System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving image data of a logo input by a user; means for using a generative artificial intelligence model to generate a logo design based on the received image data; means for transmitting the generated logo design to a user terminal; means for receiving a fine-tuning request from the user; means for generating a regenerated logo design based on the fine-tuning request; and means for transmitting a final version of the logo design to the user terminal.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] Traditionally, logo design required the commissioning of specialized designers, which was time-consuming and costly. It was also difficult for users to specifically express their own image, making it difficult to obtain a satisfactory logo design. Furthermore, the time required to request a second designer for fine adjustments was inefficient in today's business environment, where rapid response is required. The present invention aims to solve these problems. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including: means for receiving image data of a logo input by a user; means for using a generative artificial intelligence model to generate a logo design based on the received image data; means for transmitting the generated logo design to a user terminal; means for receiving a fine-tuning request from the user; means for generating a regenerated logo design based on the fine-tuning request; and means for transmitting the final logo design to the user terminal. The system may also include a means for generating logo designs for use on business cards, signs, websites, and social networking services, or a means for providing an interface through which a user can input image data for the logo design, thereby enabling efficient and rapid provision of high-quality logo designs.

[0006] "User Terminal" means the electronic device used by a User to access the Logo Creation Tool, enter data, and receive the generated Logo.

[0007] The "receiving means" is a function that allows the system to receive image data and fine adjustment requests input by the user.

[0008] "Image data" refers to information in which the user describes their wishes and requirements regarding the logo.

[0009] A "generative artificial intelligence model" is an algorithm or program that automatically generates logo designs based on learned data.

[0010] The "generation means" is a function that generates a logo design based on the user's image data using a generative artificial intelligence model.

[0011] The "transmission means" is a function for transmitting the generated logo design to the user terminal.

[0012] A "tweak request" is a request by a user for minor changes or modifications to the generated logo design.

[0013] The "regeneration means" is a function that regenerates the logo design upon receiving a fine-tuning request from the user.

[0014] The "final logo design" is the logo design that is finally created after reflecting the user's fine-tuning requests.

[0015] An "interface" is an input screen or operating means that a user uses to input logo image data. [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 relates to a system that allows users to easily create and fine-tune logo designs. How this system is implemented will be described below in detail.

[0038] This system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, and a fine-tuning means. The following describes how each component works together to generate a logo design.

[0039] First, a user launches a logo creation tool web page or application on a device (e.g., a personal computer or smartphone). The user uses text fields and pull-down menus on the interface to input image data for the logo, inputting their requirements and preferences for the logo, such as "colorful," "simple," or "friendly." Once input is complete, the device sends this image data to the server.

[0040] The server receives image data sent from the user terminal using the receiving means. The generating means in the server applies the received image data to a generative AI model based on the data. This generative AI model is an algorithm that has previously learned data from a wide variety of logo designs, and can automatically generate a logo that meets the user's requirements.

[0041] The logo design generated by the generation means is temporarily stored in the server. This logo design is then sent to the user's terminal via the transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request. The terminal then sends this fine-tuning request to the server.

[0042] The server again receives the fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request, and regenerates the logo design. The regenerated logo design is again sent to the user terminal via the transmitting means. This process is repeated until the user obtains a logo design that satisfies them.

[0043] Finally, once the user is satisfied with the logo design, they can click the download button to save the logo to their device, where they can use it on business cards, signs, websites, social networking services, etc.

[0044] As a concrete example, let's explain the process of creating a logo for a newly opened cafe. The user starts up their PC, opens the logo creation tool webpage, and inputs the following requirements: "simple but warm design," "for cafes," and "brown tones." The data is sent to the server, which generates a logo based on a generative artificial intelligence model. The generated logo is a simple, brown design with a cup and coffee beans motif. If the user requests a "slightly more vibrant brown" as a fine-tuning request, the server regenerates the logo, ultimately resulting in a logo that satisfies the user. This logo is then used for the cafe's signage, menu, and business cards.

[0045] The above is a specific embodiment of the present invention, which can significantly reduce the effort and cost required for creating a logo design as in the past, and can quickly respond to the diverse needs of users.

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] The user launches the logo creation tool web page or application on their device (PC or smartphone).

[0049] Step 2:

[0050] The user enters image data for the logo (e.g., simple, colorful, friendly, etc.) using text fields and pull-down menus on the interface.

[0051] Step 3:

[0052] The user checks the image data entered and clicks the send button. The device sends this image data to the server.

[0053] Step 4:

[0054] The server receives the image data sent from the user using the receiving means, and the received data is processed within the server.

[0055] Step 5:

[0056] The server uses a generation means to apply the received image data to a generative artificial intelligence model, which has previously learned data on a wide variety of logo designs.

[0057] Step 6:

[0058] The generative AI model generates a logo design based on the user's requirements, and the generated logo design is temporarily stored on the server.

[0059] Step 7:

[0060] The server transmits the generated logo design to the user terminal via the transmission means.

[0061] Step 8:

[0062] The user reviews the logo design received on their device and, if necessary, makes minor adjustments (e.g., changes to colors or fonts), inputs a minor adjustment request into the interface.

[0063] Step 9:

[0064] The user submits a nudge request, which the device sends to the server.

[0065] Step 10:

[0066] The server again receives the fine-tuning request from the user using the receiving means, and applies the received fine-tuning data to the generating means to generate a regenerated logo design.

[0067] Step 11:

[0068] The server then transmits the regenerated logo design to the user terminal again using the transmission means, and this process is repeated as necessary until the user is satisfied with the logo design.

[0069] Step 12:

[0070] The user finally confirms the logo design they are satisfied with and clicks the download button, which saves the logo design to their device.

[0071] Step 13:

[0072] Users can use the logos they save on business cards, signs, websites, social networking services, etc.

[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 logo design creation systems require time and effort, making it difficult to instantly create the design a user desires. Additionally, the cost of hiring a professional designer and the need for frequent adjustments increase the overall cost. This makes it difficult for individual businesses and small and medium-sized enterprises in particular to quickly obtain a satisfactory logo design at low cost.

[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 receiving image data of a logo entered by a user, means for using a generation algorithm to generate a logo design based on the received image data, means for transmitting the generated logo design to the user's computer, means for receiving a fine-tuning request from the user, means for generating a regenerated logo design based on the fine-tuning request, means for transmitting the final logo design to the user's computer, and means for the user to download the final logo design. This allows the user to obtain a satisfactory logo design quickly and at low cost.

[0078] "User Computer" means the electronic device used to generate, display, tweak and download the Logo Design.

[0079] "Means for receiving" refers to a communication function for sending data or requests entered by the user to the server.

[0080] A "generative algorithm" is a program or mathematical method that automatically creates a logo design based on received data.

[0081] "Transmitting means" refers to a communications function for transferring the generated or regenerated logo design to the user's computer.

[0082] A "tweak request" is a request for minor changes made by a user to the generated logo design.

[0083] A "regenerating means" is a program or process for regenerating a logo design based on a tweak request.

[0084] "Means for downloading" refers to the ability to save the final logo design to the user's computer.

[0085] A "business card" is a small paper or plastic card onto which a logo design is printed.

[0086] An "advertising panel" is a large display medium on which a logo design is displayed.

[0087] "Online Site" means any web page or internet resource on which the logo design is used.

[0088] "Virtual communication tools" are online communication methods such as social networking services.

[0089] This invention relates to a system that allows users to easily generate and fine-tune logo designs. The system includes a user terminal, a server, a generative artificial intelligence model (generative AI model), a receiving means, a generating means, a transmitting means, and a fine-tuning means.

[0090] First, a user launches a logo creation tool webpage or application on a device such as a personal computer or smartphone. The user inputs their logo preferences, such as "simple," "colorful," or "friendly," through text fields and pull-down menus on the interface. For example, they can enter prompts like the following:

[0091] "I'd like to create a logo design for a new cafe I'm opening. I'd like it to be simple but warm, with a brownish color scheme."

[0092] When the user completes the input, the terminal transmits the input data to the server, and the server receives the image data transmitted from the user terminal using the receiving means.

[0093] The generation means in the server applies the received data to a generative AI model. This generative AI model has previously learned data from a wide variety of logo designs, and can automatically generate a logo that meets the user's requirements. The generation means uses this generative AI model to generate a logo design based on the user's preferences. For example, for a user who wants a simple, warm design, the generation means generates a brown logo with a cup and coffee bean motif.

[0094] The generated logo design is temporarily stored in the server and then sent to the user's terminal via a transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request. The terminal then sends this fine-tuning request to the server.

[0095] The server again receives a fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request and regenerates the logo design. The regenerated logo design is again sent to the user terminal via the transmitting means. This process is repeated until the user obtains a logo design that satisfies them.

[0096] Finally, once users are satisfied with the logo design, they can click the download button to save it to their device. Users can then use the downloaded logo on business cards, advertising panels, online sites, virtual communication tools, and more.

[0097] Using this system, users can create logo designs more quickly and at lower cost than with conventional methods, which will result in greater convenience, especially for individual entrepreneurs and small and medium-sized businesses.

[0098] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0099] Step 1:

[0100] A user launches a logo creation tool webpage or application on a personal computer or smartphone. The user inputs their logo preferences, such as "colorful," "simple," or "friendly," through text fields and pull-down menus on the interface. This is the input data.

[0101] Step 2:

[0102] The terminal sends the data entered by the user to the server, which includes the user's design requirements and wishes. Specifically, the data is sent in JSON format, which the server parses and uses in the next step.

[0103] Step 3:

[0104] The server receives input data sent from the user terminal using the receiving means. After receiving the data, it checks the integrity of the data and cleanses it as necessary, preparing it for application to the generative AI model.

[0105] Step 4:

[0106] The generation means within the server applies the received data to a generative artificial intelligence model (generative AI model). Here, the generative AI model uses an algorithm that has previously learned data from a wide variety of logo designs. This algorithm analyzes the input data and automatically generates a logo design that matches the user's preferences. Specifically, it outputs a simple, brown design with a cup and coffee bean motif.

[0107] Step 5:

[0108] The generated logo design is temporarily stored in the server, and then transmitted to the user's terminal via a transmission means. The transmitted data includes the image file of the generated logo and metadata.

[0109] Step 6:

[0110] Users can review the logo design displayed on their device and, if necessary, make minor adjustments to the color, font, placement, etc., by entering their adjustment request through the interface. The more specific the request, the more precise the adjustments will be in the next regeneration process.

[0111] Step 7:

[0112] The device sends the user's tweak request to the server, which includes the specific changes they want to make, such as "make it a slightly brighter brown." The request is then analyzed again by the server.

[0113] Step 8:

[0114] The server receives the fine-tuning request from the user again using the receiving means, then validates it and prepares for regeneration based on the request content.

[0115] Step 9:

[0116] The generator in the server reapplies the data to the generative AI model based on the fine-tuning request. The generative AI model then analyzes the input data and the fine-tuning request again to generate an improved logo design. For example, a new logo with a more vibrant shade of brown is output.

[0117] Step 10:

[0118] The regenerated logo design is again transmitted to the user terminal via the transmission means, and this process is repeated until the generated design meets the user's wishes.

[0119] Step 11:

[0120] Once the user has confirmed the final logo design they are satisfied with, they can click the download button to save the logo to their device. The downloaded logo can then be used on business cards, advertising panels, online sites, virtual communication tools, and more.

[0121] (Application example 1)

[0122] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0123] In conventional logo design systems, the process for users to generate and fine-tune designs is complicated, making it difficult to respond quickly, especially in dynamic environments such as stores and event sites. Furthermore, there was a lack of means for real-time design generation and fine-tuning that utilizes increasingly popular smart devices. This made it difficult for users to efficiently obtain designs that satisfied them.

[0124] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0125] In this invention, the server includes means for receiving image data of a logo input by a user, means for using a generative artificial intelligence model to generate a logo design based on the received image data, means for transmitting the generated logo design to a user terminal, means for receiving a fine-tuning request from the user, means for generating a regenerated logo design based on the fine-tuning request, means for displaying the generated logo design in real time via a smart device, and means for inputting additional prompts and fine-tuning requests using an input interface of the smart device, thereby enabling a user to generate and fine-tune logo designs in real time in a physical store or in a dynamic environment.

[0126] "User Device" means an electronic device used by a User to create and fine-tune a Logo Design, including a smartphone or computer.

[0127] The "means for receiving" is a function for obtaining logo image data and fine-tuning requests sent by users.

[0128] A "generative artificial intelligence model" is a machine learning algorithm trained to automatically create logo designs based on received image data.

[0129] The "transmitting means" is a function for transferring the generated logo design or the regenerated logo design to a user terminal.

[0130] A "tweak request" is a request from a user to modify the color, font, placement, etc. of the generated logo design.

[0131] "Smart devices" are mobile devices with advanced functions, such as smart glasses and smartphones.

[0132] "Means for displaying in real time" refers to a function that visually presents the instantly generated logo design on the screen of a smart device.

[0133] "Input Interface" means the functionality that allows users to input logo design requirements and tweak requests using voice commands or touch controls.

[0134] "Additional prompts" are additional information that the user enters to further specify the design.

[0135] This invention provides a system for generating and fine-tuning logo designs in real time using smart devices (e.g., smart glasses or smartphones). Specific implementations of this system are described below.

[0136] First, the user puts on the smart glasses and inputs their logo design requirements using voice commands or touch operations, such as prompts like "Create a colorful and simple logo" or "Make it a warm design." These prompts are then sent to the server through the smart glasses' input interface.

[0137] The server receives the prompt sentence from the user using the receiving means, and then generates a logo design based on the prompt sentence using a generative artificial intelligence model, and the generated logo design is displayed in real time on the smart glasses via the transmitting means.

[0138] The user can check the generated logo design on the smart glasses display and input fine-tuning requests as needed, such as "Make the font a little cuter" or "Make the background color orange" via voice commands. These requests are then sent back to the server.

[0139] The server receives the user's fine-tuning request using the receiving means, and generates a regenerated logo design using the generating means. This regenerated logo design is also displayed on the smart glasses via the transmitting means. This allows the user to repeatedly make adjustments in real time until a satisfactory logo design is obtained.

[0140] Finally, once the user is satisfied with the logo design, they can generate a QR code (registered trademark) via the smart glasses and share it in a format that can be downloaded to a smartphone or computer.

[0141] As a concrete example, consider a scenario in which the owner of a newly opening cafe wears smart glasses and designs a logo in front of the store. The owner first voice-inputs, "Create a warm, simple logo," and checks the generated logo. He then inputs a request for minor adjustments, such as "a darker brown," and checks the re-adjusted logo. In this way, he finally arrives at a design he is satisfied with, which can be immediately used on menus and signs via QR code on the spot.

[0142] Example prompt sentence:

[0143] "Create a colorful and simple logo"

[0144] "Make the font a little cuter"

[0145] "Make the background orange"

[0146] The system allows users to efficiently and intuitively generate and fine-tune logo designs in brick-and-mortar and dynamic environments.

[0147] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0148] Step 1:

[0149] A user uses a smart device to input a request for a logo design using voice commands or touch operations. For example, the user enters a prompt such as "Create a colorful and simple logo." The input prompt is sent to the server through the input interface of the smart device. The input is the prompt, and the output is the data sent to the server.

[0150] Step 2:

[0151] The server receives the prompt text sent by the user. It acquires the prompt text using the receiving means and parses the data. The input is the prompt text from the user, and the output is the parsed data of the prompt text.

[0152] Step 3:

[0153] The server applies a generative AI model based on the received prompt to generate a logo design. The generative AI model is used to automatically create a logo design that meets the user's requirements. The input is the analyzed prompt data, and the output is the generated logo design data.

[0154] Step 4:

[0155] The server transfers the generated logo design to the smart device via a transmission means. The logo design data is displayed on the smart device display in real time. The input is the generated logo design data, and the output is the logo design displayed on the smart device.

[0156] Step 5:

[0157] The user checks the logo design on the display of the smart device and, if necessary, inputs a request for fine-tuning using voice commands. For example, the user can request specific fine-tuning such as "make the font a little cuter" or "make the background color orange." The input is the fine-tuning request made by the user, and the output is the fine-tuning request data sent to the server.

[0158] Step 6:

[0159] The server receives a fine-tuning request from the user using the receiving means. The server analyzes the data again and generates a regenerated logo design using the generating means. The input is the fine-tuning request data from the user, and the output is the regenerated logo design data.

[0160] Step 7:

[0161] The server transfers the regenerated logo design to the smart device via a transmission means. The new logo design generated by the server is displayed on the smart device in real time. The input is the data of the regenerated logo design, and the output is the new logo design displayed on the smart device.

[0162] Step 8:

[0163] The user finally confirms and finalizes the logo design they are satisfied with. A QR code is generated for the final logo design and shared in a format that can be downloaded to a smartphone or PC. The input is the data of the final logo design, and the output is the logo design data in a shareable format.

[0164] In this way, it is possible for users to create and fine-tune logo designs in real time using their smart devices.

[0165] 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.

[0166] This invention relates to a system that generates logo designs that are adapted to the user's emotions by combining an emotion engine that recognizes the user's emotions. How this system is implemented will be described below in detail.

[0167] This system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine. The following describes how each component works together to realize emotion recognition and logo design generation.

[0168] First, a user launches the logo creation tool's web page or application using a device (e.g., a personal computer or smartphone). The user then inputs their wishes and requests using text fields and pull-down menus set up on the interface for inputting logo image data. At the same time, the emotion engine analyzes the user's facial expressions and voice to recognize their emotional state. Once input is complete, the device sends this image data and the output data from the emotion engine to the server.

