System

Abstract

A system is provided.SOLUTION: A system comprising: an interface means for a user to input an idea; a server means for receiving and storing the idea input through the interface means; a generation means for automatically generating content based on the idea stored in the server means; a means for providing the content generated by the generation means to the user; and a means for storing the evaluation and feedback and providing the evaluation and feedback to other users.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] Conventional digital collaborative creation platforms have the problem of making it difficult for users to collaborate efficiently in real time. Furthermore, the mechanisms for automatically generating content based on ideas proposed by users are inadequate. As a result, interaction and evaluation between users do not function well, making it difficult to generate high-quality content. The objective of this invention is to solve these problems. [Means for solving the problem]

[0005] To solve this problem, we provide a system having the following configuration: an interface means for users to input ideas, a server means for receiving and storing the ideas input through the interface means, a generation means for automatically generating content based on the ideas stored in the server means, a means for providing users with the content generated by the generation means, a means for accepting user ratings and feedback on the generated content, and a means for storing the ratings and feedback and providing them to other users. This system enables smooth real-time collaborative creation between users and the automatic generation process, enabling the efficient generation of high-quality content.

[0006] "User" refers to a person who uses the system to propose ideas and generate and evaluate content.

[0007] "Interface means" refers to the parts that have functions such as input screens and forms that allow users to input ideas.

[0008] "Server means" refers to a system or device for receiving and storing ideas input through the interface means, and for delivering information to the generating means and users.

[0009] "Generation means" refers to a system or device that has the function of automatically generating content such as text, designs, and programs based on ideas stored in the server means.

[0010] The "means for providing" refers to a part having a function for displaying the content generated by the generation means to the user and making it usable.

[0011] "Means for accepting ratings and feedback" refers to the part that has the functionality for users to input and submit ratings and comments on generated content.

[0012] "Means for storing ratings and feedback" refers to the part that has the function of storing ratings and feedback received from users in a database and sharing them with other users. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The following describes an embodiment of the present invention. This system provides a platform that allows users to collaborate in real time, and is composed of the following main components and their operations.

[0035] User login

[0036] A user accesses the platform from their device and authenticates by entering their username and password into the login screen. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device, allowing the user to begin activities on the system.

[0037] Idea proposal

[0038] After logging in, users can use the interface to input new ideas. The input idea is sent to the server by pressing the submit button. The server receives the idea and stores it in a database. The interface includes a text input field and the ability to select related tags and categories, allowing users to intuitively submit ideas.

[0039] Automatic generation by generative AI

[0040] When the server detects that a new idea has been posted, it sends the idea to the generation AI, which generates various content based on the idea. For example, if a user proposes the idea of ​​an "environmentally friendly water bottle," the generation AI will automatically generate a detailed product description, design proposals, and related program code based on the idea.

[0041] Providing generated results

[0042] The generated content is provided to the user via the server, and the generated results are displayed on the user's device, allowing the user to further develop and modify their ideas.

[0043] Accepting ratings and feedback

[0044] Users can provide feedback on the generated content in the form of ratings (e.g., star ratings or scores) or comments. These feedbacks are entered through the interface means and sent to the server by pressing the send button.

[0045] Save and share ratings and feedback

[0046] The server stores the ratings and feedback received in a database and displays them in real time to other users, who can then provide further feedback or suggest ideas.

[0047] Specific examples

[0048] For example, suppose User A proposes an idea for an "environmentally friendly water bottle," and the generative AI generates a product description and design proposal based on this idea. User A views this and submits an idea adding the additional features of "thin and lightweight." This revised idea is also processed again by the generative AI, and a new generated result is provided. Meanwhile, User B provides feedback on the generated content, saying, "The design is excellent, but I would like it to be more portable." User A then makes further revisions, and the generative AI generates new content that takes user feedback into account.

[0049] In this way, this system enables real-time collaborative creation between users and efficiently generates high-quality content.

[0050] The processing flow will be explained below.

[0051] Step 1:

[0052] The user accesses the login screen from their device and enters their username and password.

[0053] Step 2:

[0054] The server receives the username and password, checks them against the credentials stored in a database, and if authentication is successful, generates a session ID and sends it back to the user's device.

[0055] Step 3:

[0056] After logging in, the user inputs a new idea using the interface means, and then presses the send button when input is complete.

[0057] Step 4:

[0058] The server receives ideas submitted by users, stores them in a database, and detects when new ideas are posted.

[0059] Step 5:

[0060] The server activates a trigger that sends the stored ideas to the generative AI, which then generates content such as text, designs, and programs based on the ideas.

[0061] Step 6:

[0062] The generation AI sends the generated content back to the server, which prepares it for delivery to the user's device.

[0063] Step 7:

[0064] The server provides the generated content to the user's device, and the user can check the generated results on their own device.

[0065] Step 8:

[0066] The user can rate and provide feedback on the provided content, which is input through an interface means.

[0067] Step 9:

[0068] Users submit their ratings and feedback to the server by pressing the submit button, which receives them and stores them in a database.

[0069] Step 10:

[0070] The server displays the stored ratings and feedback to other users in real time, allowing other users to view the ratings and feedback and provide further ideas or suggestions for revision.

[0071] By repeating this cycle, we can continue to produce high-quality content together.

[0072] Example 1

[0073] 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."

[0074] In today's highly information-driven society, there is a growing need for platforms that allow users to collaborate in real time and efficiently generate high-quality content. However, conventional systems often do not allow users to collaborate in real time, and feedback on generated content is often delayed. Furthermore, user authentication and session management are insufficient, creating security issues. Furthermore, the entire process, from proposing ideas to providing generated content, evaluation, feedback, and improvement, can sometimes not proceed smoothly.

[0075] 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.

[0076] In this invention, the server includes an interface means for users to input ideas, a means for receiving and saving ideas input through the interface means, a means for automatically generating content based on ideas, a means for providing the generated content to users, a means for accepting user ratings and feedback on the generated content, a means for saving the ratings and feedback and providing them to other users, a means for authenticating users using authentication information and generating a session ID, and a means for displaying other users' ratings and feedback in real time. This enables real-time collaboration between users and enables the efficient generation and improvement of high-quality content.

[0077] "Interface means" refers to the input screen or input field where users can input their ideas, and also includes the function of selecting tags and categories.

[0078] "Server means" refers to a server device having the function of receiving ideas from users and storing them in a database.

[0079] "Generation means" refers to AI models or software that automatically generate content based on ideas stored on a server.

[0080] "Providing means" refers to the function of transmitting the generated content to the user and displaying it on the user's terminal.

[0081] "Means for accepting ratings and feedback" refers to input functions and communication means for accepting ratings and comments on generated content from users.

[0082] "Rating and feedback storage means" refers to the functionality to store received ratings and feedback in a database and share them with other users.

[0083] "Authentication means" refers to a server device that has the function of verifying a user's authentication information and generating a session ID.

[0084] "Real-time display means" refers to a system that has the ability to instantly display other users' ratings and feedback.

[0085] The following describes an embodiment of the present invention. This system provides a platform that allows users to collaborate in real time, and is composed of the following main components and their operations.

[0086] User login

[0087] A user accesses the platform using their device and authenticates by entering their username and password into the login screen. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device, allowing the user to begin their activities on the system.

[0088] Idea proposal

[0089] After logging in, users can use the interface to input new ideas. The input idea is sent to the server by pressing the submit button. The server receives the idea and stores it in a database. The interface includes a text input field and the ability to select related tags and categories, allowing users to intuitively submit ideas.

[0090] Automatic generation by generative AI

[0091] When the server detects that a new idea has been posted, it sends the idea to a generative AI model, which generates various content based on the idea. For example, if a user proposes the idea of ​​an "environmentally friendly water bottle," the generative AI model will automatically generate a detailed product description, design proposals, and related program code based on the idea.

[0092] Providing generated results

[0093] The generated content is provided to the user via the server, and the generated results are displayed on the user's device, allowing the user to further develop and modify their ideas.

[0094] Accepting ratings and feedback

[0095] Users can provide feedback in the form of ratings and comments on the generated content. These feedbacks are input through the interface means and sent to the server by pressing the send button.

[0096] Save and share ratings and feedback

[0097] The server stores the ratings and feedback received in a database and displays them in real time to other users, who can then provide further feedback or suggest ideas.

[0098] Specific examples

[0099] For example, suppose User A proposes an idea for an "environmentally friendly water bottle," and the generative AI generates a product description and design proposal based on this idea. User A views this and submits an idea adding the additional features of "thin and lightweight." This revised idea is also processed again by the generative AI, and a new generated result is provided. Meanwhile, User B provides feedback on the generated content, saying, "The design is excellent, but I would like it to be more portable." User A then makes further revisions, and the generative AI generates new content that takes user feedback into account.

[0100] Prompt Sentence Examples

[0101] Use the following prompt for your generative AI model:

[0102] "A user has submitted an idea for an 'eco-friendly water bottle.' Based on this idea, please generate a detailed product description, design ideas, and related program code."

[0103] In this way, the system enables real-time collaborative creation between users and efficiently generates high-quality content.

[0104] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0105] Step 1: User Login

[0106] Input: The user accesses the platform's login screen from their device and enters their username and password.

[0107] Server behavior:

[0108] The server receives the authentication information entered by the user.

[0109] A database is queried to match the entered credentials with stored credentials.

[0110] If authentication is successful, a session ID is generated and returned to the user's device.

[0111] Output: A session ID is returned to the user's terminal and the user can begin their activities on the system.

[0112] Step 2: Pitch your idea

[0113] Input: After logging in, the user uses the interface means to input a new idea.

[0114] User Action:

[0115] The interface includes a text entry field and the ability to select relevant tags and categories.

[0116] The user presses the submit button to send the entered idea to the server.

[0117] Server behavior:

[0118] The server receives the submitted ideas.

[0119] Store your ideas in a database.

[0120] Output: New ideas stored in the database.

[0121] Step 3: Automatic generation by generative AI

[0122] Input: A new idea stored in the database

[0123] Server behavior:

[0124] The server detects when a new idea is saved to the database.

[0125] Send the idea to a generative AI model, which is the means of generation.

[0126] Generative AI model in action:

[0127] The generative AI model analyzes the received ideas.

[0128] Based on the idea, various content (e.g., product descriptions, design proposals, related program code) is generated.

[0129] Output: The content generated by a generative AI model.

[0130] Step 4: Providing the generated results

[0131] Input: Content generated by a generative AI model

[0132] Server behavior:

[0133] The generated content is sent to the user's device.

[0134] User Action:

[0135] The generated results are displayed on the user's device.

[0136] Output: The generated results displayed on the user's terminal.

[0137] Step 5: Rating and receiving feedback

[0138] Input: User ratings and comments on generated content

[0139] User Action:

[0140] Users can provide ratings and feedback on generated content.

[0141] The entered rating and feedback are sent to the server using the submit button.

[0142] Server behavior:

[0143] The server stores the received ratings and feedback in a database.

[0144] Output: Ratings and feedback stored in a database.

[0145] Step 6: Save and share your ratings and feedback

[0146] Input: Ratings and feedback stored in the database

[0147] Server behavior:

[0148] The server displays the received ratings and feedback in real time on other users' devices.

[0149] User Action:

[0150] Other users can view this and provide further feedback or suggest ideas.

[0151] Output: Ratings and feedback displayed on other users' devices.

[0152] (Application example 1)

[0153] 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."

[0154] Modern brick-and-mortar stores require efficient improvements and optimization of store layout and design. However, traditional methods require a lot of time and effort, and communication between multiple stakeholders is often difficult. Furthermore, there is a lack of means to quickly put proposed ideas into concrete form.

[0155] 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.

[0156] In this invention, the server includes an interface means for users to input ideas, a server means for receiving and saving the input ideas, a generation means for automatically generating content based on ideas, a means for providing the generated content to users, a means for receiving user ratings and feedback on the generated content, a means for saving the ratings and feedback and providing them to other users, a means for proposing ideas for store layout and design and for improving them collaboratively with multiple users, and a means for reflecting feedback in real time and presenting an optimal store design. This enables rapid communication between parties involved and enables efficient improvement and optimization of store layout and design.

[0157] The "interface means" is an input means for the user to input ideas.

[0158] "Server means" refers to storage means for receiving and storing ideas input through interface means.

[0159] The "creation means" is a generation means for automatically generating content based on ideas stored in the server means.

[0160] The "providing means" is a providing means for providing the content generated by the generating means to the user.

[0161] The "rating and feedback receiving means" is a receiving means for receiving user ratings and feedback on the generated content.

[0162] "Ratings and feedback storage means" refers to a storage means for storing received ratings and feedback and providing them to other users.

[0163] "Collaborative improvement methods" are methods for proposing and improving ideas for store layout and design jointly with multiple users.

[0164] The "real-time feedback reflection means" is a means for reflecting real-time feedback from users and presenting optimal store designs.

[0165] To implement this invention, a system including the following means is required. The operation of each means and the flow of the entire system will be described below.

[0166] The server is built using the programming language Python and the framework Flask, and uses SQLAlchemy for database management. OpenAI's API is used as the generative AI model. The system proposes and improves ideas for the layout and design of physical stores through the user interface, server-side processing, and generative AI.

[0167] Users access the system by operating a smartphone or smart glasses. First, the user logs in through an interface and inputs their idea. The input idea is sent to the server, which stores it in a database. The server then sends the stored idea to a generation AI, which then automatically generates specific content based on the idea. The content may include text, design, and code.

[0168] The generated content is provided to the user via the server, and the user can further develop their ideas based on it. For example, when a user proposes an idea for the placement of a new product, they can send the following prompt to the generation AI:

[0169] Store layout idea: Place new products in front of the register and run a campaign to motivate customers to buy.

[0170] Based on this prompt, the AI ​​generates detailed placement plans and specific campaign content. The results are presented to the user in the following format:

[0171] By placing new products in front of the cash register, customers are more likely to buy them. In addition, tasting events are held on weekends to allow customers to experience the products firsthand, which promotes sales.

[0172] Based on the generated results, users can revise and improve their ideas in collaboration with other users and store staff. Real-time feedback is sent to the server as needed, and the server uses this feedback to generate new content. Ratings and feedback are stored in a database, where other users can view and rate them.

[0173] This enables rapid communication between stakeholders, allowing for efficient improvement and optimization of store layout and design.Specific examples of how this system can be used include proposing new product placement, layout changes, and new interior designs in stores.

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] The user uses the interface means to enter a username and password on the login screen. This sends the login information to the server. The server compares the received login information with the authentication information in the database, and if authentication is successful, generates a session ID and returns it to the user's terminal. By receiving the session ID, the user is granted access to the system and can perform the next operation.

[0177] Step 2:

[0178] The user inputs an idea through an interface means. The idea input section provides fields for selecting tags and categories related to the specific idea content. When the user presses the "Submit" button, the idea information is transferred to the server. The server receives this information and stores it in a database. The input data is stored in text format.

[0179] Step 3:

[0180] When the server detects that a new idea has been saved to the database, it sends the idea information to the generative AI model. The generative AI model automatically generates related content based on the prompt text. Specifically, it generates detailed descriptions, designs, or code based on the idea proposed by the user. The content output from the generative AI model is returned to the server and saved back into the database. An example of a prompt text that could be entered is, "Store layout idea: Place new products in front of the register and run a campaign to increase purchasing motivation."

[0181] Step 4:

[0182] The server sends the generated content to the user's device. The user can view the generated content through an interface and further develop their ideas. This allows the user to visually confirm the specific design proposals and campaign details generated by the generative AI.

[0183] Step 5:

[0184] Users rate and provide feedback on the generated content. Ratings are entered in the form of stars or scores, and feedback is entered in the form of comments. When the user presses the "Submit" button, the rating and feedback information is sent to the server, which receives it and stores it in a database.

[0185] Step 6:

[0186] The evaluations and feedback received are displayed to other users in real time via the server. Other users can view these and provide new feedback or suggest ideas. Users can also refer to other users' feedback to revise and improve their ideas.

[0187] Step 7:

[0188] Improved ideas and feedback are then passed back to the generative AI model to generate new content. This process is repeated, and through collaboration between users, the optimal store design and layout is derived. The new content generated is then provided to users again, allowing for continuous improvement.

[0189] 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.

[0190] As an embodiment of the present invention, the details of a collaborative creation platform combined with an emotion engine are described below. This system realizes the creation of higher quality content by combining real-time collaborative creation between users with emotion recognition functionality.

[0191] User login

[0192] The user accesses the login screen from their device and enters their username and password to authenticate. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device. This allows the user to begin activities on the system.

[0193] Idea suggestion and emotion recognition

[0194] After logging in, a user can input a new idea using the interface means. This input is analyzed by the emotion engine to recognize the user's emotional state (e.g., happy, excited, worried, etc.). The recognized emotion data is sent to the server along with the idea.

[0195] Automatic generation by generative AI

[0196] The server receives the idea and emotion data submitted by the user and sends it to the generation AI, which generates appropriate content based on the received idea and emotion data. For example, if a user submits an idea for an "environmentally friendly water bottle" along with a happy emotion, the generation AI will generate a colorful, well-designed product description and design proposal that reflects this emotion.

[0197] Providing generated results

[0198] The generated content is provided to the user via a server. The generated results are displayed on the user's device, allowing the user to further develop or modify their ideas. Emotional data is also displayed, allowing the user to see how their own emotions are reflected in the content.

[0199] Accepting ratings and feedback and recognizing emotions

[0200] Users can rate and provide feedback on the generated content. The emotion engine recognizes the emotions contained in the user's feedback. For example, if a user gives feedback expressing dissatisfaction, that emotion will also be sent.

[0201] Save and share ratings and feedback

[0202] The server stores the ratings and feedback received from users in a database and displays them to other users in real time. Other users can also refer to these ratings and feedback and provide further ideas or suggestions for revisions. In particular, emotional data is displayed together, so users can understand the emotions behind the feedback.

[0203] Specific examples

[0204] For example, suppose user A proposes the idea of ​​an "environmentally friendly water bottle" with a happy emotion, and the generation AI generates a colorful and well-designed product description and design proposal based on this idea. User A reviews this and suggests a revision, saying "it should be lighter and easier to carry," along with a dissatisfied emotion. Based on this feedback and emotion, the generation AI regenerates a lighter and more portable design proposal. At the same time, user B provides feedback on the generated design proposal with a satisfied emotion, saying "this design is excellent." This allows user A to understand user B's emotions and consider further improvements.

