate a design, this data will be referenced to provide more personalized suggestions.

[1432] Input: Feedback data packet

[1433] Output: Updated preference database

[1434] (Application example 2)

[1435] 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."

[1436] Many conventional nail design generation systems generate designs based on the user's color and design preferences, but do not support personalization that takes into account the user's emotional state or in-store usage. This makes it difficult for users to obtain a design that matches their current emotions and circumstances. Furthermore, real-time design suggestions in-store and improved user satisfaction have not been fully realized.

[1437] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the emotional state of the user, means for personalizing the design based on the analyzed emotional state, and means for recognizing the face of the user at the physical store and visualizing the design generated in real time. This makes it possible to generate personalized nail designs in real time, taking into account the emotional state of the user and usage at the physical store.

[1438] "User" refers to an individual who utilizes the system to input colors and designs and select generated designs.

[1439] "Colors and Images" refers to the preferred colors and specific design themes that the user inputs into the system.

[1440] "Generative AI" refers to AI technology that generates new designs based on colors and images entered by the user.

[1441] "Generated design" refers to a nail design idea created by generative artificial intelligence.

[1442] "Means for displaying" refers to a device or software interface for visually presenting the generated design to a user.

[1443] "Means for selection and feedback" refers to a mechanism that allows users to select the best design from the generated designs and provide feedback.

[1444] "Means for analyzing emotional state" refers to technology that analyzes data such as the user's facial expressions and voice to understand their emotional state at that time.

[1445] "Personalization tools" refers to mechanisms that optimize the design for each individual user based on the user's emotional state.

[1446] "Facial recognition" refers to technology used to detect a user's facial features and identify individual users.

[1447] "Means for visualizing the generated design in real time" refers to technologies and devices that allow the generated design to be instantly shown to the user.

[1448] "Means for recording feedback and reflecting it in the next design generation" refers to a system in which evaluations and opinions obtained from users are stored in a database and reflected in the design generation process from the next time onwards.

[1449] This invention is a system in which a generation AI automatically generates nail designs based on the colors and images input by the user, and then recognizes the user's emotional state to make personalized suggestions. This system has the following configuration and processing steps.

[1450] Hardware and Software Configuration

[1451] The system includes a user-operated device (smartphone, tablet, or head-mounted display) and a server-based generative AI and database. It uses a camera and microphone for emotion recognition, OpenCV and DeepFace libraries for facial recognition and emotion analysis, and OpenAI's GPT-3 for generating nail designs.

[1452] Processing flow

[1453] 1. User Input and Emotion Recognition

[1454] The user launches the application using a device (e.g., a smartphone) and inputs the desired color and image. For example, the user inputs the theme "blue" and "stars." The application then analyzes the user's face and voice in real time using a camera and microphone to recognize their emotional state. In this example, the application recognizes that the user is relaxed.

[1455] 2. Data transmission and analysis

[1456] The device receives the color and image data entered by the user, as well as the emotion data analyzed by the emotion recognition engine, and transmits this data to the server. The data is first converted into data packets.

[1457] 3. Nail design generation

[1458] The server analyzes the received data packets and uses them as input for the generative AI (OpenAI GPT-3). The generative AI generates multiple nail design ideas based on the user's specified colors and images, as well as the analysis results of an emotion recognition engine. For example, it can generate a calming nail design combining blue and silver stars, or a design with stars arranged on a blue and white gradient.

[1459] 4. Personalized recommendations

[1460] The AI ​​also references the user's past preference data to generate more personalized designs. For example, it creates a calming nail design with a starry sky motif, taking into account the user's past choice of "night sky motif" design and their current emotional state of relaxation.

[1461] 5. Submit and display your design

[1462] The generated nail design proposals are converted into data packets and sent from the server to the terminal. The terminal analyzes the received design data packets and displays multiple design proposals on the interface. The user can visually check these design proposals.

[1463] Specific examples

[1464] For example, if a user inputs the themes "blue" and "stars" and the emotion engine recognizes this as relaxing, the generative AI will generate a prompt like this:

[1465] "Create a nail design with a blue and star theme that matches your relaxed mood."