[0169] The server receives the image data and emotion data sent from the user terminal using the receiving means. The generating means in the server applies the received image data and emotion data to a generative artificial intelligence model based on the data. This generative artificial intelligence model is an algorithm that has previously learned data on a wide variety of logo designs, and can automatically generate a logo that matches the user's requests and emotions.

[0170] The logo design generated by the generation means is temporarily stored in the server. This logo design is then sent to the user's terminal via the transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request into the interface. The terminal then sends this fine-tuning request to the server.

[0171] The server again receives a fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request, and regenerates the logo design. The regenerated logo design is again transmitted to the user terminal via the transmitting means. This process is repeated as necessary until the user obtains a logo design that satisfies them.

[0172] Finally, once the user is satisfied with the logo design, they can click the download button to save the logo to their device, where they can use it on business cards, signs, websites, social networking services, etc.

[0173] As a concrete example, we will explain the process when User C creates a logo for a newly established sports club. User C starts up his / her PC, opens the logo creation tool webpage, and inputs the requirements of "cool design," "for sports clubs," and "reddish color." At the same time, the emotion engine analyzes User C's facial expressions and recognizes his / her excited state. This data is sent to the server, and a logo is generated based on the generative artificial intelligence model. The generated logo has a sports emblem-style design and an energetic reddish color. If User C requests a "slightly darker red" as a fine-tuning request, the server regenerates the logo, and a highly satisfying logo is finally obtained. This logo is used for the sports club's uniforms and posters.

[0174] The above is a specific embodiment of the present invention, which can significantly reduce the effort and cost required for creating a logo design as in the past, and quickly provide a high-quality logo design that matches the user's emotions.

[0175] The processing flow will be explained below.

[0176] Step 1:

[0177] The user launches the logo creation tool web page or application on their device (PC or smartphone).

[0178] Step 2:

[0179] The user enters image data for the logo (e.g., simple, colorful, friendly, etc.) using text fields and pull-down menus on the interface.

[0180] Step 3:

[0181] The user activates the device's camera and microphone. The emotion engine analyzes the user's facial expressions and voice to recognize the user's emotional state (e.g., happy, excited, calm, etc.).

[0182] Step 4:

[0183] The user checks the image data they entered and the emotion engine's recognition results, then clicks the send button. The device then sends this data to the server.

[0184] Step 5:

[0185] The server receives the image data and emotion data sent from the user terminal using the receiving means, and the received data is processed within the server.

[0186] Step 6:

[0187] The server uses a generation means to apply the received image data and emotion data to a generative artificial intelligence model, which has previously learned data on a wide variety of logo designs.

[0188] Step 7:

[0189] A generative AI model generates a logo design based on the user's requirements and emotions. The generated logo design is temporarily stored on the server.

[0190] Step 8:

[0191] The server transmits the generated logo design to the user terminal via the transmission means.

[0192] Step 9:

[0193] The user reviews the logo design received on their device, and if they wish to make any fine adjustments to the color, font, placement, etc., they can enter their fine-tuning request into the interface.

[0194] Step 10:

[0195] The user submits a nudge request, which the device sends to the server.

[0196] Step 11:

[0197] The server again receives the fine-tuning request from the user using the receiving means, and applies the received fine-tuning data to the generating means to generate a regenerated logo design.

[0198] Step 12:

[0199] The server then transmits the regenerated logo design to the user terminal again using the transmission means, and this process is repeated as necessary until the user is satisfied with the logo design.

[0200] Step 13:

[0201] The user finally confirms the logo design they are satisfied with and clicks the download button, which saves the logo design to their device.

[0202] Step 14:

[0203] Users can use the logos they save on business cards, signs, websites, social networking services, etc.

[0204] Example 2

[0205] 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."

[0206] In conventional logo design systems, users simply input their design image, making it difficult to generate a logo design that takes into account the user's emotional state. Furthermore, fine-tuning the logo design according to the user's requests is time-consuming, preventing an efficient design process. Furthermore, there is a need to provide high-quality logo designs quickly while increasing user satisfaction.

[0207] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving logo image data and emotion data input by the user, means for using a generative artificial intelligence model to generate a logo design based on the received image data and emotion data, means for transmitting the generated logo design to the user terminal, means for receiving a fine-tuning request from the user, means for generating a re-generated logo design based on the fine-tuning request, and means for transmitting the final logo design to the user terminal. This makes it possible to quickly generate a high-quality logo design that reflects the user's emotional state and to flexibly fine-tune the design according to the user's requests.

[0208] "Logo image data" is digital data that includes visual information such as the shape, color, and text of the logo designed by the user.

[0209] "Emotional data" is digital data that indicates the user's emotional state, obtained by analyzing the user's facial expressions and voice.

[0210] A "generative artificial intelligence model" is an AI model that includes a pre-trained algorithm to generate logo designs.

[0211] A "user terminal" is an electronic device used by a user to operate the logo creation tool, such as a personal computer or smartphone.

[0212] The "receiving means" refers to a network interface or software module for receiving data sent from a user terminal.

[0213] "Generating means" refers to a processing device or software module for generating a logo design using a generative artificial intelligence model based on received image data and emotion data.

[0214] The "transmission means" refers to a network interface or software module for sending the generated logo design to a user terminal.

[0215] A "tweak request" is data that a user uses to request changes to the color, font, placement, etc. of the generated logo design.

[0216] A "regenerated logo design" is a logo design that has been regenerated by a generative artificial intelligence model based on a user's fine-tuning requests.

[0217] "Final logo design" refers to the logo design that is finalized to the user's satisfaction.

[0218] MODE FOR CARRYING OUT THE INVENTION

[0219] This invention relates to a system that generates logo designs that are adapted to the emotions of a user by combining an emotion engine that recognizes the emotions of the user. A method for implementing this system will be specifically described below.

[0220] The system includes a user terminal, a server, a generative artificial intelligence model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine.

[0221] Hardware and software used

[0222] 1. Hardware:

[0223] personal computer

[0224] Smartphone

[0225] 2. Software:

[0226] Logo creation tool (web page or application)

[0227] Emotion Engine

[0228] server

[0229] Generative AI Models

[0230] System action

[0231] User Action:

[0232] A user uses a personal computer or smartphone to launch a logo creation tool web page or application and enters logo design requirements, such as "cool design," "for a sports club," and "red tones," through text fields and pull-down menus.

[0233] Emotion Engine in action:

[0234] The emotion engine uses the camera and microphone on the user's device to analyze the user's facial expressions and voice to recognize the user's emotional state. For example, when the user is typing, the emotion engine records emotions such as excitement or joy.

[0235] Sending data:

[0236] The user terminal assembles the input requirement data and the emotion data acquired by the emotion engine into packets and transmits them to the server via a network connection.

[0237] Server Action:

[0238] The server receives the image data and emotion data sent from the user terminal using the receiving means, and the generating means applies the received data using a generative artificial intelligence model to generate a logo design that matches the user's request and emotion.

[0239] Generate and submit your logo design:

[0240] The generated logo design is temporarily stored in the server and then sent to the user's terminal using a transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they can input a fine adjustment request into the interface.

[0241] Tweak request and regeneration:

[0242] The terminal sends a fine-tuning request to the server, the server's receiving means receives the request again, and the generating means reapplies the generative artificial intelligence model to regenerate the logo design, and this process is repeated until the user is satisfied.

[0243] Final review and save:

[0244] Once the user is satisfied with the logo design, they can click the download button to save the final logo design to their device. They can then use the downloaded logo on business cards, signs, websites, social networking services, etc.

[0245] Specific examples

[0246] For example, the following shows the process when user C creates a logo for a newly established sports club.

[0247] User C starts up his / her PC and opens the logo creation tool webpage. He / she then inputs requirements such as "cool design," "for a sports club," and "reddish color." At the same time, the emotion engine analyzes User C's facial expressions and recognizes his / her excited state. This data is sent to the server, and the generative AI model generates a logo. The generated logo has a sports emblem-style design and an energetic reddish color. If User C requests a slight adjustment such as "a slightly darker red," the server regenerates the logo, and finally a logo that satisfies him / her is obtained. This logo is used for the sports club's uniforms and posters.

[0248] Prompt Sentence Examples

[0249] User requirements: Cool design, for sports clubs, red color

[0250] User Emotion: Excited

[0251] This system makes it possible to quickly provide high-quality logo designs that reflect the user's emotions, significantly reducing the effort and cost required for traditional logo design and enabling a design process that meets user expectations.

[0252] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0253] Step 1:

[0254] A user launches a logo creation tool web page or application on a personal computer or smartphone. The user inputs specific logo design requirements using text fields and pull-down menus on the interface. Examples of inputs include "cool design," "for sports clubs," and "reddish colors." This input data is temporarily stored on the device for use in later processing steps.

[0255] Step 2:

[0256] While the user is entering requirements, the emotion engine analyzes the user's facial expressions and voice in real time using the device's built-in camera and microphone. The emotion engine recognizes the user's emotional state (e.g., excitement, joy, etc.) as digital data and captures it as emotion data. This emotion data is temporarily stored in the device along with the requirement data.

[0257] Step 3:

[0258] The device sends the requirement data entered by the user and the emotion data acquired by the emotion engine to the server. At this time, the data is sent in packet format using an appropriate protocol (HTTP, HTTPS, etc.). The sent data includes text information and emotion data.

[0259] Step 4:

[0260] The server receives the requirement data and emotion data sent from the terminal using the receiving means. The received data is stored in an appropriate database or cache in the server. The generating means then receives the data and applies it to a corresponding generative AI model. The generative AI model uses a pre-trained algorithm to generate a logo design that matches the user's requirements and emotions.

[0261] Step 5:

[0262] The logo design generated by the generating means is temporarily stored in the server. This logo design is then transmitted to the user's terminal via the transmitting means. An appropriate encoding technique is used for transmission to ensure the reliability of the data. The user can then view the generated logo design on their terminal.

[0263] Step 6:

[0264] The user can review the generated logo design and input requests for fine-tuning if necessary. For example, they can enter specific requests into the interface, such as "I want the red to be a little darker." This input data is then temporarily saved on the device.

[0265] Step 7:

[0266] The device sends the user's fine-tuning request to the server. The data transmission at this time uses the same protocol and method as the initial data transmission. The specific fine-tuning request content is included in the data packet.

[0267] Step 8:

[0268] The server again receives the fine-tuning request from the user using the receiving means. The received data is processed within the server, and the generating means again applies the generative artificial intelligence model. As a result, a new logo design based on the fine-tuning request is generated.

[0269] Step 9:

[0270] The regenerated logo design is again sent via the transmission means to the user terminal, where the user can review the regenerated logo design and repeat this process until satisfied.

[0271] Step 10:

[0272] Finally, once the user is satisfied with the logo design, they click the download button to save it to their device. This downloaded logo design can then be used on business cards, signs, websites, social networking services, etc.

[0273] (Application example 2)

[0274] 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."

[0275] Conventional logo generation systems are unable to design logos that take user emotions into account, and as a result, the resulting logos often do not perfectly match the user's intentions or emotions. Furthermore, generating a logo based on user emotions could potentially make online presences such as virtual stores more unique and appealing, but no system has been available that can achieve this. There is a need for a system that solves this problem and generates logos that adapt to user emotions.

[0276] 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 receiving logo image data input by the user, means for analyzing the user's facial expression image and voice data to recognize emotions, means for using a generative artificial intelligence model to generate a logo design based on the received image data and the recognized emotion, means for transmitting the generated logo design to the user terminal, means for receiving a fine-tuning request from the user, means for generating a re-generated logo design based on the fine-tuning request, and means for transmitting the final logo design to the user terminal. This makes it possible to adapt to the user's emotions and create unique and attractive logos for use in virtual stores, etc.

[0277] The "means for receiving image data of a logo entered by a user" refers to an apparatus and process for receiving image or graphic data of a logo entered by a user through a device.

[0278] "Means for recognizing emotions by analyzing facial images and voice data of a user" refers to a device and program that analyzes the user's facial movements and voice nuances and determines the user's emotional state from that information.

[0279] "Means using a generative artificial intelligence model to generate a logo design based on received image data and recognized emotions" refers to a device and program that uses collected logo image data and emotion data as input and automatically generates a logo design using an appropriate algorithm.

[0280] The "means for transmitting the generated logo design to the user terminal" refers to a device and process for transmitting the generated logo design data to a terminal operated by the user.

[0281] The "means for receiving tweak requests from a user" refers to devices and processes for receiving tweak requests made by a user to the generated logo.

[0282] The "means for generating a regenerated logo design based on a fine-tuning request" refers to a device and a program for regenerating a logo design based on a fine-tuning request from a user.

[0283] The "means for transmitting the final logo design to the user terminal" refers to the device and process for transmitting the final logo design, which has been fine-tuned and completed, to the terminal operated by the user.

[0284] This invention relates to a system that recognizes a user's emotions and generates a logo design that is adapted to the user's emotions. The system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine. How these components work together will be described below.

[0285] First, the user launches the logo creation tool application through their device (smartphone or personal computer). This application provides an interface where the user can input image data for the logo design. The user can input the desired logo style and color theme. At the same time, the device's camera and microphone are used to capture the user's facial expression images and voice data. The emotion engine analyzes this data and recognizes the user's emotions.

[0286] Once the emotion engine outputs the analysis results, the device transmits this emotion data and the user's image data to the server. The server first receives this data using the receiving means. Next, the generating means uses a generative artificial intelligence model to generate a logo design based on the received data. This generative artificial intelligence model has previously studied a wide variety of logo designs and can generate a logo that suits the user's emotions and requests.

[0287] The generated logo design is sent from the server to the user's terminal. The user can review the logo design and send a request for fine-tuning if necessary. A specific example of a fine-tuning request might be "make the color a little darker." This request is also sent to the server, which receives it again using the receiving means. The generating means regenerates the logo based on the fine-tuning request, generating a new logo design that reflects the user's requirements. This process is repeated until the user is satisfied with the logo.

[0288] The main hardware used is a smartphone or personal computer equipped with a camera and microphone, while the software includes "EmotionEngine" for emotion analysis, a logo generation algorithm for generative AI models, "requests" a library for handling HTTP requests, and "Pillow" for image processing.

[0289] As a concrete example, consider the case where a user wants to create a logo for a new virtual store. The user launches the application and inputs the requirements of a "modern style" and a "blue color theme." At the same time, the camera takes a picture of the user's face and the microphone records their voice. The emotion engine analyzes this data and recognizes the user's emotions as "excitement" and "happiness." This data is sent to the server, and a logo is generated based on the generative AI model.

[0290] The following prompt sentences are used as examples:

[0291] Emotion data: Excitement 0.8, Joy 0.9

[0292] User request: Style: Modern, Color: Blue

[0293] This allows the system to generate a logo that is optimal for the virtual store, and it is also flexible enough to accommodate users' requests for fine-tuning.

[0294] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0295] Step 1:

[0296] A user launches a logo creation tool application on a smartphone or personal computer. The user inputs the logo style and color theme and uses the application's interface to input this information. The camera also captures the user's face and the microphone records audio data. The input data consists of image data of the logo design, facial expressions, and audio data. With this data input, the emotion engine is ready to analyze it.

[0297] Step 2:

[0298] The device uses an emotion engine to analyze the user's facial expression images and voice data and recognize emotional data. The emotion engine determines the user's emotional state from the facial expression and voice and quantifies emotions such as "excitement" or "happiness." Emotional data is output in a format such as "excitement 0.8, happiness 0.9." The input data is facial expression images and voice data, and the output data is quantified emotional data.

[0299] Step 3:

[0300] The terminal transmits the image data and emotion data of the acquired logo to the server. The transmitted data also includes the style and color theme requests input by the user. When this data reaches the server, it is provided to the generation means. The input data is the image data, emotion data, and user requirements, and these are transmitted.

[0301] Step 4:

[0302] The server's generation means generates a logo design using a generative artificial intelligence model based on the received image data and emotion data. The generative AI model has previously studied a wide variety of logo designs and outputs a logo that suits the user's request and emotion. The input data are image data, emotion data, and the user's request, and the output data is the generated logo design.

[0303] Step 5:

[0304] The server sends the generated logo design to the user terminal, which displays the logo design and allows the user to input fine-tuning requests if necessary. The input data is the generated logo design, and the output data is the display on the user terminal.

[0305] Step 6:

[0306] The user inputs a fine-tuning request for the logo. For example, the user inputs a specific request such as "make the color a little darker" and requests regeneration. The input data is the user's fine-tuning request.

[0307] Step 7:

[0308] The terminal transmits the user's fine-tuning request to the server. The server receives the fine-tuning request again using the receiving means. The input data is the user's fine-tuning request, which is transmitted to the server.

[0309] Step 8:

[0310] The server's generation means regenerates the logo based on the tweak request. The generative AI model generates a new logo design that reflects the user's requirements. The input data is the tweak request and the original logo design, and the output data is the regenerated logo design.

[0311] Step 9:

[0312] The server sends the final logo design to the user's device. If the user is satisfied, the final logo design can be downloaded and used in a virtual store, etc. The input data is the regenerated logo design, and the output data is the final logo that can be sent to and downloaded from the user's device.

[0313] 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.

[0314] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0315] 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.

[0316] [Second embodiment]

[0317] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0318] 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.