[0205] In this way, combining an emotion engine with generative AI enables real-time collaboration and emotion recognition between users, enabling the efficient generation of high-quality content.

[0206] The processing flow will be explained below.

[0207] Step 1:

[0208] The user accesses the login screen on their device and enters their username and password. The server receives this and checks it against the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device.

[0209] Step 2:

[0210] After logging in, the user inputs a new idea using the interface means. The input idea is analyzed by the emotion engine to recognize the user's emotional state. The recognized emotion data is sent to the server along with the idea.

[0211] Step 3:

[0212] The server receives the ideas and emotion data sent by the user, stores them in a database, and sends them to the generation AI.

[0213] Step 4:

[0214] The generative AI generates appropriate content based on the ideas and emotional data it receives. For example, if the idea for an "eco-friendly water bottle" is submitted along with a happy emotion, the generative AI will generate a colorful and well-designed product description and design proposal.

[0215] Step 5:

[0216] The generated content is sent back to the server, which prepares it for delivery to the user's terminal.

[0217] Step 6:

[0218] The server provides the generated content to the user's device, where the user can check the generated results on their own device. Emotion data is also displayed, allowing the user to see how their emotions are reflected.

[0219] Step 7:

[0220] The user evaluates and gives feedback on the provided content. When the user writes the feedback, the emotion engine works again to recognize the emotion data of the feedback.

[0221] Step 8:

[0222] The user submits the evaluation, feedback, and emotional data to the server by pressing the submit button. The server receives the data and stores it in a database.

[0223] Step 9:

[0224] The server displays the received ratings, feedback, and emotional data to other users in real time, allowing other users to view the ratings and feedback and provide further ideas or suggestions for revision.

[0225] Step 10:

[0226] Each time a new idea or revision is submitted, the server requests the AI ​​to process it again and delivers the new generated results, allowing users to collaborate in real time and continue their creative activities based on the generated results.

[0227] Example 2

[0228] 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."

[0229] In conventional collaborative creation platforms, even when users input ideas, their emotions are often not taken into account and are not reflected in the generated content. This makes it difficult to generate high-quality content that reflects the user's emotions. Furthermore, when users evaluate or give feedback on generated content, their emotions cannot be properly captured, which creates an issue that makes the collaborative creation process inefficient.

[0230] 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 an interface means for a user to input ideas, a means for receiving and storing the ideas input through the interface means, a generation means for automatically generating content based on the ideas and emotion data stored in the server means, a means for providing the content generated by the generation means to users in real time, a means for accepting user ratings and feedback on the generated content, an emotion engine means for analyzing emotions included in the ratings and feedback, and a means for storing the ratings and feedback and providing them to other users in real time. This enables the generation of high-quality content that reflects user emotions and the sharing of real-time feedback.

[0231] "Interface means" refers to the input means used by users to enter ideas, ratings, and feedback into the system.

[0232] "Server means" is a general term for hardware and software that stores and processes data received from users and provides linkage functions with other means.

[0233] The "generation means" refers to an algorithm or program for automatically generating appropriate content based on the ideas and emotional data stored in the server means.

[0234] "Real-time delivery means" refers to communication means and software functions that allow generated content and feedback information to be delivered to users in real time.

[0235] The "means for receiving ratings and feedback" refers to an interface and processing means for receiving input of ratings and feedback given by users on generated content.

[0236] "Emotion engine means" refers to an algorithm or program for analyzing emotions from user input and feedback.

[0237] "Means for providing to other users in real time" refers to communication means and software functions for instantly providing to other users the ratings and feedback entered by the user, as well as the associated emotional data.

[0238] "Content" refers to information expressions such as text, design, and program code.

[0239] The present invention relates to a collaborative creation platform that combines an emotion engine and generative AI. A specific embodiment of this system is described below in detail.

[0240] The system is realized using user devices, a server, and software components such as an emotion engine and a generative AI model.

[0241] User login

[0242] A user accesses the login screen from their own device (for example, a PC or smartphone) and enters their username and password for authentication. At this time, the device accesses the login URL via a browser. The server compares the input information with the authentication information stored in the database, and if authentication is successful, generates a session ID and returns it to the user's device. This allows the user to begin activities on the system.

[0243] Idea suggestion and emotion recognition

[0244] After logging in, users input new ideas using the device interface. The server sends the input to an emotion engine (e.g., a natural language processing algorithm) to analyze the user's emotional state. The analyzed emotion data is stored on the server along with the idea.

[0245] Automatic generation by generative AI

[0246] The server sends the idea and emotion data submitted by the user to a generative AI. The generative AI (e.g., a natural language generation model such as GPT-3) generates appropriate content based on this data. For example, if a user submits an idea for an "environmentally friendly water bottle" along with a fun emotion, the generative AI will generate a colorful and well-designed product description and design proposal.

[0247] Providing generated results

[0248] The generated content is provided to the user via a server. The generated results are displayed on the user's device, allowing the user to further develop or modify the idea. Emotion data is also displayed, allowing the user to see how their own emotions are reflected in the content.

[0249] Accepting ratings and feedback and recognizing emotions

[0250] Users can rate and provide feedback on the generated content. The server then sends the user's feedback to the emotion engine and recognizes the emotions contained in the feedback. For example, if a user suggests a revision such as "make it lighter and easier to carry" along with a dissatisfied emotion, the emotion is also sent.

[0251] Save and share ratings and feedback

[0252] The server stores the ratings and feedback received from users in a database and displays them to other users in real time. Other users can refer to these ratings and feedback and provide further ideas or suggestions for revisions. In particular, emotional data is displayed together, so users can understand the emotions behind the feedback.

[0253] Specific examples

[0254] For example, suppose User A proposes the idea of ​​an "environmentally friendly water bottle" with a happy emotion, and the generation AI generates a colorful and well-designed product description and design proposal. User A reviews this and suggests a revision, saying, "It should be lighter and easier to carry," along with a feeling of dissatisfaction. Based on this feedback and emotion, the generation AI regenerates a lighter and more portable design proposal. At the same time, User B provides feedback on the generated design proposal with a feeling of satisfaction, saying, "This design is excellent." This allows User A to understand User B's emotions and consider further improvements.

[0255] Examples of prompt statements

[0256] Here are some example prompts to enter into the generative AI model:

[0257] User: I came up with the idea for an eco-friendly water bottle and it's fun.

[0258] Prompt: Generate a colorful and well-designed product description and design proposal based on this idea.

[0259]

[0260] User: I'm happy with the generated design and I don't see any need for further improvement.

[0261] Prompt: Use this feedback to give your final approval to the generated design proposal.

[0262]

[0263] User: After looking at the generated design, I feel dissatisfied and want something lighter and more portable.

[0264] Prompt: Use this feedback and sentiment to generate a lighter, more portable design.

[0265] The above is a detailed description of the embodiment of the present invention.

[0266] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0267] Step 1: User logs in via the login screen

[0268] The user accesses the login screen from their device and enters their username and password. The device sends this information to the server. Input data: username and password. Output data: HTTP request to the server.

[0269] Step 2: Server authenticates

[0270] The server receives the user's input information and compares it with the authentication information in the database, thereby verifying the user's authenticity. Input data: User name and password. Output data: Authentication result (success / failure).

[0271] Step 3: Generate a session ID upon successful authentication

[0272] If authentication is successful, the server generates a session ID and returns it to the user's device. Input data: Authentication success signal. Output data: Session ID. Specifically, a unique session ID is generated using a session management library and returned in the HTTP response.

[0273] Step 4: User submits idea

[0274] After logging in, the user uses the interface to enter a new idea. This idea is sent from the device to the server. Input data: idea. Output data: HTTP request to the server. Specific actions include entering an idea in the text box and clicking the submit button.

[0275] Step 5: The server sends the idea to the emotion engine

[0276] The server sends the received idea to the emotion engine, which uses a natural language processing algorithm to analyze the emotional state of the idea. Input data: idea. Output data: emotion data. Specifically, it sends a POST request to the emotion engine's API and receives the emotion analysis results.

[0277] Step 6: The server stores the emotion data

[0278] The server stores the analyzed emotion data together with the idea in a database. Input data: Idea and emotion data. Output data: INSERT query to the database. Specific operations include executing the database query and saving the data.

[0279] Step 7: The server sends the idea and emotion data to the generative AI.

[0280] The server sends the saved ideas and emotion data to the generation AI. Input data: Ideas and emotion data. Output data: API request to the generation AI. Specifically, it sends a request to the generation AI's API to request the generation of appropriate content.

[0281] Step 8: Generative AI generates content

[0282] The generative AI generates content based on the ideas and emotional data it receives. Input data: Ideas and emotional data. Output data: Generated content. Specifically, it analyzes and generates content using an internal algorithm, and returns the results.

[0283] Step 9: The server sends the results back to the user

[0284] The generated content is provided to the user through the server. Input data: Generated content. Output data: HTTP response to the user. The specific operation is to return the generated content as an HTTP response.

[0285] Step 10: User checks the generated results

[0286] The generated results are displayed on the user's device and the user confirms them. Input data: Generated content. Output data: Displayed on the user's screen. Specific actions include visually checking and confirming the content displayed on the web page.

[0287] Step 11: User Provides Feedback

[0288] Users rate and provide feedback on the generated content. This feedback is sent from the device to the server. Input data: Feedback. Output data: HTTP request to the server. Specific operations involve entering feedback in the rating input form and clicking the submit button.

[0289] Step 12: The server sends feedback to the emotion engine

[0290] The server sends the user's feedback to the emotion engine for emotion analysis. Input data: feedback. Output data: emotion data. Specifically, the server sends the feedback text to the emotion engine and receives the analysis results.

[0291] Step 13: Server stores feedback

[0292] The server stores the user's feedback and emotion data in a database. Input data: Feedback and emotion data. Output data: INSERT query to the database. Specific operations include executing a database query and saving the feedback and emotion data.

[0293] Step 14: The server shares the feedback with other users

[0294] The server provides feedback and emotional data to other users in real time. Input data: Feedback and emotional data. Output data: Data sent to other users. Specific operations include displaying the feedback and emotional data on other users' screens using real-time technologies such as WebSocket.

[0295] (Application example 2)

[0296] 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."

[0297] While conventional content generation systems can automatically generate content that reflects a user's ideas, they lack the ability to analyze a user's emotions in real time and provide personalized content based on those emotions. This makes it difficult to provide content that appropriately reflects the user's emotional state, limiting the quality of the user experience. The present invention aims to solve these problems by providing a system that can analyze a user's emotions in real time and provide personalized content based on those emotions.

[0298] The specification processing by the specification 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 interface means for a user to input ideas, means for receiving and storing ideas input through the interface means, generation means for automatically generating content based on the ideas stored in the server means, emotion analysis means for analyzing user emotions in real time using emotion recognition and acquiring emotion data, means for providing the content generated by the generation means to the user, means for accepting user ratings and feedback on the generated content, and means for storing the ratings and feedback and providing them to other users. This makes it possible to analyze user emotions in real time and provide personalized content based on those emotions.

[0299] "Interface means" refers to the input devices and software that allow users to access the system and input ideas.

[0300] "Server Means" refers to a computer server and its programs for receiving, storing, processing and managing data entered by users.

[0301] "Generation means" refers to the generation AI and its program for automatically generating content based on ideas stored on the server.

[0302] "Emotion analysis means" refers to an emotion recognition engine and its program for recognizing and analyzing a user's emotions in real time.

[0303] "Providing means" refers to technology and programs for displaying or transmitting content generated by generating means to a user's device.

[0304] "Rating and Feedback Measures" refers to the technology and programs used to accept and analyze ratings and opinions on content from users.

[0305] "Storage and provision means" refers to the technology and programs for storing ratings and feedback on a server and displaying and providing them to other users.

[0306] "Content" refers to an information production that includes at least one of text, design, video, or audio.

[0307] "Emotion data" refers to data that indicates the emotional state of the user analyzed by the emotion analysis means.

[0308] Basic system configuration

[0309] As an embodiment of the present invention, a system is configured that includes the following main components.

[0310] 1. User Device

[0311] Provide an interface for users to input ideas, such as a keyboard, mouse, touchscreen, or voice input device.

[0312] 2. Server

[0313] Servers receive and store data from users, and specifically include databases and storage systems.

[0314] The server has a generation means for generating content based on ideas sent by users. A generative AI model (e.g., GPT-4) is used as the generation means.

[0315] The server includes an emotion analysis system that analyzes user emotions in real time, specifically using an emotion recognition engine (e.g., Face API, Emotion API).

[0316] 3. Means of provision

[0317] This includes technology and programs for transmitting the generated content to a user terminal and displaying it.

[0318] 4. Evaluation and feedback measures

[0319] The system also includes a system for users to input and accept ratings and feedback on the generated content, using an interface means that operates on the user terminal.

[0320] 5. Storage and provision means

[0321] The server includes technology and programs for storing the received feedback in a database and providing it to other users in real time.

[0322] Program processing description

[0323] The system operates as follows.

[0324] 1. Enter and save your ideas

[0325] The user inputs ideas through an interface means from the user terminal, and the input ideas are sent to the server and stored in the database.

[0326] 2. Emotion Recognition Using Emotion Analysis Methods

[0327] When a user inputs an idea through the interface means, the emotion analysis means analyzes the user's emotion in real time and acquires the emotion data, which is also transmitted to the server together with the idea.

[0328] 3. Content generation using generative AI models

[0329] The server automatically generates appropriate content based on the stored ideas and emotion data using a generative AI model, GPT-4.

[0330] 4. Provision of Content

[0331] The content generated by the generating means is transmitted to the user terminal through the providing means, and the user confirms the content.

[0332] 5. Accepting Ratings and Feedback

[0333] Users can rate and provide feedback on the generated content, which is also sent to the server and stored in the database.

[0334] 6. Storage and provision

[0335] The received feedback is provided to other users in real time, allowing them to see the feedback and share improvements.

[0336] Specific examples

[0337] For example, suppose a user is wearing a head-mounted display and watching a movie. If the emotion analysis means analyzes the user's facial expression and recognizes the emotion "sad," the generated emotion data is sent to a generative AI model (e.g., GPT-4). Based on this emotion data, the generative AI model generates or recommends new appropriate content, such as an inspiring movie or soothing content. An example of a specific prompt sentence is, "The user is feeling sad. Recommend a comforting and emotionally uplifting movie."

[0338] In this way, this system is able to analyze users' emotions in real time and automatically generate and provide personalized content based on those emotions.

[0339] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0340] Step 1: User input

[0341] The user inputs ideas through an interface means using a user terminal (e.g., a head-mounted display). The input here includes text input, voice input, etc. The input ideas are transmitted as data to the server.

[0342] input:

[0343] User-supplied ideas (text, voice, etc.)

[0344] output:

[0345] Idea events sent to the server

[0346] Specific behavior:

[0347] A user enters the idea "eco-friendly water bottle" into the text box and presses the submit button.

[0348] Step 2: Save your idea

[0349] The server receives the ideas sent from the user's device and stores them in a database, along with additional information such as the date and time of entry and the user ID.

[0350] input:

[0351] Idea data received by the server

[0352] output:

[0353] Idea entries stored in a database

[0354] Specific behavior:

[0355] The idea of ​​an "eco-friendly water bottle" is sent to the server and stored in a database.

[0356] Step 3: Real-time sentiment analysis

[0357] When a user inputs an idea, the emotion analysis means analyzes the user's facial expression and obtains emotion data, which is then sent to the server together with the idea.

[0358] input:

[0359] Real-time facial expression data of users

[0360] output:

[0361] Emotion data sent to the server

[0362] Specific behavior:

[0363] While the user is entering their idea for an "environmentally friendly water bottle," the camera analyzes the user's facial expression and obtains emotional data such as "fun."

[0364] Step 4: Content generation using generative AI models

[0365] The server takes the idea and its sentiment data and sends prompts to a generative AI model (e.g., GPT-4) to generate content, which is then properly formatted and ready to be served to the user.

[0366] input:

[0367] Stored ideas and sentiment data

[0368] output:

[0369] Content generated by generative AI models

[0370] Specific behavior:

[0371] The server sends the idea of ​​an "environmentally friendly water bottle" and the emotion data of "fun" to the generative AI model, and uses a prompt to generate a colorful and well-designed product description. The example prompt is "The user proposed an idea for an environmentally friendly water bottle and is feeling happy. Generate a colorful and creative product description."

[0372] Step 5: Providing generated content

[0373] The generated content is sent from the server to the user's device and provided to the user, who then checks the generated content on the device.

[0374] input:

[0375] Generated content data

[0376] output:

[0377] Content displayed on the user's device

[0378] Specific behavior:

[0379] The generated product description is displayed on the user's head-mounted display.

[0380] Step 6: Provide your rating and feedback

[0381] The user inputs ratings and feedback for the generated content, and the ratings and feedback input using the interface means are transmitted to the server.

[0382] input:

[0383] User Ratings and Feedback Data

[0384] output:

[0385] Rating and feedback events sent to the server

[0386] Specific behavior:

[0387] The user reviews the generated product description, enters feedback such as "lighter and more portable," and presses the submit button.

[0388] Step 7: Save your ratings and feedback

[0389] The server stores the ratings and feedback received from users in a database, which also includes emotional data.

[0390] input:

[0391] Rating and feedback data received by the server

[0392] output:

[0393] Rating and feedback entries stored in a database

[0394] Specific behavior:

[0395] The feedback such as "it should be lighter and easier to carry" and the emotional data such as "dissatisfied" are stored in a database.

[0396] Step 8: Rate and provide feedback

[0397] The server provides the stored ratings and feedback to other users in real time, who can then refer to it and provide further ideas and feedback.

[0398] input:

[0399] Rating and feedback data stored in a database

[0400] output:

[0401] Ratings and feedback provided to other users

[0402] Specific behavior:

[0403] See other users' real-time feedback on "lighter and more portable" and add or consider your own ideas.

[0404] This will enable real-time analysis of user sentiment as a whole, and the generation and provision of personalized content based on that sentiment. It will also enable the sharing of evaluations and feedback to support collaborative creation among users.

[0405] 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.

[0406] 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.

[0407] 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.

[0408] [Second embodiment]

[0409] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0410] 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.

[0411] 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).

