System

Abstract

A system is provided.SOLUTION: This system includes a means for allowing a user to register his or her favorite pattern or character, a means for storing the registered favorite pattern or character, a means for automatically generating a stamp on the basis of conversation contents, a means for presenting the generated stamp to the user, and a means for allowing the user to select the presented stamp.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] Stickers and emojis are widely used in modern communication tools, but there is a problem in that it is difficult to provide a wide range of options because there are only a limited number of stickers with specific characters or designs that suit users' preferences. It is also time-consuming and expensive for illustrators to provide new stickers. There is a need to solve these problems and provide an environment where users can use a wider variety of stickers. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system that includes a means for a user to register their favorite pictures and characters, a means for saving the registered pictures and characters, a means for automatically generating stamps based on the content of a conversation, a means for presenting the generated stamps to the user, and a means for the user to select from the presented stamps. Furthermore, by including a means for training an AI model that generates stamps based on the favorite pictures and characters registered by the user, and a means for using existing illustrations provided by illustrators as learning data, a system that can automatically generate a wide range of stamp options and meet user needs is realized.

[0006] "User" refers to an individual or group that uses the system to register their favorite designs or characters and use the generated stamps.

[0007] "Pictures and characters" refers to images or illustrations displayed as stamps, such as specific designs or characters that users prefer.

[0008] "Means for registration" refers to a function that provides a process or interface for users to input and save their preferred images or characters into the system.

[0009] "Means of storage" refers to the functions and methods for storing registered image and character information in a database or memory.

[0010] "Means for automatically generating stickers based on conversation content" refers to AI models and algorithms that analyze user interactions and sent messages and generate appropriate stickers.

[0011] The "means for presenting generated stamps to the user" refers to a method or interface for visually displaying generated stamp candidates to the user.

[0012] "Means of selection" refers to the method or interface that allows a user to select and use the desired stamp from the stamps presented.

[0013] "Means for training an AI model" refers to the processes and techniques used to train an AI model using existing data so that it can generate stickers based on user preferences and interactions.

[0014] "Training data" refers to existing illustrations and related information provided by illustrators that are used to train the AI ​​model. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] To implement the system of the present invention, three main entities work together: the server, the terminal, and the user. This system allows users to register their favorite pictures and characters, and then uses that information to automatically generate stamps based on the content of the conversation, providing appropriate stamps to the user.

[0037] Server Processing

[0038] 1. Storing your information and preferences

[0039] The server receives the information about the preferred designs and characters sent by the user and stores it in a database, allowing the system to accumulate the user's registered preferences.

[0040] 2. Training the AI ​​model

[0041] The server receives existing illustration data provided by the illustrator and uses it as learning data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stamps based on the user's conversation content.

[0042] 3. Stamp generation and presentation

[0043] When a user's message is received, the server analyzes the content, selects appropriate images and characters, and generates stamps. The generated stamp candidates are sent to the user's device and displayed.

[0044] Terminal handling

[0045] 1. Providing a user interface

[0046] The device provides an interface for users to register their favorite pictures and characters, as well as an interface for displaying stamps according to the flow of conversation.

[0047] 2. Data transmission and reception

[0048] The device sends the user's registration information and interaction log to the server, which conveys the user's interaction context to the server. The device receives the stamp list sent from the server and displays it to the user.

[0049] 3. Selecting and Using Stamps

[0050] The system provides an interface for users to select the desired stamp from the provided stamps and insert it into the conversation. The selected stamp is then sent from the device to the conversation partner.

[0051] User Actions

[0052] 1. Register your preferences

[0053] Users can specify their favorite designs and characters through the app on their device. For example, if a user likes a "smiling cat," they enter this information into the app and send it to the server.

[0054] 2. Starting a dialogue

[0055] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[0056] 3. Check and use stamps

[0057] The user selects an appropriate stamp from the list of stamp candidates sent by the server based on the content of the conversation. For example, a "smiling cat" stamp is suggested for the message "Today was fun." The user selects this stamp, inserts it into the conversation, and sends it.

[0058] Specific examples

[0059] 1. Register your favorite designs and characters

[0060] User A registers "dog characters" as a preference. He enters this information into the device app and sends it to the server.

[0061] 2. Interaction and stamp generation

[0062] When user A sends the message "good night," the server analyzes this message and generates a stamp of a dog saying "good night."

[0063] 3. Check and Use

[0064] User A checks the stamp list sent from the server, selects the "Goodnight Dog" stamp and sends it to the person he or she is talking to.

[0065] This system allows users to freely create stamps that suit their preferences and enjoy rich communication.

[0066] The processing flow will be explained below.

[0067] The process steps for users to register their favorite designs and characters and use stamps during conversations

[0068] Step 1: Users register their favorite designs and characters

[0069] 1. User: Enter your favorite image or character into the device app. For example, "dog character."

[0070] 2. Terminal: Converts the user's input preferences into data packets.

[0071] 3. Terminal: Sends the converted data packets to the server.

[0072] Step 2: The server stores the user information

[0073] 1. Server: Analyzes data packets received from users and extracts their preferred images and character information.

[0074] 2. Server: Stores the extracted information in a database.

[0075] Step 3: Train the AI ​​model

[0076] 1. Illustrator: Upload an existing illustration to the server as learning data.

[0077] 2. Server: Stores the received illustration data in a database and performs preprocessing (size adjustment, noise removal, etc.).

[0078] 3. Server: Trains the AI ​​model using the preprocessed illustration data, properly tags each illustration, and generates stickers for the corresponding user conversations.

[0079] Step 4: User initiates interaction

[0080] 1. User: Sends a message to the person they are interacting with through the app, for example, "I had a great time today."

[0081] 2. Terminal: Converts the user's message into data packets and sends them to the server.

[0082] Step 5: The server generates and presents the stamp

[0083] 1. Server: Analyzes the received message data and understands the conversation content.

[0084] 2. Server: Taking into account the analysis results and the user's preferred designs and character information, the server uses an AI model to generate appropriate stamps.

[0085] 3. Server: Arranges the generated stamp candidates into a list and sends it to the user's device.

[0086] Step 6: Your device will display suggested stickers

[0087] 1. Terminal: The stamp list data received from the server is displayed on the user interface, visually presenting multiple stamps in thumbnail format.

[0088] 2. User: Select the desired stamp from the presented stamp list.

[0089] Step 7: User selects sticker and sends it

[0090] 1. User: Selects the "Smiling Dog" stamp from the presented stamps and sends it to the person he or she is talking to.

[0091] 2. Terminal: Converts the selected stamp data into a data packet and sends it to the other terminal.

[0092] In this way, users, devices, and servers work together to enable users to easily create stamps based on their preferences and enjoy rich communication.

[0093] Example 1

[0094] 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."

[0095] In conventional messaging systems, users must manually select emojis and stickers, making it difficult to quickly find the right stickers that match their individual preferences. This disrupts the flow of conversation and detracts from the user experience. Furthermore, there is no automated method for identifying stickers based on individual user preferences, requiring constant manual intervention. Therefore, there is a need to improve user convenience and enable richer communication.

[0096] 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.

[0097] In this invention, the server includes means for a user to register visual information and characters that the user likes, means for saving the registered visual information and characters that the user likes, means for automatically generating digital emojis based on the content of a conversation, means for presenting the generated digital emojis to the user, and means for the user to select the presented digital emojis. This allows the user to quickly find digital emojis that match their preferences, enabling smoother communication without interrupting the flow of conversation.

[0098] "User" means an individual or organization that uses the system to register their preferred visual information or characters and communicates through messaging services.

[0099] "Visual information" refers to visual content such as favorite images, designs, characters, etc. registered by users.

[0100] "Character" refers to an image of a specific person, animal, fictional creature, or other character that a user likes.

[0101] "Digital Emoji" are system-generated illustrations or icons for use in messages.

[0102] An "artificial intelligence model" is a software program that includes machine learning algorithms to analyze user preferences and conversational content and generate digital emojis based on that analysis.

[0103] An "image provider" is an individual or organization that provides existing images to be used as training data for an artificial intelligence model.

[0104] "Conversation content" refers to the content of text messages and discussions exchanged between users via messaging services.

[0105] "Messaging Service" refers to an application or platform that allows users to send and receive text messages.

[0106] "Server" refers to the computer system that stores and manages user preference information and generated digital emojis, and generates digital emojis as needed.

[0107] This system allows users to register their preferred visual information and characters, and then automatically generates and presents digital emojis based on that information in response to the content of the conversation. To implement this system, three main entities work together: a server, a terminal, and a user.

[0108] Server Processing

[0109] 1. Storing your information and preferences

[0110] The server receives the visual information and character data that the user sends from their device and stores it in a database. Databases such as MySQL and PostgreSQL can be used for efficient information management.

[0111] 2. Training the AI ​​model

[0112] The server receives existing visual data provided by image providers and uses it as training data for an AI model. Using machine learning frameworks such as TensorFlow and PyTorch, it trains a model that can tag images based on visual information and generate digital emojis that adapt to the user's conversation.

[0113] 3. Digital Emoji Generation and Presentation

[0114] Upon receiving a user's message, the server uses NLP technology to analyze its content and generate digital emojis based on appropriate visual information and characters. The generated digital emoji candidates are packaged in JSON format and sent to the user's device.

[0115] Terminal handling

[0116] 1. Providing a user interface

[0117] The device provides an interface for users to register their favorite visual information and characters. Users can easily register visual information using a smartphone app or web app. It also provides an interface that displays digital emojis as the conversation progresses.

[0118] 2. Data transmission and reception

[0119] The device sends the visual information data and conversation log entered by the user to the server using an HTTP POST request. The server then receives a list of digital emoji candidates and displays them to the user.

[0120] 3. Selection and Use of Digital Emojis

[0121] The user selects the desired digital emoji from the provided ones and uses the interface to insert them into the conversation. The selected digital emoji is then sent to the other person via the terminal.

[0122] User Actions

[0123] 1. Register your preferences

[0124] Users can specify their preferred visual information and characters through the app on their device. For example, if a user likes a "smiling cat," they enter this information in the app's input field and send it to the server.

[0125] 2. Starting a dialogue

[0126] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[0127] 3. Checking and using digital emojis

[0128] The user can select an appropriate digital emoji from the candidates sent by the server. For example, in response to the message "I had a great day," a digital emoji of a "smiling cat" is suggested. The user selects this emoji and sends it to the person they are speaking with.

[0129] Specific examples

[0130] 1. Register your favorite visual information and characters

[0131] User A registers "dog characters" as a preference. He enters this information into the device app and sends it to the server.

[0132] 2. Interaction and Digital Emoji Generation

[0133] When User A sends the message "good night," the server parses the message and generates a digital emoji of a dog saying "good night."

[0134] 3. Check and Use

[0135] User A checks the list of digital emojis sent from the server, selects the digital emoji "Goodnight dog" and sends it to the person he is talking to.

[0136] Prompt Sentence Examples

[0137] 1. "Please register dog characters as your favorite."

[0138] 2. "What did you have for lunch today?"

[0139] 3. "What emoji is appropriate for saying thank you?"

[0140] This system allows users to freely create digital emojis according to their preferences and enjoy richer communication. The AI ​​model also provides high-quality digital emojis that match the user's preferences.

[0141] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0142] System processing steps

[0143] Step 1:

[0144] The user opens the application on their device and registers their preferred visual information and characters. The user enters "smiling cat" as their preference and presses the send button. At this time, the device packages the entered information as JSON-formatted data. The input is visual information such as "smiling cat," and the output is JSON-formatted data.

[0145] Step 2:

[0146] The terminal sends the packaged JSON data to the server using an HTTP POST request: the input is the packaged JSON data, and the output is an HTTP request to the server's endpoint.

[0147] Step 3:

[0148] The server receives the HTTP request and parses the JSON data. The parsed results are saved in a database. The input is JSON data, and the output is visual information data saved in the database. The specific operation is to execute an INSERT query against MySQL.

[0149] Step 4:

[0150] The server acquires existing visual information data provided by the image provider. It uses this data to train an AI model. The input is the visual information data provided by the image provider, and the output is the trained AI model. Specifically, the machine learning algorithm is trained using TensorFlow and PyTorch.

[0151] Step 5:

[0152] A user starts a message exchange with a conversation partner, for example, sending a message such as "I had fun today." The input is the text message "I had fun today," and the output is the message sent from the terminal to the server.

[0153] Step 6:

[0154] The server receives the user's message and analyzes the message content using NLP techniques. The input is the text message and the output is the analysis result. Specific operations include text analysis using spaCy and Transformers.

[0155] Step 7:

[0156] Based on the analysis results, the server selects appropriate visual information and characters to generate a digital emoji. This process uses a trained AI model. The input is the analysis results and the trained model, and the output is a digital emoji. Specific operations include running the AI ​​model's inference engine.

[0157] Step 8:

[0158] The server packages the generated digital emoji candidates in JSON format and sends them to the user's device. The input is the digital emoji, and the output is an HTTP response to the user's device. The specific operations include generating and sending data in JSON format.

[0159] Step 9:

[0160] The device analyzes the received digital emoji candidates and displays them on the user interface. The input is digital emoji data in JSON format, and the output is digital emoji candidates displayed on the user interface.