[0319] 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).

[0320] 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.

[0321] 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.

[0322] 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).

[0323] 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.

[0324] 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.

[0325] 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.

[0326] 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.

[0327] 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.

[0328] 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."

[0329] This invention relates to a system that allows users to easily create and fine-tune logo designs. How this system is implemented will be described below in detail.

[0330] This system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, and a fine-tuning means. The following describes how each component works together to generate a logo design.

[0331] First, a user launches a logo creation tool web page or application on a device (e.g., a personal computer or smartphone). The user uses text fields and pull-down menus on the interface to input image data for the logo, inputting their requirements and preferences for the logo, such as "colorful," "simple," or "friendly." Once input is complete, the device sends this image data to the server.

[0332] The server receives image data sent from the user terminal using the receiving means. The generating means in the server applies the received image data to a generative AI model based on the data. This generative AI model is an algorithm that has previously learned data from a wide variety of logo designs, and can automatically generate a logo that meets the user's requirements.

[0333] The logo design generated by the generation means is temporarily stored in the server. This logo design is then sent to the user's terminal via the transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request. The terminal then sends this fine-tuning request to the server.

[0334] The server again receives the fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request, and regenerates the logo design. The regenerated logo design is again sent to the user terminal via the transmitting means. This process is repeated until the user obtains a logo design that satisfies them.

[0335] Finally, once the user is satisfied with the logo design, they can click the download button to save the logo to their device, where they can use it on business cards, signs, websites, social networking services, etc.

[0336] As a concrete example, let's explain the process of creating a logo for a newly opened cafe. The user starts up their PC, opens the logo creation tool webpage, and inputs the following requirements: "simple but warm design," "for cafes," and "brown tones." The data is sent to the server, which generates a logo based on a generative artificial intelligence model. The generated logo is a simple, brown design with a cup and coffee beans motif. If the user requests a "slightly more vibrant brown" as a fine-tuning request, the server regenerates the logo, ultimately resulting in a logo that satisfies the user. This logo is then used for the cafe's signage, menu, and business cards.

[0337] The above is a specific embodiment of the present invention, which can significantly reduce the effort and cost required for creating a logo design as in the past, and can quickly respond to the diverse needs of users.

[0338] The processing flow will be explained below.

[0339] Step 1:

[0340] The user launches the logo creation tool web page or application on their device (PC or smartphone).

[0341] Step 2:

[0342] The user enters image data for the logo (e.g., simple, colorful, friendly, etc.) using text fields and pull-down menus on the interface.

[0343] Step 3:

[0344] The user checks the image data entered and clicks the send button. The device sends this image data to the server.

[0345] Step 4:

[0346] The server receives the image data sent from the user using the receiving means, and the received data is processed within the server.

[0347] Step 5:

[0348] The server uses a generation means to apply the received image data to a generative artificial intelligence model, which has previously learned data on a wide variety of logo designs.

[0349] Step 6:

[0350] The generative AI model generates a logo design based on the user's requirements, and the generated logo design is temporarily stored on the server.

[0351] Step 7:

[0352] The server transmits the generated logo design to the user terminal via the transmission means.

[0353] Step 8:

[0354] The user reviews the logo design received on their device and, if necessary, makes minor adjustments (e.g., changes to colors or fonts), inputs a minor adjustment request into the interface.

[0355] Step 9:

[0356] The user submits a nudge request, which the device sends to the server.

[0357] Step 10:

[0358] The server again receives the fine-tuning request from the user using the receiving means, and applies the received fine-tuning data to the generating means to generate a regenerated logo design.

[0359] Step 11:

[0360] The server then transmits the regenerated logo design to the user terminal again using the transmission means, and this process is repeated as necessary until the user is satisfied with the logo design.

[0361] Step 12:

[0362] The user finally confirms the logo design they are satisfied with and clicks the download button, which saves the logo design to their device.

[0363] Step 13:

[0364] Users can use the logos they save on business cards, signs, websites, social networking services, etc.

[0365] Example 1

[0366] 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."

[0367] Conventional logo design creation systems require time and effort, making it difficult to instantly create the design a user desires. Additionally, the cost of hiring a professional designer and the need for frequent adjustments increase the overall cost. This makes it difficult for individual businesses and small and medium-sized enterprises in particular to quickly obtain a satisfactory logo design at low cost.

[0368] 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.

[0369] In this invention, the server includes means for receiving image data of a logo entered by a user, means for using a generation algorithm to generate a logo design based on the received image data, means for transmitting the generated logo design to the user's computer, means for receiving a fine-tuning request from the user, means for generating a regenerated logo design based on the fine-tuning request, means for transmitting the final logo design to the user's computer, and means for the user to download the final logo design. This allows the user to obtain a satisfactory logo design quickly and at low cost.

[0370] "User Computer" means the electronic device used to generate, display, tweak and download the Logo Design.

[0371] "Means for receiving" refers to a communication function for sending data or requests entered by the user to the server.

[0372] A "generative algorithm" is a program or mathematical method that automatically creates a logo design based on received data.

[0373] "Transmitting means" refers to a communications function for transferring the generated or regenerated logo design to the user's computer.

[0374] A "tweak request" is a request for minor changes made by a user to the generated logo design.

[0375] A "regenerating means" is a program or process for regenerating a logo design based on a tweak request.

[0376] "Means for downloading" refers to the ability to save the final logo design to the user's computer.

[0377] A "business card" is a small paper or plastic card onto which a logo design is printed.

[0378] An "advertising panel" is a large display medium on which a logo design is displayed.

[0379] "Online Site" means any web page or internet resource on which the logo design is used.

[0380] "Virtual communication tools" are online communication methods such as social networking services.

[0381] This invention relates to a system that allows users to easily generate and fine-tune logo designs. The system includes a user terminal, a server, a generative artificial intelligence model (generative AI model), a receiving means, a generating means, a transmitting means, and a fine-tuning means.

[0382] First, a user launches a logo creation tool webpage or application on a device such as a personal computer or smartphone. The user inputs their logo preferences, such as "simple," "colorful," or "friendly," through text fields and pull-down menus on the interface. For example, they can enter prompts like the following:

[0383] "I'd like to create a logo design for a new cafe I'm opening. I'd like it to be simple but warm, with a brownish color scheme."

[0384] When the user completes the input, the terminal transmits the input data to the server, and the server receives the image data transmitted from the user terminal using the receiving means.

[0385] The generation means in the server applies the received data to a generative AI model. This generative AI model has previously learned data from a wide variety of logo designs, and can automatically generate a logo that meets the user's requirements. The generation means uses this generative AI model to generate a logo design based on the user's preferences. For example, for a user who wants a simple, warm design, the generation means generates a brown logo with a cup and coffee bean motif.

[0386] The generated logo design is temporarily stored in the server and then sent to the user's terminal via a transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request. The terminal then sends this fine-tuning request to the server.

[0387] The server again receives a fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request and regenerates the logo design. The regenerated logo design is again sent to the user terminal via the transmitting means. This process is repeated until the user obtains a logo design that satisfies them.

[0388] Finally, once users are satisfied with the logo design, they can click the download button to save it to their device. Users can then use the downloaded logo on business cards, advertising panels, online sites, virtual communication tools, and more.

[0389] Using this system, users can create logo designs more quickly and at lower cost than with conventional methods, which will result in greater convenience, especially for individual entrepreneurs and small and medium-sized businesses.

[0390] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0391] Step 1:

[0392] A user launches a logo creation tool webpage or application on a personal computer or smartphone. The user inputs their logo preferences, such as "colorful," "simple," or "friendly," through text fields and pull-down menus on the interface. This is the input data.

[0393] Step 2:

[0394] The terminal sends the data entered by the user to the server, which includes the user's design requirements and wishes. Specifically, the data is sent in JSON format, which the server parses and uses in the next step.

[0395] Step 3:

[0396] The server receives input data sent from the user terminal using the receiving means. After receiving the data, it checks the integrity of the data and cleanses it as necessary, preparing it for application to the generative AI model.

[0397] Step 4:

[0398] The generation means within the server applies the received data to a generative artificial intelligence model (generative AI model). Here, the generative AI model uses an algorithm that has previously learned data from a wide variety of logo designs. This algorithm analyzes the input data and automatically generates a logo design that matches the user's preferences. Specifically, it outputs a simple, brown design with a cup and coffee bean motif.

[0399] Step 5:

[0400] The generated logo design is temporarily stored in the server, and then transmitted to the user's terminal via a transmission means. The transmitted data includes the image file of the generated logo and metadata.

[0401] Step 6:

[0402] Users can review the logo design displayed on their device and, if necessary, make minor adjustments to the color, font, placement, etc., by entering their adjustment request through the interface. The more specific the request, the more precise the adjustments will be in the next regeneration process.

[0403] Step 7:

[0404] The device sends the user's tweak request to the server, which includes the specific changes they want to make, such as "make it a slightly brighter brown." The request is then analyzed again by the server.

[0405] Step 8:

[0406] The server receives the fine-tuning request from the user again using the receiving means, then validates it and prepares for regeneration based on the request content.

[0407] Step 9:

[0408] The generator in the server reapplies the data to the generative AI model based on the fine-tuning request. The generative AI model then analyzes the input data and the fine-tuning request again to generate an improved logo design. For example, a new logo with a more vibrant shade of brown is output.

[0409] Step 10:

[0410] The regenerated logo design is again transmitted to the user terminal via the transmission means, and this process is repeated until the generated design meets the user's wishes.

[0411] Step 11:

[0412] Once the user has confirmed the final logo design they are satisfied with, they can click the download button to save the logo to their device. The downloaded logo can then be used on business cards, advertising panels, online sites, virtual communication tools, and more.

[0413] (Application example 1)

[0414] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0415] In conventional logo design systems, the process for users to generate and fine-tune designs is complicated, making it difficult to respond quickly, especially in dynamic environments such as stores and event sites. Furthermore, there was a lack of means for real-time design generation and fine-tuning that utilizes increasingly popular smart devices. This made it difficult for users to efficiently obtain designs that satisfied them.

[0416] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0417] In this invention, the server includes means for receiving image data of a logo input by a user, means for using a generative artificial intelligence model to generate a logo design based on the received image data, means for transmitting the generated logo design to a user terminal, means for receiving a fine-tuning request from the user, means for generating a regenerated logo design based on the fine-tuning request, means for displaying the generated logo design in real time via a smart device, and means for inputting additional prompts and fine-tuning requests using an input interface of the smart device, thereby enabling a user to generate and fine-tune logo designs in real time in a physical store or in a dynamic environment.

[0418] "User Device" means an electronic device used by a User to create and fine-tune a Logo Design, including a smartphone or computer.

[0419] The "means for receiving" is a function for obtaining logo image data and fine-tuning requests sent by users.

[0420] A "generative artificial intelligence model" is a machine learning algorithm trained to automatically create logo designs based on received image data.

[0421] The "transmitting means" is a function for transferring the generated logo design or the regenerated logo design to a user terminal.

[0422] A "tweak request" is a request from a user to modify the color, font, placement, etc. of the generated logo design.

[0423] "Smart devices" are mobile devices with advanced functions, such as smart glasses and smartphones.

[0424] "Means for displaying in real time" refers to a function that visually presents the instantly generated logo design on the screen of a smart device.

[0425] "Input Interface" means the functionality that allows users to input logo design requirements and tweak requests using voice commands or touch controls.

[0426] "Additional prompts" are additional information that the user enters to further specify the design.

[0427] This invention provides a system for generating and fine-tuning logo designs in real time using smart devices (e.g., smart glasses or smartphones). Specific implementations of this system are described below.

[0428] First, the user puts on the smart glasses and inputs their logo design requirements using voice commands or touch operations, such as prompts like "Create a colorful and simple logo" or "Make it a warm design." These prompts are then sent to the server through the smart glasses' input interface.

[0429] The server receives the prompt sentence from the user using the receiving means, and then generates a logo design based on the prompt sentence using a generative artificial intelligence model, and the generated logo design is displayed in real time on the smart glasses via the transmitting means.

[0430] The user can check the generated logo design on the smart glasses display and input fine-tuning requests as needed, such as "Make the font a little cuter" or "Make the background color orange" via voice commands. These requests are then sent back to the server.

[0431] The server receives the user's fine-tuning request using the receiving means, and generates a regenerated logo design using the generating means. This regenerated logo design is also displayed on the smart glasses via the transmitting means. This allows the user to repeatedly make adjustments in real time until a satisfactory logo design is obtained.

[0432] Finally, once the user is satisfied with the logo design, a QR code is generated via the smart glasses and shared in a downloadable format to a smartphone or computer.

[0433] As a concrete example, consider a scenario in which the owner of a newly opening cafe wears smart glasses and designs a logo in front of the store. The owner first voice-inputs, "Create a warm, simple logo," and checks the generated logo. He then inputs a request for minor adjustments, such as "a darker brown," and checks the re-adjusted logo. In this way, he finally arrives at a design he is satisfied with, which can be immediately used on menus and signs via QR code on the spot.

[0434] Example prompt sentence:

[0435] "Create a colorful and simple logo"

[0436] "Make the font a little cuter"

[0437] "Make the background orange"

[0438] The system allows users to efficiently and intuitively generate and fine-tune logo designs in brick-and-mortar and dynamic environments.

[0439] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0440] Step 1:

[0441] A user uses a smart device to input a request for a logo design using voice commands or touch operations. For example, the user enters a prompt such as "Create a colorful and simple logo." The input prompt is sent to the server through the input interface of the smart device. The input is the prompt, and the output is the data sent to the server.

[0442] Step 2:

[0443] The server receives the prompt text sent by the user. It acquires the prompt text using the receiving means and parses the data. The input is the prompt text from the user, and the output is the parsed data of the prompt text.

[0444] Step 3:

[0445] The server applies a generative AI model based on the received prompt to generate a logo design. The generative AI model is used to automatically create a logo design that meets the user's requirements. The input is the analyzed prompt data, and the output is the generated logo design data.

[0446] Step 4:

[0447] The server transfers the generated logo design to the smart device via a transmission means. The logo design data is displayed on the smart device display in real time. The input is the generated logo design data, and the output is the logo design displayed on the smart device.

[0448] Step 5:

[0449] The user checks the logo design on the display of the smart device and, if necessary, inputs a request for fine-tuning using voice commands. For example, the user can request specific fine-tuning such as "make the font a little cuter" or "make the background color orange." The input is the fine-tuning request made by the user, and the output is the fine-tuning request data sent to the server.

[0450] Step 6:

[0451] The server receives a fine-tuning request from the user using the receiving means. The server analyzes the data again and generates a regenerated logo design using the generating means. The input is the fine-tuning request data from the user, and the output is the regenerated logo design data.

[0452] Step 7:

[0453] The server transfers the regenerated logo design to the smart device via a transmission means. The new logo design generated by the server is displayed on the smart device in real time. The input is the data of the regenerated logo design, and the output is the new logo design displayed on the smart device.

[0454] Step 8:

[0455] The user finally confirms and finalizes the logo design they are satisfied with. A QR code is generated for the final logo design and shared in a format that can be downloaded to a smartphone or PC. The input is the data of the final logo design, and the output is the logo design data in a shareable format.

[0456] In this way, it is possible for users to create and fine-tune logo designs in real time using their smart devices.

[0457] 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.

[0458] This invention relates to a system that generates logo designs that are adapted to the user's emotions by combining an emotion engine that recognizes the user's emotions. How this system is implemented will be described below in detail.

[0459] This system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine. The following describes how each component works together to realize emotion recognition and logo design generation.

[0460] First, a user launches the logo creation tool's web page or application using a device (e.g., a personal computer or smartphone). The user then inputs their wishes and requests using text fields and pull-down menus set up on the interface for inputting logo image data. At the same time, the emotion engine analyzes the user's facial expressions and voice to recognize their emotional state. Once input is complete, the device sends this image data and the output data from the emotion engine to the server.

[0461] The server receives the image data and emotion data sent from the user terminal using the receiving means. The generating means in the server applies the received image data and emotion data to a generative artificial intelligence model based on the data. This generative artificial intelligence model is an algorithm that has previously learned data on a wide variety of logo designs, and can automatically generate a logo that matches the user's requests and emotions.

[0462] The logo design generated by the generation means is temporarily stored in the server. This logo design is then sent to the user's terminal via the transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request into the interface. The terminal then sends this fine-tuning request to the server.

[0463] The server again receives a fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request, and regenerates the logo design. The regenerated logo design is again transmitted to the user terminal via the transmitting means. This process is repeated as necessary until the user obtains a logo design that satisfies them.

[0464] Finally, once the user is satisfied with the logo design, they can click the download button to save the logo to their device, where they can use it on business cards, signs, websites, social networking services, etc.

[0465] As a concrete example, we will explain the process when User C creates a logo for a newly established sports club. User C starts up his / her PC, opens the logo creation tool webpage, and inputs the requirements of "cool design," "for sports clubs," and "reddish color." At the same time, the emotion engine analyzes User C's facial expressions and recognizes his / her excited state. This data is sent to the server, and a logo is generated based on the generative artificial intelligence model. The generated logo has a sports emblem-style design and an energetic reddish color. If User C requests a "slightly darker red" as a fine-tuning request, the server regenerates the logo, and a highly satisfying logo is finally obtained. This logo is used for the sports club's uniforms and posters.