[0412] 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.

[0413] 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.

[0414] 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).

[0415] 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.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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."

[0421] The following describes an embodiment of the present invention. This system provides a platform that allows users to collaborate in real time, and is composed of the following main components and their operations.

[0422] User login

[0423] A user accesses the platform from their device and authenticates by entering their username and password into the login screen. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device, allowing the user to begin activities on the system.

[0424] Idea proposal

[0425] After logging in, users can use the interface to input new ideas. The input idea is sent to the server by pressing the submit button. The server receives the idea and stores it in a database. The interface includes a text input field and the ability to select related tags and categories, allowing users to intuitively submit ideas.

[0426] Automatic generation by generative AI

[0427] When the server detects that a new idea has been posted, it sends the idea to the generation AI, which generates various content based on the idea. For example, if a user proposes the idea of ​​an "environmentally friendly water bottle," the generation AI will automatically generate a detailed product description, design proposals, and related program code based on the idea.

[0428] Providing generated results

[0429] The generated content is provided to the user via the server, and the generated results are displayed on the user's device, allowing the user to further develop and modify their ideas.

[0430] Accepting ratings and feedback

[0431] Users can provide feedback on the generated content in the form of ratings (e.g., star ratings or scores) or comments. These feedbacks are entered through the interface means and sent to the server by pressing the send button.

[0432] Save and share ratings and feedback

[0433] The server stores the ratings and feedback received in a database and displays them in real time to other users, who can then provide further feedback or suggest ideas.

[0434] Specific examples

[0435] For example, suppose User A proposes an idea for an "environmentally friendly water bottle," and the generative AI generates a product description and design proposal based on this idea. User A views this and submits an idea adding the additional features of "thin and lightweight." This revised idea is also processed again by the generative AI, and a new generated result is provided. Meanwhile, User B provides feedback on the generated content, saying, "The design is excellent, but I would like it to be more portable." User A then makes further revisions, and the generative AI generates new content that takes user feedback into account.

[0436] In this way, this system enables real-time collaborative creation between users and efficiently generates high-quality content.

[0437] The processing flow will be explained below.

[0438] Step 1:

[0439] The user accesses the login screen from their device and enters their username and password.

[0440] Step 2:

[0441] The server receives the username and password, checks them against the credentials stored in a database, and if authentication is successful, generates a session ID and sends it back to the user's device.

[0442] Step 3:

[0443] After logging in, the user inputs a new idea using the interface means, and then presses the send button when input is complete.

[0444] Step 4:

[0445] The server receives ideas submitted by users, stores them in a database, and detects when new ideas are posted.

[0446] Step 5:

[0447] The server activates a trigger that sends the stored ideas to the generative AI, which then generates content such as text, designs, and programs based on the ideas.

[0448] Step 6:

[0449] The generation AI sends the generated content back to the server, which prepares it for delivery to the user's device.

[0450] Step 7:

[0451] The server provides the generated content to the user's device, and the user can check the generated results on their own device.

[0452] Step 8:

[0453] The user can rate and provide feedback on the provided content, which is input through an interface means.

[0454] Step 9:

[0455] Users submit their ratings and feedback to the server by pressing the submit button, which receives them and stores them in a database.

[0456] Step 10:

[0457] The server displays the stored ratings and feedback to other users in real time, allowing other users to view the ratings and feedback and provide further ideas or suggestions for revision.

[0458] By repeating this cycle, we can continue to produce high-quality content together.

[0459] Example 1

[0460] 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."

[0461] In today's highly information-driven society, there is a growing need for platforms that allow users to collaborate in real time and efficiently generate high-quality content. However, conventional systems often do not allow users to collaborate in real time, and feedback on generated content is often delayed. Furthermore, user authentication and session management are insufficient, creating security issues. Furthermore, the entire process, from proposing ideas to providing generated content, evaluation, feedback, and improvement, can sometimes not proceed smoothly.

[0462] 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.

[0463] In this invention, the server includes an interface means for users to input ideas, a means for receiving and saving ideas input through the interface means, a means for automatically generating content based on ideas, a means for providing the generated content to users, a means for accepting user ratings and feedback on the generated content, a means for saving the ratings and feedback and providing them to other users, a means for authenticating users using authentication information and generating a session ID, and a means for displaying other users' ratings and feedback in real time. This enables real-time collaboration between users and enables the efficient generation and improvement of high-quality content.

[0464] "Interface means" refers to the input screen or input field where users can input their ideas, and also includes the function of selecting tags and categories.

[0465] "Server means" refers to a server device having the function of receiving ideas from users and storing them in a database.

[0466] "Generation means" refers to AI models or software that automatically generate content based on ideas stored on a server.

[0467] "Providing means" refers to the function of transmitting the generated content to the user and displaying it on the user's terminal.

[0468] "Means for accepting ratings and feedback" refers to input functions and communication means for accepting ratings and comments on generated content from users.

[0469] "Rating and feedback storage means" refers to the functionality to store received ratings and feedback in a database and share them with other users.

[0470] "Authentication means" refers to a server device that has the function of verifying a user's authentication information and generating a session ID.

[0471] "Real-time display means" refers to a system that has the ability to instantly display other users' ratings and feedback.

[0472] The following describes an embodiment of the present invention. This system provides a platform that allows users to collaborate in real time, and is composed of the following main components and their operations.

[0473] User login

[0474] A user accesses the platform using their device and authenticates by entering their username and password into the login screen. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device, allowing the user to begin their activities on the system.

[0475] Idea proposal

[0476] After logging in, users can use the interface to input new ideas. The input idea is sent to the server by pressing the submit button. The server receives the idea and stores it in a database. The interface includes a text input field and the ability to select related tags and categories, allowing users to intuitively submit ideas.

[0477] Automatic generation by generative AI

[0478] When the server detects that a new idea has been posted, it sends the idea to a generative AI model, which generates various content based on the idea. For example, if a user proposes the idea of ​​an "environmentally friendly water bottle," the generative AI model will automatically generate a detailed product description, design proposals, and related program code based on the idea.

[0479] Providing generated results

[0480] The generated content is provided to the user via the server, and the generated results are displayed on the user's device, allowing the user to further develop and modify their ideas.

[0481] Accepting ratings and feedback

[0482] Users can provide feedback in the form of ratings and comments on the generated content. These feedbacks are input through the interface means and sent to the server by pressing the send button.

[0483] Save and share ratings and feedback

[0484] The server stores the ratings and feedback received in a database and displays them in real time to other users, who can then provide further feedback or suggest ideas.

[0485] Specific examples

[0486] For example, suppose User A proposes an idea for an "environmentally friendly water bottle," and the generative AI generates a product description and design proposal based on this idea. User A views this and submits an idea adding the additional features of "thin and lightweight." This revised idea is also processed again by the generative AI, and a new generated result is provided. Meanwhile, User B provides feedback on the generated content, saying, "The design is excellent, but I would like it to be more portable." User A then makes further revisions, and the generative AI generates new content that takes user feedback into account.

[0487] Prompt Sentence Examples

[0488] Use the following prompt for your generative AI model:

[0489] "A user has submitted an idea for an 'eco-friendly water bottle.' Based on this idea, please generate a detailed product description, design ideas, and related program code."

[0490] In this way, the system enables real-time collaborative creation between users and efficiently generates high-quality content.

[0491] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0492] Step 1: User Login

[0493] Input: The user accesses the platform's login screen from their device and enters their username and password.

[0494] Server behavior:

[0495] The server receives the authentication information entered by the user.

[0496] A database is queried to match the entered credentials with stored credentials.

[0497] If authentication is successful, a session ID is generated and returned to the user's device.

[0498] Output: A session ID is returned to the user's terminal and the user can begin their activities on the system.

[0499] Step 2: Pitch your idea

[0500] Input: After logging in, the user uses the interface means to input a new idea.

[0501] User Action:

[0502] The interface includes a text entry field and the ability to select relevant tags and categories.

[0503] The user presses the submit button to send the entered idea to the server.

[0504] Server behavior:

[0505] The server receives the submitted ideas.

[0506] Store your ideas in a database.

[0507] Output: New ideas stored in the database.

[0508] Step 3: Automatic generation by generative AI

[0509] Input: A new idea stored in the database

[0510] Server behavior:

[0511] The server detects when a new idea is saved to the database.

[0512] Send the idea to a generative AI model, which is the means of generation.

[0513] Generative AI model in action:

[0514] The generative AI model analyzes the received ideas.

[0515] Based on the idea, various content (e.g., product descriptions, design proposals, related program code) is generated.

[0516] Output: The content generated by a generative AI model.

[0517] Step 4: Providing the generated results

[0518] Input: Content generated by a generative AI model

[0519] Server behavior:

[0520] The generated content is sent to the user's device.

[0521] User Action:

[0522] The generated results are displayed on the user's device.

[0523] Output: The generated results displayed on the user's terminal.

[0524] Step 5: Rating and receiving feedback

[0525] Input: User ratings and comments on generated content

[0526] User Action:

[0527] Users can provide ratings and feedback on generated content.

[0528] The entered rating and feedback are sent to the server using the submit button.

[0529] Server behavior:

[0530] The server stores the received ratings and feedback in a database.

[0531] Output: Ratings and feedback stored in a database.

[0532] Step 6: Save and share your ratings and feedback

[0533] Input: Ratings and feedback stored in the database

[0534] Server behavior:

[0535] The server displays the received ratings and feedback in real time on other users' devices.

[0536] User Action:

[0537] Other users can view this and provide further feedback or suggest ideas.

[0538] Output: Ratings and feedback displayed on other users' devices.

[0539] (Application example 1)

[0540] 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."

[0541] Modern brick-and-mortar stores require efficient improvements and optimization of store layout and design. However, traditional methods require a lot of time and effort, and communication between multiple stakeholders is often difficult. Furthermore, there is a lack of means to quickly put proposed ideas into concrete form.

[0542] 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.

[0543] In this invention, the server includes an interface means for users to input ideas, a server means for receiving and saving the input ideas, a generation means for automatically generating content based on ideas, a means for providing the generated content to users, a means for receiving user ratings and feedback on the generated content, a means for saving the ratings and feedback and providing them to other users, a means for proposing ideas for store layout and design and for improving them collaboratively with multiple users, and a means for reflecting feedback in real time and presenting an optimal store design. This enables rapid communication between parties involved and enables efficient improvement and optimization of store layout and design.

[0544] The "interface means" is an input means for the user to input ideas.

[0545] "Server means" refers to storage means for receiving and storing ideas input through interface means.

[0546] The "creation means" is a generation means for automatically generating content based on ideas stored in the server means.

[0547] The "providing means" is a providing means for providing the content generated by the generating means to the user.

[0548] The "rating and feedback receiving means" is a receiving means for receiving user ratings and feedback on the generated content.

[0549] "Ratings and feedback storage means" refers to a storage means for storing received ratings and feedback and providing them to other users.

[0550] "Collaborative improvement methods" are methods for proposing and improving ideas for store layout and design jointly with multiple users.

[0551] The "real-time feedback reflection means" is a means for reflecting real-time feedback from users and presenting optimal store designs.

[0552] To implement this invention, a system including the following means is required. The operation of each means and the flow of the entire system will be described below.

[0553] The server is built using the programming language Python and the framework Flask, and uses SQLAlchemy for database management. OpenAI's API is used as the generative AI model. The system proposes and improves ideas for the layout and design of physical stores through the user interface, server-side processing, and generative AI.

[0554] Users access the system by operating a smartphone or smart glasses. First, the user logs in through an interface and inputs their idea. The input idea is sent to the server, which stores it in a database. The server then sends the stored idea to a generation AI, which then automatically generates specific content based on the idea. The content may include text, design, and code.

[0555] The generated content is provided to the user via the server, and the user can further develop their ideas based on it. For example, when a user proposes an idea for the placement of a new product, they can send the following prompt to the generation AI:

[0556] Store layout idea: Place new products in front of the register and run a campaign to motivate customers to buy.

[0557] Based on this prompt, the AI ​​generates detailed placement plans and specific campaign content. The results are presented to the user in the following format:

[0558] By placing new products in front of the cash register, customers are more likely to buy them. In addition, tasting events are held on weekends to allow customers to experience the products firsthand, which promotes sales.

[0559] Based on the generated results, users can revise and improve their ideas in collaboration with other users and store staff. Real-time feedback is sent to the server as needed, and the server uses this feedback to generate new content. Ratings and feedback are stored in a database, where other users can view and rate them.

[0560] This enables rapid communication between stakeholders, allowing for efficient improvement and optimization of store layout and design.Specific examples of how this system can be used include proposing new product placement, layout changes, and new interior designs in stores.

[0561] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0562] Step 1:

[0563] The user uses the interface means to enter a username and password on the login screen. This sends the login information to the server. The server compares the received login information with the authentication information in the database, and if authentication is successful, generates a session ID and returns it to the user's terminal. By receiving the session ID, the user is granted access to the system and can perform the next operation.

[0564] Step 2:

[0565] The user inputs an idea through an interface means. The idea input section provides fields for selecting tags and categories related to the specific idea content. When the user presses the "Submit" button, the idea information is transferred to the server. The server receives this information and stores it in a database. The input data is stored in text format.

[0566] Step 3:

[0567] When the server detects that a new idea has been saved to the database, it sends the idea information to the generative AI model. The generative AI model automatically generates related content based on the prompt text. Specifically, it generates detailed descriptions, designs, or code based on the idea proposed by the user. The content output from the generative AI model is returned to the server and saved back into the database. An example of a prompt text that could be entered is, "Store layout idea: Place new products in front of the register and run a campaign to increase purchasing motivation."

[0568] Step 4:

[0569] The server sends the generated content to the user's device. The user can view the generated content through an interface and further develop their ideas. This allows the user to visually confirm the specific design proposals and campaign details generated by the generative AI.

[0570] Step 5:

[0571] Users rate and provide feedback on the generated content. Ratings are entered in the form of stars or scores, and feedback is entered in the form of comments. When the user presses the "Submit" button, the rating and feedback information is sent to the server, which receives it and stores it in a database.

[0572] Step 6:

[0573] The evaluations and feedback received are displayed to other users in real time via the server. Other users can view these and provide new feedback or suggest ideas. Users can also refer to other users' feedback to revise and improve their ideas.

[0574] Step 7:

[0575] Improved ideas and feedback are then passed back to the generative AI model to generate new content. This process is repeated, and through collaboration between users, the optimal store design and layout is derived. The new content generated is then provided to users again, allowing for continuous improvement.

[0576] 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.

[0577] As an embodiment of the present invention, the details of a collaborative creation platform combined with an emotion engine are described below. This system realizes the creation of higher quality content by combining real-time collaborative creation between users with emotion recognition functionality.

[0578] User login

[0579] The user accesses the login screen from their device and enters their username and password to authenticate. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device. This allows the user to begin activities on the system.

[0580] Idea suggestion and emotion recognition

[0581] After logging in, a user can input a new idea using the interface means. This input is analyzed by the emotion engine to recognize the user's emotional state (e.g., happy, excited, worried, etc.). The recognized emotion data is sent to the server along with the idea.

[0582] Automatic generation by generative AI

[0583] The server receives the idea and emotion data submitted by the user and sends it to the generation AI, which generates appropriate content based on the received idea and emotion data. For example, if a user submits an idea for an "environmentally friendly water bottle" along with a happy emotion, the generation AI will generate a colorful, well-designed product description and design proposal that reflects this emotion.

[0584] Providing generated results

[0585] The generated content is provided to the user via a server. The generated results are displayed on the user's device, allowing the user to further develop or modify their ideas. Emotional data is also displayed, allowing the user to see how their own emotions are reflected in the content.

[0586] Accepting ratings and feedback and recognizing emotions

[0587] Users can rate and provide feedback on the generated content. The emotion engine recognizes the emotions contained in the user's feedback. For example, if a user gives feedback expressing dissatisfaction, that emotion will also be sent.

[0588] Save and share ratings and feedback

[0589] The server stores the ratings and feedback received from users in a database and displays them to other users in real time. Other users can also refer to these ratings and feedback and provide further ideas or suggestions for revisions. In particular, emotional data is displayed together, so users can understand the emotions behind the feedback.

[0590] Specific examples

[0591] For example, suppose user A proposes the idea of ​​an "environmentally friendly water bottle" with a happy emotion, and the generation AI generates a colorful and well-designed product description and design proposal based on this idea. User A reviews this and suggests a revision, saying "it should be lighter and easier to carry," along with a dissatisfied emotion. Based on this feedback and emotion, the generation AI regenerates a lighter and more portable design proposal. At the same time, user B provides feedback on the generated design proposal with a satisfied emotion, saying "this design is excellent." This allows user A to understand user B's emotions and consider further improvements.

[0592] In this way, combining an emotion engine with generative AI enables real-time collaboration and emotion recognition between users, enabling the efficient generation of high-quality content.

[0593] The processing flow will be explained below.

[0594] Step 1:

[0595] The user accesses the login screen on their device and enters their username and password. The server receives this and checks it against the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device.

[0596] Step 2:

[0597] After logging in, the user inputs a new idea using the interface means. The input idea is analyzed by the emotion engine to recognize the user's emotional state. The recognized emotion data is sent to the server along with the idea.

[0598] Step 3:

[0599] The server receives the ideas and emotion data sent by the user, stores them in a database, and sends them to the generation AI.

[0600] Step 4:

[0601] The generative AI generates appropriate content based on the ideas and emotional data it receives. For example, if the idea for an "eco-friendly water bottle" is submitted along with a happy emotion, the generative AI will generate a colorful and well-designed product description and design proposal.

[0602] Step 5:

[0603] The generated content is sent back to the server, which prepares it for delivery to the user's terminal.

[0604] Step 6:

[0605] The server provides the generated content to the user's device, where the user can check the generated results on their own device. Emotion data is also displayed, allowing the user to see how their emotions are reflected.

[0606] Step 7:

[0607] The user evaluates and gives feedback on the provided content. When the user writes the feedback, the emotion engine works again to recognize the emotion data of the feedback.

[0608] Step 8:

[0609] The user submits the evaluation, feedback, and emotional data to the server by pressing the submit button. The server receives the data and stores it in a database.

[0610] Step 9:

[0611] The server displays the received ratings, feedback, and emotional data to other users in real time, allowing other users to view the ratings and feedback and provide further ideas or suggestions for revision.