[0161] Step 10:

[0162] The user selects the desired digital emoji from the presented ones and inserts it into the conversation. For example, they select the digital emoji "smiling cat" and press the send button. The input is the user's selection, and the output is the transmission of the digital emoji to the conversation partner.

[0163] In this way, the user, device, and server all work together to create a system that can quickly and smoothly generate and display digital emojis based on the user's preferences.

[0164] (Application example 1)

[0165] 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."

[0166] In traditional brick-and-mortar stores, it was difficult to provide personalized suggestions tailored to individual customer preferences and needs, resulting in limited means for improving customer satisfaction. Furthermore, effective use of visual elements such as stamps and illustrations was also limited, leading to a tendency for dialogue with customers to be monotonous.

[0167] 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.

[0168] In this invention, the server includes a means for users to register their favorite designs and characters, a means for saving the registered favorite designs and characters, and a means for automatically generating stamps based on the content of conversations, which enables personalized suggestions to be made based on the content of customer conversations in physical stores.

[0169] A "user" is a user of the system who registers their preferred designs and characters to receive personalized services.

[0170] "Pictures and characters" refer to the illustrations and image designs that users prefer to register, and are the visual elements that form the basis for generating stamps.

[0171] "Stamps" are emojis or images used during conversations to visually express users' emotions and messages.

[0172] "Automatically generating stickers" refers to the process of using AI models and algorithms to create appropriate stickers based on the user's conversation content and registration information.

[0173] "Presenting" refers to the act of showing the generated stamp to the user.

[0174] "Selecting" refers to the act of the user choosing the stamp that best suits their taste from the ones presented.

[0175] A "physical store" refers to a commercial or service facility that exists in a physical location and where customers can visit in person to receive services.

[0176] "Customers" refer to shoppers who visit physical stores or service users and who receive personalized offers.

[0177] "Personalized offers" refers to individualized service and product proposals tailored to the customer's preferences and needs.

[0178] "Training an AI model" refers to the process of using illustrations and data to teach an artificial intelligence model and strengthen it to work effectively for a specific task.

[0179] "Content Creator" refers to a person or organization that creates illustrations or other visual content and provides it to the System.

[0180] "Existing illustrations" refer to visual materials previously created by content creators and provided for use as training data.

[0181] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[0182] Server Processing

[0183] 1. Storing your information and preferences

[0184] The server receives the user's registered favorite images and characters and stores them in a database. This allows the user to change their favorite information as many times as they like, and the system always keeps the latest user preferences.

[0185] 2. Training the AI ​​model

[0186] The server collects existing illustration data provided by content creators and uses it to train an AI model that is trained to generate stickers based on the tagged data and the user's conversation content. This process uses deep learning frameworks such as TensorFlow and PyTorch.

[0187] 3. Stamp generation and presentation

[0188] The server analyzes the user's message and generates appropriate stickers based on the user's preferences and the content of the conversation. The generated sticker candidates are sent to the user's device and displayed. Specifically, for example, a prompt phrase such as "new item arrival with a blue cat character" is input into the generative AI model to generate an appropriate sticker.

[0189] Terminal handling

[0190] 1. Providing a user interface

[0191] The device provides an interface for users to register their favorite pictures and characters, as well as an interface for displaying stamps during conversations. It is implemented as an application for smartphones and tablets.

[0192] 2. Data transmission and reception

[0193] The device sends the user's registration information and interaction log to the server. This conveys the user's interaction context to the server, which then generates stamps based on that information. The device receives the generated stamp list and displays it to the user.

[0194] 3. Selecting and Using Stamps

[0195] The user selects the desired stamp from the list of stamp candidates presented by the server through the terminal interface, and the selected stamp is inserted into the message and sent to the other party.

[0196] User Actions

[0197] 1. Register your preferences

[0198] Users use the device interface to specify their preferred image or character, such as "a smiling cat" or "I like blue items," and then input this information into the app and send it to the server.

[0199] 2. Starting a dialogue

[0200] Users can interact with store staff or AI chatbots in physical stores, for example by sending messages such as "Have new products arrived?"

[0201] 3. Check and use stamps

[0202] The user selects an appropriate stamp from the list of stamp candidates sent by the server. For example, the "Blue Cat" stamp is suggested for the message "Have new items arrived?" The user selects this stamp, inserts it into the conversation, and sends it.

[0203] Software and Hardware Requirements

[0204] Software used:

[0205] Server software: Linux (e.g., Ubuntu 20.04), Flask web framework, PostgreSQL database

[0206] AI model training: TensorFlow or PyTorch

[0207] Terminal applications: iOS app (Swift), Android app (Kotlin)

[0208] Hardware used:

[0209] Server hardware: High-performance server machine (e.g., Dell PowerEdge series)

[0210] Device: iOS or Android smartphone or tablet

[0211] Specific examples

[0212] If User A registers "Smiling Cat" as a preference, the server stores this. When User A sends a message to a physical store asking "Have new items arrived?", the server analyzes this message and inputs the prompt "New items arrived with a smiling cat character" into the AI ​​model. The AI ​​model generates an appropriate stamp and sends it to the device. User A selects the "Smiling Cat" stamp and sends it to the store clerk or chatbot, achieving personalized communication.

[0213] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0214] Step 1:

[0215] Registering user preferences

[0216] The server receives the user's favorite images and characters sent from the device, stores this information in a database, and updates the user's favorite list.

[0217] Input: User preference information (e.g., "smiling cats," "blue items")

[0218] Output: User preference information stored in a database

[0219] Step 2:

[0220] Collecting learning data and training AI models

[0221] The server collects existing illustration data provided by content creators, labels it, and trains the AI ​​model, using deep learning frameworks such as TensorFlow and PyTorch to enable the model to generate appropriate stamps.

[0222] Input: Existing illustration data and label information

[0223] Output: A trained AI model

[0224] Step 3:

[0225] Message parsing and prompt generation

[0226] The server receives the user's interactive message sent from the device and analyzes its content. Based on the analysis results, it generates a prompt sentence and inputs it into the AI ​​model. For example, if the message is "Have new items arrived?", it generates the prompt sentence "new item arrival with a smiling cat character."

[0227] Input: User interaction message

[0228] Output: Generated prompt statement

[0229] Step 4:

[0230] Stamp Generation

[0231] The server inputs the generated prompt into the AI ​​model to generate a corresponding stamp. The AI ​​model analyzes the prompt and outputs a stamp that combines an appropriate image and character.

[0232] Input: Generated prompt text

[0233] Output: Generated stamp

[0234] Step 5:

[0235] Stamp list presentation

[0236] The server sends the generated stamp list to the device and presents it to the user, who can then view the stamps displayed through the device interface.

[0237] Input: Generated stamp list

[0238] Output: Stamp list displayed on the device

[0239] Step 6:

[0240] Selecting and Using Stamps

[0241] The user selects the desired stamp from a list of stamps presented to them using the terminal interface, and the selected stamp is inserted into the message and sent to the interlocutor.

[0242] Input: User selects stamp

[0243] Output: Send selected stamps

[0244] Through the above processing steps, appropriate stamps are automatically generated based on the content of the user's dialogue, realizing personalized communication.

[0245] 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.

[0246] The system of the present invention allows users to register their favorite pictures and characters, and automatically generates stamps based on the content of the conversation and an emotion engine, thereby providing users with appropriate stamps.

[0247] Server Processing

[0248] 1. Storing your information and preferences

[0249] The server receives information about the preferred designs and characters sent by the user and stores it in a database.

[0250] 2. Training the AI ​​model

[0251] The server receives existing illustration data provided by the illustrator and uses it as training data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stickers based on the user's conversation content and emotions.

[0252] 3. Use of Emotion Engine

[0253] The server analyzes the content of the user's conversation and uses an emotion engine to recognize the user's emotions from that content. The emotion engine uses multiple language models and emotion recognition algorithms to analyze the user's emotions with high accuracy.

[0254] 4. Stamp generation and presentation

[0255] Based on the user's message and the perceived emotion, the AI ​​model generates appropriate stickers, which are then sent to the user's device for display.

[0256] Terminal handling

[0257] 1. Providing a user interface

[0258] The device provides an interface for users to register their favorite pictures and characters, as well as an interface that displays stamps based on the content of conversations and emotions.

[0259] 2. Data transmission and reception

[0260] The device sends the user's registration information and interaction log to the server, which then conveys the user's interaction context and emotional information to the server. The device also receives a stamp list sent from the server and displays it to the user.

[0261] 3. Selecting and Using Stamps

[0262] The system provides an interface for users to select the desired stamp from the provided stamps and insert it into the conversation. The selected stamp is then sent from the device to the conversation partner.

[0263] User Actions

[0264] 1. Register your preferences

[0265] Users can specify their favorite images and characters through the app on their device. For example, if a user likes "smiling dogs," they enter this information into the app and send it to the server.

[0266] 2. Starting a dialogue

[0267] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[0268] 3. Emotional Recognition

[0269] The server analyzes the received message and uses an emotion engine to identify the user's emotion. For example, it recognizes positive emotion from the message "I had fun today."

[0270] 4. Check and use stamps

[0271] The user selects an appropriate stamp from among the stamp candidates sent by the server based on the content of the conversation and the recognized emotion. For example, a "smiling dog" stamp is suggested for the message "I had fun today." The user selects this stamp, inserts it into the conversation, and sends it.

[0272] Specific examples

[0273] 1. Register your favorite designs and characters

[0274] User A registers "cat characters" as a preference. He enters this information into the device app and sends it to the server.

[0275] 2. Dialogue and Emotion Recognition

[0276] When User A sends a message saying "Work is done! Yay!", the server analyzes this message and uses an emotion engine to recognize positive emotions.

[0277] 3. Stamp creation and selection

[0278] The server uses an AI model to generate a "joyful cat" stamp based on the recognized positive emotion.

[0279] The server sends stamp candidates to the user's device, and User A selects the "Joyful Cat" stamp and sends it to the person he or she is talking to.

[0280] This system allows users to easily create stamps based on their preferences and emotions, allowing them to enjoy richer communication.

[0281] The processing flow will be explained below.

[0282] The processing steps from when the user registers their favorite pictures or characters to when the emotion engine is used to generate stamps during a conversation

[0283] Step 1: Users register their favorite designs and characters

[0284] 1. User: Enter your favorite image or character into the device app. For example, "dog character."

[0285] 2. Terminal: Converts the user's input preferences into data packets.

[0286] 3. Terminal: Sends the converted data packets to the server.

[0287] Step 2: The server stores the user information

[0288] 1. Server: Analyzes data packets received from users and extracts their preferred images and character information.

[0289] 2. Server: Stores the extracted information in a database.

[0290] Step 3: Train the AI ​​model

[0291] 1. Illustrator: Upload an existing illustration to the server as learning data.

[0292] 2. Server: Stores the received illustration data in a database and performs preprocessing (size adjustment, noise removal, etc.).

[0293] 3. Server: Trains the AI ​​model using the preprocessed illustration data, properly tags each illustration, and generates stickers for the corresponding user conversation and emotion.

[0294] Step 4: User initiates interaction

[0295] 1. User: Sends a message to the person they are interacting with through the app, for example, "I had a great time today."

[0296] 2. Terminal: Converts the user's message into data packets and sends them to the server.

[0297] Step 5: The emotion engine recognizes the user's emotions

[0298] 1. Server: Analyzes the received message data.

[0299] 2. Server: Recognizes the user's emotion from the message content using an emotion engine. For example, recognize positive emotion from the message "I had fun today."

[0300] Step 6: The server generates and presents the stamp

[0301] 1. Server: Using an AI model, the server generates appropriate stamps based on the analysis results, the user's preferred designs, character information, and recognized emotions.

[0302] 2. Server: Arranges the generated stamp candidates into a list and sends it to the user's device.

[0303] Step 7: Your device will display sticker suggestions

[0304] 1. Terminal: The stamp list received from the server is displayed on the user interface, visually presenting multiple stamps in thumbnail format.

[0305] 2. User: Select the desired stamp from the presented stamp list.

[0306] Step 8: User selects sticker and sends it

[0307] 1. User: Selects the "Smiling Dog" stamp from the presented stamps and sends it to the person he or she is talking to.

[0308] 2. Terminal: Converts the selected stamp data into a data packet and sends it to the other terminal.

[0309] In this way, the user, device, server, and emotion engine work together to enable users to easily create stamps based on their preferences and emotions, and enjoy rich communication.

[0310] Example 2

[0311] 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."

[0312] Conventional stamp generation systems have had problems such as making it difficult for users to easily select stamps that match their preferences, and not being able to provide appropriate stamps based on emotions in a timely manner. Furthermore, stamp generation is not sufficiently automated, making it impossible to generate stamps that take into account the user's conversation content and emotions.

[0313] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0314] In this invention, the server includes means for users to register their favorite images and characters, means for saving the registered favorite images and characters, means for automatically generating stamps based on the conversation content and the emotion engine, means for presenting the generated stamps to the user terminal, and means for the user to select the presented stamps via the terminal, thereby enabling timely provision of stamps based on the user's preferences and emotions.