[1466] In response to this prompt, the AI ​​will generate a calming design that combines blue and silver stars, or a relaxing design with stars placed on a blue and white gradient. Additionally, if the user has previously chosen a nail design with a "night sky" theme, the AI ​​will consider a more detailed design using a night sky motif.

[1467] This system allows users to easily try out personalized nail designs that match their emotional state and preferences at any given time, and since designs are generated and visualized in real time, it is also suitable for use in brick-and-mortar stores.

[1468] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1469] Step 1:

[1470] A user starts an application using a device (e.g., a smartphone). The user inputs the desired color and image. In this case, the input color is "blue" and the input image is "star." This information is saved on the device as user-input data.

[1471] Input: Color and image data (e.g. "blue", "star")

[1472] Output: User input data

[1473] Step 2:

[1474] The device uses the camera and microphone to analyze the user's face and voice in real time to recognize their emotional state. Here, OpenCV and DeepFace libraries are used for facial recognition and emotional analysis. The emotional state is recognized as "relaxed."

[1475] Input: User's face and voice data

[1476] Output: Emotional state data (e.g., "Relaxed")

[1477] Step 3:

[1478] The terminal takes the user's input data (color and image) and emotional state data and converts them into data packets, which are then sent to the server.

[1479] Input: User input data and emotional state data

[1480] Output: Data packet (containing user input data and emotional state data)

[1481] Step 4:

[1482] The server analyzes the received data packets and uses them as input for the generation AI. Here, OpenAI's GPT-3 is used to generate prompts and generate multiple nail design ideas. For example, the prompt generated is, "Generate a nail design with a blue and star theme that matches the relaxed emotion."

[1483] Input: Data packet (contains user input data and emotional state data)

[1484] Output: Multiple nail design ideas

[1485] Step 5:

[1486] The server converts the generated nail design proposal into a data packet and transmits it again to the terminal.

[1487] Input: Multiple nail design ideas

[1488] Output: Design Data Packet

[1489] Step 6:

[1490] The terminal analyzes the received design data packet and displays multiple design proposals on the interface, allowing the user to visually check these design proposals.

[1491] Input: Design Data Packet

[1492] Output: Multiple design ideas displayed on the interface

[1493] Step 7:

[1494] The user selects the nail design they like best from the displayed options and enters feedback such as their evaluation and thoughts on the design, requests for the next design, etc. The device then converts this feedback back into a data packet and sends it to the server.

[1495] Input: User selections and feedback

[1496] Output: Feedback data packet

[1497] Step 8:

[1498] The server analyzes the received feedback data and updates the user preference database, which is used as a reference for subsequent design generation.

[1499] Input: Feedback data packet

[1500] Output: Updated preference database

[1501] Through these steps, users can easily try out personalized nail designs that suit their emotional state and preferences at any given time. Furthermore, since designs are generated and visualized in real time, the system is suitable for use in brick-and-mortar stores.

[1502] 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.

[1503] 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.

[1504] 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.

[1505] 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.

[1506] 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.

[1507] 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.

[1508] 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).

[1509] 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.

[1510] 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."

[1511] 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.

[1512] 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).

[1513] 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.

[1514] 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.

[1515] 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.

[1516] 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.

[1517] 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.

[1518] 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.

[1519] 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.

[1520] 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.

[1521] 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.

[1522] 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.

[1523] The following is further disclosed regarding the above embodiment.

[1524] (Claim 1)

[1525] means for a user to input colors and images;

[1526] means for generating a design based on the input color and image, including a generation artificial intelligence;

[1527] means for displaying the generated design;

[1528] means for accepting selections and feedback on the generated designs;

[1529] The system includes means for recording said feedback and incorporating it into subsequent design generation.

[1530] (Claim 2)

[1531] 10. The system of claim 1, wherein the generative artificial intelligence generates personalized designs based on the user's past choices and preferences.

[1532] (Claim 3)

[1533] 2. The system of claim 1, wherein the design generation means includes means for generating and proposing a plurality of design proposals to the user.