[0612] Step 10:

[0613] Each time a new idea or revision is submitted, the server requests the AI ​​to process it again and delivers the new generated results, allowing users to collaborate in real time and continue their creative activities based on the generated results.

[0614] Example 2

[0615] 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."

[0616] In conventional collaborative creation platforms, even when users input ideas, their emotions are often not taken into account and are not reflected in the generated content. This makes it difficult to generate high-quality content that reflects the user's emotions. Furthermore, when users evaluate or give feedback on generated content, their emotions cannot be properly captured, which creates an issue that makes the collaborative creation process inefficient.

[0617] 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 an interface means for a user to input ideas, a means for receiving and storing the ideas input through the interface means, a generation means for automatically generating content based on the ideas and emotion data stored in the server means, a means for providing the content generated by the generation means to users in real time, a means for accepting user ratings and feedback on the generated content, an emotion engine means for analyzing emotions included in the ratings and feedback, and a means for storing the ratings and feedback and providing them to other users in real time. This enables the generation of high-quality content that reflects user emotions and the sharing of real-time feedback.

[0618] "Interface means" refers to the input means used by users to enter ideas, ratings, and feedback into the system.

[0619] "Server means" is a general term for hardware and software that stores and processes data received from users and provides linkage functions with other means.

[0620] The "generation means" refers to an algorithm or program for automatically generating appropriate content based on the ideas and emotional data stored in the server means.

[0621] "Real-time delivery means" refers to communication means and software functions that allow generated content and feedback information to be delivered to users in real time.

[0622] The "means for receiving ratings and feedback" refers to an interface and processing means for receiving input of ratings and feedback given by users on generated content.

[0623] "Emotion engine means" refers to an algorithm or program for analyzing emotions from user input and feedback.

[0624] "Means for providing to other users in real time" refers to communication means and software functions for instantly providing to other users the ratings and feedback entered by the user, as well as the associated emotional data.

[0625] "Content" refers to information expressions such as text, design, and program code.

[0626] The present invention relates to a collaborative creation platform that combines an emotion engine and generative AI. A specific embodiment of this system is described below in detail.

[0627] The system is realized using user devices, a server, and software components such as an emotion engine and a generative AI model.

[0628] User login

[0629] A user accesses the login screen from their own device (for example, a PC or smartphone) and enters their username and password for authentication. At this time, the device accesses the login URL via a browser. The server compares the input information with the authentication information stored in the database, and if authentication is successful, generates a session ID and returns it to the user's device. This allows the user to begin activities on the system.

[0630] Idea suggestion and emotion recognition

[0631] After logging in, users input new ideas using the device interface. The server sends the input to an emotion engine (e.g., a natural language processing algorithm) to analyze the user's emotional state. The analyzed emotion data is stored on the server along with the idea.

[0632] Automatic generation by generative AI

[0633] The server sends the idea and emotion data submitted by the user to a generative AI. The generative AI (e.g., a natural language generation model such as GPT-3) generates appropriate content based on this data. For example, if a user submits an idea for an "environmentally friendly water bottle" along with a fun emotion, the generative AI will generate a colorful and well-designed product description and design proposal.

[0634] Providing generated results

[0635] The generated content is provided to the user via a server. The generated results are displayed on the user's device, allowing the user to further develop or modify the idea. Emotion data is also displayed, allowing the user to see how their own emotions are reflected in the content.

[0636] Accepting ratings and feedback and recognizing emotions

[0637] Users can rate and provide feedback on the generated content. The server then sends the user's feedback to the emotion engine and recognizes the emotions contained in the feedback. For example, if a user suggests a revision such as "make it lighter and easier to carry" along with a dissatisfied emotion, the emotion is also sent.

[0638] Save and share ratings and feedback

[0639] The server stores the ratings and feedback received from users in a database and displays them to other users in real time. Other users can refer to these ratings and feedback and provide further ideas or suggestions for revisions. In particular, emotional data is displayed together, so users can understand the emotions behind the feedback.

[0640] Specific examples

[0641] For example, suppose User A proposes the idea of ​​an "environmentally friendly water bottle" with a happy emotion, and the generation AI generates a colorful and well-designed product description and design proposal. User A reviews this and suggests a revision, saying, "It should be lighter and easier to carry," along with a feeling of dissatisfaction. Based on this feedback and emotion, the generation AI regenerates a lighter and more portable design proposal. At the same time, User B provides feedback on the generated design proposal with a feeling of satisfaction, saying, "This design is excellent." This allows User A to understand User B's emotions and consider further improvements.

[0642] Examples of prompt statements

[0643] Here are some example prompts to enter into the generative AI model:

[0644] User: I came up with the idea for an eco-friendly water bottle and it's fun.

[0645] Prompt: Generate a colorful and well-designed product description and design proposal based on this idea.

[0646]

[0647] User: I'm happy with the generated design and I don't see any need for further improvement.

[0648] Prompt: Use this feedback to give your final approval to the generated design proposal.

[0649]

[0650] User: After looking at the generated design, I feel dissatisfied and want something lighter and more portable.

[0651] Prompt: Use this feedback and sentiment to generate a lighter, more portable design.

[0652] The above is a detailed description of the embodiment of the present invention.

[0653] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0654] Step 1: User logs in via the login screen

[0655] The user accesses the login screen from their device and enters their username and password. The device sends this information to the server. Input data: username and password. Output data: HTTP request to the server.

[0656] Step 2: Server authenticates

[0657] The server receives the user's input information and compares it with the authentication information in the database, thereby verifying the user's authenticity. Input data: User name and password. Output data: Authentication result (success / failure).

[0658] Step 3: Generate a session ID upon successful authentication

[0659] If authentication is successful, the server generates a session ID and returns it to the user's device. Input data: Authentication success signal. Output data: Session ID. Specifically, a unique session ID is generated using a session management library and returned in the HTTP response.

[0660] Step 4: User submits idea

[0661] After logging in, the user uses the interface to enter a new idea. This idea is sent from the device to the server. Input data: idea. Output data: HTTP request to the server. Specific actions include entering an idea in the text box and clicking the submit button.

[0662] Step 5: The server sends the idea to the emotion engine

[0663] The server sends the received idea to the emotion engine, which uses a natural language processing algorithm to analyze the emotional state of the idea. Input data: idea. Output data: emotion data. Specifically, it sends a POST request to the emotion engine's API and receives the emotion analysis results.

[0664] Step 6: The server stores the emotion data

[0665] The server stores the analyzed emotion data together with the idea in a database. Input data: Idea and emotion data. Output data: INSERT query to the database. Specific operations include executing the database query and saving the data.

[0666] Step 7: The server sends the idea and emotion data to the generative AI.

[0667] The server sends the saved ideas and emotion data to the generation AI. Input data: Ideas and emotion data. Output data: API request to the generation AI. Specifically, it sends a request to the generation AI's API to request the generation of appropriate content.

[0668] Step 8: Generative AI generates content

[0669] The generative AI generates content based on the ideas and emotional data it receives. Input data: Ideas and emotional data. Output data: Generated content. Specifically, it analyzes and generates content using an internal algorithm, and returns the results.

[0670] Step 9: The server sends the results back to the user

[0671] The generated content is provided to the user through the server. Input data: Generated content. Output data: HTTP response to the user. The specific operation is to return the generated content as an HTTP response.

[0672] Step 10: User checks the generated results

[0673] The generated results are displayed on the user's device and the user confirms them. Input data: Generated content. Output data: Displayed on the user's screen. Specific actions include visually checking and confirming the content displayed on the web page.

[0674] Step 11: User Provides Feedback

[0675] Users rate and provide feedback on the generated content. This feedback is sent from the device to the server. Input data: Feedback. Output data: HTTP request to the server. Specific operations involve entering feedback in the rating input form and clicking the submit button.

[0676] Step 12: The server sends feedback to the emotion engine

[0677] The server sends the user's feedback to the emotion engine for emotion analysis. Input data: feedback. Output data: emotion data. Specifically, the server sends the feedback text to the emotion engine and receives the analysis results.

[0678] Step 13: Server stores feedback

[0679] The server stores the user's feedback and emotion data in a database. Input data: Feedback and emotion data. Output data: INSERT query to the database. Specific operations include executing a database query and saving the feedback and emotion data.

[0680] Step 14: The server shares the feedback with other users

[0681] The server provides feedback and emotional data to other users in real time. Input data: Feedback and emotional data. Output data: Data sent to other users. Specific operations include displaying the feedback and emotional data on other users' screens using real-time technologies such as WebSocket.

[0682] (Application example 2)

[0683] 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."

[0684] While conventional content generation systems can automatically generate content that reflects a user's ideas, they lack the ability to analyze a user's emotions in real time and provide personalized content based on those emotions. This makes it difficult to provide content that appropriately reflects the user's emotional state, limiting the quality of the user experience. The present invention aims to solve these problems by providing a system that can analyze a user's emotions in real time and provide personalized content based on those emotions.

[0685] The specification processing by the specification 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 interface means for a user to input ideas, means for receiving and storing ideas input through the interface means, generation means for automatically generating content based on the ideas stored in the server means, emotion analysis means for analyzing user emotions in real time using emotion recognition and acquiring emotion data, means for providing the content generated by the generation means to the user, means for accepting user ratings and feedback on the generated content, and means for storing the ratings and feedback and providing them to other users. This makes it possible to analyze user emotions in real time and provide personalized content based on those emotions.

[0686] "Interface means" refers to the input devices and software that allow users to access the system and input ideas.

[0687] "Server Means" refers to a computer server and its programs for receiving, storing, processing and managing data entered by users.

[0688] "Generation means" refers to the generation AI and its program for automatically generating content based on ideas stored on the server.

[0689] "Emotion analysis means" refers to an emotion recognition engine and its program for recognizing and analyzing a user's emotions in real time.

[0690] "Providing means" refers to technology and programs for displaying or transmitting content generated by generating means to a user's device.

[0691] "Rating and Feedback Measures" refers to the technology and programs used to accept and analyze ratings and opinions on content from users.

[0692] "Storage and provision means" refers to the technology and programs for storing ratings and feedback on a server and displaying and providing them to other users.

[0693] "Content" refers to an information production that includes at least one of text, design, video, or audio.

[0694] "Emotion data" refers to data that indicates the emotional state of the user analyzed by the emotion analysis means.

[0695] Basic system configuration

[0696] As an embodiment of the present invention, a system is configured that includes the following main components.

[0697] 1. User Device

[0698] Provide an interface for users to input ideas, such as a keyboard, mouse, touchscreen, or voice input device.

[0699] 2. Server

[0700] Servers receive and store data from users, and specifically include databases and storage systems.

[0701] The server has a generation means for generating content based on ideas sent by users. A generative AI model (e.g., GPT-4) is used as the generation means.

[0702] The server includes an emotion analysis system that analyzes user emotions in real time, specifically using an emotion recognition engine (e.g., Face API, Emotion API).

[0703] 3. Means of provision

[0704] This includes technology and programs for transmitting the generated content to a user terminal and displaying it.

[0705] 4. Evaluation and feedback measures

[0706] The system also includes a system for users to input and accept ratings and feedback on the generated content, using an interface means that operates on the user terminal.

[0707] 5. Storage and provision means

[0708] The server includes technology and programs for storing the received feedback in a database and providing it to other users in real time.

[0709] Program processing description

[0710] The system operates as follows.

[0711] 1. Enter and save your ideas

[0712] The user inputs ideas through an interface means from the user terminal, and the input ideas are sent to the server and stored in the database.

[0713] 2. Emotion Recognition Using Emotion Analysis Methods

[0714] When a user inputs an idea through the interface means, the emotion analysis means analyzes the user's emotion in real time and acquires the emotion data, which is also transmitted to the server together with the idea.

[0715] 3. Content generation using generative AI models

[0716] The server automatically generates appropriate content based on the stored ideas and emotion data using a generative AI model, GPT-4.

[0717] 4. Provision of Content

[0718] The content generated by the generating means is transmitted to the user terminal through the providing means, and the user confirms the content.

[0719] 5. Accepting Ratings and Feedback

[0720] Users can rate and provide feedback on the generated content, which is also sent to the server and stored in the database.

[0721] 6. Storage and provision

[0722] The received feedback is provided to other users in real time, allowing them to see the feedback and share improvements.

[0723] Specific examples

[0724] For example, suppose a user is wearing a head-mounted display and watching a movie. If the emotion analysis means analyzes the user's facial expression and recognizes the emotion "sad," the generated emotion data is sent to a generative AI model (e.g., GPT-4). Based on this emotion data, the generative AI model generates or recommends new appropriate content, such as an inspiring movie or soothing content. An example of a specific prompt sentence is, "The user is feeling sad. Recommend a comforting and emotionally uplifting movie."

[0725] In this way, this system is able to analyze users' emotions in real time and automatically generate and provide personalized content based on those emotions.

[0726] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0727] Step 1: User input

[0728] The user inputs ideas through an interface means using a user terminal (e.g., a head-mounted display). The input here includes text input, voice input, etc. The input ideas are transmitted as data to the server.

[0729] input:

[0730] User-supplied ideas (text, voice, etc.)

[0731] output:

[0732] Idea events sent to the server

[0733] Specific behavior:

[0734] A user enters the idea "eco-friendly water bottle" into the text box and presses the submit button.

[0735] Step 2: Save your idea

[0736] The server receives the ideas sent from the user's device and stores them in a database, along with additional information such as the date and time of entry and the user ID.

[0737] input:

[0738] Idea data received by the server

[0739] output:

[0740] Idea entries stored in a database

[0741] Specific behavior:

[0742] The idea of ​​an "eco-friendly water bottle" is sent to the server and stored in a database.

[0743] Step 3: Real-time sentiment analysis

[0744] When a user inputs an idea, the emotion analysis means analyzes the user's facial expression and obtains emotion data, which is then sent to the server together with the idea.

[0745] input:

[0746] Real-time facial expression data of users

[0747] output:

[0748] Emotion data sent to the server

[0749] Specific behavior:

[0750] While the user is entering their idea for an "environmentally friendly water bottle," the camera analyzes the user's facial expression and obtains emotional data such as "fun."

[0751] Step 4: Content generation using generative AI models

[0752] The server takes the idea and its sentiment data and sends prompts to a generative AI model (e.g., GPT-4) to generate content, which is then properly formatted and ready to be served to the user.

[0753] input:

[0754] Stored ideas and sentiment data

[0755] output:

[0756] Content generated by generative AI models

[0757] Specific behavior:

[0758] The server sends the idea of ​​an "environmentally friendly water bottle" and the emotion data of "fun" to the generative AI model, and uses a prompt to generate a colorful and well-designed product description. The example prompt is "The user proposed an idea for an environmentally friendly water bottle and is feeling happy. Generate a colorful and creative product description."

[0759] Step 5: Providing generated content

[0760] The generated content is sent from the server to the user's device and provided to the user, who then checks the generated content on the device.

[0761] input:

[0762] Generated content data

[0763] output:

[0764] Content displayed on the user's device

[0765] Specific behavior:

[0766] The generated product description is displayed on the user's head-mounted display.

[0767] Step 6: Provide your rating and feedback

[0768] The user inputs ratings and feedback for the generated content, and the ratings and feedback input using the interface means are transmitted to the server.

[0769] input:

[0770] User Ratings and Feedback Data

[0771] output:

[0772] Rating and feedback events sent to the server

[0773] Specific behavior:

[0774] The user reviews the generated product description, enters feedback such as "lighter and more portable," and presses the submit button.

[0775] Step 7: Save your ratings and feedback

[0776] The server stores the ratings and feedback received from users in a database, which also includes emotional data.

[0777] input:

[0778] Rating and feedback data received by the server

[0779] output:

[0780] Rating and feedback entries stored in a database

[0781] Specific behavior:

[0782] The feedback such as "it should be lighter and easier to carry" and the emotional data such as "dissatisfied" are stored in a database.

[0783] Step 8: Rate and provide feedback

[0784] The server provides the stored ratings and feedback to other users in real time, who can then refer to it and provide further ideas and feedback.

[0785] input:

[0786] Rating and feedback data stored in a database

[0787] output:

[0788] Ratings and feedback provided to other users

[0789] Specific behavior:

[0790] See other users' real-time feedback on "lighter and more portable" and add or consider your own ideas.

[0791] This will enable real-time analysis of user sentiment as a whole, and the generation and provision of personalized content based on that sentiment. It will also enable the sharing of evaluations and feedback to support collaborative creation among users.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] [Third embodiment]

[0796] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0797] 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.

[0798] 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).

[0799] 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.

[0800] 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.

[0801] 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).

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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."

[0808] The following describes an embodiment of the present invention. This system provides a platform that allows users to collaborate in real time, and is composed of the following main components and their operations.

[0809] User login

[0810] A user accesses the platform from their device and authenticates by entering their username and password into the login screen. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device, allowing the user to begin activities on the system.

[0811] Idea proposal

[0812] After logging in, users can use the interface to input new ideas. The input idea is sent to the server by pressing the submit button. The server receives the idea and stores it in a database. The interface includes a text input field and the ability to select related tags and categories, allowing users to intuitively submit ideas.

[0813] Automatic generation by generative AI

[0814] When the server detects that a new idea has been posted, it sends the idea to the generation AI, which generates various content based on the idea. For example, if a user proposes the idea of ​​an "environmentally friendly water bottle," the generation AI will automatically generate a detailed product description, design proposals, and related program code based on the idea.

[0815] Providing generated results

[0816] The generated content is provided to the user via the server, and the generated results are displayed on the user's device, allowing the user to further develop and modify their ideas.

[0817] Accepting ratings and feedback

[0818] Users can provide feedback on the generated content in the form of ratings (e.g., star ratings or scores) or comments. These feedbacks are entered through the interface means and sent to the server by pressing the send button.

[0819] Save and share ratings and feedback

[0820] The server stores the ratings and feedback received in a database and displays them in real time to other users, who can then provide further feedback or suggest ideas.

[0821] Specific examples

[0822] For example, suppose User A proposes an idea for an "environmentally friendly water bottle," and the generative AI generates a product description and design proposal based on this idea. User A views this and submits an idea adding the additional features of "thin and lightweight." This revised idea is also processed again by the generative AI, and a new generated result is provided. Meanwhile, User B provides feedback on the generated content, saying, "The design is excellent, but I would like it to be more portable." User A then makes further revisions, and the generative AI generates new content that takes user feedback into account.