[0315] "User" refers to an individual or corporation that uses the system, and is the entity that primarily performs the operations of registering, selecting, and sending stamps.

[0316] "Images and characters" are visual expressions designated by users as their preferences, and are the materials used to generate stamps.

[0317] A "stamp" is an image or icon added to a message in digital communication to visually convey emotions or intentions.

[0318] A "generative AI model" is a model that uses artificial intelligence to automatically generate stamps based on user preferences and conversation content.

[0319] An "emotion engine" is a system or algorithm that analyzes the content of a user's conversation and recognizes the emotions contained within it.

[0320] The "database" is a system for storing and managing users' preferred images, characters, and related information such as conversation logs.

[0321] A "prompt" is text information that is input into a generative AI model and used to generate a specific stamp or response.

[0322] A "terminal" is a device used by a user to access and operate the system, such as a smartphone, tablet, or PC.

[0323] A "server" is a central computer system that operates and manages the entire system, and processes data and generates stamps in response to user requests.

[0324] "Interface" is a general term for the operation screen and input / output devices that allow users to interact with the system.

[0325] The system of the present invention allows users to register their favorite images and characters, and automatically generates stamps based on the content of the conversation and an emotion engine, thereby providing appropriate stamps to users. Specific embodiments of the system are described below.

[0326] Server Processing

[0327] Storing User Information and Preferences

[0328] The server receives the user's favorite images and character information sent from the device and stores it in a database. "MySQL" can be used as the database software. For example, information such as the user ID, favorite character, and registration date and time is stored.

[0329] Training an AI model

[0330] The server receives existing image data provided by the image creator and uses it as training data for the AI ​​model. The image data is tagged, for example, a cat image is tagged with "cat," "cute," and "smiling." Then, using TensorFlow and PyTorch, a stamp generation model is trained based on the conversation content and emotions.

[0331] Use of emotion engine

[0332] The server receives the user's conversation content sent from the device and uses an emotion engine to recognize the user's emotions from the content. The emotion engine can use tools such as Google Cloud Natural Language API or IBM Watson. This allows for highly accurate analysis of the user's emotions.

[0333] Stamp generation and presentation

[0334] The server uses an AI model to automatically generate appropriate stickers based on the recognized emotions and user preferences, and sends the generated sticker candidates to the user's device, where they are presented to the user.

[0335] Terminal handling

[0336] Providing a user interface

[0337] The device provides an interface for users to register their favorite images and characters, such as a form entry screen and an image selection screen, as well as an interface for displaying stamps based on the user's dialogue and emotions.

[0338] Sending and receiving data

[0339] The terminal transmits the user's input preference information to the server, transmits the user's interaction log to the server, conveys the user's interaction context and emotion information to the server, and receives the stamp list transmitted from the server and displays it to the user.

[0340] Selecting and Using Stamps

[0341] The terminal provides an interface for the user to select a desired stamp from the stamps presented and insert it into the conversation. The selected stamp is then sent from the terminal to the conversation partner.

[0342] User Actions

[0343] Register your preferences

[0344] The user launches the app on their device, inputs their favorite image or character, for example, "smiling dog," and sends it to the server.

[0345] Starting a conversation

[0346] The user opens a message exchange screen with the person they are talking to, enters a message such as "I had fun today," and sends it.

[0347] Emotion recognition

[0348] The server analyzes the received message and uses an emotion engine to identify the user's emotion. For example, it recognizes positive emotion from the message "I had fun today."

[0349] Checking and using stamps

[0350] The stamp candidates sent from the server are displayed on the user's device, and the user selects the appropriate stamp from the presented stamps and presses the select button.

[0351] Specific examples

[0352] 1. Register your favorite images and characters

[0353] User A registers "cat characters" as a preference. He enters "cat" into the device app and sends it to the server.

[0354] 2. Dialogue and Emotion Recognition

[0355] When User A sends a message saying "Work is done! Yay!", the server analyzes this message and uses an emotion engine to recognize positive emotions.

[0356] 3. Stamp creation and selection

[0357] The server generates a stamp of a happy cat using an AI model based on the recognized positive emotion. The server sends stamp candidates to the user's device, and User A selects the "happy cat" stamp and sends it to the person he or she is talking to.

[0358] Prompt Sentence Examples

[0359] 1. Register your preferences for designs and characters

[0360] "My favorite character is 'Cat'. Please register this information."

[0361] 2. Message sending for dialogue and emotion recognition

[0362] "Job done! Yay!"

[0363] 3. Using the generated stamp

[0364] Select "Joyful Cat" and send.

[0365] This system allows users to easily create stamps based on their preferences and emotions, allowing them to enjoy richer communication.

[0366] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0367] Step 1:

[0368] Users register their favorite images and characters

[0369] Input: The user inputs and sends their preferred image or character through the device interface.

[0370] How it works: The device receives information entered by the user through forms and selection screens and sends it to the server.

[0371] Output: The device sends the preference information entered by the user to the server, which receives this information.

[0372] Step 2:

[0373] Storing User Information and Preferences

[0374] Input: The user's preferred image and character information sent in Step 1.

[0375] Operation: The server stores the received information in a database. For example, it uses "MySQL" to register the user ID, favorite character, and registration date and time.

[0376] Output: The server sends a confirmation message to the device indicating that the save is complete.

[0377] Step 3:

[0378] Training an AI model

[0379] Input: Existing image data and tagging data provided by the image creator.

[0380] How it works: The server tags images and preprocesses the data. This preprocessed data is used to train a generative AI model using TensorFlow and PyTorch. The model learns to generate stickers based on the user's conversation content and emotions using the tag information.

[0381] Output: A fully trained generative AI model.

[0382] Step 4:

[0383] Receiving conversation content

[0384] Input: Message exchanges between the user and their interlocutor.

[0385] How it works: The device sends the messages the user sends to the server, which receives and stores them.

[0386] Output: The server is ready to parse and process the received conversation content.

[0387] Step 5:

[0388] Emotion recognition

[0389] Input: The conversation received in step 4.

[0390] How it works: The server uses an emotion engine to analyze the conversation and identify the user's emotions. For example, it uses Google Cloud Natural Language API or IBM Watson to analyze emotion data.

[0391] Output: Identified user sentiment data.

[0392] Step 6:

[0393] Stamp Generation

[0394] Input: Identified emotion data and user's preferred image or character information.

[0395] How it works: The server generates optimal stamps using a generative AI model. Emotional data and preference information are input to the generative AI model as prompts.

[0396] Output: The generated stamp candidates.

[0397] Step 7:

[0398] Sending and displaying stamps

[0399] Input: Generated stamp candidates.

[0400] Operation: The server sends the generated stamp candidates to the user terminal and displays them to the user. The terminal displays the stamp candidates in the user interface.

[0401] Output: User can see the stamp suggestions.

[0402] Step 8:

[0403] Select a stamp

[0404] Input: The stamp selected by the user.

[0405] How it works: The user selects the desired stamp from the ones presented and presses the "Send" button. The device then sends this selection to the server.

[0406] Output: The selected stamps are sent to the server.

[0407] Step 9:

[0408] Send Selected Stamps

[0409] Input: The stamp selected in step 8.

[0410] Operation: The server sends the selected stamp to the conversation partner. The terminal displays the selected stamp to the conversation partner.

[0411] Output: The stamp is sent to the person you are talking to and displayed.

[0412] This allows users to easily send stamps based on their preferences and emotions to their interlocutors, enabling richer communication.

[0413] (Application example 2)

[0414] 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."

[0415] Communication with customers in virtual stores is mainly text-based, resulting in limited emotional communication. Furthermore, it is difficult to respond flexibly to customer emotions, limiting the quality of service. Given this background, there is a need for a system that can appropriately recognize customer emotions in virtual stores and provide appropriate stamps to enable richer communication.

[0416] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0417] In this invention, the server includes means for a user to register their favorite pictures and characters, means for saving the registered favorite pictures and characters, means for automatically generating stamps based on conversation content and emotion analysis, means for presenting the generated stamps to the user, means for the user to select the presented stamps, emotion analysis means for recognizing emotions from the content of the user's message, and means for presenting stamps generated in accordance with the recognized emotions on the virtual store interface. This makes it possible to improve the quality of communication by recognizing customer emotions in the virtual store in real time and providing stamps in response to those emotions.

[0418] "User" refers to a person or company that uses the system to register their favorite designs or characters and generate and use stamps.

[0419] "Pictures and characters" are illustrations, images, symbols, etc. that users select as their preferences.

[0420] "Storage means" refers to a storage device or database for storing information about the images and characters registered by the user.

[0421] "Conversation content" refers to messages and text information sent by users on the system.

[0422] "Sentiment analysis" is the process of analyzing the content of a user's message to recognize their emotional state.

[0423] "Stamps" are emoticons or illustrations generated for users to use in their messages.

[0424] "Means for automatic generation" refers to the process by which the system automatically generates stamps based on the content of the user's conversation and sentiment analysis.

[0425] The "presentation means" is an interface for visually presenting the generated stamp to the user.

[0426] The "selection means" is an operation interface that allows the user to select the desired stamp from among the stamps presented.

[0427] "Emotion analysis tools" are algorithms or software that recognize emotions from users' messages.

[0428] A "virtual store" is an online store that offers products and services over the Internet.

[0429] An "AI model" is an artificial intelligence algorithm that generates stamps based on the content of the conversation and emotions.

[0430] The "virtual store interface" is the user interface through which customers interact with the system.

[0431] The system of the present invention allows users to register their favorite images and characters, and automatically generates and displays stamps based on conversation content and sentiment analysis. In implementing this system, the server, terminal, and user components work in conjunction with each other.

[0432] Server Processing

[0433] 1. Storing your information and preferences

[0434] The server receives the user's preferred designs and characters and stores them in a database. New designs and characters registered by the user are updated in real time.

[0435] 2. Training the AI ​​model

[0436] The server receives existing illustration data provided by the illustrator and uses it as training data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stickers based on the user's conversation content and emotions. Specific software used includes TensorFlow and PyTorch.

[0437] 3. Use of sentiment analysis engines

[0438] The server analyzes the user's conversation content and uses a sentiment analysis engine to recognize the user's emotions from the content. This engine analyzes emotions with high accuracy using natural language processing models (e.g., BERT and GPT-3).

[0439] 4. Stamp generation and presentation

[0440] Based on the user's message and the recognized emotion, the AI ​​model generates appropriate stickers. The generated sticker candidates are sent to the user's device and displayed. Generative Adversarial Networks (GANs) and DALL-E are used for generation.

[0441] Terminal handling

[0442] 1. Providing a user interface

[0443] The device provides an interface for users to register their favorite pictures and characters, as well as an interface that displays stamps based on the content of conversations and emotions.

[0444] 2. Data transmission and reception

[0445] The device sends the user's registration information and interaction log to the server, which then conveys the user's interaction context and emotional information to the server. The device also receives a stamp list sent from the server and displays it to the user.

[0446] 3. Selecting and Using Stamps

[0447] It provides an interface for users to select the desired stamp from the provided stamps, and the selected stamp is sent from the terminal to the interlocutor.

[0448] User Actions

[0449] 1. Register your preferences

[0450] Users can specify their favorite images and characters through the app on their device. For example, if a user likes "smiling dogs," they enter this information into the app and send it to the server.

[0451] 2. Starting a dialogue

[0452] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[0453] 3. Emotional Recognition

[0454] The server analyzes the received message and uses a sentiment analysis engine to identify the user's sentiment. For example, it recognizes positive sentiment from a message such as "I had fun today."

[0455] 4. Check and use stamps

[0456] The user selects an appropriate stamp from among the stamp candidates sent by the server based on the content of the conversation and the recognized emotion. For example, a "smiling dog" stamp is suggested for the message "I had fun today." The user selects this stamp, inserts it into the conversation, and sends it.

[0457] Specific examples

[0458] For example, if User A registers "cat characters" as a favorite and sends a message saying "Work is done! Yay!", the server will analyze this message and recognize the positive emotion. Based on this, a "joyful cat" stamp will be generated and presented to User A. User A can then select this stamp and send it to the person they are interacting with, achieving engaging, emotion-based communication.

[0459] Example prompt sentence:

[0460] A user sent a message saying, "I really liked this product!" Recognize the emotion from this message and generate an appropriate sticker based on the user's favorite character, "cat."

[0461] In this way, the system of the present invention automatically generates and provides stamps that correspond to the user's emotions, thereby improving the user experience in the virtual store.

[0462] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0463] Step 1:

[0464] The server provides the terminal with an interface that allows users to register their favorite pictures and characters.

[0465] Input: User's preferred designs and character information

[0466] Output: Temporarily save registered information

[0467] Specific operation: The user inputs information such as "smiling dog" through the device interface, and the device temporarily stores this preference information.

[0468] Step 2:

[0469] The terminal transmits the user's registered favorite images and character information to the server.

[0470] Input: User preference information (e.g., "smiling dogs")

[0471] Output: Data sent to the server, confirmation message

[0472] Specific operation: The preference information is sent from the device to the server, which receives it and stores it in the database. After completion, a confirmation message is displayed on the device.

[0473] Step 3:

[0474] The server stores the registration information submitted by the user in a database.