[0466] The above is a specific embodiment of the present invention, which can significantly reduce the effort and cost required for creating a logo design as in the past, and quickly provide a high-quality logo design that matches the user's emotions.

[0467] The processing flow will be explained below.

[0468] Step 1:

[0469] The user launches the logo creation tool web page or application on their device (PC or smartphone).

[0470] Step 2:

[0471] The user enters image data for the logo (e.g., simple, colorful, friendly, etc.) using text fields and pull-down menus on the interface.

[0472] Step 3:

[0473] The user activates the device's camera and microphone. The emotion engine analyzes the user's facial expressions and voice to recognize the user's emotional state (e.g., happy, excited, calm, etc.).

[0474] Step 4:

[0475] The user checks the image data they entered and the emotion engine's recognition results, then clicks the send button. The device then sends this data to the server.

[0476] Step 5:

[0477] The server receives the image data and emotion data sent from the user terminal using the receiving means, and the received data is processed within the server.

[0478] Step 6:

[0479] The server uses a generation means to apply the received image data and emotion data to a generative artificial intelligence model, which has previously learned data on a wide variety of logo designs.

[0480] Step 7:

[0481] A generative AI model generates a logo design based on the user's requirements and emotions. The generated logo design is temporarily stored on the server.

[0482] Step 8:

[0483] The server transmits the generated logo design to the user terminal via the transmission means.

[0484] Step 9:

[0485] The user reviews the logo design received on their device, and if they wish to make any fine adjustments to the color, font, placement, etc., they can enter their fine-tuning request into the interface.

[0486] Step 10:

[0487] The user submits a nudge request, which the device sends to the server.

[0488] Step 11:

[0489] The server again receives the fine-tuning request from the user using the receiving means, and applies the received fine-tuning data to the generating means to generate a regenerated logo design.

[0490] Step 12:

[0491] The server then transmits the regenerated logo design to the user terminal again using the transmission means, and this process is repeated as necessary until the user is satisfied with the logo design.

[0492] Step 13:

[0493] The user finally confirms the logo design they are satisfied with and clicks the download button, which saves the logo design to their device.

[0494] Step 14:

[0495] Users can use the logos they save on business cards, signs, websites, social networking services, etc.

[0496] Example 2

[0497] 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."

[0498] In conventional logo design systems, users simply input their design image, making it difficult to generate a logo design that takes into account the user's emotional state. Furthermore, fine-tuning the logo design according to the user's requests is time-consuming, preventing an efficient design process. Furthermore, there is a need to provide high-quality logo designs quickly while increasing user satisfaction.

[0499] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving logo image data and emotion data input by the user, means for using a generative artificial intelligence model to generate a logo design based on the received image data and emotion data, means for transmitting the generated logo design to the user terminal, means for receiving a fine-tuning request from the user, means for generating a re-generated logo design based on the fine-tuning request, and means for transmitting the final logo design to the user terminal. This makes it possible to quickly generate a high-quality logo design that reflects the user's emotional state and to flexibly fine-tune the design according to the user's requests.

[0500] "Logo image data" is digital data that includes visual information such as the shape, color, and text of the logo designed by the user.

[0501] "Emotional data" is digital data that indicates the user's emotional state, obtained by analyzing the user's facial expressions and voice.

[0502] A "generative artificial intelligence model" is an AI model that includes a pre-trained algorithm to generate logo designs.

[0503] A "user terminal" is an electronic device used by a user to operate the logo creation tool, such as a personal computer or smartphone.

[0504] The "receiving means" refers to a network interface or software module for receiving data sent from a user terminal.

[0505] "Generating means" refers to a processing device or software module for generating a logo design using a generative artificial intelligence model based on received image data and emotion data.

[0506] The "transmission means" refers to a network interface or software module for sending the generated logo design to a user terminal.

[0507] A "tweak request" is data that a user uses to request changes to the color, font, placement, etc. of the generated logo design.

[0508] A "regenerated logo design" is a logo design that has been regenerated by a generative artificial intelligence model based on a user's fine-tuning requests.

[0509] "Final logo design" refers to the logo design that is finalized to the user's satisfaction.

[0510] MODE FOR CARRYING OUT THE INVENTION

[0511] This invention relates to a system that generates logo designs that are adapted to the emotions of a user by combining an emotion engine that recognizes the emotions of the user. A method for implementing this system will be specifically described below.

[0512] The system includes a user terminal, a server, a generative artificial intelligence model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine.

[0513] Hardware and software used

[0514] 1. Hardware:

[0515] personal computer

[0516] Smartphone

[0517] 2. Software:

[0518] Logo creation tool (web page or application)

[0519] Emotion Engine

[0520] server

[0521] Generative AI Models

[0522] System action

[0523] User Action:

[0524] A user uses a personal computer or smartphone to launch a logo creation tool web page or application and enters logo design requirements, such as "cool design," "for a sports club," and "red tones," through text fields and pull-down menus.

[0525] Emotion Engine in action:

[0526] The emotion engine uses the camera and microphone on the user's device to analyze the user's facial expressions and voice to recognize the user's emotional state. For example, when the user is typing, the emotion engine records emotions such as excitement or joy.

[0527] Sending data:

[0528] The user terminal assembles the input requirement data and the emotion data acquired by the emotion engine into packets and transmits them to the server via a network connection.

[0529] Server Action:

[0530] The server receives the image data and emotion data sent from the user terminal using the receiving means, and the generating means applies the received data using a generative artificial intelligence model to generate a logo design that matches the user's request and emotion.

[0531] Generate and submit your logo design:

[0532] The generated logo design is temporarily stored in the server and then sent to the user's terminal using a transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they can input a fine adjustment request into the interface.

[0533] Tweak request and regeneration:

[0534] The terminal sends a fine-tuning request to the server, the server's receiving means receives the request again, and the generating means reapplies the generative artificial intelligence model to regenerate the logo design, and this process is repeated until the user is satisfied.

[0535] Final review and save:

[0536] Once the user is satisfied with the logo design, they can click the download button to save the final logo design to their device. They can then use the downloaded logo on business cards, signs, websites, social networking services, etc.

[0537] Specific examples

[0538] For example, the following shows the process when user C creates a logo for a newly established sports club.

[0539] User C starts up his / her PC and opens the logo creation tool webpage. He / she then inputs requirements such as "cool design," "for a sports club," and "reddish color." At the same time, the emotion engine analyzes User C's facial expressions and recognizes his / her excited state. This data is sent to the server, and the generative AI model generates a logo. The generated logo has a sports emblem-style design and an energetic reddish color. If User C requests a slight adjustment such as "a slightly darker red," the server regenerates the logo, and finally a logo that satisfies him / her is obtained. This logo is used for the sports club's uniforms and posters.

[0540] Prompt Sentence Examples

[0541] User requirements: Cool design, for sports clubs, red color

[0542] User Emotion: Excited

[0543] This system makes it possible to quickly provide high-quality logo designs that reflect the user's emotions, significantly reducing the effort and cost required for traditional logo design and enabling a design process that meets user expectations.

[0544] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] A user launches a logo creation tool web page or application on a personal computer or smartphone. The user inputs specific logo design requirements using text fields and pull-down menus on the interface. Examples of inputs include "cool design," "for sports clubs," and "reddish colors." This input data is temporarily stored on the device for use in later processing steps.

[0547] Step 2:

[0548] While the user is entering requirements, the emotion engine analyzes the user's facial expressions and voice in real time using the device's built-in camera and microphone. The emotion engine recognizes the user's emotional state (e.g., excitement, joy, etc.) as digital data and captures it as emotion data. This emotion data is temporarily stored in the device along with the requirement data.

[0549] Step 3:

[0550] The device sends the requirement data entered by the user and the emotion data acquired by the emotion engine to the server. At this time, the data is sent in packet format using an appropriate protocol (HTTP, HTTPS, etc.). The sent data includes text information and emotion data.

[0551] Step 4:

[0552] The server receives the requirement data and emotion data sent from the terminal using the receiving means. The received data is stored in an appropriate database or cache in the server. The generating means then receives the data and applies it to a corresponding generative AI model. The generative AI model uses a pre-trained algorithm to generate a logo design that matches the user's requirements and emotions.

[0553] Step 5:

[0554] The logo design generated by the generating means is temporarily stored in the server. This logo design is then transmitted to the user's terminal via the transmitting means. An appropriate encoding technique is used for transmission to ensure the reliability of the data. The user can then view the generated logo design on their terminal.

[0555] Step 6:

[0556] The user can review the generated logo design and input requests for fine-tuning if necessary. For example, they can enter specific requests into the interface, such as "I want the red to be a little darker." This input data is then temporarily saved on the device.

[0557] Step 7:

[0558] The device sends the user's fine-tuning request to the server. The data transmission at this time uses the same protocol and method as the initial data transmission. The specific fine-tuning request content is included in the data packet.

[0559] Step 8:

[0560] The server again receives the fine-tuning request from the user using the receiving means. The received data is processed within the server, and the generating means again applies the generative artificial intelligence model. As a result, a new logo design based on the fine-tuning request is generated.

[0561] Step 9:

[0562] The regenerated logo design is again sent via the transmission means to the user terminal, where the user can review the regenerated logo design and repeat this process until satisfied.

[0563] Step 10:

[0564] Finally, once the user is satisfied with the logo design, they click the download button to save it to their device. This downloaded logo design can then be used on business cards, signs, websites, social networking services, etc.

[0565] (Application example 2)

[0566] 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."

[0567] Conventional logo generation systems are unable to design logos that take user emotions into account, and as a result, the resulting logos often do not perfectly match the user's intentions or emotions. Furthermore, generating a logo based on user emotions could potentially make online presences such as virtual stores more unique and appealing, but no system has been available that can achieve this. There is a need for a system that solves this problem and generates logos that adapt to user emotions.

[0568] 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 receiving logo image data input by the user, means for analyzing the user's facial expression image and voice data to recognize emotions, means for using a generative artificial intelligence model to generate a logo design based on the received image data and the recognized emotion, means for transmitting the generated logo design to the user terminal, means for receiving a fine-tuning request from the user, means for generating a re-generated logo design based on the fine-tuning request, and means for transmitting the final logo design to the user terminal. This makes it possible to adapt to the user's emotions and create unique and attractive logos for use in virtual stores, etc.

[0569] The "means for receiving image data of a logo entered by a user" refers to an apparatus and process for receiving image or graphic data of a logo entered by a user through a device.

[0570] "Means for recognizing emotions by analyzing facial images and voice data of a user" refers to a device and program that analyzes the user's facial movements and voice nuances and determines the user's emotional state from that information.

[0571] "Means using a generative artificial intelligence model to generate a logo design based on received image data and recognized emotions" refers to a device and program that uses collected logo image data and emotion data as input and automatically generates a logo design using an appropriate algorithm.

[0572] The "means for transmitting the generated logo design to the user terminal" refers to a device and process for transmitting the generated logo design data to a terminal operated by the user.

[0573] The "means for receiving tweak requests from a user" refers to devices and processes for receiving tweak requests made by a user to the generated logo.

[0574] The "means for generating a regenerated logo design based on a fine-tuning request" refers to a device and a program for regenerating a logo design based on a fine-tuning request from a user.

[0575] The "means for transmitting the final logo design to the user terminal" refers to the device and process for transmitting the final logo design, which has been fine-tuned and completed, to the terminal operated by the user.

[0576] This invention relates to a system that recognizes a user's emotions and generates a logo design that is adapted to the user's emotions. The system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine. How these components work together will be described below.

[0577] First, the user launches the logo creation tool application through their device (smartphone or personal computer). This application provides an interface where the user can input image data for the logo design. The user can input the desired logo style and color theme. At the same time, the device's camera and microphone are used to capture the user's facial expression images and voice data. The emotion engine analyzes this data and recognizes the user's emotions.

[0578] Once the emotion engine outputs the analysis results, the device transmits this emotion data and the user's image data to the server. The server first receives this data using the receiving means. Next, the generating means uses a generative artificial intelligence model to generate a logo design based on the received data. This generative artificial intelligence model has previously studied a wide variety of logo designs and can generate a logo that suits the user's emotions and requests.

[0579] The generated logo design is sent from the server to the user's terminal. The user can review the logo design and send a request for fine-tuning if necessary. A specific example of a fine-tuning request might be "make the color a little darker." This request is also sent to the server, which receives it again using the receiving means. The generating means regenerates the logo based on the fine-tuning request, generating a new logo design that reflects the user's requirements. This process is repeated until the user is satisfied with the logo.

[0580] The main hardware used is a smartphone or personal computer equipped with a camera and microphone, while the software includes "EmotionEngine" for emotion analysis, a logo generation algorithm for generative AI models, "requests" a library for handling HTTP requests, and "Pillow" for image processing.

[0581] As a concrete example, consider the case where a user wants to create a logo for a new virtual store. The user launches the application and inputs the requirements of a "modern style" and a "blue color theme." At the same time, the camera takes a picture of the user's face and the microphone records their voice. The emotion engine analyzes this data and recognizes the user's emotions as "excitement" and "happiness." This data is sent to the server, and a logo is generated based on the generative AI model.

[0582] The following prompt sentences are used as examples:

[0583] Emotion data: Excitement 0.8, Joy 0.9

[0584] User request: Style: Modern, Color: Blue

[0585] This allows the system to generate a logo that is optimal for the virtual store, and it is also flexible enough to accommodate users' requests for fine-tuning.

[0586] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0587] Step 1:

[0588] A user launches a logo creation tool application on a smartphone or personal computer. The user inputs the logo style and color theme and uses the application's interface to input this information. The camera also captures the user's face and the microphone records audio data. The input data consists of image data of the logo design, facial expressions, and audio data. With this data input, the emotion engine is ready to analyze it.

[0589] Step 2:

[0590] The device uses an emotion engine to analyze the user's facial expression images and voice data and recognize emotional data. The emotion engine determines the user's emotional state from the facial expression and voice and quantifies emotions such as "excitement" or "happiness." Emotional data is output in a format such as "excitement 0.8, happiness 0.9." The input data is facial expression images and voice data, and the output data is quantified emotional data.

[0591] Step 3:

[0592] The terminal transmits the image data and emotion data of the acquired logo to the server. The transmitted data also includes the style and color theme requests input by the user. When this data reaches the server, it is provided to the generation means. The input data is the image data, emotion data, and user requirements, and these are transmitted.

[0593] Step 4:

[0594] The server's generation means generates a logo design using a generative artificial intelligence model based on the received image data and emotion data. The generative AI model has previously studied a wide variety of logo designs and outputs a logo that suits the user's request and emotion. The input data are image data, emotion data, and the user's request, and the output data is the generated logo design.

[0595] Step 5:

[0596] The server sends the generated logo design to the user terminal, which displays the logo design and allows the user to input fine-tuning requests if necessary. The input data is the generated logo design, and the output data is the display on the user terminal.

[0597] Step 6:

[0598] The user inputs a fine-tuning request for the logo. For example, the user inputs a specific request such as "make the color a little darker" and requests regeneration. The input data is the user's fine-tuning request.

[0599] Step 7:

[0600] The terminal transmits the user's fine-tuning request to the server. The server receives the fine-tuning request again using the receiving means. The input data is the user's fine-tuning request, which is transmitted to the server.

[0601] Step 8:

[0602] The server's generation means regenerates the logo based on the tweak request. The generative AI model generates a new logo design that reflects the user's requirements. The input data is the tweak request and the original logo design, and the output data is the regenerated logo design.

[0603] Step 9:

[0604] The server sends the final logo design to the user's device. If the user is satisfied, the final logo design can be downloaded and used in a virtual store, etc. The input data is the regenerated logo design, and the output data is the final logo that can be sent to and downloaded from the user's device.

[0605] 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.

[0606] 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.

[0607] 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.

[0608] [Third embodiment]

[0609] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0610] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0611] 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).

[0612] 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.

[0613] 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.

[0614] 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).

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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."

[0621] This invention relates to a system that allows users to easily create and fine-tune logo designs. How this system is implemented will be described below in detail.

[0622] This system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, and a fine-tuning means. The following describes how each component works together to generate a logo design.

[0623] First, a user launches a logo creation tool web page or application on a device (e.g., a personal computer or smartphone). The user uses text fields and pull-down menus on the interface to input image data for the logo, inputting their requirements and preferences for the logo, such as "colorful," "simple," or "friendly." Once input is complete, the device sends this image data to the server.

[0624] The server receives image data sent from the user terminal using the receiving means. The generating means in the server applies the received image data to a generative AI model based on the data. This generative AI model is an algorithm that has previously learned data from a wide variety of logo designs, and can automatically generate a logo that meets the user's requirements.

[0625] The logo design generated by the generation means is temporarily stored in the server. This logo design is then sent to the user's terminal via the transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request. The terminal then sends this fine-tuning request to the server.

[0626] The server again receives the fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request, and regenerates the logo design. The regenerated logo design is again sent to the user terminal via the transmitting means. This process is repeated until the user obtains a logo design that satisfies them.

[0627] Finally, once the user is satisfied with the logo design, they can click the download button to save the logo to their device, where they can use it on business cards, signs, websites, social networking services, etc.

[0628] As a concrete example, let's explain the process of creating a logo for a newly opened cafe. The user starts up their PC, opens the logo creation tool webpage, and inputs the following requirements: "simple but warm design," "for cafes," and "brown tones." The data is sent to the server, which generates a logo based on a generative artificial intelligence model. The generated logo is a simple, brown design with a cup and coffee beans motif. If the user requests a "slightly more vibrant brown" as a fine-tuning request, the server regenerates the logo, ultimately resulting in a logo that satisfies the user. This logo is then used for the cafe's signage, menu, and business cards.