[0823] In this way, this system enables real-time collaborative creation between users and efficiently generates high-quality content.

[0824] The processing flow will be explained below.

[0825] Step 1:

[0826] The user accesses the login screen from their device and enters their username and password.

[0827] Step 2:

[0828] The server receives the username and password, checks them against the credentials stored in a database, and if authentication is successful, generates a session ID and sends it back to the user's device.

[0829] Step 3:

[0830] After logging in, the user inputs a new idea using the interface means, and then presses the send button when input is complete.

[0831] Step 4:

[0832] The server receives ideas submitted by users, stores them in a database, and detects when new ideas are posted.

[0833] Step 5:

[0834] The server activates a trigger that sends the stored ideas to the generative AI, which then generates content such as text, designs, and programs based on the ideas.

[0835] Step 6:

[0836] The generation AI sends the generated content back to the server, which prepares it for delivery to the user's device.

[0837] Step 7:

[0838] The server provides the generated content to the user's device, and the user can check the generated results on their own device.

[0839] Step 8:

[0840] The user can rate and provide feedback on the provided content, which is input through an interface means.

[0841] Step 9:

[0842] Users submit their ratings and feedback to the server by pressing the submit button, which receives them and stores them in a database.

[0843] Step 10:

[0844] The server displays the stored ratings and feedback to other users in real time, allowing other users to view the ratings and feedback and provide further ideas or suggestions for revision.

[0845] By repeating this cycle, we can continue to produce high-quality content together.

[0846] Example 1

[0847] 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."

[0848] In today's highly information-driven society, there is a growing need for platforms that allow users to collaborate in real time and efficiently generate high-quality content. However, conventional systems often do not allow users to collaborate in real time, and feedback on generated content is often delayed. Furthermore, user authentication and session management are insufficient, creating security issues. Furthermore, the entire process, from proposing ideas to providing generated content, evaluation, feedback, and improvement, can sometimes not proceed smoothly.

[0849] 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.

[0850] In this invention, the server includes an interface means for users to input ideas, a means for receiving and saving ideas input through the interface means, a means for automatically generating content based on ideas, a means for providing the generated content to users, a means for accepting user ratings and feedback on the generated content, a means for saving the ratings and feedback and providing them to other users, a means for authenticating users using authentication information and generating a session ID, and a means for displaying other users' ratings and feedback in real time. This enables real-time collaboration between users and enables the efficient generation and improvement of high-quality content.

[0851] "Interface means" refers to the input screen or input field where users can input their ideas, and also includes the function of selecting tags and categories.

[0852] "Server means" refers to a server device having the function of receiving ideas from users and storing them in a database.

[0853] "Generation means" refers to AI models or software that automatically generate content based on ideas stored on a server.

[0854] "Providing means" refers to the function of transmitting the generated content to the user and displaying it on the user's terminal.

[0855] "Means for accepting ratings and feedback" refers to input functions and communication means for accepting ratings and comments on generated content from users.

[0856] "Rating and feedback storage means" refers to the functionality to store received ratings and feedback in a database and share them with other users.

[0857] "Authentication means" refers to a server device that has the function of verifying a user's authentication information and generating a session ID.

[0858] "Real-time display means" refers to a system that has the ability to instantly display other users' ratings and feedback.

[0859] The following describes an embodiment of the present invention. This system provides a platform that allows users to collaborate in real time, and is composed of the following main components and their operations.

[0860] User login

[0861] A user accesses the platform using their device and authenticates by entering their username and password into the login screen. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device, allowing the user to begin their activities on the system.

[0862] Idea proposal

[0863] After logging in, users can use the interface to input new ideas. The input idea is sent to the server by pressing the submit button. The server receives the idea and stores it in a database. The interface includes a text input field and the ability to select related tags and categories, allowing users to intuitively submit ideas.

[0864] Automatic generation by generative AI

[0865] When the server detects that a new idea has been posted, it sends the idea to a generative AI model, which generates various content based on the idea. For example, if a user proposes the idea of ​​an "environmentally friendly water bottle," the generative AI model will automatically generate a detailed product description, design proposals, and related program code based on the idea.

[0866] Providing generated results

[0867] The generated content is provided to the user via the server, and the generated results are displayed on the user's device, allowing the user to further develop and modify their ideas.

[0868] Accepting ratings and feedback

[0869] Users can provide feedback in the form of ratings and comments on the generated content. These feedbacks are input through the interface means and sent to the server by pressing the send button.

[0870] Save and share ratings and feedback

[0871] The server stores the ratings and feedback received in a database and displays them in real time to other users, who can then provide further feedback or suggest ideas.

[0872] Specific examples

[0873] For example, suppose User A proposes an idea for an "environmentally friendly water bottle," and the generative AI generates a product description and design proposal based on this idea. User A views this and submits an idea adding the additional features of "thin and lightweight." This revised idea is also processed again by the generative AI, and a new generated result is provided. Meanwhile, User B provides feedback on the generated content, saying, "The design is excellent, but I would like it to be more portable." User A then makes further revisions, and the generative AI generates new content that takes user feedback into account.

[0874] Prompt Sentence Examples

[0875] Use the following prompt for your generative AI model:

[0876] "A user has submitted an idea for an 'eco-friendly water bottle.' Based on this idea, please generate a detailed product description, design ideas, and related program code."

[0877] In this way, the system enables real-time collaborative creation between users and efficiently generates high-quality content.

[0878] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0879] Step 1: User Login

[0880] Input: The user accesses the platform's login screen from their device and enters their username and password.

[0881] Server behavior:

[0882] The server receives the authentication information entered by the user.

[0883] A database is queried to match the entered credentials with stored credentials.

[0884] If authentication is successful, a session ID is generated and returned to the user's device.

[0885] Output: A session ID is returned to the user's terminal and the user can begin their activities on the system.

[0886] Step 2: Pitch your idea

[0887] Input: After logging in, the user uses the interface means to input a new idea.

[0888] User Action:

[0889] The interface includes a text entry field and the ability to select relevant tags and categories.

[0890] The user presses the submit button to send the entered idea to the server.

[0891] Server behavior:

[0892] The server receives the submitted ideas.

[0893] Store your ideas in a database.

[0894] Output: New ideas stored in the database.

[0895] Step 3: Automatic generation by generative AI

[0896] Input: A new idea stored in the database

[0897] Server behavior:

[0898] The server detects when a new idea is saved to the database.

[0899] Send the idea to a generative AI model, which is the means of generation.

[0900] Generative AI model in action:

[0901] The generative AI model analyzes the received ideas.

[0902] Based on the idea, various content (e.g., product descriptions, design proposals, related program code) is generated.

[0903] Output: The content generated by a generative AI model.

[0904] Step 4: Providing the generated results

[0905] Input: Content generated by a generative AI model

[0906] Server behavior:

[0907] The generated content is sent to the user's device.

[0908] User Action:

[0909] The generated results are displayed on the user's device.

[0910] Output: The generated results displayed on the user's terminal.

[0911] Step 5: Rating and receiving feedback

[0912] Input: User ratings and comments on generated content

[0913] User Action:

[0914] Users can provide ratings and feedback on generated content.

[0915] The entered rating and feedback are sent to the server using the submit button.

[0916] Server behavior:

[0917] The server stores the received ratings and feedback in a database.

[0918] Output: Ratings and feedback stored in a database.

[0919] Step 6: Save and share your ratings and feedback

[0920] Input: Ratings and feedback stored in the database

[0921] Server behavior:

[0922] The server displays the received ratings and feedback in real time on other users' devices.

[0923] User Action:

[0924] Other users can view this and provide further feedback or suggest ideas.

[0925] Output: Ratings and feedback displayed on other users' devices.

[0926] (Application example 1)

[0927] 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."

[0928] Modern brick-and-mortar stores require efficient improvements and optimization of store layout and design. However, traditional methods require a lot of time and effort, and communication between multiple stakeholders is often difficult. Furthermore, there is a lack of means to quickly put proposed ideas into concrete form.

[0929] 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.

[0930] In this invention, the server includes an interface means for users to input ideas, a server means for receiving and saving the input ideas, a generation means for automatically generating content based on ideas, a means for providing the generated content to users, a means for receiving user ratings and feedback on the generated content, a means for saving the ratings and feedback and providing them to other users, a means for proposing ideas for store layout and design and for improving them collaboratively with multiple users, and a means for reflecting feedback in real time and presenting an optimal store design. This enables rapid communication between parties involved and enables efficient improvement and optimization of store layout and design.

[0931] The "interface means" is an input means for the user to input ideas.

[0932] "Server means" refers to storage means for receiving and storing ideas input through interface means.

[0933] The "creation means" is a generation means for automatically generating content based on ideas stored in the server means.

[0934] The "providing means" is a providing means for providing the content generated by the generating means to the user.

[0935] The "rating and feedback receiving means" is a receiving means for receiving user ratings and feedback on the generated content.

[0936] "Ratings and feedback storage means" refers to a storage means for storing received ratings and feedback and providing them to other users.

[0937] "Collaborative improvement methods" are methods for proposing and improving ideas for store layout and design jointly with multiple users.

[0938] The "real-time feedback reflection means" is a means for reflecting real-time feedback from users and presenting optimal store designs.

[0939] To implement this invention, a system including the following means is required. The operation of each means and the flow of the entire system will be described below.

[0940] The server is built using the programming language Python and the framework Flask, and uses SQLAlchemy for database management. OpenAI's API is used as the generative AI model. The system proposes and improves ideas for the layout and design of physical stores through the user interface, server-side processing, and generative AI.

[0941] Users access the system by operating a smartphone or smart glasses. First, the user logs in through an interface and inputs their idea. The input idea is sent to the server, which stores it in a database. The server then sends the stored idea to a generation AI, which then automatically generates specific content based on the idea. The content may include text, design, and code.

[0942] The generated content is provided to the user via the server, and the user can further develop their ideas based on it. For example, when a user proposes an idea for the placement of a new product, they can send the following prompt to the generation AI:

[0943] Store layout idea: Place new products in front of the register and run a campaign to motivate customers to buy.

[0944] Based on this prompt, the AI ​​generates detailed placement plans and specific campaign content. The results are presented to the user in the following format:

[0945] By placing new products in front of the cash register, customers are more likely to buy them. In addition, tasting events are held on weekends to allow customers to experience the products firsthand, which promotes sales.

[0946] Based on the generated results, users can revise and improve their ideas in collaboration with other users and store staff. Real-time feedback is sent to the server as needed, and the server uses this feedback to generate new content. Ratings and feedback are stored in a database, where other users can view and rate them.

[0947] This enables rapid communication between stakeholders, allowing for efficient improvement and optimization of store layout and design.Specific examples of how this system can be used include proposing new product placement, layout changes, and new interior designs in stores.

[0948] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0949] Step 1:

[0950] The user uses the interface means to enter a username and password on the login screen. This sends the login information to the server. The server compares the received login information with the authentication information in the database, and if authentication is successful, generates a session ID and returns it to the user's terminal. By receiving the session ID, the user is granted access to the system and can perform the next operation.

[0951] Step 2:

[0952] The user inputs an idea through an interface means. The idea input section provides fields for selecting tags and categories related to the specific idea content. When the user presses the "Submit" button, the idea information is transferred to the server. The server receives this information and stores it in a database. The input data is stored in text format.

[0953] Step 3:

[0954] When the server detects that a new idea has been saved to the database, it sends the idea information to the generative AI model. The generative AI model automatically generates related content based on the prompt text. Specifically, it generates detailed descriptions, designs, or code based on the idea proposed by the user. The content output from the generative AI model is returned to the server and saved back into the database. An example of a prompt text that could be entered is, "Store layout idea: Place new products in front of the register and run a campaign to increase purchasing motivation."

[0955] Step 4:

[0956] The server sends the generated content to the user's device. The user can view the generated content through an interface and further develop their ideas. This allows the user to visually confirm the specific design proposals and campaign details generated by the generative AI.

[0957] Step 5:

[0958] Users rate and provide feedback on the generated content. Ratings are entered in the form of stars or scores, and feedback is entered in the form of comments. When the user presses the "Submit" button, the rating and feedback information is sent to the server, which receives it and stores it in a database.

[0959] Step 6:

[0960] The evaluations and feedback received are displayed to other users in real time via the server. Other users can view these and provide new feedback or suggest ideas. Users can also refer to other users' feedback to revise and improve their ideas.

[0961] Step 7:

[0962] Improved ideas and feedback are then passed back to the generative AI model to generate new content. This process is repeated, and through collaboration between users, the optimal store design and layout is derived. The new content generated is then provided to users again, allowing for continuous improvement.

[0963] 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.

[0964] As an embodiment of the present invention, the details of a collaborative creation platform combined with an emotion engine are described below. This system realizes the creation of higher quality content by combining real-time collaborative creation between users with emotion recognition functionality.

[0965] User login

[0966] The user accesses the login screen from their device and enters their username and password to authenticate. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device. This allows the user to begin activities on the system.

[0967] Idea suggestion and emotion recognition

[0968] After logging in, a user can input a new idea using the interface means. This input is analyzed by the emotion engine to recognize the user's emotional state (e.g., happy, excited, worried, etc.). The recognized emotion data is sent to the server along with the idea.

[0969] Automatic generation by generative AI

[0970] The server receives the idea and emotion data submitted by the user and sends it to the generation AI, which generates appropriate content based on the received idea and emotion data. For example, if a user submits an idea for an "environmentally friendly water bottle" along with a happy emotion, the generation AI will generate a colorful, well-designed product description and design proposal that reflects this emotion.

[0971] Providing generated results

[0972] The generated content is provided to the user via a server. The generated results are displayed on the user's device, allowing the user to further develop or modify their ideas. Emotional data is also displayed, allowing the user to see how their own emotions are reflected in the content.

[0973] Accepting ratings and feedback and recognizing emotions

[0974] Users can rate and provide feedback on the generated content. The emotion engine recognizes the emotions contained in the user's feedback. For example, if a user gives feedback expressing dissatisfaction, that emotion will also be sent.

[0975] Save and share ratings and feedback

[0976] The server stores the ratings and feedback received from users in a database and displays them to other users in real time. Other users can also refer to these ratings and feedback and provide further ideas or suggestions for revisions. In particular, emotional data is displayed together, so users can understand the emotions behind the feedback.

[0977] Specific examples

[0978] For example, suppose user A proposes the idea of ​​an "environmentally friendly water bottle" with a happy emotion, and the generation AI generates a colorful and well-designed product description and design proposal based on this idea. User A reviews this and suggests a revision, saying "it should be lighter and easier to carry," along with a dissatisfied emotion. Based on this feedback and emotion, the generation AI regenerates a lighter and more portable design proposal. At the same time, user B provides feedback on the generated design proposal with a satisfied emotion, saying "this design is excellent." This allows user A to understand user B's emotions and consider further improvements.

[0979] In this way, combining an emotion engine with generative AI enables real-time collaboration and emotion recognition between users, enabling the efficient generation of high-quality content.

[0980] The processing flow will be explained below.

[0981] Step 1:

[0982] The user accesses the login screen on their device and enters their username and password. The server receives this and checks it against the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device.

[0983] Step 2:

[0984] After logging in, the user inputs a new idea using the interface means. The input idea is analyzed by the emotion engine to recognize the user's emotional state. The recognized emotion data is sent to the server along with the idea.

[0985] Step 3:

[0986] The server receives the ideas and emotion data sent by the user, stores them in a database, and sends them to the generation AI.

[0987] Step 4:

[0988] The generative AI generates appropriate content based on the ideas and emotional data it receives. For example, if the idea for an "eco-friendly water bottle" is submitted along with a happy emotion, the generative AI will generate a colorful and well-designed product description and design proposal.

[0989] Step 5:

[0990] The generated content is sent back to the server, which prepares it for delivery to the user's terminal.

[0991] Step 6:

[0992] The server provides the generated content to the user's device, where the user can check the generated results on their own device. Emotion data is also displayed, allowing the user to see how their emotions are reflected.

[0993] Step 7:

[0994] The user evaluates and gives feedback on the provided content. When the user writes the feedback, the emotion engine works again to recognize the emotion data of the feedback.

[0995] Step 8:

[0996] The user submits the evaluation, feedback, and emotional data to the server by pressing the submit button. The server receives the data and stores it in a database.

[0997] Step 9:

[0998] The server displays the received ratings, feedback, and emotional data to other users in real time, allowing other users to view the ratings and feedback and provide further ideas or suggestions for revision.

[0999] Step 10:

[1000] Each time a new idea or revision is submitted, the server requests the AI ​​to process it again and delivers the new generated results, allowing users to collaborate in real time and continue their creative activities based on the generated results.

[1001] Example 2

[1002] 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."

[1003] In conventional collaborative creation platforms, even when users input ideas, their emotions are often not taken into account and are not reflected in the generated content. This makes it difficult to generate high-quality content that reflects the user's emotions. Furthermore, when users evaluate or give feedback on generated content, their emotions cannot be properly captured, which creates an issue that makes the collaborative creation process inefficient.

[1004] 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 an interface means for a user to input ideas, a means for receiving and storing the ideas input through the interface means, a generation means for automatically generating content based on the ideas and emotion data stored in the server means, a means for providing the content generated by the generation means to users in real time, a means for accepting user ratings and feedback on the generated content, an emotion engine means for analyzing emotions included in the ratings and feedback, and a means for storing the ratings and feedback and providing them to other users in real time. This enables the generation of high-quality content that reflects user emotions and the sharing of real-time feedback.

[1005] "Interface means" refers to the input means used by users to enter ideas, ratings, and feedback into the system.

[1006] "Server means" is a general term for hardware and software that stores and processes data received from users and provides linkage functions with other means.

[1007] The "generation means" refers to an algorithm or program for automatically generating appropriate content based on the ideas and emotional data stored in the server means.

[1008] "Real-time delivery means" refers to communication means and software functions that allow generated content and feedback information to be delivered to users in real time.

[1009] The "means for receiving ratings and feedback" refers to an interface and processing means for receiving input of ratings and feedback given by users on generated content.

[1010] "Emotion engine means" refers to an algorithm or program for analyzing emotions from user input and feedback.

[1011] "Means for providing to other users in real time" refers to communication means and software functions for instantly providing to other users the ratings and feedback entered by the user, as well as the associated emotional data.