[0475] Input: User preference information

[0476] Output: User preferences stored in a database

[0477] What happens: The server updates the database, storing the user's preferences, such as "smiling dogs."

[0478] Step 4:

[0479] The server provides an interface for analyzing the content of the user's conversation.

[0480] Input: A message that the user types

[0481] Output: Send message to server

[0482] Specific operation: The device sends the message entered by the user in the chat (e.g., "Today was fun") to the server.

[0483] Step 5:

[0484] The server analyzes the received message using a sentiment analysis engine.

[0485] Input: User's message

[0486] Output: Parsed emotion data

[0487] Specific operation: The server uses a natural language processing model (BERT or GPT-3) to analyze positive emotions from the message "I had fun today."

[0488] Step 6:

[0489] The server generates stamps based on the analyzed emotional data and the user's preferences.

[0490] Input: Emotion data, preferred picture information

[0491] Output: Generated stamp

[0492] Specific operation: Using AI models (TensorFlow, GANs, DALL-E), we generate "smiling dog" stamps that match positive emotions.

[0493] Step 7:

[0494] The server transmits the generated stamp to the terminal and presents it to the user.

[0495] Input: Generated stamp data

[0496] Output: Send stamp data to the terminal

[0497] Specific operation: The server sends the "smiling dog" stamp data to the terminal and displays the stamp on the display interface.

[0498] Step 8:

[0499] The terminal provides an interface for the user to select from the presented stamps.

[0500] Input: Presented stamp

[0501] Output: User selection data

[0502] Specific behavior: The user selects the "smiling dog" sticker that is displayed.

[0503] Step 9:

[0504] The terminal operates to transmit the stamp selected by the user to the interlocutor.

[0505] Input: User's stamp selection data

[0506] Output: Send stamp to the person you are talking to

[0507] Specific operation: The device sends the "smiling dog" stamp selected by the user to the person it is talking to.

[0508] In this way, stamps are generated and displayed in real time according to the user's conversation content and emotions, enabling richer communication.

[0509] 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.

[0510] 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.

[0511] 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.

[0512] [Second embodiment]

[0513] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0514] 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.

[0515] 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).

[0516] 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.

[0517] 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.

[0518] 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).

[0519] 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.

[0520] 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.

[0521] 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.

[0522] 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.

[0523] 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.

[0524] 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."

[0525] To implement the system of the present invention, three main entities work together: the server, the terminal, and the user. This system allows users to register their favorite pictures and characters, and then uses that information to automatically generate stamps based on the content of the conversation, providing appropriate stamps to the user.

[0526] Server Processing

[0527] 1. Storing your information and preferences

[0528] The server receives the information about the preferred designs and characters sent by the user and stores it in a database, allowing the system to accumulate the user's registered preferences.

[0529] 2. Training the AI ​​model

[0530] The server receives existing illustration data provided by the illustrator and uses it as learning data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stamps based on the user's conversation content.

[0531] 3. Stamp generation and presentation

[0532] When a user's message is received, the server analyzes the content, selects appropriate images and characters, and generates stamps. The generated stamp candidates are sent to the user's device and displayed.

[0533] Terminal handling

[0534] 1. Providing a user interface

[0535] The device provides an interface for users to register their favorite pictures and characters, as well as an interface for displaying stamps according to the flow of conversation.

[0536] 2. Data transmission and reception

[0537] The device sends the user's registration information and interaction log to the server, which conveys the user's interaction context to the server. The device receives the stamp list sent from the server and displays it to the user.

[0538] 3. Selecting and Using Stamps

[0539] The system provides an interface for users to select the desired stamp from the provided stamps and insert it into the conversation. The selected stamp is then sent from the device to the conversation partner.

[0540] User Actions

[0541] 1. Register your preferences

[0542] Users can specify their favorite designs and characters through the app on their device. For example, if a user likes a "smiling cat," they enter this information into the app and send it to the server.

[0543] 2. Starting a dialogue

[0544] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[0545] 3. Check and use stamps

[0546] The user selects an appropriate stamp from the list of stamp candidates sent by the server based on the content of the conversation. For example, a "smiling cat" stamp is suggested for the message "Today was fun." The user selects this stamp, inserts it into the conversation, and sends it.

[0547] Specific examples

[0548] 1. Register your favorite designs and characters

[0549] User A registers "dog characters" as a preference. He enters this information into the device app and sends it to the server.

[0550] 2. Interaction and stamp generation

[0551] When user A sends the message "good night," the server analyzes this message and generates a stamp of a dog saying "good night."

[0552] 3. Check and Use

[0553] User A checks the stamp list sent from the server, selects the "Goodnight Dog" stamp and sends it to the person he or she is talking to.

[0554] This system allows users to freely create stamps that suit their preferences and enjoy rich communication.

[0555] The processing flow will be explained below.

[0556] The process steps for users to register their favorite designs and characters and use stamps during conversations

[0557] Step 1: Users register their favorite designs and characters

[0558] 1. User: Enter your favorite image or character into the device app. For example, "dog character."

[0559] 2. Terminal: Converts the user's input preferences into data packets.

[0560] 3. Terminal: Sends the converted data packets to the server.

[0561] Step 2: The server stores the user information

[0562] 1. Server: Analyzes data packets received from users and extracts their preferred images and character information.

[0563] 2. Server: Stores the extracted information in a database.

[0564] Step 3: Train the AI ​​model

[0565] 1. Illustrator: Upload an existing illustration to the server as learning data.

[0566] 2. Server: Stores the received illustration data in a database and performs preprocessing (size adjustment, noise removal, etc.).

[0567] 3. Server: Trains the AI ​​model using the preprocessed illustration data, properly tags each illustration, and generates stickers for the corresponding user conversations.

[0568] Step 4: User initiates interaction

[0569] 1. User: Sends a message to the person they are interacting with through the app, for example, "I had a great time today."

[0570] 2. Terminal: Converts the user's message into data packets and sends them to the server.

[0571] Step 5: The server generates and presents the stamp

[0572] 1. Server: Analyzes the received message data and understands the conversation content.

[0573] 2. Server: Taking into account the analysis results and the user's preferred designs and character information, the server uses an AI model to generate appropriate stamps.

[0574] 3. Server: Arranges the generated stamp candidates into a list and sends it to the user's device.

[0575] Step 6: Your device will display suggested stickers

[0576] 1. Terminal: The stamp list data received from the server is displayed on the user interface, visually presenting multiple stamps in thumbnail format.

[0577] 2. User: Select the desired stamp from the presented stamp list.

[0578] Step 7: User selects sticker and sends it

[0579] 1. User: Selects the "Smiling Dog" stamp from the presented stamps and sends it to the person he or she is talking to.

[0580] 2. Terminal: Converts the selected stamp data into a data packet and sends it to the other terminal.

[0581] In this way, users, devices, and servers work together to enable users to easily create stamps based on their preferences and enjoy rich communication.

[0582] Example 1

[0583] 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."

[0584] In conventional messaging systems, users must manually select emojis and stickers, making it difficult to quickly find the right stickers that match their individual preferences. This disrupts the flow of conversation and detracts from the user experience. Furthermore, there is no automated method for identifying stickers based on individual user preferences, requiring constant manual intervention. Therefore, there is a need to improve user convenience and enable richer communication.

[0585] 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.

[0586] In this invention, the server includes means for a user to register visual information and characters that the user likes, means for saving the registered visual information and characters that the user likes, means for automatically generating digital emojis based on the content of a conversation, means for presenting the generated digital emojis to the user, and means for the user to select the presented digital emojis. This allows the user to quickly find digital emojis that match their preferences, enabling smoother communication without interrupting the flow of conversation.

[0587] "User" means an individual or organization that uses the system to register their preferred visual information or characters and communicates through messaging services.

[0588] "Visual information" refers to visual content such as favorite images, designs, characters, etc. registered by users.

[0589] "Character" refers to an image of a specific person, animal, fictional creature, or other character that a user likes.

[0590] "Digital Emoji" are system-generated illustrations or icons for use in messages.

[0591] An "artificial intelligence model" is a software program that includes machine learning algorithms to analyze user preferences and conversational content and generate digital emojis based on that analysis.

[0592] An "image provider" is an individual or organization that provides existing images to be used as training data for an artificial intelligence model.

[0593] "Conversation content" refers to the content of text messages and discussions exchanged between users via messaging services.

[0594] "Messaging Service" refers to an application or platform that allows users to send and receive text messages.

[0595] "Server" refers to the computer system that stores and manages user preference information and generated digital emojis, and generates digital emojis as needed.

[0596] This system allows users to register their preferred visual information and characters, and then automatically generates and presents digital emojis based on that information in response to the content of the conversation. To implement this system, three main entities work together: a server, a terminal, and a user.

[0597] Server Processing

[0598] 1. Storing your information and preferences

[0599] The server receives the visual information and character data that the user sends from their device and stores it in a database. Databases such as MySQL and PostgreSQL can be used for efficient information management.

[0600] 2. Training the AI ​​model

[0601] The server receives existing visual data provided by image providers and uses it as training data for an AI model. Using machine learning frameworks such as TensorFlow and PyTorch, it trains a model that can tag images based on visual information and generate digital emojis that adapt to the user's conversation.

[0602] 3. Digital Emoji Generation and Presentation

[0603] Upon receiving a user's message, the server uses NLP technology to analyze its content and generate digital emojis based on appropriate visual information and characters. The generated digital emoji candidates are packaged in JSON format and sent to the user's device.

[0604] Terminal handling

[0605] 1. Providing a user interface

[0606] The device provides an interface for users to register their favorite visual information and characters. Users can easily register visual information using a smartphone app or web app. It also provides an interface that displays digital emojis as the conversation progresses.

[0607] 2. Data transmission and reception

[0608] The device sends the visual information data and conversation log entered by the user to the server using an HTTP POST request. The server then receives a list of digital emoji candidates and displays them to the user.

[0609] 3. Selection and Use of Digital Emojis

[0610] The user selects the desired digital emoji from the provided ones and uses the interface to insert them into the conversation. The selected digital emoji is then sent to the other person via the terminal.

[0611] User Actions

[0612] 1. Register your preferences

[0613] Users can specify their preferred visual information and characters through the app on their device. For example, if a user likes a "smiling cat," they enter this information in the app's input field and send it to the server.

[0614] 2. Starting a dialogue

[0615] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[0616] 3. Checking and using digital emojis

[0617] The user can select an appropriate digital emoji from the candidates sent by the server. For example, in response to the message "I had a great day," a digital emoji of a "smiling cat" is suggested. The user selects this emoji and sends it to the person they are speaking with.

[0618] Specific examples

[0619] 1. Register your favorite visual information and characters

[0620] User A registers "dog characters" as a preference. He enters this information into the device app and sends it to the server.

[0621] 2. Interaction and Digital Emoji Generation

[0622] When User A sends the message "good night," the server parses the message and generates a digital emoji of a dog saying "good night."

[0623] 3. Check and Use

[0624] User A checks the list of digital emojis sent from the server, selects the digital emoji "Goodnight dog" and sends it to the person he is talking to.

[0625] Prompt Sentence Examples

[0626] 1. "Please register dog characters as your favorite."

[0627] 2. "What did you have for lunch today?"

[0628] 3. "What emoji is appropriate for saying thank you?"

[0629] This system allows users to freely create digital emojis according to their preferences and enjoy richer communication. The AI ​​model also provides high-quality digital emojis that match the user's preferences.

[0630] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0631] System processing steps

[0632] Step 1:

[0633] The user opens the application on their device and registers their preferred visual information and characters. The user enters "smiling cat" as their preference and presses the send button. At this time, the device packages the entered information as JSON-formatted data. The input is visual information such as "smiling cat," and the output is JSON-formatted data.

[0634] Step 2:

[0635] The terminal sends the packaged JSON data to the server using an HTTP POST request: the input is the packaged JSON data, and the output is an HTTP request to the server's endpoint.

[0636] Step 3:

[0637] The server receives the HTTP request and parses the JSON data. The parsed results are saved in a database. The input is JSON data, and the output is visual information data saved in the database. The specific operation is to execute an INSERT query against MySQL.

[0638] Step 4:

[0639] The server acquires existing visual information data provided by the image provider. It uses this data to train an AI model. The input is the visual information data provided by the image provider, and the output is the trained AI model. Specifically, the machine learning algorithm is trained using TensorFlow and PyTorch.

[0640] Step 5:

[0641] A user starts a message exchange with a conversation partner, for example, sending a message such as "I had fun today." The input is the text message "I had fun today," and the output is the message sent from the terminal to the server.

[0642] Step 6:

[0643] The server receives the user's message and analyzes the message content using NLP techniques. The input is the text message and the output is the analysis result. Specific operations include text analysis using spaCy and Transformers.

[0644] Step 7:

[0645] Based on the analysis results, the server selects appropriate visual information and characters to generate a digital emoji. This process uses a trained AI model. The input is the analysis results and the trained model, and the output is a digital emoji. Specific operations include running the AI ​​model's inference engine.

[0646] Step 8:

[0647] The server packages the generated digital emoji candidates in JSON format and sends them to the user's device. The input is the digital emoji, and the output is an HTTP response to the user's device. The specific operations include generating and sending data in JSON format.