[0629] The above is a specific embodiment of the present invention, which can significantly reduce the effort and cost required for creating a logo design as in the past, and can quickly respond to the diverse needs of users.

[0630] The processing flow will be explained below.

[0631] Step 1:

[0632] The user launches the logo creation tool web page or application on their device (PC or smartphone).

[0633] Step 2:

[0634] The user enters image data for the logo (e.g., simple, colorful, friendly, etc.) using text fields and pull-down menus on the interface.

[0635] Step 3:

[0636] The user checks the image data entered and clicks the send button. The device sends this image data to the server.

[0637] Step 4:

[0638] The server receives the image data sent from the user using the receiving means, and the received data is processed within the server.

[0639] Step 5:

[0640] The server uses a generation means to apply the received image data to a generative artificial intelligence model, which has previously learned data on a wide variety of logo designs.

[0641] Step 6:

[0642] The generative AI model generates a logo design based on the user's requirements, and the generated logo design is temporarily stored on the server.

[0643] Step 7:

[0644] The server transmits the generated logo design to the user terminal via the transmission means.

[0645] Step 8:

[0646] The user reviews the logo design received on their device and, if necessary, makes minor adjustments (e.g., changes to colors or fonts), inputs a minor adjustment request into the interface.

[0647] Step 9:

[0648] The user submits a nudge request, which the device sends to the server.

[0649] Step 10:

[0650] The server again receives the fine-tuning request from the user using the receiving means, and applies the received fine-tuning data to the generating means to generate a regenerated logo design.

[0651] Step 11:

[0652] The server then transmits the regenerated logo design to the user terminal again using the transmission means, and this process is repeated as necessary until the user is satisfied with the logo design.

[0653] Step 12:

[0654] The user finally confirms the logo design they are satisfied with and clicks the download button, which saves the logo design to their device.

[0655] Step 13:

[0656] Users can use the logos they save on business cards, signs, websites, social networking services, etc.

[0657] Example 1

[0658] 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."

[0659] Conventional logo design creation systems require time and effort, making it difficult to instantly create the design a user desires. Additionally, the cost of hiring a professional designer and the need for frequent adjustments increase the overall cost. This makes it difficult for individual businesses and small and medium-sized enterprises in particular to quickly obtain a satisfactory logo design at low cost.

[0660] 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.

[0661] In this invention, the server includes means for receiving image data of a logo entered by a user, means for using a generation algorithm to generate a logo design based on the received image data, means for transmitting the generated logo design to the user's computer, means for receiving a fine-tuning request from the user, means for generating a regenerated logo design based on the fine-tuning request, means for transmitting the final logo design to the user's computer, and means for the user to download the final logo design. This allows the user to obtain a satisfactory logo design quickly and at low cost.

[0662] "User Computer" means the electronic device used to generate, display, tweak and download the Logo Design.

[0663] "Means for receiving" refers to a communication function for sending data or requests entered by the user to the server.

[0664] A "generative algorithm" is a program or mathematical method that automatically creates a logo design based on received data.

[0665] "Transmitting means" refers to a communications function for transferring the generated or regenerated logo design to the user's computer.

[0666] A "tweak request" is a request for minor changes made by a user to the generated logo design.

[0667] A "regenerating means" is a program or process for regenerating a logo design based on a tweak request.

[0668] "Means for downloading" refers to the ability to save the final logo design to the user's computer.

[0669] A "business card" is a small paper or plastic card onto which a logo design is printed.

[0670] An "advertising panel" is a large display medium on which a logo design is displayed.

[0671] "Online Site" means any web page or internet resource on which the logo design is used.

[0672] "Virtual communication tools" are online communication methods such as social networking services.

[0673] This invention relates to a system that allows users to easily generate and fine-tune logo designs. The system includes a user terminal, a server, a generative artificial intelligence model (generative AI model), a receiving means, a generating means, a transmitting means, and a fine-tuning means.

[0674] First, a user launches a logo creation tool webpage or application on a device such as a personal computer or smartphone. The user inputs their logo preferences, such as "simple," "colorful," or "friendly," through text fields and pull-down menus on the interface. For example, they can enter prompts like the following:

[0675] "I'd like to create a logo design for a new cafe I'm opening. I'd like it to be simple but warm, with a brownish color scheme."

[0676] When the user completes the input, the terminal transmits the input data to the server, and the server receives the image data transmitted from the user terminal using the receiving means.

[0677] The generation means in the server applies the received data to a generative AI model. This generative AI model has previously learned data from a wide variety of logo designs, and can automatically generate a logo that meets the user's requirements. The generation means uses this generative AI model to generate a logo design based on the user's preferences. For example, for a user who wants a simple, warm design, the generation means generates a brown logo with a cup and coffee bean motif.

[0678] The generated logo design is temporarily stored in the server and then sent to the user's terminal via a transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request. The terminal then sends this fine-tuning request to the server.

[0679] The server again receives a fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request and regenerates the logo design. The regenerated logo design is again sent to the user terminal via the transmitting means. This process is repeated until the user obtains a logo design that satisfies them.

[0680] Finally, once users are satisfied with the logo design, they can click the download button to save it to their device. Users can then use the downloaded logo on business cards, advertising panels, online sites, virtual communication tools, and more.

[0681] Using this system, users can create logo designs more quickly and at lower cost than with conventional methods, which will result in greater convenience, especially for individual entrepreneurs and small and medium-sized businesses.

[0682] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0683] Step 1:

[0684] A user launches a logo creation tool webpage or application on a personal computer or smartphone. The user inputs their logo preferences, such as "colorful," "simple," or "friendly," through text fields and pull-down menus on the interface. This is the input data.

[0685] Step 2:

[0686] The terminal sends the data entered by the user to the server, which includes the user's design requirements and wishes. Specifically, the data is sent in JSON format, which the server parses and uses in the next step.

[0687] Step 3:

[0688] The server receives input data sent from the user terminal using the receiving means. After receiving the data, it checks the integrity of the data and cleanses it as necessary, preparing it for application to the generative AI model.

[0689] Step 4:

[0690] The generation means within the server applies the received data to a generative artificial intelligence model (generative AI model). Here, the generative AI model uses an algorithm that has previously learned data from a wide variety of logo designs. This algorithm analyzes the input data and automatically generates a logo design that matches the user's preferences. Specifically, it outputs a simple, brown design with a cup and coffee bean motif.

[0691] Step 5:

[0692] The generated logo design is temporarily stored in the server, and then transmitted to the user's terminal via a transmission means. The transmitted data includes the image file of the generated logo and metadata.

[0693] Step 6:

[0694] Users can review the logo design displayed on their device and, if necessary, make minor adjustments to the color, font, placement, etc., by entering their adjustment request through the interface. The more specific the request, the more precise the adjustments will be in the next regeneration process.

[0695] Step 7:

[0696] The device sends the user's tweak request to the server, which includes the specific changes they want to make, such as "make it a slightly brighter brown." The request is then analyzed again by the server.

[0697] Step 8:

[0698] The server receives the fine-tuning request from the user again using the receiving means, then validates it and prepares for regeneration based on the request content.

[0699] Step 9:

[0700] The generator in the server reapplies the data to the generative AI model based on the fine-tuning request. The generative AI model then analyzes the input data and the fine-tuning request again to generate an improved logo design. For example, a new logo with a more vibrant shade of brown is output.

[0701] Step 10:

[0702] The regenerated logo design is again transmitted to the user terminal via the transmission means, and this process is repeated until the generated design meets the user's wishes.

[0703] Step 11:

[0704] Once the user has confirmed the final logo design they are satisfied with, they can click the download button to save the logo to their device. The downloaded logo can then be used on business cards, advertising panels, online sites, virtual communication tools, and more.

[0705] (Application example 1)

[0706] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0707] In conventional logo design systems, the process for users to generate and fine-tune designs is complicated, making it difficult to respond quickly, especially in dynamic environments such as stores and event sites. Furthermore, there was a lack of means for real-time design generation and fine-tuning that utilizes increasingly popular smart devices. This made it difficult for users to efficiently obtain designs that satisfied them.

[0708] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0709] In this invention, the server includes means for receiving image data of a logo input by a user, means for using a generative artificial intelligence model to generate a logo design based on the received image data, means for transmitting the generated logo design to a user terminal, means for receiving a fine-tuning request from the user, means for generating a regenerated logo design based on the fine-tuning request, means for displaying the generated logo design in real time via a smart device, and means for inputting additional prompts and fine-tuning requests using an input interface of the smart device, thereby enabling a user to generate and fine-tune logo designs in real time in a physical store or in a dynamic environment.

[0710] "User Device" means an electronic device used by a User to create and fine-tune a Logo Design, including a smartphone or computer.

[0711] The "means for receiving" is a function for obtaining logo image data and fine-tuning requests sent by users.

[0712] A "generative artificial intelligence model" is a machine learning algorithm trained to automatically create logo designs based on received image data.

[0713] The "transmitting means" is a function for transferring the generated logo design or the regenerated logo design to a user terminal.

[0714] A "tweak request" is a request from a user to modify the color, font, placement, etc. of the generated logo design.

[0715] "Smart devices" are mobile devices with advanced functions, such as smart glasses and smartphones.

[0716] "Means for displaying in real time" refers to a function that visually presents the instantly generated logo design on the screen of a smart device.

[0717] "Input Interface" means the functionality that allows users to input logo design requirements and tweak requests using voice commands or touch controls.

[0718] "Additional prompts" are additional information that the user enters to further specify the design.

[0719] This invention provides a system for generating and fine-tuning logo designs in real time using smart devices (e.g., smart glasses or smartphones). Specific implementations of this system are described below.

[0720] First, the user puts on the smart glasses and inputs their logo design requirements using voice commands or touch operations, such as prompts like "Create a colorful and simple logo" or "Make it a warm design." These prompts are then sent to the server through the smart glasses' input interface.

[0721] The server receives the prompt sentence from the user using the receiving means, and then generates a logo design based on the prompt sentence using a generative artificial intelligence model, and the generated logo design is displayed in real time on the smart glasses via the transmitting means.

[0722] The user can check the generated logo design on the smart glasses display and input fine-tuning requests as needed, such as "Make the font a little cuter" or "Make the background color orange" via voice commands. These requests are then sent back to the server.

[0723] The server receives the user's fine-tuning request using the receiving means, and generates a regenerated logo design using the generating means. This regenerated logo design is also displayed on the smart glasses via the transmitting means. This allows the user to repeatedly make adjustments in real time until a satisfactory logo design is obtained.

[0724] Finally, once the user is satisfied with the logo design, a QR code is generated via the smart glasses and shared in a downloadable format to a smartphone or computer.

[0725] As a concrete example, consider a scenario in which the owner of a newly opening cafe wears smart glasses and designs a logo in front of the store. The owner first voice-inputs, "Create a warm, simple logo," and checks the generated logo. He then inputs a request for minor adjustments, such as "a darker brown," and checks the re-adjusted logo. In this way, he finally arrives at a design he is satisfied with, which can be immediately used on menus and signs via QR code on the spot.

[0726] Example prompt sentence:

[0727] "Create a colorful and simple logo"

[0728] "Make the font a little cuter"

[0729] "Make the background orange"

[0730] The system allows users to efficiently and intuitively generate and fine-tune logo designs in brick-and-mortar and dynamic environments.

[0731] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0732] Step 1:

[0733] A user uses a smart device to input a request for a logo design using voice commands or touch operations. For example, the user enters a prompt such as "Create a colorful and simple logo." The input prompt is sent to the server through the input interface of the smart device. The input is the prompt, and the output is the data sent to the server.

[0734] Step 2:

[0735] The server receives the prompt text sent by the user. It acquires the prompt text using the receiving means and parses the data. The input is the prompt text from the user, and the output is the parsed data of the prompt text.

[0736] Step 3:

[0737] The server applies a generative AI model based on the received prompt to generate a logo design. The generative AI model is used to automatically create a logo design that meets the user's requirements. The input is the analyzed prompt data, and the output is the generated logo design data.

[0738] Step 4:

[0739] The server transfers the generated logo design to the smart device via a transmission means. The logo design data is displayed on the smart device display in real time. The input is the generated logo design data, and the output is the logo design displayed on the smart device.

[0740] Step 5:

[0741] The user checks the logo design on the display of the smart device and, if necessary, inputs a request for fine-tuning using voice commands. For example, the user can request specific fine-tuning such as "make the font a little cuter" or "make the background color orange." The input is the fine-tuning request made by the user, and the output is the fine-tuning request data sent to the server.

[0742] Step 6:

[0743] The server receives a fine-tuning request from the user using the receiving means. The server analyzes the data again and generates a regenerated logo design using the generating means. The input is the fine-tuning request data from the user, and the output is the regenerated logo design data.

[0744] Step 7:

[0745] The server transfers the regenerated logo design to the smart device via a transmission means. The new logo design generated by the server is displayed on the smart device in real time. The input is the data of the regenerated logo design, and the output is the new logo design displayed on the smart device.

[0746] Step 8:

[0747] The user finally confirms and finalizes the logo design they are satisfied with. A QR code is generated for the final logo design and shared in a format that can be downloaded to a smartphone or PC. The input is the data of the final logo design, and the output is the logo design data in a shareable format.

[0748] In this way, it is possible for users to create and fine-tune logo designs in real time using their smart devices.

[0749] 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.

[0750] This invention relates to a system that generates logo designs that are adapted to the user's emotions by combining an emotion engine that recognizes the user's emotions. How this system is implemented will be described below in detail.

[0751] This system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine. The following describes how each component works together to realize emotion recognition and logo design generation.

[0752] First, a user launches the logo creation tool's web page or application using a device (e.g., a personal computer or smartphone). The user then inputs their wishes and requests using text fields and pull-down menus set up on the interface for inputting logo image data. At the same time, the emotion engine analyzes the user's facial expressions and voice to recognize their emotional state. Once input is complete, the device sends this image data and the output data from the emotion engine to the server.

[0753] The server receives the image data and emotion data sent from the user terminal using the receiving means. The generating means in the server applies the received image data and emotion data to a generative artificial intelligence model based on the data. This generative artificial intelligence model is an algorithm that has previously learned data on a wide variety of logo designs, and can automatically generate a logo that matches the user's requests and emotions.

[0754] The logo design generated by the generation means is temporarily stored in the server. This logo design is then sent to the user's terminal via the transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request into the interface. The terminal then sends this fine-tuning request to the server.

[0755] The server again receives a fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request, and regenerates the logo design. The regenerated logo design is again transmitted to the user terminal via the transmitting means. This process is repeated as necessary until the user obtains a logo design that satisfies them.

[0756] Finally, once the user is satisfied with the logo design, they can click the download button to save the logo to their device, where they can use it on business cards, signs, websites, social networking services, etc.

[0757] As a concrete example, we will explain the process when User C creates a logo for a newly established sports club. User C starts up his / her PC, opens the logo creation tool webpage, and inputs the requirements of "cool design," "for sports clubs," and "reddish color." At the same time, the emotion engine analyzes User C's facial expressions and recognizes his / her excited state. This data is sent to the server, and a logo is generated based on the generative artificial intelligence model. The generated logo has a sports emblem-style design and an energetic reddish color. If User C requests a "slightly darker red" as a fine-tuning request, the server regenerates the logo, and a highly satisfying logo is finally obtained. This logo is used for the sports club's uniforms and posters.

[0758] The above is a specific embodiment of the present invention, which can significantly reduce the effort and cost required for creating a logo design as in the past, and quickly provide a high-quality logo design that matches the user's emotions.

[0759] The processing flow will be explained below.

[0760] Step 1:

[0761] The user launches the logo creation tool web page or application on their device (PC or smartphone).

[0762] Step 2:

[0763] The user enters image data for the logo (e.g., simple, colorful, friendly, etc.) using text fields and pull-down menus on the interface.

[0764] Step 3:

[0765] The user activates the device's camera and microphone. The emotion engine analyzes the user's facial expressions and voice to recognize the user's emotional state (e.g., happy, excited, calm, etc.).

[0766] Step 4:

[0767] The user checks the image data they entered and the emotion engine's recognition results, then clicks the send button. The device then sends this data to the server.

[0768] Step 5:

[0769] The server receives the image data and emotion data sent from the user terminal using the receiving means, and the received data is processed within the server.

[0770] Step 6:

[0771] The server uses a generation means to apply the received image data and emotion data to a generative artificial intelligence model, which has previously learned data on a wide variety of logo designs.

[0772] Step 7:

[0773] A generative AI model generates a logo design based on the user's requirements and emotions. The generated logo design is temporarily stored on the server.

[0774] Step 8:

[0775] The server transmits the generated logo design to the user terminal via the transmission means.

[0776] Step 9:

[0777] The user reviews the logo design received on their device, and if they wish to make any fine adjustments to the color, font, placement, etc., they can enter their fine-tuning request into the interface.

[0778] Step 10:

[0779] The user submits a nudge request, which the device sends to the server.

[0780] Step 11:

[0781] The server again receives the fine-tuning request from the user using the receiving means, and applies the received fine-tuning data to the generating means to generate a regenerated logo design.

[0782] Step 12:

[0783] The server then transmits the regenerated logo design to the user terminal again using the transmission means, and this process is repeated as necessary until the user is satisfied with the logo design.