[1012] "Content" refers to information expressions such as text, design, and program code.

[1013] The present invention relates to a collaborative creation platform that combines an emotion engine and generative AI. A specific embodiment of this system is described below in detail.

[1014] The system is realized using user devices, a server, and software components such as an emotion engine and a generative AI model.

[1015] User login

[1016] A user accesses the login screen from their own device (for example, a PC or smartphone) and enters their username and password for authentication. At this time, the device accesses the login URL via a browser. The server compares the input information with the authentication information stored in the database, and if authentication is successful, generates a session ID and returns it to the user's device. This allows the user to begin activities on the system.

[1017] Idea suggestion and emotion recognition

[1018] After logging in, users input new ideas using the device interface. The server sends the input to an emotion engine (e.g., a natural language processing algorithm) to analyze the user's emotional state. The analyzed emotion data is stored on the server along with the idea.

[1019] Automatic generation by generative AI

[1020] The server sends the idea and emotion data submitted by the user to a generative AI. The generative AI (e.g., a natural language generation model such as GPT-3) generates appropriate content based on this data. For example, if a user submits an idea for an "environmentally friendly water bottle" along with a fun emotion, the generative AI will generate a colorful and well-designed product description and design proposal.

[1021] Providing generated results

[1022] The generated content is provided to the user via a server. The generated results are displayed on the user's device, allowing the user to further develop or modify the idea. Emotion data is also displayed, allowing the user to see how their own emotions are reflected in the content.

[1023] Accepting ratings and feedback and recognizing emotions

[1024] Users can rate and provide feedback on the generated content. The server then sends the user's feedback to the emotion engine and recognizes the emotions contained in the feedback. For example, if a user suggests a revision such as "make it lighter and easier to carry" along with a dissatisfied emotion, the emotion is also sent.

[1025] Save and share ratings and feedback

[1026] The server stores the ratings and feedback received from users in a database and displays them to other users in real time. Other users can refer to these ratings and feedback and provide further ideas or suggestions for revisions. In particular, emotional data is displayed together, so users can understand the emotions behind the feedback.

[1027] Specific examples

[1028] For example, suppose User A proposes the idea of ​​an "environmentally friendly water bottle" with a happy emotion, and the generation AI generates a colorful and well-designed product description and design proposal. User A reviews this and suggests a revision, saying, "It should be lighter and easier to carry," along with a feeling of dissatisfaction. Based on this feedback and emotion, the generation AI regenerates a lighter and more portable design proposal. At the same time, User B provides feedback on the generated design proposal with a feeling of satisfaction, saying, "This design is excellent." This allows User A to understand User B's emotions and consider further improvements.

[1029] Examples of prompt statements

[1030] Here are some example prompts to enter into the generative AI model:

[1031] User: I came up with the idea for an eco-friendly water bottle and it's fun.

[1032] Prompt: Generate a colorful and well-designed product description and design proposal based on this idea.

[1033]

[1034] User: I'm happy with the generated design and I don't see any need for further improvement.

[1035] Prompt: Use this feedback to give your final approval to the generated design proposal.

[1036]

[1037] User: After looking at the generated design, I feel dissatisfied and want something lighter and more portable.

[1038] Prompt: Use this feedback and sentiment to generate a lighter, more portable design.

[1039] The above is a detailed description of the embodiment of the present invention.

[1040] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1041] Step 1: User logs in via the login screen

[1042] The user accesses the login screen from their device and enters their username and password. The device sends this information to the server. Input data: username and password. Output data: HTTP request to the server.

[1043] Step 2: Server authenticates

[1044] The server receives the user's input information and compares it with the authentication information in the database, thereby verifying the user's authenticity. Input data: User name and password. Output data: Authentication result (success / failure).

[1045] Step 3: Generate a session ID upon successful authentication

[1046] If authentication is successful, the server generates a session ID and returns it to the user's device. Input data: Authentication success signal. Output data: Session ID. Specifically, a unique session ID is generated using a session management library and returned in the HTTP response.

[1047] Step 4: User submits idea

[1048] After logging in, the user uses the interface to enter a new idea. This idea is sent from the device to the server. Input data: idea. Output data: HTTP request to the server. Specific actions include entering an idea in the text box and clicking the submit button.

[1049] Step 5: The server sends the idea to the emotion engine

[1050] The server sends the received idea to the emotion engine, which uses a natural language processing algorithm to analyze the emotional state of the idea. Input data: idea. Output data: emotion data. Specifically, it sends a POST request to the emotion engine's API and receives the emotion analysis results.

[1051] Step 6: The server stores the emotion data

[1052] The server stores the analyzed emotion data together with the idea in a database. Input data: Idea and emotion data. Output data: INSERT query to the database. Specific operations include executing the database query and saving the data.

[1053] Step 7: The server sends the idea and emotion data to the generative AI.

[1054] The server sends the saved ideas and emotion data to the generation AI. Input data: Ideas and emotion data. Output data: API request to the generation AI. Specifically, it sends a request to the generation AI's API to request the generation of appropriate content.

[1055] Step 8: Generative AI generates content

[1056] The generative AI generates content based on the ideas and emotional data it receives. Input data: Ideas and emotional data. Output data: Generated content. Specifically, it analyzes and generates content using an internal algorithm, and returns the results.

[1057] Step 9: The server sends the results back to the user

[1058] The generated content is provided to the user through the server. Input data: Generated content. Output data: HTTP response to the user. The specific operation is to return the generated content as an HTTP response.

[1059] Step 10: User checks the generated results

[1060] The generated results are displayed on the user's device and the user confirms them. Input data: Generated content. Output data: Displayed on the user's screen. Specific actions include visually checking and confirming the content displayed on the web page.

[1061] Step 11: User Provides Feedback

[1062] Users rate and provide feedback on the generated content. This feedback is sent from the device to the server. Input data: Feedback. Output data: HTTP request to the server. Specific operations involve entering feedback in the rating input form and clicking the submit button.

[1063] Step 12: The server sends feedback to the emotion engine

[1064] The server sends the user's feedback to the emotion engine for emotion analysis. Input data: feedback. Output data: emotion data. Specifically, the server sends the feedback text to the emotion engine and receives the analysis results.

[1065] Step 13: Server stores feedback

[1066] The server stores the user's feedback and emotion data in a database. Input data: Feedback and emotion data. Output data: INSERT query to the database. Specific operations include executing a database query and saving the feedback and emotion data.

[1067] Step 14: The server shares the feedback with other users

[1068] The server provides feedback and emotional data to other users in real time. Input data: Feedback and emotional data. Output data: Data sent to other users. Specific operations include displaying the feedback and emotional data on other users' screens using real-time technologies such as WebSocket.

[1069] (Application example 2)

[1070] 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."

[1071] While conventional content generation systems can automatically generate content that reflects a user's ideas, they lack the ability to analyze a user's emotions in real time and provide personalized content based on those emotions. This makes it difficult to provide content that appropriately reflects the user's emotional state, limiting the quality of the user experience. The present invention aims to solve these problems by providing a system that can analyze a user's emotions in real time and provide personalized content based on those emotions.

[1072] The specification processing by the specification 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 interface means for a user to input ideas, means for receiving and storing ideas input through the interface means, generation means for automatically generating content based on the ideas stored in the server means, emotion analysis means for analyzing user emotions in real time using emotion recognition and acquiring emotion data, means for providing the content generated by the generation means to the user, means for accepting user ratings and feedback on the generated content, and means for storing the ratings and feedback and providing them to other users. This makes it possible to analyze user emotions in real time and provide personalized content based on those emotions.

[1073] "Interface means" refers to the input devices and software that allow users to access the system and input ideas.

[1074] "Server Means" refers to a computer server and its programs for receiving, storing, processing and managing data entered by users.

[1075] "Generation means" refers to the generation AI and its program for automatically generating content based on ideas stored on the server.

[1076] "Emotion analysis means" refers to an emotion recognition engine and its program for recognizing and analyzing a user's emotions in real time.

[1077] "Providing means" refers to technology and programs for displaying or transmitting content generated by generating means to a user's device.

[1078] "Rating and Feedback Measures" refers to the technology and programs used to accept and analyze ratings and opinions on content from users.

[1079] "Storage and provision means" refers to the technology and programs for storing ratings and feedback on a server and displaying and providing them to other users.

[1080] "Content" refers to an information production that includes at least one of text, design, video, or audio.

[1081] "Emotion data" refers to data that indicates the emotional state of the user analyzed by the emotion analysis means.

[1082] Basic system configuration

[1083] As an embodiment of the present invention, a system is configured that includes the following main components.

[1084] 1. User Device

[1085] Provide an interface for users to input ideas, such as a keyboard, mouse, touchscreen, or voice input device.

[1086] 2. Server

[1087] Servers receive and store data from users, and specifically include databases and storage systems.

[1088] The server has a generation means for generating content based on ideas sent by users. A generative AI model (e.g., GPT-4) is used as the generation means.

[1089] The server includes an emotion analysis system that analyzes user emotions in real time, specifically using an emotion recognition engine (e.g., Face API, Emotion API).

[1090] 3. Means of provision

[1091] This includes technology and programs for transmitting the generated content to a user terminal and displaying it.

[1092] 4. Evaluation and feedback measures

[1093] The system also includes a system for users to input and accept ratings and feedback on the generated content, using an interface means that operates on the user terminal.

[1094] 5. Storage and provision means

[1095] The server includes technology and programs for storing the received feedback in a database and providing it to other users in real time.

[1096] Program processing description

[1097] The system operates as follows.

[1098] 1. Enter and save your ideas

[1099] The user inputs ideas through an interface means from the user terminal, and the input ideas are sent to the server and stored in the database.

[1100] 2. Emotion Recognition Using Emotion Analysis Methods

[1101] When a user inputs an idea through the interface means, the emotion analysis means analyzes the user's emotion in real time and acquires the emotion data, which is also transmitted to the server together with the idea.

[1102] 3. Content generation using generative AI models

[1103] The server automatically generates appropriate content based on the stored ideas and emotion data using a generative AI model, GPT-4.

[1104] 4. Provision of Content

[1105] The content generated by the generating means is transmitted to the user terminal through the providing means, and the user confirms the content.

[1106] 5. Accepting Ratings and Feedback

[1107] Users can rate and provide feedback on the generated content, which is also sent to the server and stored in the database.

[1108] 6. Storage and provision

[1109] The received feedback is provided to other users in real time, allowing them to see the feedback and share improvements.

[1110] Specific examples

[1111] For example, suppose a user is wearing a head-mounted display and watching a movie. If the emotion analysis means analyzes the user's facial expression and recognizes the emotion "sad," the generated emotion data is sent to a generative AI model (e.g., GPT-4). Based on this emotion data, the generative AI model generates or recommends new appropriate content, such as an inspiring movie or soothing content. An example of a specific prompt sentence is, "The user is feeling sad. Recommend a comforting and emotionally uplifting movie."

[1112] In this way, this system is able to analyze users' emotions in real time and automatically generate and provide personalized content based on those emotions.

[1113] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1114] Step 1: User input

[1115] The user inputs ideas through an interface means using a user terminal (e.g., a head-mounted display). The input here includes text input, voice input, etc. The input ideas are transmitted as data to the server.

[1116] input:

[1117] User-supplied ideas (text, voice, etc.)

[1118] output:

[1119] Idea events sent to the server

[1120] Specific behavior:

[1121] A user enters the idea "eco-friendly water bottle" into the text box and presses the submit button.

[1122] Step 2: Save your idea

[1123] The server receives the ideas sent from the user's device and stores them in a database, along with additional information such as the date and time of entry and the user ID.

[1124] input:

[1125] Idea data received by the server

[1126] output:

[1127] Idea entries stored in a database

[1128] Specific behavior:

[1129] The idea of ​​an "eco-friendly water bottle" is sent to the server and stored in a database.

[1130] Step 3: Real-time sentiment analysis

[1131] When a user inputs an idea, the emotion analysis means analyzes the user's facial expression and obtains emotion data, which is then sent to the server together with the idea.

[1132] input:

[1133] Real-time facial expression data of users

[1134] output:

[1135] Emotion data sent to the server

[1136] Specific behavior:

[1137] While the user is entering their idea for an "environmentally friendly water bottle," the camera analyzes the user's facial expression and obtains emotional data such as "fun."

[1138] Step 4: Content generation using generative AI models

[1139] The server takes the idea and its sentiment data and sends prompts to a generative AI model (e.g., GPT-4) to generate content, which is then properly formatted and ready to be served to the user.

[1140] input:

[1141] Stored ideas and sentiment data

[1142] output:

[1143] Content generated by generative AI models

[1144] Specific behavior:

[1145] The server sends the idea of ​​an "environmentally friendly water bottle" and the emotion data of "fun" to the generative AI model, and uses a prompt to generate a colorful and well-designed product description. The example prompt is "The user proposed an idea for an environmentally friendly water bottle and is feeling happy. Generate a colorful and creative product description."

[1146] Step 5: Providing generated content

[1147] The generated content is sent from the server to the user's device and provided to the user, who then checks the generated content on the device.

[1148] input:

[1149] Generated content data

[1150] output:

[1151] Content displayed on the user's device

[1152] Specific behavior:

[1153] The generated product description is displayed on the user's head-mounted display.

[1154] Step 6: Provide your rating and feedback

[1155] The user inputs ratings and feedback for the generated content, and the ratings and feedback input using the interface means are transmitted to the server.

[1156] input:

[1157] User Ratings and Feedback Data

[1158] output:

[1159] Rating and feedback events sent to the server

[1160] Specific behavior:

[1161] The user reviews the generated product description, enters feedback such as "lighter and more portable," and presses the submit button.

[1162] Step 7: Save your ratings and feedback

[1163] The server stores the ratings and feedback received from users in a database, which also includes emotional data.

[1164] input:

[1165] Rating and feedback data received by the server

[1166] output:

[1167] Rating and feedback entries stored in a database

[1168] Specific behavior:

[1169] The feedback such as "it should be lighter and easier to carry" and the emotional data such as "dissatisfied" are stored in a database.

[1170] Step 8: Rate and provide feedback

[1171] The server provides the stored ratings and feedback to other users in real time, who can then refer to it and provide further ideas and feedback.

[1172] input:

[1173] Rating and feedback data stored in a database

[1174] output:

[1175] Ratings and feedback provided to other users

[1176] Specific behavior:

[1177] See other users' real-time feedback on "lighter and more portable" and add or consider your own ideas.

[1178] This will enable real-time analysis of user sentiment as a whole, and the generation and provision of personalized content based on that sentiment. It will also enable the sharing of evaluations and feedback to support collaborative creation among users.

[1179] 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.

[1180] 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.

[1181] 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.

[1182] [Fourth embodiment]

[1183] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1184] 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.

[1185] 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).

[1186] 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.

[1187] 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.

[1188] 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).

[1189] 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.

[1190] 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.

[1191] 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.

[1192] 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.

[1193] 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.

[1194] 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.

[1195] 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."

[1196] The following describes an embodiment of the present invention. This system provides a platform that allows users to collaborate in real time, and is composed of the following main components and their operations.

[1197] User login

[1198] A user accesses the platform from their device and authenticates by entering their username and password into the login screen. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device, allowing the user to begin activities on the system.

[1199] Idea proposal

[1200] After logging in, users can use the interface to input new ideas. The input idea is sent to the server by pressing the submit button. The server receives the idea and stores it in a database. The interface includes a text input field and the ability to select related tags and categories, allowing users to intuitively submit ideas.

[1201] Automatic generation by generative AI

[1202] When the server detects that a new idea has been posted, it sends the idea to the generation AI, which generates various content based on the idea. For example, if a user proposes the idea of ​​an "environmentally friendly water bottle," the generation AI will automatically generate a detailed product description, design proposals, and related program code based on the idea.

[1203] Providing generated results

[1204] The generated content is provided to the user via the server, and the generated results are displayed on the user's device, allowing the user to further develop and modify their ideas.

[1205] Accepting ratings and feedback

[1206] Users can provide feedback on the generated content in the form of ratings (e.g., star ratings or scores) or comments. These feedbacks are entered through the interface means and sent to the server by pressing the send button.

[1207] Save and share ratings and feedback

[1208] The server stores the ratings and feedback received in a database and displays them in real time to other users, who can then provide further feedback or suggest ideas.

[1209] Specific examples

[1210] For example, suppose User A proposes an idea for an "environmentally friendly water bottle," and the generative AI generates a product description and design proposal based on this idea. User A views this and submits an idea adding the additional features of "thin and lightweight." This revised idea is also processed again by the generative AI, and a new generated result is provided. Meanwhile, User B provides feedback on the generated content, saying, "The design is excellent, but I would like it to be more portable." User A then makes further revisions, and the generative AI generates new content that takes user feedback into account.

[1211] In this way, this system enables real-time collaborative creation between users and efficiently generates high-quality content.

[1212] The processing flow will be explained below.

[1213] Step 1:

[1214] The user accesses the login screen from their device and enters their username and password.

[1215] Step 2:

[1216] The server receives the username and password, checks them against the credentials stored in a database, and if authentication is successful, generates a session ID and sends it back to the user's device.

[1217] Step 3:

[1218] After logging in, the user inputs a new idea using the interface means, and then presses the send button when input is complete.

[1219] Step 4:

[1220] The server receives ideas submitted by users, stores them in a database, and detects when new ideas are posted.

[1221] Step 5:

[1222] The server activates a trigger that sends the stored ideas to the generative AI, which then generates content such as text, designs, and programs based on the ideas.

[1223] Step 6:

[1224] The generation AI sends the generated content back to the server, which prepares it for delivery to the user's device.

[1225] Step 7:

[1226] The server provides the generated content to the user's device, and the user can check the generated results on their own device.

[1227] Step 8:

[1228] The user can rate and provide feedback on the provided content, which is input through an interface means.

[1229] Step 9:

[1230] Users submit their ratings and feedback to the server by pressing the submit button, which receives them and stores them in a database.

[1231] Step 10:

[1232] The server displays the stored ratings and feedback to other users in real time, allowing other users to view the ratings and feedback and provide further ideas or suggestions for revision.

[1233] By repeating this cycle, we can continue to produce high-quality content together.

[1234] Example 1

[1235] 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."