[0648] Step 9:

[0649] The device analyzes the received digital emoji candidates and displays them on the user interface. The input is digital emoji data in JSON format, and the output is digital emoji candidates displayed on the user interface.

[0650] Step 10:

[0651] The user selects the desired digital emoji from the presented ones and inserts it into the conversation. For example, they select the digital emoji "smiling cat" and press the send button. The input is the user's selection, and the output is the transmission of the digital emoji to the conversation partner.

[0652] In this way, the user, device, and server all work together to create a system that can quickly and smoothly generate and display digital emojis based on the user's preferences.

[0653] (Application example 1)

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

[0655] In traditional brick-and-mortar stores, it was difficult to provide personalized suggestions tailored to individual customer preferences and needs, resulting in limited means for improving customer satisfaction. Furthermore, effective use of visual elements such as stamps and illustrations was also limited, leading to a tendency for dialogue with customers to be monotonous.

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

[0657] In this invention, the server includes a means for users to register their favorite designs and characters, a means for saving the registered favorite designs and characters, and a means for automatically generating stamps based on the content of conversations, which enables personalized suggestions to be made based on the content of customer conversations in physical stores.

[0658] A "user" is a user of the system who registers their preferred designs and characters to receive personalized services.

[0659] "Pictures and characters" refer to the illustrations and image designs that users prefer to register, and are the visual elements that form the basis for generating stamps.

[0660] "Stamps" are emojis or images used during conversations to visually express users' emotions and messages.

[0661] "Automatically generating stickers" refers to the process of using AI models and algorithms to create appropriate stickers based on the user's conversation content and registration information.

[0662] "Presenting" refers to the act of showing the generated stamp to the user.

[0663] "Selecting" refers to the act of the user choosing the stamp that best suits their taste from the ones presented.

[0664] A "physical store" refers to a commercial or service facility that exists in a physical location and where customers can visit in person to receive services.

[0665] "Customers" refer to shoppers who visit physical stores or service users and who receive personalized offers.

[0666] "Personalized offers" refers to individualized service and product proposals tailored to the customer's preferences and needs.

[0667] "Training an AI model" refers to the process of using illustrations and data to teach an artificial intelligence model and strengthen it to work effectively for a specific task.

[0668] "Content Creator" refers to a person or organization that creates illustrations or other visual content and provides it to the System.

[0669] "Existing illustrations" refer to visual materials previously created by content creators and provided for use as training data.

[0670] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[0671] Server Processing

[0672] 1. Storing your information and preferences

[0673] The server receives the user's registered favorite images and characters and stores them in a database. This allows the user to change their favorite information as many times as they like, and the system always keeps the latest user preferences.

[0674] 2. Training the AI ​​model

[0675] The server collects existing illustration data provided by content creators and uses it to train an AI model that is trained to generate stickers based on the tagged data and the user's conversation content. This process uses deep learning frameworks such as TensorFlow and PyTorch.

[0676] 3. Stamp generation and presentation

[0677] The server analyzes the user's message and generates appropriate stickers based on the user's preferences and the content of the conversation. The generated sticker candidates are sent to the user's device and displayed. Specifically, for example, a prompt phrase such as "new item arrival with a blue cat character" is input into the generative AI model to generate an appropriate sticker.

[0678] Terminal handling

[0679] 1. Providing a user interface

[0680] The device provides an interface for users to register their favorite pictures and characters, as well as an interface for displaying stamps during conversations. It is implemented as an application for smartphones and tablets.

[0681] 2. Data transmission and reception

[0682] The device sends the user's registration information and interaction log to the server. This conveys the user's interaction context to the server, which then generates stamps based on that information. The device receives the generated stamp list and displays it to the user.

[0683] 3. Selecting and Using Stamps

[0684] The user selects the desired stamp from the list of stamp candidates presented by the server through the terminal interface, and the selected stamp is inserted into the message and sent to the other party.

[0685] User Actions

[0686] 1. Register your preferences

[0687] Users use the device interface to specify their preferred image or character, such as "a smiling cat" or "I like blue items," and then input this information into the app and send it to the server.

[0688] 2. Starting a dialogue

[0689] Users can interact with store staff or AI chatbots in physical stores, for example by sending messages such as "Have new products arrived?"

[0690] 3. Check and use stamps

[0691] The user selects an appropriate stamp from the list of stamp candidates sent by the server. For example, the "Blue Cat" stamp is suggested for the message "Have new items arrived?" The user selects this stamp, inserts it into the conversation, and sends it.

[0692] Software and Hardware Requirements

[0693] Software used:

[0694] Server software: Linux (e.g., Ubuntu 20.04), Flask web framework, PostgreSQL database

[0695] AI model training: TensorFlow or PyTorch

[0696] Terminal applications: iOS app (Swift), Android app (Kotlin)

[0697] Hardware used:

[0698] Server hardware: High-performance server machine (e.g., Dell PowerEdge series)

[0699] Device: iOS or Android smartphone or tablet

[0700] Specific examples

[0701] If User A registers "Smiling Cat" as a preference, the server stores this. When User A sends a message to a physical store asking "Have new items arrived?", the server analyzes this message and inputs the prompt "New items arrived with a smiling cat character" into the AI ​​model. The AI ​​model generates an appropriate stamp and sends it to the device. User A selects the "Smiling Cat" stamp and sends it to the store clerk or chatbot, achieving personalized communication.

[0702] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0703] Step 1:

[0704] Registering user preferences

[0705] The server receives the user's favorite images and characters sent from the device, stores this information in a database, and updates the user's favorite list.

[0706] Input: User preference information (e.g., "smiling cats," "blue items")

[0707] Output: User preference information stored in a database

[0708] Step 2:

[0709] Collecting learning data and training AI models

[0710] The server collects existing illustration data provided by content creators, labels it, and trains the AI ​​model, using deep learning frameworks such as TensorFlow and PyTorch to enable the model to generate appropriate stamps.

[0711] Input: Existing illustration data and label information

[0712] Output: A trained AI model

[0713] Step 3:

[0714] Message parsing and prompt generation

[0715] The server receives the user's interactive message sent from the device and analyzes its content. Based on the analysis results, it generates a prompt sentence and inputs it into the AI ​​model. For example, if the message is "Have new items arrived?", it generates the prompt sentence "new item arrival with a smiling cat character."

[0716] Input: User interaction message

[0717] Output: Generated prompt statement

[0718] Step 4:

[0719] Stamp Generation

[0720] The server inputs the generated prompt into the AI ​​model to generate a corresponding stamp. The AI ​​model analyzes the prompt and outputs a stamp that combines an appropriate image and character.

[0721] Input: Generated prompt text

[0722] Output: Generated stamp

[0723] Step 5:

[0724] Stamp list presentation

[0725] The server sends the generated stamp list to the device and presents it to the user, who can then view the stamps displayed through the device interface.

[0726] Input: Generated stamp list

[0727] Output: Stamp list displayed on the device

[0728] Step 6:

[0729] Selecting and Using Stamps

[0730] The user selects the desired stamp from a list of stamps presented to them using the terminal interface, and the selected stamp is inserted into the message and sent to the interlocutor.

[0731] Input: User selects stamp

[0732] Output: Send selected stamps

[0733] Through the above processing steps, appropriate stamps are automatically generated based on the content of the user's dialogue, realizing personalized communication.

[0734] 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.

[0735] The system of the present invention allows users to register their favorite pictures and characters, and automatically generates stamps based on the content of the conversation and an emotion engine, thereby providing users with appropriate stamps.

[0736] Server Processing

[0737] 1. Storing your information and preferences

[0738] The server receives information about the preferred designs and characters sent by the user and stores it in a database.

[0739] 2. Training the AI ​​model

[0740] The server receives existing illustration data provided by the illustrator and uses it as training data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stickers based on the user's conversation content and emotions.

[0741] 3. Use of Emotion Engine

[0742] The server analyzes the content of the user's conversation and uses an emotion engine to recognize the user's emotions from that content. The emotion engine uses multiple language models and emotion recognition algorithms to analyze the user's emotions with high accuracy.

[0743] 4. Stamp generation and presentation

[0744] Based on the user's message and the perceived emotion, the AI ​​model generates appropriate stickers, which are then sent to the user's device for display.

[0745] Terminal handling

[0746] 1. Providing a user interface

[0747] The device provides an interface for users to register their favorite pictures and characters, as well as an interface that displays stamps based on the content of conversations and emotions.

[0748] 2. Data transmission and reception

[0749] The device sends the user's registration information and interaction log to the server, which then conveys the user's interaction context and emotional information to the server. The device also receives a stamp list sent from the server and displays it to the user.

[0750] 3. Selecting and Using Stamps

[0751] The system provides an interface for users to select the desired stamp from the provided stamps and insert it into the conversation. The selected stamp is then sent from the device to the conversation partner.

[0752] User Actions

[0753] 1. Register your preferences

[0754] Users can specify their favorite images and characters through the app on their device. For example, if a user likes "smiling dogs," they enter this information into the app and send it to the server.

[0755] 2. Starting a dialogue

[0756] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[0757] 3. Emotional Recognition

[0758] The server analyzes the received message and uses an emotion engine to identify the user's emotion. For example, it recognizes positive emotion from the message "I had fun today."

[0759] 4. Check and use stamps

[0760] The user selects an appropriate stamp from among the stamp candidates sent by the server based on the content of the conversation and the recognized emotion. For example, a "smiling dog" stamp is suggested for the message "I had fun today." The user selects this stamp, inserts it into the conversation, and sends it.

[0761] Specific examples

[0762] 1. Register your favorite designs and characters

[0763] User A registers "cat characters" as a preference. He enters this information into the device app and sends it to the server.

[0764] 2. Dialogue and Emotion Recognition

[0765] When User A sends a message saying "Work is done! Yay!", the server analyzes this message and uses an emotion engine to recognize positive emotions.

[0766] 3. Stamp creation and selection

[0767] The server uses an AI model to generate a "joyful cat" stamp based on the recognized positive emotion.

[0768] The server sends stamp candidates to the user's device, and User A selects the "Joyful Cat" stamp and sends it to the person he or she is talking to.

[0769] This system allows users to easily create stamps based on their preferences and emotions, allowing them to enjoy richer communication.

[0770] The processing flow will be explained below.

[0771] The processing steps from when the user registers their favorite pictures or characters to when the emotion engine is used to generate stamps during a conversation

[0772] Step 1: Users register their favorite designs and characters

[0773] 1. User: Enter your favorite image or character into the device app. For example, "dog character."

[0774] 2. Terminal: Converts the user's input preferences into data packets.

[0775] 3. Terminal: Sends the converted data packets to the server.

[0776] Step 2: The server stores the user information

[0777] 1. Server: Analyzes data packets received from users and extracts their preferred images and character information.

[0778] 2. Server: Stores the extracted information in a database.

[0779] Step 3: Train the AI ​​model

[0780] 1. Illustrator: Upload an existing illustration to the server as learning data.

[0781] 2. Server: Stores the received illustration data in a database and performs preprocessing (size adjustment, noise removal, etc.).

[0782] 3. Server: Trains the AI ​​model using the preprocessed illustration data, properly tags each illustration, and generates stickers for the corresponding user conversation and emotion.

[0783] Step 4: User initiates interaction

[0784] 1. User: Sends a message to the person they are interacting with through the app, for example, "I had a great time today."

[0785] 2. Terminal: Converts the user's message into data packets and sends them to the server.

[0786] Step 5: The emotion engine recognizes the user's emotions

[0787] 1. Server: Analyzes the received message data.

[0788] 2. Server: Recognizes the user's emotion from the message content using an emotion engine. For example, recognize positive emotion from the message "I had fun today."

[0789] Step 6: The server generates and presents the stamp

[0790] 1. Server: Using an AI model, the server generates appropriate stamps based on the analysis results, the user's preferred designs, character information, and recognized emotions.

[0791] 2. Server: Arranges the generated stamp candidates into a list and sends it to the user's device.

[0792] Step 7: Your device will display sticker suggestions

[0793] 1. Terminal: The stamp list received from the server is displayed on the user interface, visually presenting multiple stamps in thumbnail format.

[0794] 2. User: Select the desired stamp from the presented stamp list.

[0795] Step 8: User selects sticker and sends it

[0796] 1. User: Selects the "Smiling Dog" stamp from the presented stamps and sends it to the person he or she is talking to.

[0797] 2. Terminal: Converts the selected stamp data into a data packet and sends it to the other terminal.

[0798] In this way, the user, device, server, and emotion engine work together to enable users to easily create stamps based on their preferences and emotions, and enjoy rich communication.

[0799] Example 2

[0800] 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."

[0801] Conventional stamp generation systems have had problems such as making it difficult for users to easily select stamps that match their preferences, and not being able to provide appropriate stamps based on emotions in a timely manner. Furthermore, stamp generation is not sufficiently automated, making it impossible to generate stamps that take into account the user's conversation content and emotions.