[0784] Step 13:

[0785] The user finally confirms the logo design they are satisfied with and clicks the download button, which saves the logo design to their device.

[0786] Step 14:

[0787] Users can use the logos they save on business cards, signs, websites, social networking services, etc.

[0788] Example 2

[0789] 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."

[0790] In conventional logo design systems, users simply input their design image, making it difficult to generate a logo design that takes into account the user's emotional state. Furthermore, fine-tuning the logo design according to the user's requests is time-consuming, preventing an efficient design process. Furthermore, there is a need to provide high-quality logo designs quickly while increasing user satisfaction.

[0791] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving logo image data and emotion data input by the user, means for using a generative artificial intelligence model to generate a logo design based on the received image data and emotion data, means for transmitting the generated logo design to the user terminal, means for receiving a fine-tuning request from the user, means for generating a re-generated logo design based on the fine-tuning request, and means for transmitting the final logo design to the user terminal. This makes it possible to quickly generate a high-quality logo design that reflects the user's emotional state and to flexibly fine-tune the design according to the user's requests.

[0792] "Logo image data" is digital data that includes visual information such as the shape, color, and text of the logo designed by the user.

[0793] "Emotional data" is digital data that indicates the user's emotional state, obtained by analyzing the user's facial expressions and voice.

[0794] A "generative artificial intelligence model" is an AI model that includes a pre-trained algorithm to generate logo designs.

[0795] A "user terminal" is an electronic device used by a user to operate the logo creation tool, such as a personal computer or smartphone.

[0796] The "receiving means" refers to a network interface or software module for receiving data sent from a user terminal.

[0797] "Generating means" refers to a processing device or software module for generating a logo design using a generative artificial intelligence model based on received image data and emotion data.

[0798] The "transmission means" refers to a network interface or software module for sending the generated logo design to a user terminal.

[0799] A "tweak request" is data that a user uses to request changes to the color, font, placement, etc. of the generated logo design.

[0800] A "regenerated logo design" is a logo design that has been regenerated by a generative artificial intelligence model based on a user's fine-tuning requests.

[0801] "Final logo design" refers to the logo design that is finalized to the user's satisfaction.

[0802] MODE FOR CARRYING OUT THE INVENTION

[0803] This invention relates to a system that generates logo designs that are adapted to the emotions of a user by combining an emotion engine that recognizes the emotions of the user. A method for implementing this system will be specifically described below.

[0804] The system includes a user terminal, a server, a generative artificial intelligence model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine.

[0805] Hardware and software used

[0806] 1. Hardware:

[0807] personal computer

[0808] Smartphone

[0809] 2. Software:

[0810] Logo creation tool (web page or application)

[0811] Emotion Engine

[0812] server

[0813] Generative AI Models

[0814] System action

[0815] User Action:

[0816] A user uses a personal computer or smartphone to launch a logo creation tool web page or application and enters logo design requirements, such as "cool design," "for a sports club," and "red tones," through text fields and pull-down menus.

[0817] Emotion Engine in action:

[0818] The emotion engine uses the camera and microphone on the user's device to analyze the user's facial expressions and voice to recognize the user's emotional state. For example, when the user is typing, the emotion engine records emotions such as excitement or joy.

[0819] Sending data:

[0820] The user terminal assembles the input requirement data and the emotion data acquired by the emotion engine into packets and transmits them to the server via a network connection.

[0821] Server Action:

[0822] The server receives the image data and emotion data sent from the user terminal using the receiving means, and the generating means applies the received data using a generative artificial intelligence model to generate a logo design that matches the user's request and emotion.

[0823] Generate and submit your logo design:

[0824] The generated logo design is temporarily stored in the server and then sent to the user's terminal using a transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they can input a fine adjustment request into the interface.

[0825] Tweak request and regeneration:

[0826] The terminal sends a fine-tuning request to the server, the server's receiving means receives the request again, and the generating means reapplies the generative artificial intelligence model to regenerate the logo design, and this process is repeated until the user is satisfied.

[0827] Final review and save:

[0828] Once the user is satisfied with the logo design, they can click the download button to save the final logo design to their device. They can then use the downloaded logo on business cards, signs, websites, social networking services, etc.

[0829] Specific examples

[0830] For example, the following shows the process when user C creates a logo for a newly established sports club.

[0831] User C starts up his / her PC and opens the logo creation tool webpage. He / she then inputs requirements such as "cool design," "for a sports club," and "reddish color." At the same time, the emotion engine analyzes User C's facial expressions and recognizes his / her excited state. This data is sent to the server, and the generative AI model generates a logo. The generated logo has a sports emblem-style design and an energetic reddish color. If User C requests a slight adjustment such as "a slightly darker red," the server regenerates the logo, and finally a logo that satisfies him / her is obtained. This logo is used for the sports club's uniforms and posters.

[0832] Prompt Sentence Examples

[0833] User requirements: Cool design, for sports clubs, red color

[0834] User Emotion: Excited

[0835] This system makes it possible to quickly provide high-quality logo designs that reflect the user's emotions, significantly reducing the effort and cost required for traditional logo design and enabling a design process that meets user expectations.

[0836] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0837] Step 1:

[0838] A user launches a logo creation tool web page or application on a personal computer or smartphone. The user inputs specific logo design requirements using text fields and pull-down menus on the interface. Examples of inputs include "cool design," "for sports clubs," and "reddish colors." This input data is temporarily stored on the device for use in later processing steps.

[0839] Step 2:

[0840] While the user is entering requirements, the emotion engine analyzes the user's facial expressions and voice in real time using the device's built-in camera and microphone. The emotion engine recognizes the user's emotional state (e.g., excitement, joy, etc.) as digital data and captures it as emotion data. This emotion data is temporarily stored in the device along with the requirement data.

[0841] Step 3:

[0842] The device sends the requirement data entered by the user and the emotion data acquired by the emotion engine to the server. At this time, the data is sent in packet format using an appropriate protocol (HTTP, HTTPS, etc.). The sent data includes text information and emotion data.

[0843] Step 4:

[0844] The server receives the requirement data and emotion data sent from the terminal using the receiving means. The received data is stored in an appropriate database or cache in the server. The generating means then receives the data and applies it to a corresponding generative AI model. The generative AI model uses a pre-trained algorithm to generate a logo design that matches the user's requirements and emotions.

[0845] Step 5:

[0846] The logo design generated by the generating means is temporarily stored in the server. This logo design is then transmitted to the user's terminal via the transmitting means. An appropriate encoding technique is used for transmission to ensure the reliability of the data. The user can then view the generated logo design on their terminal.

[0847] Step 6:

[0848] The user can review the generated logo design and input requests for fine-tuning if necessary. For example, they can enter specific requests into the interface, such as "I want the red to be a little darker." This input data is then temporarily saved on the device.

[0849] Step 7:

[0850] The device sends the user's fine-tuning request to the server. The data transmission at this time uses the same protocol and method as the initial data transmission. The specific fine-tuning request content is included in the data packet.

[0851] Step 8:

[0852] The server again receives the fine-tuning request from the user using the receiving means. The received data is processed within the server, and the generating means again applies the generative artificial intelligence model. As a result, a new logo design based on the fine-tuning request is generated.

[0853] Step 9:

[0854] The regenerated logo design is again sent via the transmission means to the user terminal, where the user can review the regenerated logo design and repeat this process until satisfied.

[0855] Step 10:

[0856] Finally, once the user is satisfied with the logo design, they click the download button to save it to their device. This downloaded logo design can then be used on business cards, signs, websites, social networking services, etc.

[0857] (Application example 2)

[0858] 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."

[0859] Conventional logo generation systems are unable to design logos that take user emotions into account, and as a result, the resulting logos often do not perfectly match the user's intentions or emotions. Furthermore, generating a logo based on user emotions could potentially make online presences such as virtual stores more unique and appealing, but no system has been available that can achieve this. There is a need for a system that solves this problem and generates logos that adapt to user emotions.

[0860] 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 receiving logo image data input by the user, means for analyzing the user's facial expression image and voice data to recognize emotions, means for using a generative artificial intelligence model to generate a logo design based on the received image data and the recognized emotion, means for transmitting the generated logo design to the user terminal, means for receiving a fine-tuning request from the user, means for generating a re-generated logo design based on the fine-tuning request, and means for transmitting the final logo design to the user terminal. This makes it possible to adapt to the user's emotions and create unique and attractive logos for use in virtual stores, etc.

[0861] The "means for receiving image data of a logo entered by a user" refers to an apparatus and process for receiving image or graphic data of a logo entered by a user through a device.

[0862] "Means for recognizing emotions by analyzing facial images and voice data of a user" refers to a device and program that analyzes the user's facial movements and voice nuances and determines the user's emotional state from that information.

[0863] "Means using a generative artificial intelligence model to generate a logo design based on received image data and recognized emotions" refers to a device and program that uses collected logo image data and emotion data as input and automatically generates a logo design using an appropriate algorithm.

[0864] The "means for transmitting the generated logo design to the user terminal" refers to a device and process for transmitting the generated logo design data to a terminal operated by the user.

[0865] The "means for receiving tweak requests from a user" refers to devices and processes for receiving tweak requests made by a user to the generated logo.

[0866] The "means for generating a regenerated logo design based on a fine-tuning request" refers to a device and a program for regenerating a logo design based on a fine-tuning request from a user.

[0867] The "means for transmitting the final logo design to the user terminal" refers to the device and process for transmitting the final logo design, which has been fine-tuned and completed, to the terminal operated by the user.

[0868] This invention relates to a system that recognizes a user's emotions and generates a logo design that is adapted to the user's emotions. The system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine. How these components work together will be described below.

[0869] First, the user launches the logo creation tool application through their device (smartphone or personal computer). This application provides an interface where the user can input image data for the logo design. The user can input the desired logo style and color theme. At the same time, the device's camera and microphone are used to capture the user's facial expression images and voice data. The emotion engine analyzes this data and recognizes the user's emotions.

[0870] Once the emotion engine outputs the analysis results, the device transmits this emotion data and the user's image data to the server. The server first receives this data using the receiving means. Next, the generating means uses a generative artificial intelligence model to generate a logo design based on the received data. This generative artificial intelligence model has previously studied a wide variety of logo designs and can generate a logo that suits the user's emotions and requests.

[0871] The generated logo design is sent from the server to the user's terminal. The user can review the logo design and send a request for fine-tuning if necessary. A specific example of a fine-tuning request might be "make the color a little darker." This request is also sent to the server, which receives it again using the receiving means. The generating means regenerates the logo based on the fine-tuning request, generating a new logo design that reflects the user's requirements. This process is repeated until the user is satisfied with the logo.

[0872] The main hardware used is a smartphone or personal computer equipped with a camera and microphone, while the software includes "EmotionEngine" for emotion analysis, a logo generation algorithm for generative AI models, "requests" a library for handling HTTP requests, and "Pillow" for image processing.

[0873] As a concrete example, consider the case where a user wants to create a logo for a new virtual store. The user launches the application and inputs the requirements of a "modern style" and a "blue color theme." At the same time, the camera takes a picture of the user's face and the microphone records their voice. The emotion engine analyzes this data and recognizes the user's emotions as "excitement" and "happiness." This data is sent to the server, and a logo is generated based on the generative AI model.

[0874] The following prompt sentences are used as examples:

[0875] Emotion data: Excitement 0.8, Joy 0.9

[0876] User request: Style: Modern, Color: Blue

[0877] This allows the system to generate a logo that is optimal for the virtual store, and it is also flexible enough to accommodate users' requests for fine-tuning.

[0878] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0879] Step 1:

[0880] A user launches a logo creation tool application on a smartphone or personal computer. The user inputs the logo style and color theme and uses the application's interface to input this information. The camera also captures the user's face and the microphone records audio data. The input data consists of image data of the logo design, facial expressions, and audio data. With this data input, the emotion engine is ready to analyze it.

[0881] Step 2:

[0882] The device uses an emotion engine to analyze the user's facial expression images and voice data and recognize emotional data. The emotion engine determines the user's emotional state from the facial expression and voice and quantifies emotions such as "excitement" or "happiness." Emotional data is output in a format such as "excitement 0.8, happiness 0.9." The input data is facial expression images and voice data, and the output data is quantified emotional data.

[0883] Step 3:

[0884] The terminal transmits the image data and emotion data of the acquired logo to the server. The transmitted data also includes the style and color theme requests input by the user. When this data reaches the server, it is provided to the generation means. The input data is the image data, emotion data, and user requirements, and these are transmitted.

[0885] Step 4:

[0886] The server's generation means generates a logo design using a generative artificial intelligence model based on the received image data and emotion data. The generative AI model has previously studied a wide variety of logo designs and outputs a logo that suits the user's request and emotion. The input data are image data, emotion data, and the user's request, and the output data is the generated logo design.

[0887] Step 5:

[0888] The server sends the generated logo design to the user terminal, which displays the logo design and allows the user to input fine-tuning requests if necessary. The input data is the generated logo design, and the output data is the display on the user terminal.

[0889] Step 6:

[0890] The user inputs a fine-tuning request for the logo. For example, the user inputs a specific request such as "make the color a little darker" and requests regeneration. The input data is the user's fine-tuning request.

[0891] Step 7:

[0892] The terminal transmits the user's fine-tuning request to the server. The server receives the fine-tuning request again using the receiving means. The input data is the user's fine-tuning request, which is transmitted to the server.

[0893] Step 8:

[0894] The server's generation means regenerates the logo based on the tweak request. The generative AI model generates a new logo design that reflects the user's requirements. The input data is the tweak request and the original logo design, and the output data is the regenerated logo design.

[0895] Step 9:

[0896] The server sends the final logo design to the user's device. If the user is satisfied, the final logo design can be downloaded and used in a virtual store, etc. The input data is the regenerated logo design, and the output data is the final logo that can be sent to and downloaded from the user's device.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] [Fourth embodiment]

[0901] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0902] 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.

[0903] 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).

[0904] 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.

[0905] 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.

[0906] 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).

[0907] 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.

[0908] 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.

[0909] 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.

[0910] 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.

[0911] 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.

[0912] 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.

[0913] 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."

[0914] This invention relates to a system that allows users to easily create and fine-tune logo designs. How this system is implemented will be described below in detail.

[0915] This system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, and a fine-tuning means. The following describes how each component works together to generate a logo design.

[0916] First, a user launches a logo creation tool web page or application on a device (e.g., a personal computer or smartphone). The user uses text fields and pull-down menus on the interface to input image data for the logo, inputting their requirements and preferences for the logo, such as "colorful," "simple," or "friendly." Once input is complete, the device sends this image data to the server.

[0917] The server receives image data sent from the user terminal using the receiving means. The generating means in the server applies the received image data to a generative AI model based on the data. This generative AI model is an algorithm that has previously learned data from a wide variety of logo designs, and can automatically generate a logo that meets the user's requirements.

[0918] The logo design generated by the generation means is temporarily stored in the server. This logo design is then sent to the user's terminal via the transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request. The terminal then sends this fine-tuning request to the server.

[0919] The server again receives the fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request, and regenerates the logo design. The regenerated logo design is again sent to the user terminal via the transmitting means. This process is repeated until the user obtains a logo design that satisfies them.

[0920] Finally, once the user is satisfied with the logo design, they can click the download button to save the logo to their device, where they can use it on business cards, signs, websites, social networking services, etc.

[0921] As a concrete example, let's explain the process of creating a logo for a newly opened cafe. The user starts up their PC, opens the logo creation tool webpage, and inputs the following requirements: "simple but warm design," "for cafes," and "brown tones." The data is sent to the server, which generates a logo based on a generative artificial intelligence model. The generated logo is a simple, brown design with a cup and coffee beans motif. If the user requests a "slightly more vibrant brown" as a fine-tuning request, the server regenerates the logo, ultimately resulting in a logo that satisfies the user. This logo is then used for the cafe's signage, menu, and business cards.

[0922] The above is a specific embodiment of the present invention, which can significantly reduce the effort and cost required for creating a logo design as in the past, and can quickly respond to the diverse needs of users.

[0923] The processing flow will be explained below.

[0924] Step 1:

[0925] The user launches the logo creation tool web page or application on their device (PC or smartphone).

[0926] Step 2:

[0927] The user enters image data for the logo (e.g., simple, colorful, friendly, etc.) using text fields and pull-down menus on the interface.

[0928] Step 3:

[0929] The user checks the image data entered and clicks the send button. The device sends this image data to the server.

[0930] Step 4:

[0931] The server receives the image data sent from the user using the receiving means, and the received data is processed within the server.

[0932] Step 5:

[0933] The server uses a generation means to apply the received image data to a generative artificial intelligence model, which has previously learned data on a wide variety of logo designs.

[0934] Step 6:

[0935] The generative AI model generates a logo design based on the user's requirements, and the generated logo design is temporarily stored on the server.

[0936] Step 7:

[0937] The server transmits the generated logo design to the user terminal via the transmission means.

[0938] Step 8:

[0939] The user reviews the logo design received on their device and, if necessary, makes minor adjustments (e.g., changes to colors or fonts), inputs a minor adjustment request into the interface.

[0940] Step 9:

[0941] The user submits a nudge request, which the device sends to the server.

[0942] Step 10:

[0943] The server again receives the fine-tuning request from the user using the receiving means, and applies the received fine-tuning data to the generating means to generate a regenerated logo design.