[1236] In today's highly information-driven society, there is a growing need for platforms that allow users to collaborate in real time and efficiently generate high-quality content. However, conventional systems often do not allow users to collaborate in real time, and feedback on generated content is often delayed. Furthermore, user authentication and session management are insufficient, creating security issues. Furthermore, the entire process, from proposing ideas to providing generated content, evaluation, feedback, and improvement, can sometimes not proceed smoothly.

[1237] 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.

[1238] In this invention, the server includes an interface means for users to input ideas, a means for receiving and saving ideas input through the interface means, a means for automatically generating content based on ideas, a means for providing the generated content to users, a means for accepting user ratings and feedback on the generated content, a means for saving the ratings and feedback and providing them to other users, a means for authenticating users using authentication information and generating a session ID, and a means for displaying other users' ratings and feedback in real time. This enables real-time collaboration between users and enables the efficient generation and improvement of high-quality content.

[1239] "Interface means" refers to the input screen or input field where users can input their ideas, and also includes the function of selecting tags and categories.

[1240] "Server means" refers to a server device having the function of receiving ideas from users and storing them in a database.

[1241] "Generation means" refers to AI models or software that automatically generate content based on ideas stored on a server.

[1242] "Providing means" refers to the function of transmitting the generated content to the user and displaying it on the user's terminal.

[1243] "Means for accepting ratings and feedback" refers to input functions and communication means for accepting ratings and comments on generated content from users.

[1244] "Rating and feedback storage means" refers to the functionality to store received ratings and feedback in a database and share them with other users.

[1245] "Authentication means" refers to a server device that has the function of verifying a user's authentication information and generating a session ID.

[1246] "Real-time display means" refers to a system that has the ability to instantly display other users' ratings and feedback.

[1247] The following describes an embodiment of the present invention. This system provides a platform that allows users to collaborate in real time, and is composed of the following main components and their operations.

[1248] User login

[1249] A user accesses the platform using their device and authenticates by entering their username and password into the login screen. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device, allowing the user to begin their activities on the system.

[1250] Idea proposal

[1251] After logging in, users can use the interface to input new ideas. The input idea is sent to the server by pressing the submit button. The server receives the idea and stores it in a database. The interface includes a text input field and the ability to select related tags and categories, allowing users to intuitively submit ideas.

[1252] Automatic generation by generative AI

[1253] When the server detects that a new idea has been posted, it sends the idea to a generative AI model, which generates various content based on the idea. For example, if a user proposes the idea of ​​an "environmentally friendly water bottle," the generative AI model will automatically generate a detailed product description, design proposals, and related program code based on the idea.

[1254] Providing generated results

[1255] The generated content is provided to the user via the server, and the generated results are displayed on the user's device, allowing the user to further develop and modify their ideas.

[1256] Accepting ratings and feedback

[1257] Users can provide feedback in the form of ratings and comments on the generated content. These feedbacks are input through the interface means and sent to the server by pressing the send button.

[1258] Save and share ratings and feedback

[1259] The server stores the ratings and feedback received in a database and displays them in real time to other users, who can then provide further feedback or suggest ideas.

[1260] Specific examples

[1261] For example, suppose User A proposes an idea for an "environmentally friendly water bottle," and the generative AI generates a product description and design proposal based on this idea. User A views this and submits an idea adding the additional features of "thin and lightweight." This revised idea is also processed again by the generative AI, and a new generated result is provided. Meanwhile, User B provides feedback on the generated content, saying, "The design is excellent, but I would like it to be more portable." User A then makes further revisions, and the generative AI generates new content that takes user feedback into account.

[1262] Prompt Sentence Examples

[1263] Use the following prompt for your generative AI model:

[1264] "A user has submitted an idea for an 'eco-friendly water bottle.' Based on this idea, please generate a detailed product description, design ideas, and related program code."

[1265] In this way, the system enables real-time collaborative creation between users and efficiently generates high-quality content.

[1266] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1267] Step 1: User Login

[1268] Input: The user accesses the platform's login screen from their device and enters their username and password.

[1269] Server behavior:

[1270] The server receives the authentication information entered by the user.

[1271] A database is queried to match the entered credentials with stored credentials.

[1272] If authentication is successful, a session ID is generated and returned to the user's device.

[1273] Output: A session ID is returned to the user's terminal and the user can begin their activities on the system.

[1274] Step 2: Pitch your idea

[1275] Input: After logging in, the user uses the interface means to input a new idea.

[1276] User Action:

[1277] The interface includes a text entry field and the ability to select relevant tags and categories.

[1278] The user presses the submit button to send the entered idea to the server.

[1279] Server behavior:

[1280] The server receives the submitted ideas.

[1281] Store your ideas in a database.

[1282] Output: New ideas stored in the database.

[1283] Step 3: Automatic generation by generative AI

[1284] Input: A new idea stored in the database

[1285] Server behavior:

[1286] The server detects when a new idea is saved to the database.

[1287] Send the idea to a generative AI model, which is the means of generation.

[1288] Generative AI model in action:

[1289] The generative AI model analyzes the received ideas.

[1290] Based on the idea, various content (e.g., product descriptions, design proposals, related program code) is generated.

[1291] Output: The content generated by a generative AI model.

[1292] Step 4: Providing the generated results

[1293] Input: Content generated by a generative AI model

[1294] Server behavior:

[1295] The generated content is sent to the user's device.

[1296] User Action:

[1297] The generated results are displayed on the user's device.

[1298] Output: The generated results displayed on the user's terminal.

[1299] Step 5: Rating and receiving feedback

[1300] Input: User ratings and comments on generated content

[1301] User Action:

[1302] Users can provide ratings and feedback on generated content.

[1303] The entered rating and feedback are sent to the server using the submit button.

[1304] Server behavior:

[1305] The server stores the received ratings and feedback in a database.

[1306] Output: Ratings and feedback stored in a database.

[1307] Step 6: Save and share your ratings and feedback

[1308] Input: Ratings and feedback stored in the database

[1309] Server behavior:

[1310] The server displays the received ratings and feedback in real time on other users' devices.

[1311] User Action:

[1312] Other users can view this and provide further feedback or suggest ideas.

[1313] Output: Ratings and feedback displayed on other users' devices.

[1314] (Application example 1)

[1315] 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."

[1316] Modern brick-and-mortar stores require efficient improvements and optimization of store layout and design. However, traditional methods require a lot of time and effort, and communication between multiple stakeholders is often difficult. Furthermore, there is a lack of means to quickly put proposed ideas into concrete form.

[1317] 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.

[1318] In this invention, the server includes an interface means for users to input ideas, a server means for receiving and saving the input ideas, a generation means for automatically generating content based on ideas, a means for providing the generated content to users, a means for receiving user ratings and feedback on the generated content, a means for saving the ratings and feedback and providing them to other users, a means for proposing ideas for store layout and design and for improving them collaboratively with multiple users, and a means for reflecting feedback in real time and presenting an optimal store design. This enables rapid communication between parties involved and enables efficient improvement and optimization of store layout and design.

[1319] The "interface means" is an input means for the user to input ideas.

[1320] "Server means" refers to storage means for receiving and storing ideas input through interface means.

[1321] The "creation means" is a generation means for automatically generating content based on ideas stored in the server means.

[1322] The "providing means" is a providing means for providing the content generated by the generating means to the user.

[1323] The "rating and feedback receiving means" is a receiving means for receiving user ratings and feedback on the generated content.

[1324] "Ratings and feedback storage means" refers to a storage means for storing received ratings and feedback and providing them to other users.

[1325] "Collaborative improvement methods" are methods for proposing and improving ideas for store layout and design jointly with multiple users.

[1326] The "real-time feedback reflection means" is a means for reflecting real-time feedback from users and presenting optimal store designs.

[1327] To implement this invention, a system including the following means is required. The operation of each means and the flow of the entire system will be described below.

[1328] The server is built using the programming language Python and the framework Flask, and uses SQLAlchemy for database management. OpenAI's API is used as the generative AI model. The system proposes and improves ideas for the layout and design of physical stores through the user interface, server-side processing, and generative AI.

[1329] Users access the system by operating a smartphone or smart glasses. First, the user logs in through an interface and inputs their idea. The input idea is sent to the server, which stores it in a database. The server then sends the stored idea to a generation AI, which then automatically generates specific content based on the idea. The content may include text, design, and code.

[1330] The generated content is provided to the user via the server, and the user can further develop their ideas based on it. For example, when a user proposes an idea for the placement of a new product, they can send the following prompt to the generation AI:

[1331] Store layout idea: Place new products in front of the register and run a campaign to motivate customers to buy.

[1332] Based on this prompt, the AI ​​generates detailed placement plans and specific campaign content. The results are presented to the user in the following format:

[1333] By placing new products in front of the cash register, customers are more likely to buy them. In addition, tasting events are held on weekends to allow customers to experience the products firsthand, which promotes sales.

[1334] Based on the generated results, users can revise and improve their ideas in collaboration with other users and store staff. Real-time feedback is sent to the server as needed, and the server uses this feedback to generate new content. Ratings and feedback are stored in a database, where other users can view and rate them.

[1335] This enables rapid communication between stakeholders, allowing for efficient improvement and optimization of store layout and design.Specific examples of how this system can be used include proposing new product placement, layout changes, and new interior designs in stores.

[1336] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1337] Step 1:

[1338] The user uses the interface means to enter a username and password on the login screen. This sends the login information to the server. The server compares the received login information with the authentication information in the database, and if authentication is successful, generates a session ID and returns it to the user's terminal. By receiving the session ID, the user is granted access to the system and can perform the next operation.

[1339] Step 2:

[1340] The user inputs an idea through an interface means. The idea input section provides fields for selecting tags and categories related to the specific idea content. When the user presses the "Submit" button, the idea information is transferred to the server. The server receives this information and stores it in a database. The input data is stored in text format.

[1341] Step 3:

[1342] When the server detects that a new idea has been saved to the database, it sends the idea information to the generative AI model. The generative AI model automatically generates related content based on the prompt text. Specifically, it generates detailed descriptions, designs, or code based on the idea proposed by the user. The content output from the generative AI model is returned to the server and saved back into the database. An example of a prompt text that could be entered is, "Store layout idea: Place new products in front of the register and run a campaign to increase purchasing motivation."

[1343] Step 4:

[1344] The server sends the generated content to the user's device. The user can view the generated content through an interface and further develop their ideas. This allows the user to visually confirm the specific design proposals and campaign details generated by the generative AI.

[1345] Step 5:

[1346] Users rate and provide feedback on the generated content. Ratings are entered in the form of stars or scores, and feedback is entered in the form of comments. When the user presses the "Submit" button, the rating and feedback information is sent to the server, which receives it and stores it in a database.

[1347] Step 6:

[1348] The evaluations and feedback received are displayed to other users in real time via the server. Other users can view these and provide new feedback or suggest ideas. Users can also refer to other users' feedback to revise and improve their ideas.

[1349] Step 7:

[1350] Improved ideas and feedback are then passed back to the generative AI model to generate new content. This process is repeated, and through collaboration between users, the optimal store design and layout is derived. The new content generated is then provided to users again, allowing for continuous improvement.

[1351] 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.

[1352] As an embodiment of the present invention, the details of a collaborative creation platform combined with an emotion engine are described below. This system realizes the creation of higher quality content by combining real-time collaborative creation between users with emotion recognition functionality.

[1353] User login

[1354] The user accesses the login screen from their device and enters their username and password to authenticate. The server receives this and compares it with the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device. This allows the user to begin activities on the system.

[1355] Idea suggestion and emotion recognition

[1356] After logging in, a user can input a new idea using the interface means. This input is analyzed by the emotion engine to recognize the user's emotional state (e.g., happy, excited, worried, etc.). The recognized emotion data is sent to the server along with the idea.

[1357] Automatic generation by generative AI

[1358] The server receives the idea and emotion data submitted by the user and sends it to the generation AI, which generates appropriate content based on the received idea and emotion data. For example, if a user submits an idea for an "environmentally friendly water bottle" along with a happy emotion, the generation AI will generate a colorful, well-designed product description and design proposal that reflects this emotion.

[1359] Providing generated results

[1360] The generated content is provided to the user via a server. The generated results are displayed on the user's device, allowing the user to further develop or modify their ideas. Emotional data is also displayed, allowing the user to see how their own emotions are reflected in the content.

[1361] Accepting ratings and feedback and recognizing emotions

[1362] Users can rate and provide feedback on the generated content. The emotion engine recognizes the emotions contained in the user's feedback. For example, if a user gives feedback expressing dissatisfaction, that emotion will also be sent.

[1363] Save and share ratings and feedback

[1364] The server stores the ratings and feedback received from users in a database and displays them to other users in real time. Other users can also refer to these ratings and feedback and provide further ideas or suggestions for revisions. In particular, emotional data is displayed together, so users can understand the emotions behind the feedback.

[1365] Specific examples

[1366] For example, suppose user A proposes the idea of ​​an "environmentally friendly water bottle" with a happy emotion, and the generation AI generates a colorful and well-designed product description and design proposal based on this idea. User A reviews this and suggests a revision, saying "it should be lighter and easier to carry," along with a dissatisfied emotion. Based on this feedback and emotion, the generation AI regenerates a lighter and more portable design proposal. At the same time, user B provides feedback on the generated design proposal with a satisfied emotion, saying "this design is excellent." This allows user A to understand user B's emotions and consider further improvements.

[1367] In this way, combining an emotion engine with generative AI enables real-time collaboration and emotion recognition between users, enabling the efficient generation of high-quality content.

[1368] The processing flow will be explained below.

[1369] Step 1:

[1370] The user accesses the login screen on their device and enters their username and password. The server receives this and checks it against the authentication information stored in the database. If authentication is successful, the server generates a session ID and sends it back to the user's device.

[1371] Step 2:

[1372] After logging in, the user inputs a new idea using the interface means. The input idea is analyzed by the emotion engine to recognize the user's emotional state. The recognized emotion data is sent to the server along with the idea.

[1373] Step 3:

[1374] The server receives the ideas and emotion data sent by the user, stores them in a database, and sends them to the generation AI.

[1375] Step 4:

[1376] The generative AI generates appropriate content based on the ideas and emotional data it receives. For example, if the idea for an "eco-friendly water bottle" is submitted along with a happy emotion, the generative AI will generate a colorful and well-designed product description and design proposal.

[1377] Step 5:

[1378] The generated content is sent back to the server, which prepares it for delivery to the user's terminal.

[1379] Step 6:

[1380] The server provides the generated content to the user's device, where the user can check the generated results on their own device. Emotion data is also displayed, allowing the user to see how their emotions are reflected.

[1381] Step 7:

[1382] The user evaluates and gives feedback on the provided content. When the user writes the feedback, the emotion engine works again to recognize the emotion data of the feedback.

[1383] Step 8:

[1384] The user submits the evaluation, feedback, and emotional data to the server by pressing the submit button. The server receives the data and stores it in a database.

[1385] Step 9:

[1386] The server displays the received ratings, feedback, and emotional data to other users in real time, allowing other users to view the ratings and feedback and provide further ideas or suggestions for revision.

[1387] Step 10:

[1388] Each time a new idea or revision is submitted, the server requests the AI ​​to process it again and delivers the new generated results, allowing users to collaborate in real time and continue their creative activities based on the generated results.

[1389] Example 2

[1390] 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."

[1391] In conventional collaborative creation platforms, even when users input ideas, their emotions are often not taken into account and are not reflected in the generated content. This makes it difficult to generate high-quality content that reflects the user's emotions. Furthermore, when users evaluate or give feedback on generated content, their emotions cannot be properly captured, which creates an issue that makes the collaborative creation process inefficient.

[1392] 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 an interface means for a user to input ideas, a means for receiving and storing the ideas input through the interface means, a generation means for automatically generating content based on the ideas and emotion data stored in the server means, a means for providing the content generated by the generation means to users in real time, a means for accepting user ratings and feedback on the generated content, an emotion engine means for analyzing emotions included in the ratings and feedback, and a means for storing the ratings and feedback and providing them to other users in real time. This enables the generation of high-quality content that reflects user emotions and the sharing of real-time feedback.

[1393] "Interface means" refers to the input means used by users to enter ideas, ratings, and feedback into the system.

[1394] "Server means" is a general term for hardware and software that stores and processes data received from users and provides linkage functions with other means.

[1395] The "generation means" refers to an algorithm or program for automatically generating appropriate content based on the ideas and emotional data stored in the server means.

[1396] "Real-time delivery means" refers to communication means and software functions that allow generated content and feedback information to be delivered to users in real time.

[1397] The "means for receiving ratings and feedback" refers to an interface and processing means for receiving input of ratings and feedback given by users on generated content.

[1398] "Emotion engine means" refers to an algorithm or program for analyzing emotions from user input and feedback.

[1399] "Means for providing to other users in real time" refers to communication means and software functions for instantly providing to other users the ratings and feedback entered by the user, as well as the associated emotional data.

[1400] "Content" refers to information expressions such as text, design, and program code.

[1401] The present invention relates to a collaborative creation platform that combines an emotion engine and generative AI. A specific embodiment of this system is described below in detail.

[1402] The system is realized using user devices, a server, and software components such as an emotion engine and a generative AI model.

[1403] User login

[1404] A user accesses the login screen from their own device (for example, a PC or smartphone) and enters their username and password for authentication. At this time, the device accesses the login URL via a browser. The server compares the input information with the authentication information stored in the database, and if authentication is successful, generates a session ID and returns it to the user's device. This allows the user to begin activities on the system.

[1405] Idea suggestion and emotion recognition

[1406] After logging in, users input new ideas using the device interface. The server sends the input to an emotion engine (e.g., a natural language processing algorithm) to analyze the user's emotional state. The analyzed emotion data is stored on the server along with the idea.

[1407] Automatic generation by generative AI

[1408] The server sends the idea and emotion data submitted by the user to a generative AI. The generative AI (e.g., a natural language generation model such as GPT-3) generates appropriate content based on this data. For example, if a user submits an idea for an "environmentally friendly water bottle" along with a fun emotion, the generative AI will generate a colorful and well-designed product description and design proposal.

[1409] Providing generated results

[1410] The generated content is provided to the user via a server. The generated results are displayed on the user's device, allowing the user to further develop or modify the idea. Emotion data is also displayed, allowing the user to see how their own emotions are reflected in the content.