[0802] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0803] In this invention, the server includes means for users to register their favorite images and characters, means for saving the registered favorite images and characters, means for automatically generating stamps based on the conversation content and the emotion engine, means for presenting the generated stamps to the user terminal, and means for the user to select the presented stamps via the terminal, thereby enabling timely provision of stamps based on the user's preferences and emotions.

[0804] "User" refers to an individual or corporation that uses the system, and is the entity that primarily performs the operations of registering, selecting, and sending stamps.

[0805] "Images and characters" are visual expressions designated by users as their preferences, and are the materials used to generate stamps.

[0806] A "stamp" is an image or icon added to a message in digital communication to visually convey emotions or intentions.

[0807] A "generative AI model" is a model that uses artificial intelligence to automatically generate stamps based on user preferences and conversation content.

[0808] An "emotion engine" is a system or algorithm that analyzes the content of a user's conversation and recognizes the emotions contained within it.

[0809] The "database" is a system for storing and managing users' preferred images, characters, and related information such as conversation logs.

[0810] A "prompt" is text information that is input into a generative AI model and used to generate a specific stamp or response.

[0811] A "terminal" is a device used by a user to access and operate the system, such as a smartphone, tablet, or PC.

[0812] A "server" is a central computer system that operates and manages the entire system, and processes data and generates stamps in response to user requests.

[0813] "Interface" is a general term for the operation screen and input / output devices that allow users to interact with the system.

[0814] The system of the present invention allows users to register their favorite images and characters, and automatically generates stamps based on the content of the conversation and an emotion engine, thereby providing appropriate stamps to users. Specific embodiments of the system are described below.

[0815] Server Processing

[0816] Storing User Information and Preferences

[0817] The server receives the user's favorite images and character information sent from the device and stores it in a database. "MySQL" can be used as the database software. For example, information such as the user ID, favorite character, and registration date and time is stored.

[0818] Training an AI model

[0819] The server receives existing image data provided by the image creator and uses it as training data for the AI ​​model. The image data is tagged, for example, a cat image is tagged with "cat," "cute," and "smiling." Then, using TensorFlow and PyTorch, a stamp generation model is trained based on the conversation content and emotions.

[0820] Use of emotion engine

[0821] The server receives the user's conversation content sent from the device and uses an emotion engine to recognize the user's emotions from the content. The emotion engine can use tools such as Google Cloud Natural Language API or IBM Watson. This allows for highly accurate analysis of the user's emotions.

[0822] Stamp generation and presentation

[0823] The server uses an AI model to automatically generate appropriate stickers based on the recognized emotions and user preferences, and sends the generated sticker candidates to the user's device, where they are presented to the user.

[0824] Terminal handling

[0825] Providing a user interface

[0826] The device provides an interface for users to register their favorite images and characters, such as a form entry screen and an image selection screen, as well as an interface for displaying stamps based on the user's dialogue and emotions.

[0827] Sending and receiving data

[0828] The terminal transmits the user's input preference information to the server, transmits the user's interaction log to the server, conveys the user's interaction context and emotion information to the server, and receives the stamp list transmitted from the server and displays it to the user.

[0829] Selecting and Using Stamps

[0830] The terminal provides an interface for the user to select a desired stamp from the stamps presented and insert it into the conversation. The selected stamp is then sent from the terminal to the conversation partner.

[0831] User Actions

[0832] Register your preferences

[0833] The user launches the app on their device, inputs their favorite image or character, for example, "smiling dog," and sends it to the server.

[0834] Starting a conversation

[0835] The user opens a message exchange screen with the person they are talking to, enters a message such as "I had fun today," and sends it.

[0836] Emotion recognition

[0837] The server analyzes the received message and uses an emotion engine to identify the user's emotion. For example, it recognizes positive emotion from the message "I had fun today."

[0838] Checking and using stamps

[0839] The stamp candidates sent from the server are displayed on the user's device, and the user selects the appropriate stamp from the presented stamps and presses the select button.

[0840] Specific examples

[0841] 1. Register your favorite images and characters

[0842] User A registers "cat characters" as a preference. He enters "cat" into the device app and sends it to the server.

[0843] 2. Dialogue and Emotion Recognition

[0844] When User A sends a message saying "Work is done! Yay!", the server analyzes this message and uses an emotion engine to recognize positive emotions.

[0845] 3. Stamp creation and selection

[0846] The server generates a stamp of a happy cat using an AI model based on the recognized positive emotion. The server sends stamp candidates to the user's device, and User A selects the "happy cat" stamp and sends it to the person he or she is talking to.

[0847] Prompt Sentence Examples

[0848] 1. Register your preferences for designs and characters

[0849] "My favorite character is 'Cat'. Please register this information."

[0850] 2. Message sending for dialogue and emotion recognition

[0851] "Job done! Yay!"

[0852] 3. Using the generated stamp

[0853] Select "Joyful Cat" and send.

[0854] This system allows users to easily create stamps based on their preferences and emotions, allowing them to enjoy richer communication.

[0855] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0856] Step 1:

[0857] Users register their favorite images and characters

[0858] Input: The user inputs and sends their preferred image or character through the device interface.

[0859] How it works: The device receives information entered by the user through forms and selection screens and sends it to the server.

[0860] Output: The device sends the preference information entered by the user to the server, which receives this information.

[0861] Step 2:

[0862] Storing User Information and Preferences

[0863] Input: The user's preferred image and character information sent in Step 1.

[0864] Operation: The server stores the received information in a database. For example, it uses "MySQL" to register the user ID, favorite character, and registration date and time.

[0865] Output: The server sends a confirmation message to the device indicating that the save is complete.

[0866] Step 3:

[0867] Training an AI model

[0868] Input: Existing image data and tagging data provided by the image creator.

[0869] How it works: The server tags images and preprocesses the data. This preprocessed data is used to train a generative AI model using TensorFlow and PyTorch. The model learns to generate stickers based on the user's conversation content and emotions using the tag information.

[0870] Output: A fully trained generative AI model.

[0871] Step 4:

[0872] Receiving conversation content

[0873] Input: Message exchanges between the user and their interlocutor.

[0874] How it works: The device sends the messages the user sends to the server, which receives and stores them.

[0875] Output: The server is ready to parse and process the received conversation content.

[0876] Step 5:

[0877] Emotion recognition

[0878] Input: The conversation received in step 4.

[0879] How it works: The server uses an emotion engine to analyze the conversation and identify the user's emotions. For example, it uses Google Cloud Natural Language API or IBM Watson to analyze emotion data.

[0880] Output: Identified user sentiment data.

[0881] Step 6:

[0882] Stamp Generation

[0883] Input: Identified emotion data and user's preferred image or character information.

[0884] How it works: The server generates optimal stamps using a generative AI model. Emotional data and preference information are input to the generative AI model as prompts.

[0885] Output: The generated stamp candidates.

[0886] Step 7:

[0887] Sending and displaying stamps

[0888] Input: Generated stamp candidates.

[0889] Operation: The server sends the generated stamp candidates to the user terminal and displays them to the user. The terminal displays the stamp candidates in the user interface.

[0890] Output: User can see the stamp suggestions.

[0891] Step 8:

[0892] Select a stamp

[0893] Input: The stamp selected by the user.

[0894] How it works: The user selects the desired stamp from the ones presented and presses the "Send" button. The device then sends this selection to the server.

[0895] Output: The selected stamps are sent to the server.

[0896] Step 9:

[0897] Send Selected Stamps

[0898] Input: The stamp selected in step 8.

[0899] Operation: The server sends the selected stamp to the conversation partner. The terminal displays the selected stamp to the conversation partner.

[0900] Output: The stamp is sent to the person you are talking to and displayed.

[0901] This allows users to easily send stamps based on their preferences and emotions to their interlocutors, enabling richer communication.

[0902] (Application example 2)

[0903] 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."

[0904] Communication with customers in virtual stores is mainly text-based, resulting in limited emotional communication. Furthermore, it is difficult to respond flexibly to customer emotions, limiting the quality of service. Given this background, there is a need for a system that can appropriately recognize customer emotions in virtual stores and provide appropriate stamps to enable richer communication.

[0905] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0906] In this invention, the server includes means for a user to register their favorite pictures and characters, means for saving the registered favorite pictures and characters, means for automatically generating stamps based on conversation content and emotion analysis, means for presenting the generated stamps to the user, means for the user to select the presented stamps, emotion analysis means for recognizing emotions from the content of the user's message, and means for presenting stamps generated in accordance with the recognized emotions on the virtual store interface. This makes it possible to improve the quality of communication by recognizing customer emotions in the virtual store in real time and providing stamps in response to those emotions.

[0907] "User" refers to a person or company that uses the system to register their favorite designs or characters and generate and use stamps.

[0908] "Pictures and characters" are illustrations, images, symbols, etc. that users select as their preferences.

[0909] "Storage means" refers to a storage device or database for storing information about the images and characters registered by the user.

[0910] "Conversation content" refers to messages and text information sent by users on the system.

[0911] "Sentiment analysis" is the process of analyzing the content of a user's message to recognize their emotional state.

[0912] "Stamps" are emoticons or illustrations generated for users to use in their messages.

[0913] "Means for automatic generation" refers to the process by which the system automatically generates stamps based on the content of the user's conversation and sentiment analysis.

[0914] The "presentation means" is an interface for visually presenting the generated stamp to the user.

[0915] The "selection means" is an operation interface that allows the user to select the desired stamp from among the stamps presented.

[0916] "Emotion analysis tools" are algorithms or software that recognize emotions from users' messages.

[0917] A "virtual store" is an online store that offers products and services over the Internet.

[0918] An "AI model" is an artificial intelligence algorithm that generates stamps based on the content of the conversation and emotions.

[0919] The "virtual store interface" is the user interface through which customers interact with the system.

[0920] The system of the present invention allows users to register their favorite images and characters, and automatically generates and displays stamps based on conversation content and sentiment analysis. In implementing this system, the server, terminal, and user components work in conjunction with each other.

[0921] Server Processing

[0922] 1. Storing your information and preferences

[0923] The server receives the user's preferred designs and characters and stores them in a database. New designs and characters registered by the user are updated in real time.

[0924] 2. Training the AI ​​model

[0925] The server receives existing illustration data provided by the illustrator and uses it as training data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stickers based on the user's conversation content and emotions. Specific software used includes TensorFlow and PyTorch.

[0926] 3. Use of sentiment analysis engines

[0927] The server analyzes the user's conversation content and uses a sentiment analysis engine to recognize the user's emotions from the content. This engine analyzes emotions with high accuracy using natural language processing models (e.g., BERT and GPT-3).

[0928] 4. Stamp generation and presentation

[0929] Based on the user's message and the recognized emotion, the AI ​​model generates appropriate stickers. The generated sticker candidates are sent to the user's device and displayed. Generative Adversarial Networks (GANs) and DALL-E are used for generation.

[0930] Terminal handling

[0931] 1. Providing a user interface

[0932] The device provides an interface for users to register their favorite pictures and characters, as well as an interface that displays stamps based on the content of conversations and emotions.

[0933] 2. Data transmission and reception

[0934] The device sends the user's registration information and interaction log to the server, which then conveys the user's interaction context and emotional information to the server. The device also receives a stamp list sent from the server and displays it to the user.

[0935] 3. Selecting and Using Stamps

[0936] It provides an interface for users to select the desired stamp from the provided stamps, and the selected stamp is sent from the terminal to the interlocutor.

[0937] User Actions

[0938] 1. Register your preferences

[0939] Users can specify their favorite images and characters through the app on their device. For example, if a user likes "smiling dogs," they enter this information into the app and send it to the server.

[0940] 2. Starting a dialogue

[0941] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[0942] 3. Emotional Recognition

[0943] The server analyzes the received message and uses a sentiment analysis engine to identify the user's sentiment. For example, it recognizes positive sentiment from a message such as "I had fun today."

[0944] 4. Check and use stamps

[0945] The user selects an appropriate stamp from among the stamp candidates sent by the server based on the content of the conversation and the recognized emotion. For example, a "smiling dog" stamp is suggested for the message "I had fun today." The user selects this stamp, inserts it into the conversation, and sends it.

[0946] Specific examples

[0947] For example, if User A registers "cat characters" as a favorite and sends a message saying "Work is done! Yay!", the server will analyze this message and recognize the positive emotion. Based on this, a "joyful cat" stamp will be generated and presented to User A. User A can then select this stamp and send it to the person they are interacting with, achieving engaging, emotion-based communication.

[0948] Example prompt sentence:

[0949] A user sent a message saying, "I really liked this product!" Recognize the emotion from this message and generate an appropriate sticker based on the user's favorite character, "cat."

[0950] In this way, the system of the present invention automatically generates and provides stamps that correspond to the user's emotions, thereby improving the user experience in the virtual store.

[0951] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0952] Step 1:

[0953] The server provides the terminal with an interface that allows users to register their favorite pictures and characters.

[0954] Input: User's preferred designs and character information

[0955] Output: Temporarily save registered information

[0956] Specific operation: The user inputs information such as "smiling dog" through the device interface, and the device temporarily stores this preference information.

[0957] Step 2:

[0958] The terminal transmits the user's registered favorite images and character information to the server.