[0944] Step 11:

[0945] The server then transmits the regenerated logo design to the user terminal again using the transmission means, and this process is repeated as necessary until the user is satisfied with the logo design.

[0946] Step 12:

[0947] The user finally confirms the logo design they are satisfied with and clicks the download button, which saves the logo design to their device.

[0948] Step 13:

[0949] Users can use the logos they save on business cards, signs, websites, social networking services, etc.

[0950] Example 1

[0951] 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."

[0952] Conventional logo design creation systems require time and effort, making it difficult to instantly create the design a user desires. Additionally, the cost of hiring a professional designer and the need for frequent adjustments increase the overall cost. This makes it difficult for individual businesses and small and medium-sized enterprises in particular to quickly obtain a satisfactory logo design at low cost.

[0953] 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.

[0954] In this invention, the server includes means for receiving image data of a logo entered by a user, means for using a generation algorithm to generate a logo design based on the received image data, means for transmitting the generated logo design to the user's computer, means for receiving a fine-tuning request from the user, means for generating a regenerated logo design based on the fine-tuning request, means for transmitting the final logo design to the user's computer, and means for the user to download the final logo design. This allows the user to obtain a satisfactory logo design quickly and at low cost.

[0955] "User Computer" means the electronic device used to generate, display, tweak and download the Logo Design.

[0956] "Means for receiving" refers to a communication function for sending data or requests entered by the user to the server.

[0957] A "generative algorithm" is a program or mathematical method that automatically creates a logo design based on received data.

[0958] "Transmitting means" refers to a communications function for transferring the generated or regenerated logo design to the user's computer.

[0959] A "tweak request" is a request for minor changes made by a user to the generated logo design.

[0960] A "regenerating means" is a program or process for regenerating a logo design based on a tweak request.

[0961] "Means for downloading" refers to the ability to save the final logo design to the user's computer.

[0962] A "business card" is a small paper or plastic card onto which a logo design is printed.

[0963] An "advertising panel" is a large display medium on which a logo design is displayed.

[0964] "Online Site" means any web page or internet resource on which the logo design is used.

[0965] "Virtual communication tools" are online communication methods such as social networking services.

[0966] This invention relates to a system that allows users to easily generate and fine-tune logo designs. The system includes a user terminal, a server, a generative artificial intelligence model (generative AI model), a receiving means, a generating means, a transmitting means, and a fine-tuning means.

[0967] First, a user launches a logo creation tool webpage or application on a device such as a personal computer or smartphone. The user inputs their logo preferences, such as "simple," "colorful," or "friendly," through text fields and pull-down menus on the interface. For example, they can enter prompts like the following:

[0968] "I'd like to create a logo design for a new cafe I'm opening. I'd like it to be simple but warm, with a brownish color scheme."

[0969] When the user completes the input, the terminal transmits the input data to the server, and the server receives the image data transmitted from the user terminal using the receiving means.

[0970] The generation means in the server applies the received data to a generative AI model. This generative AI model has previously learned data from a wide variety of logo designs, and can automatically generate a logo that meets the user's requirements. The generation means uses this generative AI model to generate a logo design based on the user's preferences. For example, for a user who wants a simple, warm design, the generation means generates a brown logo with a cup and coffee bean motif.

[0971] The generated logo design is temporarily stored in the server and then sent to the user's terminal via a transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request. The terminal then sends this fine-tuning request to the server.

[0972] The server again receives a fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request and regenerates the logo design. The regenerated logo design is again sent to the user terminal via the transmitting means. This process is repeated until the user obtains a logo design that satisfies them.

[0973] Finally, once users are satisfied with the logo design, they can click the download button to save it to their device. Users can then use the downloaded logo on business cards, advertising panels, online sites, virtual communication tools, and more.

[0974] Using this system, users can create logo designs more quickly and at lower cost than with conventional methods, which will result in greater convenience, especially for individual entrepreneurs and small and medium-sized businesses.

[0975] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0976] Step 1:

[0977] A user launches a logo creation tool webpage or application on a personal computer or smartphone. The user inputs their logo preferences, such as "colorful," "simple," or "friendly," through text fields and pull-down menus on the interface. This is the input data.

[0978] Step 2:

[0979] The terminal sends the data entered by the user to the server, which includes the user's design requirements and wishes. Specifically, the data is sent in JSON format, which the server parses and uses in the next step.

[0980] Step 3:

[0981] The server receives input data sent from the user terminal using the receiving means. After receiving the data, it checks the integrity of the data and cleanses it as necessary, preparing it for application to the generative AI model.

[0982] Step 4:

[0983] The generation means within the server applies the received data to a generative artificial intelligence model (generative AI model). Here, the generative AI model uses an algorithm that has previously learned data from a wide variety of logo designs. This algorithm analyzes the input data and automatically generates a logo design that matches the user's preferences. Specifically, it outputs a simple, brown design with a cup and coffee bean motif.

[0984] Step 5:

[0985] The generated logo design is temporarily stored in the server, and then transmitted to the user's terminal via a transmission means. The transmitted data includes the image file of the generated logo and metadata.

[0986] Step 6:

[0987] Users can review the logo design displayed on their device and, if necessary, make minor adjustments to the color, font, placement, etc., by entering their adjustment request through the interface. The more specific the request, the more precise the adjustments will be in the next regeneration process.

[0988] Step 7:

[0989] The device sends the user's tweak request to the server, which includes the specific changes they want to make, such as "make it a slightly brighter brown." The request is then analyzed again by the server.

[0990] Step 8:

[0991] The server receives the fine-tuning request from the user again using the receiving means, then validates it and prepares for regeneration based on the request content.

[0992] Step 9:

[0993] The generator in the server reapplies the data to the generative AI model based on the fine-tuning request. The generative AI model then analyzes the input data and the fine-tuning request again to generate an improved logo design. For example, a new logo with a more vibrant shade of brown is output.

[0994] Step 10:

[0995] The regenerated logo design is again transmitted to the user terminal via the transmission means, and this process is repeated until the generated design meets the user's wishes.

[0996] Step 11:

[0997] Once the user has confirmed the final logo design they are satisfied with, they can click the download button to save the logo to their device. The downloaded logo can then be used on business cards, advertising panels, online sites, virtual communication tools, and more.

[0998] (Application example 1)

[0999] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1000] In conventional logo design systems, the process for users to generate and fine-tune designs is complicated, making it difficult to respond quickly, especially in dynamic environments such as stores and event sites. Furthermore, there was a lack of means for real-time design generation and fine-tuning that utilizes increasingly popular smart devices. This made it difficult for users to efficiently obtain designs that satisfied them.

[1001] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1002] In this invention, the server includes means for receiving image data of a logo input by a user, means for using a generative artificial intelligence model to generate a logo design based on the received image data, means for transmitting the generated logo design to a user terminal, means for receiving a fine-tuning request from the user, means for generating a regenerated logo design based on the fine-tuning request, means for displaying the generated logo design in real time via a smart device, and means for inputting additional prompts and fine-tuning requests using an input interface of the smart device, thereby enabling a user to generate and fine-tune logo designs in real time in a physical store or in a dynamic environment.

[1003] "User Device" means an electronic device used by a User to create and fine-tune a Logo Design, including a smartphone or computer.

[1004] The "means for receiving" is a function for obtaining logo image data and fine-tuning requests sent by users.

[1005] A "generative artificial intelligence model" is a machine learning algorithm trained to automatically create logo designs based on received image data.

[1006] The "transmitting means" is a function for transferring the generated logo design or the regenerated logo design to a user terminal.

[1007] A "tweak request" is a request from a user to modify the color, font, placement, etc. of the generated logo design.

[1008] "Smart devices" are mobile devices with advanced functions, such as smart glasses and smartphones.

[1009] "Means for displaying in real time" refers to a function that visually presents the instantly generated logo design on the screen of a smart device.

[1010] "Input Interface" means the functionality that allows users to input logo design requirements and tweak requests using voice commands or touch controls.

[1011] "Additional prompts" are additional information that the user enters to further specify the design.

[1012] This invention provides a system for generating and fine-tuning logo designs in real time using smart devices (e.g., smart glasses or smartphones). Specific implementations of this system are described below.

[1013] First, the user puts on the smart glasses and inputs their logo design requirements using voice commands or touch operations, such as prompts like "Create a colorful and simple logo" or "Make it a warm design." These prompts are then sent to the server through the smart glasses' input interface.

[1014] The server receives the prompt sentence from the user using the receiving means, and then generates a logo design based on the prompt sentence using a generative artificial intelligence model, and the generated logo design is displayed in real time on the smart glasses via the transmitting means.

[1015] The user can check the generated logo design on the smart glasses display and input fine-tuning requests as needed, such as "Make the font a little cuter" or "Make the background color orange" via voice commands. These requests are then sent back to the server.

[1016] The server receives the user's fine-tuning request using the receiving means, and generates a regenerated logo design using the generating means. This regenerated logo design is also displayed on the smart glasses via the transmitting means. This allows the user to repeatedly make adjustments in real time until a satisfactory logo design is obtained.

[1017] Finally, once the user is satisfied with the logo design, a QR code is generated via the smart glasses and shared in a downloadable format to a smartphone or computer.

[1018] As a concrete example, consider a scenario in which the owner of a newly opening cafe wears smart glasses and designs a logo in front of the store. The owner first voice-inputs, "Create a warm, simple logo," and checks the generated logo. He then inputs a request for minor adjustments, such as "a darker brown," and checks the re-adjusted logo. In this way, he finally arrives at a design he is satisfied with, which can be immediately used on menus and signs via QR code on the spot.

[1019] Example prompt sentence:

[1020] "Create a colorful and simple logo"

[1021] "Make the font a little cuter"

[1022] "Make the background orange"

[1023] The system allows users to efficiently and intuitively generate and fine-tune logo designs in brick-and-mortar and dynamic environments.

[1024] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1025] Step 1:

[1026] A user uses a smart device to input a request for a logo design using voice commands or touch operations. For example, the user enters a prompt such as "Create a colorful and simple logo." The input prompt is sent to the server through the input interface of the smart device. The input is the prompt, and the output is the data sent to the server.

[1027] Step 2:

[1028] The server receives the prompt text sent by the user. It acquires the prompt text using the receiving means and parses the data. The input is the prompt text from the user, and the output is the parsed data of the prompt text.

[1029] Step 3:

[1030] The server applies a generative AI model based on the received prompt to generate a logo design. The generative AI model is used to automatically create a logo design that meets the user's requirements. The input is the analyzed prompt data, and the output is the generated logo design data.

[1031] Step 4:

[1032] The server transfers the generated logo design to the smart device via a transmission means. The logo design data is displayed on the smart device display in real time. The input is the generated logo design data, and the output is the logo design displayed on the smart device.

[1033] Step 5:

[1034] The user checks the logo design on the display of the smart device and, if necessary, inputs a request for fine-tuning using voice commands. For example, the user can request specific fine-tuning such as "make the font a little cuter" or "make the background color orange." The input is the fine-tuning request made by the user, and the output is the fine-tuning request data sent to the server.

[1035] Step 6:

[1036] The server receives a fine-tuning request from the user using the receiving means. The server analyzes the data again and generates a regenerated logo design using the generating means. The input is the fine-tuning request data from the user, and the output is the regenerated logo design data.

[1037] Step 7:

[1038] The server transfers the regenerated logo design to the smart device via a transmission means. The new logo design generated by the server is displayed on the smart device in real time. The input is the data of the regenerated logo design, and the output is the new logo design displayed on the smart device.

[1039] Step 8:

[1040] The user finally confirms and finalizes the logo design they are satisfied with. A QR code is generated for the final logo design and shared in a format that can be downloaded to a smartphone or PC. The input is the data of the final logo design, and the output is the logo design data in a shareable format.

[1041] In this way, it is possible for users to create and fine-tune logo designs in real time using their smart devices.

[1042] 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.

[1043] This invention relates to a system that generates logo designs that are adapted to the user's emotions by combining an emotion engine that recognizes the user's emotions. How this system is implemented will be described below in detail.

[1044] This system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine. The following describes how each component works together to realize emotion recognition and logo design generation.

[1045] First, a user launches the logo creation tool's web page or application using a device (e.g., a personal computer or smartphone). The user then inputs their wishes and requests using text fields and pull-down menus set up on the interface for inputting logo image data. At the same time, the emotion engine analyzes the user's facial expressions and voice to recognize their emotional state. Once input is complete, the device sends this image data and the output data from the emotion engine to the server.

[1046] The server receives the image data and emotion data sent from the user terminal using the receiving means. The generating means in the server applies the received image data and emotion data to a generative artificial intelligence model based on the data. This generative artificial intelligence model is an algorithm that has previously learned data on a wide variety of logo designs, and can automatically generate a logo that matches the user's requests and emotions.

[1047] The logo design generated by the generation means is temporarily stored in the server. This logo design is then sent to the user's terminal via the transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they input a fine-tuning request into the interface. The terminal then sends this fine-tuning request to the server.

[1048] The server again receives a fine-tuning request from the user using the receiving means. The generating means in the server reapplies the data to the generative artificial intelligence model based on the fine-tuning request, and regenerates the logo design. The regenerated logo design is again transmitted to the user terminal via the transmitting means. This process is repeated as necessary until the user obtains a logo design that satisfies them.

[1049] Finally, once the user is satisfied with the logo design, they can click the download button to save the logo to their device, where they can use it on business cards, signs, websites, social networking services, etc.

[1050] As a concrete example, we will explain the process when User C creates a logo for a newly established sports club. User C starts up his / her PC, opens the logo creation tool webpage, and inputs the requirements of "cool design," "for sports clubs," and "reddish color." At the same time, the emotion engine analyzes User C's facial expressions and recognizes his / her excited state. This data is sent to the server, and a logo is generated based on the generative artificial intelligence model. The generated logo has a sports emblem-style design and an energetic reddish color. If User C requests a "slightly darker red" as a fine-tuning request, the server regenerates the logo, and a highly satisfying logo is finally obtained. This logo is used for the sports club's uniforms and posters.

[1051] The above is a specific embodiment of the present invention, which can significantly reduce the effort and cost required for creating a logo design as in the past, and quickly provide a high-quality logo design that matches the user's emotions.

[1052] The processing flow will be explained below.

[1053] Step 1:

[1054] The user launches the logo creation tool web page or application on their device (PC or smartphone).

[1055] Step 2:

[1056] The user enters image data for the logo (e.g., simple, colorful, friendly, etc.) using text fields and pull-down menus on the interface.

[1057] Step 3:

[1058] The user activates the device's camera and microphone. The emotion engine analyzes the user's facial expressions and voice to recognize the user's emotional state (e.g., happy, excited, calm, etc.).

[1059] Step 4:

[1060] The user checks the image data they entered and the emotion engine's recognition results, then clicks the send button. The device then sends this data to the server.

[1061] Step 5:

[1062] The server receives the image data and emotion data sent from the user terminal using the receiving means, and the received data is processed within the server.

[1063] Step 6:

[1064] The server uses a generation means to apply the received image data and emotion data to a generative artificial intelligence model, which has previously learned data on a wide variety of logo designs.

[1065] Step 7:

[1066] A generative AI model generates a logo design based on the user's requirements and emotions. The generated logo design is temporarily stored on the server.

[1067] Step 8:

[1068] The server transmits the generated logo design to the user terminal via the transmission means.

[1069] Step 9:

[1070] The user reviews the logo design received on their device, and if they wish to make any fine adjustments to the color, font, placement, etc., they can enter their fine-tuning request into the interface.

[1071] Step 10:

[1072] The user submits a nudge request, which the device sends to the server.

[1073] Step 11:

[1074] The server again receives the fine-tuning request from the user using the receiving means, and applies the received fine-tuning data to the generating means to generate a regenerated logo design.

[1075] Step 12:

[1076] The server then transmits the regenerated logo design to the user terminal again using the transmission means, and this process is repeated as necessary until the user is satisfied with the logo design.

[1077] Step 13:

[1078] The user finally confirms the logo design they are satisfied with and clicks the download button, which saves the logo design to their device.

[1079] Step 14:

[1080] Users can use the logos they save on business cards, signs, websites, social networking services, etc.

[1081] Example 2

[1082] 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."

[1083] In conventional logo design systems, users simply input their design image, making it difficult to generate a logo design that takes into account the user's emotional state. Furthermore, fine-tuning the logo design according to the user's requests is time-consuming, preventing an efficient design process. Furthermore, there is a need to provide high-quality logo designs quickly while increasing user satisfaction.

[1084] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving logo image data and emotion data input by the user, means for using a generative artificial intelligence model to generate a logo design based on the received image data and emotion data, means for transmitting the generated logo design to the user terminal, means for receiving a fine-tuning request from the user, means for generating a re-generated logo design based on the fine-tuning request, and means for transmitting the final logo design to the user terminal. This makes it possible to quickly generate a high-quality logo design that reflects the user's emotional state and to flexibly fine-tune the design according to the user's requests.

[1085] "Logo image data" is digital data that includes visual information such as the shape, color, and text of the logo designed by the user.

[1086] "Emotional data" is digital data that indicates the user's emotional state, obtained by analyzing the user's facial expressions and voice.

[1087] A "generative artificial intelligence model" is an AI model that includes a pre-trained algorithm to generate logo designs.

[1088] A "user terminal" is an electronic device used by a user to operate the logo creation tool, such as a personal computer or smartphone.

[1089] The "receiving means" refers to a network interface or software module for receiving data sent from a user terminal.