[1411] Accepting ratings and feedback and recognizing emotions

[1412] Users can rate and provide feedback on the generated content. The server then sends the user's feedback to the emotion engine and recognizes the emotions contained in the feedback. For example, if a user suggests a revision such as "make it lighter and easier to carry" along with a dissatisfied emotion, the emotion is also sent.

[1413] Save and share ratings and feedback

[1414] The server stores the ratings and feedback received from users in a database and displays them to other users in real time. Other users can refer to these ratings and feedback and provide further ideas or suggestions for revisions. In particular, emotional data is displayed together, so users can understand the emotions behind the feedback.

[1415] Specific examples

[1416] For example, suppose User A proposes the idea of ​​an "environmentally friendly water bottle" with a happy emotion, and the generation AI generates a colorful and well-designed product description and design proposal. User A reviews this and suggests a revision, saying, "It should be lighter and easier to carry," along with a feeling of dissatisfaction. Based on this feedback and emotion, the generation AI regenerates a lighter and more portable design proposal. At the same time, User B provides feedback on the generated design proposal with a feeling of satisfaction, saying, "This design is excellent." This allows User A to understand User B's emotions and consider further improvements.

[1417] Examples of prompt statements

[1418] Here are some example prompts to enter into the generative AI model:

[1419] User: I came up with the idea for an eco-friendly water bottle and it's fun.

[1420] Prompt: Generate a colorful and well-designed product description and design proposal based on this idea.

[1421]

[1422] User: I'm happy with the generated design and I don't see any need for further improvement.

[1423] Prompt: Use this feedback to give your final approval to the generated design proposal.

[1424]

[1425] User: After looking at the generated design, I feel dissatisfied and want something lighter and more portable.

[1426] Prompt: Use this feedback and sentiment to generate a lighter, more portable design.

[1427] The above is a detailed description of the embodiment of the present invention.

[1428] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1429] Step 1: User logs in via the login screen

[1430] The user accesses the login screen from their device and enters their username and password. The device sends this information to the server. Input data: username and password. Output data: HTTP request to the server.

[1431] Step 2: Server authenticates

[1432] The server receives the user's input information and compares it with the authentication information in the database, thereby verifying the user's authenticity. Input data: User name and password. Output data: Authentication result (success / failure).

[1433] Step 3: Generate a session ID upon successful authentication

[1434] If authentication is successful, the server generates a session ID and returns it to the user's device. Input data: Authentication success signal. Output data: Session ID. Specifically, a unique session ID is generated using a session management library and returned in the HTTP response.

[1435] Step 4: User submits idea

[1436] After logging in, the user uses the interface to enter a new idea. This idea is sent from the device to the server. Input data: idea. Output data: HTTP request to the server. Specific actions include entering an idea in the text box and clicking the submit button.

[1437] Step 5: The server sends the idea to the emotion engine

[1438] The server sends the received idea to the emotion engine, which uses a natural language processing algorithm to analyze the emotional state of the idea. Input data: idea. Output data: emotion data. Specifically, it sends a POST request to the emotion engine's API and receives the emotion analysis results.

[1439] Step 6: The server stores the emotion data

[1440] The server stores the analyzed emotion data together with the idea in a database. Input data: Idea and emotion data. Output data: INSERT query to the database. Specific operations include executing the database query and saving the data.

[1441] Step 7: The server sends the idea and emotion data to the generative AI.

[1442] The server sends the saved ideas and emotion data to the generation AI. Input data: Ideas and emotion data. Output data: API request to the generation AI. Specifically, it sends a request to the generation AI's API to request the generation of appropriate content.

[1443] Step 8: Generative AI generates content

[1444] The generative AI generates content based on the ideas and emotional data it receives. Input data: Ideas and emotional data. Output data: Generated content. Specifically, it analyzes and generates content using an internal algorithm, and returns the results.

[1445] Step 9: The server sends the results back to the user

[1446] The generated content is provided to the user through the server. Input data: Generated content. Output data: HTTP response to the user. The specific operation is to return the generated content as an HTTP response.

[1447] Step 10: User checks the generated results

[1448] The generated results are displayed on the user's device and the user confirms them. Input data: Generated content. Output data: Displayed on the user's screen. Specific actions include visually checking and confirming the content displayed on the web page.

[1449] Step 11: User Provides Feedback

[1450] Users rate and provide feedback on the generated content. This feedback is sent from the device to the server. Input data: Feedback. Output data: HTTP request to the server. Specific operations involve entering feedback in the rating input form and clicking the submit button.

[1451] Step 12: The server sends feedback to the emotion engine

[1452] The server sends the user's feedback to the emotion engine for emotion analysis. Input data: feedback. Output data: emotion data. Specifically, the server sends the feedback text to the emotion engine and receives the analysis results.

[1453] Step 13: Server stores feedback

[1454] The server stores the user's feedback and emotion data in a database. Input data: Feedback and emotion data. Output data: INSERT query to the database. Specific operations include executing a database query and saving the feedback and emotion data.

[1455] Step 14: The server shares the feedback with other users

[1456] The server provides feedback and emotional data to other users in real time. Input data: Feedback and emotional data. Output data: Data sent to other users. Specific operations include displaying the feedback and emotional data on other users' screens using real-time technologies such as WebSocket.

[1457] (Application example 2)

[1458] 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."

[1459] While conventional content generation systems can automatically generate content that reflects a user's ideas, they lack the ability to analyze a user's emotions in real time and provide personalized content based on those emotions. This makes it difficult to provide content that appropriately reflects the user's emotional state, limiting the quality of the user experience. The present invention aims to solve these problems by providing a system that can analyze a user's emotions in real time and provide personalized content based on those emotions.

[1460] The specification processing by the specification 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 interface means for a user to input ideas, means for receiving and storing ideas input through the interface means, generation means for automatically generating content based on the ideas stored in the server means, emotion analysis means for analyzing user emotions in real time using emotion recognition and acquiring emotion data, means for providing the content generated by the generation means to the user, means for accepting user ratings and feedback on the generated content, and means for storing the ratings and feedback and providing them to other users. This makes it possible to analyze user emotions in real time and provide personalized content based on those emotions.

[1461] "Interface means" refers to the input devices and software that allow users to access the system and input ideas.

[1462] "Server Means" refers to a computer server and its programs for receiving, storing, processing and managing data entered by users.

[1463] "Generation means" refers to the generation AI and its program for automatically generating content based on ideas stored on the server.

[1464] "Emotion analysis means" refers to an emotion recognition engine and its program for recognizing and analyzing a user's emotions in real time.

[1465] "Providing means" refers to technology and programs for displaying or transmitting content generated by generating means to a user's device.

[1466] "Rating and Feedback Measures" refers to the technology and programs used to accept and analyze ratings and opinions on content from users.

[1467] "Storage and provision means" refers to the technology and programs for storing ratings and feedback on a server and displaying and providing them to other users.

[1468] "Content" refers to an information production that includes at least one of text, design, video, or audio.

[1469] "Emotion data" refers to data that indicates the emotional state of the user analyzed by the emotion analysis means.

[1470] Basic system configuration

[1471] As an embodiment of the present invention, a system is configured that includes the following main components.

[1472] 1. User Device

[1473] Provide an interface for users to input ideas, such as a keyboard, mouse, touchscreen, or voice input device.

[1474] 2. Server

[1475] Servers receive and store data from users, and specifically include databases and storage systems.

[1476] The server has a generation means for generating content based on ideas sent by users. A generative AI model (e.g., GPT-4) is used as the generation means.

[1477] The server includes an emotion analysis system that analyzes user emotions in real time, specifically using an emotion recognition engine (e.g., Face API, Emotion API).

[1478] 3. Means of provision

[1479] This includes technology and programs for transmitting the generated content to a user terminal and displaying it.

[1480] 4. Evaluation and feedback measures

[1481] The system also includes a system for users to input and accept ratings and feedback on the generated content, using an interface means that operates on the user terminal.

[1482] 5. Storage and provision means

[1483] The server includes technology and programs for storing the received feedback in a database and providing it to other users in real time.

[1484] Program processing description

[1485] The system operates as follows.

[1486] 1. Enter and save your ideas

[1487] The user inputs ideas through an interface means from the user terminal, and the input ideas are sent to the server and stored in the database.

[1488] 2. Emotion Recognition Using Emotion Analysis Methods

[1489] When a user inputs an idea through the interface means, the emotion analysis means analyzes the user's emotion in real time and acquires the emotion data, which is also transmitted to the server together with the idea.

[1490] 3. Content generation using generative AI models

[1491] The server automatically generates appropriate content based on the stored ideas and emotion data using a generative AI model, GPT-4.

[1492] 4. Provision of Content

[1493] The content generated by the generating means is transmitted to the user terminal through the providing means, and the user confirms the content.

[1494] 5. Accepting Ratings and Feedback

[1495] Users can rate and provide feedback on the generated content, which is also sent to the server and stored in the database.

[1496] 6. Storage and provision

[1497] The received feedback is provided to other users in real time, allowing them to see the feedback and share improvements.

[1498] Specific examples

[1499] For example, suppose a user is wearing a head-mounted display and watching a movie. If the emotion analysis means analyzes the user's facial expression and recognizes the emotion "sad," the generated emotion data is sent to a generative AI model (e.g., GPT-4). Based on this emotion data, the generative AI model generates or recommends new appropriate content, such as an inspiring movie or soothing content. An example of a specific prompt sentence is, "The user is feeling sad. Recommend a comforting and emotionally uplifting movie."

[1500] In this way, this system is able to analyze users' emotions in real time and automatically generate and provide personalized content based on those emotions.

[1501] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1502] Step 1: User input

[1503] The user inputs ideas through an interface means using a user terminal (e.g., a head-mounted display). The input here includes text input, voice input, etc. The input ideas are transmitted as data to the server.

[1504] input:

[1505] User-supplied ideas (text, voice, etc.)

[1506] output:

[1507] Idea events sent to the server

[1508] Specific behavior:

[1509] A user enters the idea "eco-friendly water bottle" into the text box and presses the submit button.

[1510] Step 2: Save your idea

[1511] The server receives the ideas sent from the user's device and stores them in a database, along with additional information such as the date and time of entry and the user ID.

[1512] input:

[1513] Idea data received by the server

[1514] output:

[1515] Idea entries stored in a database

[1516] Specific behavior:

[1517] The idea of ​​an "eco-friendly water bottle" is sent to the server and stored in a database.

[1518] Step 3: Real-time sentiment analysis

[1519] When a user inputs an idea, the emotion analysis means analyzes the user's facial expression and obtains emotion data, which is then sent to the server together with the idea.

[1520] input:

[1521] Real-time facial expression data of users

[1522] output:

[1523] Emotion data sent to the server

[1524] Specific behavior:

[1525] While the user is entering their idea for an "environmentally friendly water bottle," the camera analyzes the user's facial expression and obtains emotional data such as "fun."

[1526] Step 4: Content generation using generative AI models

[1527] The server takes the idea and its sentiment data and sends prompts to a generative AI model (e.g., GPT-4) to generate content, which is then properly formatted and ready to be served to the user.

[1528] input:

[1529] Stored ideas and sentiment data

[1530] output:

[1531] Content generated by generative AI models

[1532] Specific behavior:

[1533] The server sends the idea of ​​an "environmentally friendly water bottle" and the emotion data of "fun" to the generative AI model, and uses a prompt to generate a colorful and well-designed product description. The example prompt is "The user proposed an idea for an environmentally friendly water bottle and is feeling happy. Generate a colorful and creative product description."

[1534] Step 5: Providing generated content

[1535] The generated content is sent from the server to the user's device and provided to the user, who then checks the generated content on the device.

[1536] input:

[1537] Generated content data

[1538] output:

[1539] Content displayed on the user's device

[1540] Specific behavior:

[1541] The generated product description is displayed on the user's head-mounted display.

[1542] Step 6: Provide your rating and feedback

[1543] The user inputs ratings and feedback for the generated content, and the ratings and feedback input using the interface means are transmitted to the server.

[1544] input:

[1545] User Ratings and Feedback Data

[1546] output:

[1547] Rating and feedback events sent to the server

[1548] Specific behavior:

[1549] The user reviews the generated product description, enters feedback such as "lighter and more portable," and presses the submit button.

[1550] Step 7: Save your ratings and feedback

[1551] The server stores the ratings and feedback received from users in a database, which also includes emotional data.

[1552] input:

[1553] Rating and feedback data received by the server

[1554] output:

[1555] Rating and feedback entries stored in a database

[1556] Specific behavior:

[1557] The feedback such as "it should be lighter and easier to carry" and the emotional data such as "dissatisfied" are stored in a database.

[1558] Step 8: Rate and provide feedback

[1559] The server provides the stored ratings and feedback to other users in real time, who can then refer to it and provide further ideas and feedback.

[1560] input:

[1561] Rating and feedback data stored in a database

[1562] output:

[1563] Ratings and feedback provided to other users

[1564] Specific behavior:

[1565] See other users' real-time feedback on "lighter and more portable" and add or consider your own ideas.

[1566] This will enable real-time analysis of user sentiment as a whole, and the generation and provision of personalized content based on that sentiment. It will also enable the sharing of evaluations and feedback to support collaborative creation among users.

[1567] 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.

[1568] 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.

[1569] 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.

[1570] 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.

[1571] 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.

[1572] 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.

[1573] 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).

[1574] 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.

[1575] 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."

[1576] 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.

[1577] 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).

[1578] 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.

[1579] 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.

[1580] 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.

[1581] 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.

[1582] 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.

[1583] 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.

[1584] 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.

[1585] 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.

[1586] 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.

[1587] 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.

[1588] The following is further disclosed regarding the above embodiment.

[1589] (Claim 1)

[1590] an interface means for a user to input ideas;

[1591] a server means for receiving and storing ideas input through the interface means;

[1592] a generating means for automatically generating content based on the ideas stored in the server means;

[1593] means for providing the content generated by the generating means to a user;

[1594] means for accepting user ratings and feedback on the generated content;

[1595] means for storing and providing said ratings and feedback to other users;

[1596] A system including:

[1597] (Claim 2)

[1598] 10. The system of claim 1, wherein the content includes at least one of text, design, or code.

[1599] (Claim 3)

[1600] 2. The system according to claim 1, wherein multiple users simultaneously propose ideas in real time, share, correct and improve the content generated by said generating means.

[1601] "Example 1"

[1602] (Claim 1)

[1603] an interface means for a user to input ideas;

[1604] a server means for receiving and storing ideas input through the interface means;

[1605] a generating means for automatically generating content based on the ideas stored in the server means;

[1606] means for providing the content generated by the generating means to a user;

[1607] means for accepting user ratings and feedback on the generated content;

[1608] means for storing and providing said ratings and feedback to other users;

[1609] a means for authenticating a user using the authentication information and generating a session ID;

[1610] A way to view other users' ratings and feedback in real time, and

[1611] A system including:

[1612] (Claim 2)

[1613] 10. The system of claim 1, wherein the content includes at least one of text, design, or code.

[1614] (Claim 3)

[1615] 2. The system according to claim 1, wherein multiple users simultaneously propose ideas in real time, share, correct and improve the content generated by said generating means.

[1616] "Application Example 1"

[1617] (Claim 1)

[1618] an interface means for a user to input ideas;

[1619] a server means for receiving and storing ideas input through the interface means;

[1620] a generating means for automatically generating content based on the ideas stored in the server means;

[1621] means for providing the content generated by the generating means to a user;

[1622] means for accepting user ratings and feedback on the generated content;

[1623] means for storing and providing said ratings and feedback to other users;

[1624] A way to propose ideas for store layout and design and collaborate with multiple users to improve them.

[1625] A means to reflect real-time feedback and present optimal store designs,

[1626] A system including:

[1627] (Claim 2)

[1628] 10. The system of claim 1, wherein the content includes at least one of text, design, or code.

[1629] (Claim 3)

[1630] 2. The system according to claim 1, wherein multiple users simultaneously propose ideas in real time, share, correct and improve the content generated by said generating means.

[1631] "Example 2: Combining Emotion Engines"

[1632] (Claim 1)

[1633] an interface means for a user to input ideas;

[1634] a server means for receiving and storing ideas input through the interface means;

[1635] a generating means for automatically generating content based on the ideas and emotion data stored in the server means;

[1636] means for providing the content generated by the generating means to a user in real time;

[1637] means for accepting user ratings and feedback on the generated content;

[1638] emotion engine means for analyzing emotions contained in the evaluation and feedback;

[1639] means for storing and providing said ratings and feedback to other users in real time;

[1640] A system including:

[1641] (Claim 2)

[1642] 10. The system of claim 1, wherein the content includes at least one of text, design, or code.

[1643] (Claim 3)

[1644] The system according to claim 1, wherein a plurality of users simultaneously propose ideas in real time, share the content generated by said generation means and the emotional information generated by said emotion engine means, and correct and improve the content.

[1645] "Application example 2 when combining emotion engines"

[1646] (Claim 1)

[1647] an interface means for a user to input ideas;

[1648] a server means for receiving and storing ideas input through the interface means;

[1649] a generating means for automatically generating content based on the ideas stored in the server means;

[1650] An emotion analysis means for analyzing a user's emotions in real time by emotion recognition and acquiring the emotion data;

[1651] means for providing the content generated by the generating means to a user;

[1652] means for accepting user ratings and feedback on the generated content;

[1653] means for storing and providing said ratings and feedback to other users;

[1654] A system including:

[1655] (Claim 2)

[1656] 10. The system of claim 1, wherein the content includes at least one of text, design, video, or audio.

[1657] (Claim 3)

[1658] 2. The system according to claim 1, wherein multiple users simultaneously propose ideas in real time, share, correct and improve the content generated by said generating means.

[1659] (Claim 4)

[1660] 2. The system according to claim 1, wherein the emotion analysis means generates personalized content based on the user's emotion data. [Explanation of symbols]

[1661] 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. an interface means for a user to input ideas; a server means for receiving and storing ideas input through the interface means; a generating means for automatically generating content based on the ideas stored in the server means; means for providing the content generated by the generating means to a user; means for accepting user ratings and feedback on the generated content; means for storing and providing said ratings and feedback to other users; A system including:

2. 10. The system of claim 1, wherein the content includes at least one of text, design, or code.

3. 2. The system according to claim 1, wherein a plurality of users simultaneously propose ideas in real time, share, correct and improve the content generated by said generating means.

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