[0959] Input: User preference information (e.g., "smiling dogs")

[0960] Output: Data sent to the server, confirmation message

[0961] Specific operation: The preference information is sent from the device to the server, which receives it and stores it in the database. After completion, a confirmation message is displayed on the device.

[0962] Step 3:

[0963] The server stores the registration information submitted by the user in a database.

[0964] Input: User preference information

[0965] Output: User preferences stored in a database

[0966] What happens: The server updates the database, storing the user's preferences, such as "smiling dogs."

[0967] Step 4:

[0968] The server provides an interface for analyzing the content of the user's conversation.

[0969] Input: A message that the user types

[0970] Output: Send message to server

[0971] Specific operation: The device sends the message entered by the user in the chat (e.g., "Today was fun") to the server.

[0972] Step 5:

[0973] The server analyzes the received message using a sentiment analysis engine.

[0974] Input: User's message

[0975] Output: Parsed emotion data

[0976] Specific operation: The server uses a natural language processing model (BERT or GPT-3) to analyze positive emotions from the message "I had fun today."

[0977] Step 6:

[0978] The server generates stamps based on the analyzed emotional data and the user's preferences.

[0979] Input: Emotion data, preferred picture information

[0980] Output: Generated stamp

[0981] Specific operation: Using AI models (TensorFlow, GANs, DALL-E), we generate "smiling dog" stamps that match positive emotions.

[0982] Step 7:

[0983] The server transmits the generated stamp to the terminal and presents it to the user.

[0984] Input: Generated stamp data

[0985] Output: Send stamp data to the terminal

[0986] Specific operation: The server sends the "smiling dog" stamp data to the terminal and displays the stamp on the display interface.

[0987] Step 8:

[0988] The terminal provides an interface for the user to select from the presented stamps.

[0989] Input: Presented stamp

[0990] Output: User selection data

[0991] Specific behavior: The user selects the "smiling dog" sticker that is displayed.

[0992] Step 9:

[0993] The terminal operates to transmit the stamp selected by the user to the interlocutor.

[0994] Input: User's stamp selection data

[0995] Output: Send stamp to the person you are talking to

[0996] Specific operation: The device sends the "smiling dog" stamp selected by the user to the person it is talking to.

[0997] In this way, stamps are generated and displayed in real time according to the user's conversation content and emotions, enabling richer communication.

[0998] 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.

[0999] 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.

[1000] 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.

[1001] [Third embodiment]

[1002] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1003] 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.

[1004] 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).

[1005] 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.

[1006] 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.

[1007] 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).

[1008] 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.

[1009] 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.

[1010] 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.

[1011] 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.

[1012] 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.

[1013] 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."

[1014] To implement the system of the present invention, three main entities work together: the server, the terminal, and the user. This system allows users to register their favorite pictures and characters, and then uses that information to automatically generate stamps based on the content of the conversation, providing appropriate stamps to the user.

[1015] Server Processing

[1016] 1. Storing your information and preferences

[1017] The server receives the information about the preferred designs and characters sent by the user and stores it in a database, allowing the system to accumulate the user's registered preferences.

[1018] 2. Training the AI ​​model

[1019] The server receives existing illustration data provided by the illustrator and uses it as learning data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stamps based on the user's conversation content.

[1020] 3. Stamp generation and presentation

[1021] When a user's message is received, the server analyzes the content, selects appropriate images and characters, and generates stamps. The generated stamp candidates are sent to the user's device and displayed.

[1022] Terminal handling

[1023] 1. Providing a user interface

[1024] The device provides an interface for users to register their favorite pictures and characters, as well as an interface for displaying stamps according to the flow of conversation.

[1025] 2. Data transmission and reception

[1026] The device sends the user's registration information and interaction log to the server, which conveys the user's interaction context to the server. The device receives the stamp list sent from the server and displays it to the user.

[1027] 3. Selecting and Using Stamps

[1028] The system provides an interface for users to select the desired stamp from the provided stamps and insert it into the conversation. The selected stamp is then sent from the device to the conversation partner.

[1029] User Actions

[1030] 1. Register your preferences

[1031] Users can specify their favorite designs and characters through the app on their device. For example, if a user likes a "smiling cat," they enter this information into the app and send it to the server.

[1032] 2. Starting a dialogue

[1033] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[1034] 3. Check and use stamps

[1035] The user selects an appropriate stamp from the list of stamp candidates sent by the server based on the content of the conversation. For example, a "smiling cat" stamp is suggested for the message "Today was fun." The user selects this stamp, inserts it into the conversation, and sends it.

[1036] Specific examples

[1037] 1. Register your favorite designs and characters

[1038] User A registers "dog characters" as a preference. He enters this information into the device app and sends it to the server.

[1039] 2. Interaction and stamp generation

[1040] When user A sends the message "good night," the server analyzes this message and generates a stamp of a dog saying "good night."

[1041] 3. Check and Use

[1042] User A checks the stamp list sent from the server, selects the "Goodnight Dog" stamp and sends it to the person he or she is talking to.

[1043] This system allows users to freely create stamps that suit their preferences and enjoy rich communication.

[1044] The processing flow will be explained below.

[1045] The process steps for users to register their favorite designs and characters and use stamps during conversations

[1046] Step 1: Users register their favorite designs and characters

[1047] 1. User: Enter your favorite image or character into the device app. For example, "dog character."

[1048] 2. Terminal: Converts the user's input preferences into data packets.

[1049] 3. Terminal: Sends the converted data packets to the server.

[1050] Step 2: The server stores the user information

[1051] 1. Server: Analyzes data packets received from users and extracts their preferred images and character information.

[1052] 2. Server: Stores the extracted information in a database.

[1053] Step 3: Train the AI ​​model

[1054] 1. Illustrator: Upload an existing illustration to the server as learning data.

[1055] 2. Server: Stores the received illustration data in a database and performs preprocessing (size adjustment, noise removal, etc.).

[1056] 3. Server: Trains the AI ​​model using the preprocessed illustration data, properly tags each illustration, and generates stickers for the corresponding user conversations.

[1057] Step 4: User initiates interaction

[1058] 1. User: Sends a message to the person they are interacting with through the app, for example, "I had a great time today."

[1059] 2. Terminal: Converts the user's message into data packets and sends them to the server.

[1060] Step 5: The server generates and presents the stamp

[1061] 1. Server: Analyzes the received message data and understands the conversation content.

[1062] 2. Server: Taking into account the analysis results and the user's preferred designs and character information, the server uses an AI model to generate appropriate stamps.

[1063] 3. Server: Arranges the generated stamp candidates into a list and sends it to the user's device.

[1064] Step 6: Your device will display suggested stickers

[1065] 1. Terminal: The stamp list data received from the server is displayed on the user interface, visually presenting multiple stamps in thumbnail format.

[1066] 2. User: Select the desired stamp from the presented stamp list.

[1067] Step 7: User selects sticker and sends it

[1068] 1. User: Selects the "Smiling Dog" stamp from the presented stamps and sends it to the person he or she is talking to.

[1069] 2. Terminal: Converts the selected stamp data into a data packet and sends it to the other terminal.

[1070] In this way, users, devices, and servers work together to enable users to easily create stamps based on their preferences and enjoy rich communication.

[1071] Example 1

[1072] 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."

[1073] In conventional messaging systems, users must manually select emojis and stickers, making it difficult to quickly find the right stickers that match their individual preferences. This disrupts the flow of conversation and detracts from the user experience. Furthermore, there is no automated method for identifying stickers based on individual user preferences, requiring constant manual intervention. Therefore, there is a need to improve user convenience and enable richer communication.

[1074] 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.

[1075] In this invention, the server includes means for a user to register visual information and characters that the user likes, means for saving the registered visual information and characters that the user likes, means for automatically generating digital emojis based on the content of a conversation, means for presenting the generated digital emojis to the user, and means for the user to select the presented digital emojis. This allows the user to quickly find digital emojis that match their preferences, enabling smoother communication without interrupting the flow of conversation.

[1076] "User" means an individual or organization that uses the system to register their preferred visual information or characters and communicates through messaging services.

[1077] "Visual information" refers to visual content such as favorite images, designs, characters, etc. registered by users.

[1078] "Character" refers to an image of a specific person, animal, fictional creature, or other character that a user likes.

[1079] "Digital Emoji" are system-generated illustrations or icons for use in messages.

[1080] An "artificial intelligence model" is a software program that includes machine learning algorithms to analyze user preferences and conversational content and generate digital emojis based on that analysis.

[1081] An "image provider" is an individual or organization that provides existing images to be used as training data for an artificial intelligence model.

[1082] "Conversation content" refers to the content of text messages and discussions exchanged between users via messaging services.

[1083] "Messaging Service" refers to an application or platform that allows users to send and receive text messages.

[1084] "Server" refers to the computer system that stores and manages user preference information and generated digital emojis, and generates digital emojis as needed.

[1085] This system allows users to register their preferred visual information and characters, and then automatically generates and presents digital emojis based on that information in response to the content of the conversation. To implement this system, three main entities work together: a server, a terminal, and a user.

[1086] Server Processing

[1087] 1. Storing your information and preferences

[1088] The server receives the visual information and character data that the user sends from their device and stores it in a database. Databases such as MySQL and PostgreSQL can be used for efficient information management.

[1089] 2. Training the AI ​​model

[1090] The server receives existing visual data provided by image providers and uses it as training data for an AI model. Using machine learning frameworks such as TensorFlow and PyTorch, it trains a model that can tag images based on visual information and generate digital emojis that adapt to the user's conversation.

[1091] 3. Digital Emoji Generation and Presentation

[1092] Upon receiving a user's message, the server uses NLP technology to analyze its content and generate digital emojis based on appropriate visual information and characters. The generated digital emoji candidates are packaged in JSON format and sent to the user's device.

[1093] Terminal handling

[1094] 1. Providing a user interface

[1095] The device provides an interface for users to register their favorite visual information and characters. Users can easily register visual information using a smartphone app or web app. It also provides an interface that displays digital emojis as the conversation progresses.

[1096] 2. Data transmission and reception

[1097] The device sends the visual information data and conversation log entered by the user to the server using an HTTP POST request. The server then receives a list of digital emoji candidates and displays them to the user.

[1098] 3. Selection and Use of Digital Emojis

[1099] The user selects the desired digital emoji from the provided ones and uses the interface to insert them into the conversation. The selected digital emoji is then sent to the other person via the terminal.

[1100] User Actions

[1101] 1. Register your preferences

[1102] Users can specify their preferred visual information and characters through the app on their device. For example, if a user likes a "smiling cat," they enter this information in the app's input field and send it to the server.

[1103] 2. Starting a dialogue

[1104] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[1105] 3. Checking and using digital emojis

[1106] The user can select an appropriate digital emoji from the candidates sent by the server. For example, in response to the message "I had a great day," a digital emoji of a "smiling cat" is suggested. The user selects this emoji and sends it to the person they are speaking with.

[1107] Specific examples

[1108] 1. Register your favorite visual information and characters

[1109] User A registers "dog characters" as a preference. He enters this information into the device app and sends it to the server.

[1110] 2. Interaction and Digital Emoji Generation

[1111] When User A sends the message "good night," the server parses the message and generates a digital emoji of a dog saying "good night."

[1112] 3. Check and Use

[1113] User A checks the list of digital emojis sent from the server, selects the digital emoji "Goodnight dog" and sends it to the person he is talking to.

[1114] Prompt Sentence Examples

[1115] 1. "Please register dog characters as your favorite."

[1116] 2. "What did you have for lunch today?"

[1117] 3. "What emoji is appropriate for saying thank you?"

[1118] This system allows users to freely create digital emojis according to their preferences and enjoy richer communication. The AI ​​model also provides high-quality digital emojis that match the user's preferences.

[1119] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1120] System processing steps

[1121] Step 1:

[1122] The user opens the application on their device and registers their preferred visual information and characters. The user enters "smiling cat" as their preference and presses the send button. At this time, the device packages the entered information as JSON-formatted data. The input is visual information such as "smiling cat," and the output is JSON-formatted data.

[1123] Step 2:

[1124] The terminal sends the packaged JSON data to the server using an HTTP POST request: the input is the packaged JSON data, and the output is an HTTP request to the server's endpoint.

[1125] Step 3:

[1126] The server receives the HTTP request and parses the JSON data. The parsed results are saved in a database. The input is JSON data, and the output is visual information data saved in the database. The specific operation is to execute an INSERT query against MySQL.

[1127] Step 4:

[1128] The server acquires existing visual information data provided by the image provider. It uses this data to train an AI model. The input is the visual information data provided by the image provider, and the output is the trained AI model. Specifically, the machine learning algorithm is trained using TensorFlow and PyTorch.

[1129] Step 5:

[1130] A user starts a message exchange with a conversation partner, for example, sending a message such as "I had fun today." The input is the text message "I had fun today," and the output is the message sent from the terminal to the server.

[1131] Step 6:

[1132] The server receives the user's message and analyzes the message content using NLP techniques. The input is the text message and the output is the analysis result. Specific operations include text analysis using spaCy and Transformers.

[1133] Step 7:

[1134] Based on the analysis results, the server selects appropriate visual information and characters to generate a digital emoji. This process uses a trained AI model. The input is the analysis results and the trained model, and the output is a digital emoji. Specific operations include running the AI ​​model's inference engine.