[1090] "Generating means" refers to a processing device or software module for generating a logo design using a generative artificial intelligence model based on received image data and emotion data.

[1091] The "transmission means" refers to a network interface or software module for sending the generated logo design to a user terminal.

[1092] A "tweak request" is data that a user uses to request changes to the color, font, placement, etc. of the generated logo design.

[1093] A "regenerated logo design" is a logo design that has been regenerated by a generative artificial intelligence model based on a user's fine-tuning requests.

[1094] "Final logo design" refers to the logo design that is finalized to the user's satisfaction.

[1095] MODE FOR CARRYING OUT THE INVENTION

[1096] This invention relates to a system that generates logo designs that are adapted to the emotions of a user by combining an emotion engine that recognizes the emotions of the user. A method for implementing this system will be specifically described below.

[1097] The system includes a user terminal, a server, a generative artificial intelligence model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine.

[1098] Hardware and software used

[1099] 1. Hardware:

[1100] personal computer

[1101] Smartphone

[1102] 2. Software:

[1103] Logo creation tool (web page or application)

[1104] Emotion Engine

[1105] server

[1106] Generative AI Models

[1107] System action

[1108] User Action:

[1109] A user uses a personal computer or smartphone to launch a logo creation tool web page or application and enters logo design requirements, such as "cool design," "for a sports club," and "red tones," through text fields and pull-down menus.

[1110] Emotion Engine in action:

[1111] The emotion engine uses the camera and microphone on the user's device to analyze the user's facial expressions and voice to recognize the user's emotional state. For example, when the user is typing, the emotion engine records emotions such as excitement or joy.

[1112] Sending data:

[1113] The user terminal assembles the input requirement data and the emotion data acquired by the emotion engine into packets and transmits them to the server via a network connection.

[1114] Server Action:

[1115] The server receives the image data and emotion data sent from the user terminal using the receiving means, and the generating means applies the received data using a generative artificial intelligence model to generate a logo design that matches the user's request and emotion.

[1116] Generate and submit your logo design:

[1117] The generated logo design is temporarily stored in the server and then sent to the user's terminal using a transmission means. The user checks the logo design displayed on the terminal, and if they wish to make fine adjustments to the color, font, placement, etc., they can input a fine adjustment request into the interface.

[1118] Tweak request and regeneration:

[1119] The terminal sends a fine-tuning request to the server, the server's receiving means receives the request again, and the generating means reapplies the generative artificial intelligence model to regenerate the logo design, and this process is repeated until the user is satisfied.

[1120] Final review and save:

[1121] Once the user is satisfied with the logo design, they can click the download button to save the final logo design to their device. They can then use the downloaded logo on business cards, signs, websites, social networking services, etc.

[1122] Specific examples

[1123] For example, the following shows the process when user C creates a logo for a newly established sports club.

[1124] User C starts up his / her PC and opens the logo creation tool webpage. He / she then inputs requirements such as "cool design," "for a sports club," and "reddish color." At the same time, the emotion engine analyzes User C's facial expressions and recognizes his / her excited state. This data is sent to the server, and the generative AI model generates a logo. The generated logo has a sports emblem-style design and an energetic reddish color. If User C requests a slight adjustment such as "a slightly darker red," the server regenerates the logo, and finally a logo that satisfies him / her is obtained. This logo is used for the sports club's uniforms and posters.

[1125] Prompt Sentence Examples

[1126] User requirements: Cool design, for sports clubs, red color

[1127] User Emotion: Excited

[1128] This system makes it possible to quickly provide high-quality logo designs that reflect the user's emotions, significantly reducing the effort and cost required for traditional logo design and enabling a design process that meets user expectations.

[1129] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1130] Step 1:

[1131] A user launches a logo creation tool web page or application on a personal computer or smartphone. The user inputs specific logo design requirements using text fields and pull-down menus on the interface. Examples of inputs include "cool design," "for sports clubs," and "reddish colors." This input data is temporarily stored on the device for use in later processing steps.

[1132] Step 2:

[1133] While the user is entering requirements, the emotion engine analyzes the user's facial expressions and voice in real time using the device's built-in camera and microphone. The emotion engine recognizes the user's emotional state (e.g., excitement, joy, etc.) as digital data and captures it as emotion data. This emotion data is temporarily stored in the device along with the requirement data.

[1134] Step 3:

[1135] The device sends the requirement data entered by the user and the emotion data acquired by the emotion engine to the server. At this time, the data is sent in packet format using an appropriate protocol (HTTP, HTTPS, etc.). The sent data includes text information and emotion data.

[1136] Step 4:

[1137] The server receives the requirement data and emotion data sent from the terminal using the receiving means. The received data is stored in an appropriate database or cache in the server. The generating means then receives the data and applies it to a corresponding generative AI model. The generative AI model uses a pre-trained algorithm to generate a logo design that matches the user's requirements and emotions.

[1138] Step 5:

[1139] The logo design generated by the generating means is temporarily stored in the server. This logo design is then transmitted to the user's terminal via the transmitting means. An appropriate encoding technique is used for transmission to ensure the reliability of the data. The user can then view the generated logo design on their terminal.

[1140] Step 6:

[1141] The user can review the generated logo design and input requests for fine-tuning if necessary. For example, they can enter specific requests into the interface, such as "I want the red to be a little darker." This input data is then temporarily saved on the device.

[1142] Step 7:

[1143] The device sends the user's fine-tuning request to the server. The data transmission at this time uses the same protocol and method as the initial data transmission. The specific fine-tuning request content is included in the data packet.

[1144] Step 8:

[1145] The server again receives the fine-tuning request from the user using the receiving means. The received data is processed within the server, and the generating means again applies the generative artificial intelligence model. As a result, a new logo design based on the fine-tuning request is generated.

[1146] Step 9:

[1147] The regenerated logo design is again sent via the transmission means to the user terminal, where the user can review the regenerated logo design and repeat this process until satisfied.

[1148] Step 10:

[1149] Finally, once the user is satisfied with the logo design, they click the download button to save it to their device. This downloaded logo design can then be used on business cards, signs, websites, social networking services, etc.

[1150] (Application example 2)

[1151] 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."

[1152] Conventional logo generation systems are unable to design logos that take user emotions into account, and as a result, the resulting logos often do not perfectly match the user's intentions or emotions. Furthermore, generating a logo based on user emotions could potentially make online presences such as virtual stores more unique and appealing, but no system has been available that can achieve this. There is a need for a system that solves this problem and generates logos that adapt to user emotions.

[1153] 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 receiving logo image data input by the user, means for analyzing the user's facial expression image and voice data to recognize emotions, means for using a generative artificial intelligence model to generate a logo design based on the received image data and the recognized emotion, means for transmitting the generated logo design to the user terminal, means for receiving a fine-tuning request from the user, means for generating a re-generated logo design based on the fine-tuning request, and means for transmitting the final logo design to the user terminal. This makes it possible to adapt to the user's emotions and create unique and attractive logos for use in virtual stores, etc.

[1154] The "means for receiving image data of a logo entered by a user" refers to an apparatus and process for receiving image or graphic data of a logo entered by a user through a device.

[1155] "Means for recognizing emotions by analyzing facial images and voice data of a user" refers to a device and program that analyzes the user's facial movements and voice nuances and determines the user's emotional state from that information.

[1156] "Means using a generative artificial intelligence model to generate a logo design based on received image data and recognized emotions" refers to a device and program that uses collected logo image data and emotion data as input and automatically generates a logo design using an appropriate algorithm.

[1157] The "means for transmitting the generated logo design to the user terminal" refers to a device and process for transmitting the generated logo design data to a terminal operated by the user.

[1158] The "means for receiving tweak requests from a user" refers to devices and processes for receiving tweak requests made by a user to the generated logo.

[1159] The "means for generating a regenerated logo design based on a fine-tuning request" refers to a device and a program for regenerating a logo design based on a fine-tuning request from a user.

[1160] The "means for transmitting the final logo design to the user terminal" refers to the device and process for transmitting the final logo design, which has been fine-tuned and completed, to the terminal operated by the user.

[1161] This invention relates to a system that recognizes a user's emotions and generates a logo design that is adapted to the user's emotions. The system includes a user terminal, a server, a generative AI model, a receiving means, a generating means, a transmitting means, a fine-tuning means, and an emotion engine. How these components work together will be described below.

[1162] First, the user launches the logo creation tool application through their device (smartphone or personal computer). This application provides an interface where the user can input image data for the logo design. The user can input the desired logo style and color theme. At the same time, the device's camera and microphone are used to capture the user's facial expression images and voice data. The emotion engine analyzes this data and recognizes the user's emotions.

[1163] Once the emotion engine outputs the analysis results, the device transmits this emotion data and the user's image data to the server. The server first receives this data using the receiving means. Next, the generating means uses a generative artificial intelligence model to generate a logo design based on the received data. This generative artificial intelligence model has previously studied a wide variety of logo designs and can generate a logo that suits the user's emotions and requests.

[1164] The generated logo design is sent from the server to the user's terminal. The user can review the logo design and send a request for fine-tuning if necessary. A specific example of a fine-tuning request might be "make the color a little darker." This request is also sent to the server, which receives it again using the receiving means. The generating means regenerates the logo based on the fine-tuning request, generating a new logo design that reflects the user's requirements. This process is repeated until the user is satisfied with the logo.

[1165] The main hardware used is a smartphone or personal computer equipped with a camera and microphone, while the software includes "EmotionEngine" for emotion analysis, a logo generation algorithm for generative AI models, "requests" a library for handling HTTP requests, and "Pillow" for image processing.

[1166] As a concrete example, consider the case where a user wants to create a logo for a new virtual store. The user launches the application and inputs the requirements of a "modern style" and a "blue color theme." At the same time, the camera takes a picture of the user's face and the microphone records their voice. The emotion engine analyzes this data and recognizes the user's emotions as "excitement" and "happiness." This data is sent to the server, and a logo is generated based on the generative AI model.

[1167] The following prompt sentences are used as examples:

[1168] Emotion data: Excitement 0.8, Joy 0.9

[1169] User request: Style: Modern, Color: Blue

[1170] This allows the system to generate a logo that is optimal for the virtual store, and it is also flexible enough to accommodate users' requests for fine-tuning.

[1171] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1172] Step 1:

[1173] A user launches a logo creation tool application on a smartphone or personal computer. The user inputs the logo style and color theme and uses the application's interface to input this information. The camera also captures the user's face and the microphone records audio data. The input data consists of image data of the logo design, facial expressions, and audio data. With this data input, the emotion engine is ready to analyze it.

[1174] Step 2:

[1175] The device uses an emotion engine to analyze the user's facial expression images and voice data and recognize emotional data. The emotion engine determines the user's emotional state from the facial expression and voice and quantifies emotions such as "excitement" or "happiness." Emotional data is output in a format such as "excitement 0.8, happiness 0.9." The input data is facial expression images and voice data, and the output data is quantified emotional data.

[1176] Step 3:

[1177] The terminal transmits the image data and emotion data of the acquired logo to the server. The transmitted data also includes the style and color theme requests input by the user. When this data reaches the server, it is provided to the generation means. The input data is the image data, emotion data, and user requirements, and these are transmitted.

[1178] Step 4:

[1179] The server's generation means generates a logo design using a generative artificial intelligence model based on the received image data and emotion data. The generative AI model has previously studied a wide variety of logo designs and outputs a logo that suits the user's request and emotion. The input data are image data, emotion data, and the user's request, and the output data is the generated logo design.

[1180] Step 5:

[1181] The server sends the generated logo design to the user terminal, which displays the logo design and allows the user to input fine-tuning requests if necessary. The input data is the generated logo design, and the output data is the display on the user terminal.

[1182] Step 6:

[1183] The user inputs a fine-tuning request for the logo. For example, the user inputs a specific request such as "make the color a little darker" and requests regeneration. The input data is the user's fine-tuning request.

[1184] Step 7:

[1185] The terminal transmits the user's fine-tuning request to the server. The server receives the fine-tuning request again using the receiving means. The input data is the user's fine-tuning request, which is transmitted to the server.

[1186] Step 8:

[1187] The server's generation means regenerates the logo based on the tweak request. The generative AI model generates a new logo design that reflects the user's requirements. The input data is the tweak request and the original logo design, and the output data is the regenerated logo design.

[1188] Step 9:

[1189] The server sends the final logo design to the user's device. If the user is satisfied, the final logo design can be downloaded and used in a virtual store, etc. The input data is the regenerated logo design, and the output data is the final logo that can be sent to and downloaded from the user's device.

[1190] 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.

[1191] 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.

[1192] 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.

[1193] 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.

[1194] FIG. 9 illustrates 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 behaviors 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.

[1195] 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.

[1196] 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).

[1197] 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.

[1198] 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."

[1199] 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.

[1200] 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).

[1201] 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.

[1202] 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.

[1203] 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.

[1204] 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.

[1205] 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.

[1206] 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.

[1207] 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.

[1208] 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.

[1209] 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.

[1210] 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.

[1211] The following is further disclosed regarding the above embodiment.

[1212] (Claim 1)

[1213] means for receiving image data of a logo input by a user;

[1214] means for using a generative artificial intelligence model to generate a logo design based on the received image data;

[1215] means for transmitting the generated logo design to a user terminal;

[1216] a means for receiving a nudge request from a user;

[1217] means for generating a regenerated logo design based on the tweak request;

[1218] A means for sending the final logo design to the user's device;

[1219] A system including:

[1220] (Claim 2)

[1221] 10. The system of claim 1, further comprising means for generating a logo design for use on a business card, sign, website, or social networking service.

[1222] (Claim 3)

[1223] 10. The system of claim 1, further comprising: means for providing an interface through which a user inputs image data for a logo design.

[1224] "Example 1"

[1225] (Claim 1)

[1226] means for receiving image data of a logo input by a user;

[1227] means for using a generation algorithm to generate a logo design based on the received image data;

[1228] means for transmitting the generated logo design to a user's computer;

[1229] a means for receiving a nudge request from a user;

[1230] means for generating a regenerated logo design based on the tweak request;

[1231] a means for transmitting the final logo design to the user's computer;

[1232] A way for users to download the final logo design;

[1233] A system including:

[1234] (Claim 2)

[1235] 10. The system of claim 1, further comprising means for generating a logo design for use on a business card, an advertising panel, an online site, or a virtual communication tool.

[1236] (Claim 3)

[1237] 10. The system of claim 1, further comprising: means for providing an interface through which a user inputs image data for a logo design.

[1238] "Application Example 1"

[1239] (Claim 1)

[1240] means for receiving image data of a logo input by a user;

[1241] means for using a generative artificial intelligence model to generate a logo design based on the received image data;

[1242] means for transmitting the generated logo design to a user terminal;

[1243] a means for receiving a nudge request from a user;

[1244] means for generating a regenerated logo design based on the tweak request;

[1245] A means for displaying the generated logo design in real time via a smart device;

[1246] a means for inputting additional prompts or fine-tuning requests utilizing the smart device's input interface;

[1247] A system including:

[1248] (Claim 2)

[1249] 10. The system of claim 1, further comprising means for generating a logo design for use on a business card, a sign, a website, a brick-and-mortar store interior, or digital signage.

[1250] (Claim 3)

[1251] 10. The system of claim 1, further comprising means for providing an interface for a user to input image data for a logo design by voice or a touchpad.

[1252] "Example 2: Combining Emotion Engines"

[1253] (Claim 1)

[1254] means for receiving image data and emotion data of a logo input by a user;

[1255] means for using a generative artificial intelligence model to generate a logo design based on the received image data and emotion data;

[1256] means for transmitting the generated logo design to a user terminal;

[1257] a means for receiving a nudge request from a user;

[1258] means for generating a regenerated logo design based on the tweak request;

[1259] A means for sending the final logo design to the user's device;

[1260] A system including:

[1261] (Claim 2)

[1262] 10. The system of claim 1, further comprising means for analyzing a user's facial expression and voice to recognize an emotional state.

[1263] (Claim 3)

[1264] 10. The system of claim 1, further comprising: means for providing an interface through which a user inputs image data for a logo design.

[1265] "Application example 2 when combining emotion engines"

[1266] (Claim 1)

[1267] means for receiving image data of a logo input by a user;

[1268] A means for recognizing emotions by analyzing facial expression images and voice data of a user;

[1269] means for using a generative artificial intelligence model to generate a logo design based on the received image data and the recognized emotion;

[1270] means for transmitting the generated logo design to a user terminal;

[1271] a means for receiving a nudge request from a user;

[1272] means for generating a regenerated logo design based on the tweak request;

[1273] A means for sending the final logo design to the user's device;

[1274] A system including:

[1275] (Claim 2)

[1276] 10. The system of claim 1, further comprising means for generating a logo design for use on a business card, sign, website, or social networking service.

[1277] (Claim 3)

[1278] 10. The system of claim 1, further comprising: means for providing an interface through which a user inputs image data for a logo design. [Explanation of symbols]

[1279] 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 receiving image data of a logo input by a user; means for using a generative artificial intelligence model to generate a logo design based on the received image data; means for transmitting the generated logo design to a user terminal; a means for receiving a nudge request from a user; means for generating a regenerated logo design based on the tweak request; A means for sending the final logo design to the user's device; A system including:

2. The system of claim 1 , further comprising means for generating a logo design for use on a business card, signage, website, or social networking service.

3. 10. The system of claim 1, further comprising means for providing an interface through which a user inputs image data for a logo design.

Images