[1534] "Example 1"

[1535] (Claim 1)

[1536] means for a user to input colors and images;

[1537] means for generating a prompt sentence based on the input color and image, and generating a plurality of design proposals;

[1538] means for displaying the generated design;

[1539] means for accepting selections and feedback on the generated designs;

[1540] The system includes means for recording said feedback and incorporating it into subsequent design generation.

[1541] (Claim 2)

[1542] 10. The system of claim 1, wherein the generative artificial intelligence generates personalized designs based on the user's past choices and preferences.

[1543] (Claim 3)

[1544] 2. The system according to claim 1, further comprising means for generating a prompt sentence based on the input color and image and inputting the prompt sentence to the generation artificial intelligence.

[1545] (Claim 4)

[1546] 2. The system according to claim 1, further comprising means for converting the plurality of design proposals generated by the generating artificial intelligence into data packets and transmitting the data packets to a user terminal.

[1547] "Application Example 1"

[1548] (Claim 1)

[1549] means for a user to input colors and images;

[1550] means for generating a design based on the input color and image, including a generation artificial intelligence;

[1551] means for displaying the generated design;

[1552] means for accepting selections and feedback on the generated designs;

[1553] a means for recording said feedback and incorporating it into subsequent design generation;

[1554] A means for generating design proposals based on user preferences in advance and sharing them with a service provider;

[1555] The system includes a means for a service provider to review the design proposal and make personalized suggestions to the user.

[1556] (Claim 2)

[1557] 10. The system of claim 1, wherein the generative artificial intelligence generates a personalized design based on the user's past selections and preferences, and further notifies a service provider.

[1558] (Claim 3)

[1559] 2. The system according to claim 1, wherein the design generating means includes means for generating a plurality of design proposals and proposing them to the service provider and the user.

[1560] "Example 2: Combining Emotion Engines"

[1561] (Claim 1)

[1562] means for a user to input colors and images;

[1563] means for analyzing the user's facial expressions and voice to recognize the user's emotional state;

[1564] means for generating a design based on the input color and image and the analyzed emotional state, including a generating artificial intelligence;

[1565] means for displaying the generated design;

[1566] means for accepting selections and feedback on the generated designs;

[1567] The system includes means for recording said feedback and incorporating it into subsequent design generation.

[1568] (Claim 2)

[1569] 10. The system of claim 1, wherein the generative artificial intelligence generates personalized designs based on the user's past choices and preferences.

[1570] (Claim 3)

[1571] 2. The system of claim 1, wherein the design generation means includes means for generating and proposing a plurality of design proposals to the user.

[1572] "Application example 2 when combining emotion engines"

[1573] (Claim 1)

[1574] means for a user to input colors and images;

[1575] means for generating a design based on the input color and image, including a generation artificial intelligence;

[1576] means for displaying the generated design;

[1577] means for accepting selections and feedback on the generated designs;

[1578] a means for recording said feedback and incorporating it into subsequent design generation;

[1579] a means for analyzing the emotional state of a user;

[1580] means for personalizing a design based on the analyzed emotional state;

[1581] The system includes facial recognition of brick-and-mortar users and a means to visualize the designs generated in real time.

[1582] (Claim 2)

[1583] said generating artificial intelligence generates a personalized design based on the user's past choices and preferences;

[1584] 10. The system of claim 1, wherein the system suggests designs based on the user's emotional state.

[1585] (Claim 3)

[1586] 2. The system of claim 1, wherein the design generation means includes means for generating and proposing a plurality of design proposals to the user. [Explanation of symbols]

[1587] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for a user to input colors and images; means for generating a design based on the input color and image, including a generation artificial intelligence; means for displaying the generated design; means for accepting selections and feedback on the generated designs; The system includes means for recording said feedback and incorporating it into subsequent design generation.

2. The system of claim 1 , wherein the generative artificial intelligence generates personalized designs based on the user's past choices and preferences.

3. 2. The system of claim 1, wherein the design generation means includes means for generating and proposing a plurality of design proposals to the user.

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