[1135] Step 8:

[1136] The server packages the generated digital emoji candidates in JSON format and sends them to the user's device. The input is the digital emoji, and the output is an HTTP response to the user's device. The specific operations include generating and sending data in JSON format.

[1137] Step 9:

[1138] The device analyzes the received digital emoji candidates and displays them on the user interface. The input is digital emoji data in JSON format, and the output is digital emoji candidates displayed on the user interface.

[1139] Step 10:

[1140] The user selects the desired digital emoji from the presented ones and inserts it into the conversation. For example, they select the digital emoji "smiling cat" and press the send button. The input is the user's selection, and the output is the transmission of the digital emoji to the conversation partner.

[1141] In this way, the user, device, and server all work together to create a system that can quickly and smoothly generate and display digital emojis based on the user's preferences.

[1142] (Application example 1)

[1143] 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."

[1144] In traditional brick-and-mortar stores, it was difficult to provide personalized suggestions tailored to individual customer preferences and needs, resulting in limited means for improving customer satisfaction. Furthermore, effective use of visual elements such as stamps and illustrations was also limited, leading to a tendency for dialogue with customers to be monotonous.

[1145] 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.

[1146] In this invention, the server includes a means for users to register their favorite designs and characters, a means for saving the registered favorite designs and characters, and a means for automatically generating stamps based on the content of conversations, which enables personalized suggestions to be made based on the content of customer conversations in physical stores.

[1147] A "user" is a user of the system who registers their preferred designs and characters to receive personalized services.

[1148] "Pictures and characters" refer to the illustrations and image designs that users prefer to register, and are the visual elements that form the basis for generating stamps.

[1149] "Stamps" are emojis or images used during conversations to visually express users' emotions and messages.

[1150] "Automatically generating stickers" refers to the process of using AI models and algorithms to create appropriate stickers based on the user's conversation content and registration information.

[1151] "Presenting" refers to the act of showing the generated stamp to the user.

[1152] "Selecting" refers to the act of the user choosing the stamp that best suits their taste from the ones presented.

[1153] A "physical store" refers to a commercial or service facility that exists in a physical location and where customers can visit in person to receive services.

[1154] "Customers" refer to shoppers who visit physical stores or service users and who receive personalized offers.

[1155] "Personalized offers" refers to individualized service and product proposals tailored to the customer's preferences and needs.

[1156] "Training an AI model" refers to the process of using illustrations and data to teach an artificial intelligence model and strengthen it to work effectively for a specific task.

[1157] "Content Creator" refers to a person or organization that creates illustrations or other visual content and provides it to the System.

[1158] "Existing illustrations" refer to visual materials previously created by content creators and provided for use as training data.

[1159] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[1160] Server Processing

[1161] 1. Storing your information and preferences

[1162] The server receives the user's registered favorite images and characters and stores them in a database. This allows the user to change their favorite information as many times as they like, and the system always keeps the latest user preferences.

[1163] 2. Training the AI ​​model

[1164] The server collects existing illustration data provided by content creators and uses it to train an AI model that is trained to generate stickers based on the tagged data and the user's conversation content. This process uses deep learning frameworks such as TensorFlow and PyTorch.

[1165] 3. Stamp generation and presentation

[1166] The server analyzes the user's message and generates appropriate stickers based on the user's preferences and the content of the conversation. The generated sticker candidates are sent to the user's device and displayed. Specifically, for example, a prompt phrase such as "new item arrival with a blue cat character" is input into the generative AI model to generate an appropriate sticker.

[1167] Terminal handling

[1168] 1. Providing a user interface

[1169] The device provides an interface for users to register their favorite pictures and characters, as well as an interface for displaying stamps during conversations. It is implemented as an application for smartphones and tablets.

[1170] 2. Data transmission and reception

[1171] The device sends the user's registration information and interaction log to the server. This conveys the user's interaction context to the server, which then generates stamps based on that information. The device receives the generated stamp list and displays it to the user.

[1172] 3. Selecting and Using Stamps

[1173] The user selects the desired stamp from the list of stamp candidates presented by the server through the terminal interface, and the selected stamp is inserted into the message and sent to the other party.

[1174] User Actions

[1175] 1. Register your preferences

[1176] Users use the device interface to specify their preferred image or character, such as "a smiling cat" or "I like blue items," and then input this information into the app and send it to the server.

[1177] 2. Starting a dialogue

[1178] Users can interact with store staff or AI chatbots in physical stores, for example by sending messages such as "Have new products arrived?"

[1179] 3. Check and use stamps

[1180] The user selects an appropriate stamp from the list of stamp candidates sent by the server. For example, the "Blue Cat" stamp is suggested for the message "Have new items arrived?" The user selects this stamp, inserts it into the conversation, and sends it.

[1181] Software and Hardware Requirements

[1182] Software used:

[1183] Server software: Linux (e.g., Ubuntu 20.04), Flask web framework, PostgreSQL database

[1184] AI model training: TensorFlow or PyTorch

[1185] Terminal applications: iOS app (Swift), Android app (Kotlin)

[1186] Hardware used:

[1187] Server hardware: High-performance server machine (e.g., Dell PowerEdge series)

[1188] Device: iOS or Android smartphone or tablet

[1189] Specific examples

[1190] If User A registers "Smiling Cat" as a preference, the server stores this. When User A sends a message to a physical store asking "Have new items arrived?", the server analyzes this message and inputs the prompt "New items arrived with a smiling cat character" into the AI ​​model. The AI ​​model generates an appropriate stamp and sends it to the device. User A selects the "Smiling Cat" stamp and sends it to the store clerk or chatbot, achieving personalized communication.

[1191] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1192] Step 1:

[1193] Registering user preferences

[1194] The server receives the user's favorite images and characters sent from the device, stores this information in a database, and updates the user's favorite list.

[1195] Input: User preference information (e.g., "smiling cats," "blue items")

[1196] Output: User preference information stored in a database

[1197] Step 2:

[1198] Collecting learning data and training AI models

[1199] The server collects existing illustration data provided by content creators, labels it, and trains the AI ​​model, using deep learning frameworks such as TensorFlow and PyTorch to enable the model to generate appropriate stamps.

[1200] Input: Existing illustration data and label information

[1201] Output: A trained AI model

[1202] Step 3:

[1203] Message parsing and prompt generation

[1204] The server receives the user's interactive message sent from the device and analyzes its content. Based on the analysis results, it generates a prompt sentence and inputs it into the AI ​​model. For example, if the message is "Have new items arrived?", it generates the prompt sentence "new item arrival with a smiling cat character."

[1205] Input: User interaction message

[1206] Output: Generated prompt statement

[1207] Step 4:

[1208] Stamp Generation

[1209] The server inputs the generated prompt into the AI ​​model to generate a corresponding stamp. The AI ​​model analyzes the prompt and outputs a stamp that combines an appropriate image and character.

[1210] Input: Generated prompt text

[1211] Output: Generated stamp

[1212] Step 5:

[1213] Stamp list presentation

[1214] The server sends the generated stamp list to the device and presents it to the user, who can then view the stamps displayed through the device interface.

[1215] Input: Generated stamp list

[1216] Output: Stamp list displayed on the device

[1217] Step 6:

[1218] Selecting and Using Stamps

[1219] The user selects the desired stamp from a list of stamps presented to them using the terminal interface, and the selected stamp is inserted into the message and sent to the interlocutor.

[1220] Input: User selects stamp

[1221] Output: Send selected stamps

[1222] Through the above processing steps, appropriate stamps are automatically generated based on the content of the user's dialogue, realizing personalized communication.

[1223] 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.

[1224] The system of the present invention allows users to register their favorite pictures and characters, and automatically generates stamps based on the content of the conversation and an emotion engine, thereby providing users with appropriate stamps.

[1225] Server Processing

[1226] 1. Storing your information and preferences

[1227] The server receives information about the preferred designs and characters sent by the user and stores it in a database.

[1228] 2. Training the AI ​​model

[1229] The server receives existing illustration data provided by the illustrator and uses it as training data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stickers based on the user's conversation content and emotions.

[1230] 3. Use of Emotion Engine

[1231] The server analyzes the content of the user's conversation and uses an emotion engine to recognize the user's emotions from that content. The emotion engine uses multiple language models and emotion recognition algorithms to analyze the user's emotions with high accuracy.

[1232] 4. Stamp generation and presentation

[1233] Based on the user's message and the perceived emotion, the AI ​​model generates appropriate stickers, which are then sent to the user's device for display.

[1234] Terminal handling

[1235] 1. Providing a user interface

[1236] The device provides an interface for users to register their favorite pictures and characters, as well as an interface that displays stamps based on the content of conversations and emotions.

[1237] 2. Data transmission and reception

[1238] The device sends the user's registration information and interaction log to the server, which then conveys the user's interaction context and emotional information to the server. The device also receives a stamp list sent from the server and displays it to the user.

[1239] 3. Selecting and Using Stamps

[1240] The system provides an interface for users to select the desired stamp from the provided stamps and insert it into the conversation. The selected stamp is then sent from the device to the conversation partner.

[1241] User Actions

[1242] 1. Register your preferences

[1243] Users can specify their favorite images and characters through the app on their device. For example, if a user likes "smiling dogs," they enter this information into the app and send it to the server.

[1244] 2. Starting a dialogue

[1245] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[1246] 3. Emotional Recognition

[1247] The server analyzes the received message and uses an emotion engine to identify the user's emotion. For example, it recognizes positive emotion from the message "I had fun today."

[1248] 4. Check and use stamps

[1249] The user selects an appropriate stamp from among the stamp candidates sent by the server based on the content of the conversation and the recognized emotion. For example, a "smiling dog" stamp is suggested for the message "I had fun today." The user selects this stamp, inserts it into the conversation, and sends it.

[1250] Specific examples

[1251] 1. Register your favorite designs and characters

[1252] User A registers "cat characters" as a preference. He enters this information into the device app and sends it to the server.

[1253] 2. Dialogue and Emotion Recognition

[1254] When User A sends a message saying "Work is done! Yay!", the server analyzes this message and uses an emotion engine to recognize positive emotions.

[1255] 3. Stamp creation and selection

[1256] The server uses an AI model to generate a "joyful cat" stamp based on the recognized positive emotion.

[1257] The server sends stamp candidates to the user's device, and User A selects the "Joyful Cat" stamp and sends it to the person he or she is talking to.

[1258] This system allows users to easily create stamps based on their preferences and emotions, allowing them to enjoy richer communication.

[1259] The processing flow will be explained below.

[1260] The processing steps from when the user registers their favorite pictures or characters to when the emotion engine is used to generate stamps during a conversation

[1261] Step 1: Users register their favorite designs and characters

[1262] 1. User: Enter your favorite image or character into the device app. For example, "dog character."

[1263] 2. Terminal: Converts the user's input preferences into data packets.

[1264] 3. Terminal: Sends the converted data packets to the server.

[1265] Step 2: The server stores the user information

[1266] 1. Server: Analyzes data packets received from users and extracts their preferred images and character information.

[1267] 2. Server: Stores the extracted information in a database.

[1268] Step 3: Train the AI ​​model

[1269] 1. Illustrator: Upload an existing illustration to the server as learning data.

[1270] 2. Server: Stores the received illustration data in a database and performs preprocessing (size adjustment, noise removal, etc.).

[1271] 3. Server: Trains the AI ​​model using the preprocessed illustration data, properly tags each illustration, and generates stickers for the corresponding user conversation and emotion.

[1272] Step 4: User initiates interaction

[1273] 1. User: Sends a message to the person they are interacting with through the app, for example, "I had a great time today."

[1274] 2. Terminal: Converts the user's message into data packets and sends them to the server.

[1275] Step 5: The emotion engine recognizes the user's emotions

[1276] 1. Server: Analyzes the received message data.

[1277] 2. Server: Recognizes the user's emotion from the message content using an emotion engine. For example, recognize positive emotion from the message "I had fun today."

[1278] Step 6: The server generates and presents the stamp

[1279] 1. Server: Using an AI model, the server generates appropriate stamps based on the analysis results, the user's preferred designs, character information, and recognized emotions.

[1280] 2. Server: Arranges the generated stamp candidates into a list and sends it to the user's device.

[1281] Step 7: Your device will display sticker suggestions

[1282] 1. Terminal: The stamp list received from the server is displayed on the user interface, visually presenting multiple stamps in thumbnail format.

[1283] 2. User: Select the desired stamp from the presented stamp list.

[1284] Step 8: User selects sticker and sends it

[1285] 1. User: Selects the "Smiling Dog" stamp from the presented stamps and sends it to the person he or she is talking to.

[1286] 2. Terminal: Converts the selected stamp data into a data packet and sends it to the other terminal.

[1287] In this way, the user, device, server, and emotion engine work together to enable users to easily create stamps based on their preferences and emotions, and enjoy rich communication.

[1288] Example 2

[1289] 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."

[1290] Conventional stamp generation systems have had problems such as making it difficult for users to easily select stamps that match their preferences, and not being able to provide appropriate stamps based on emotions in a timely manner. Furthermore, stamp generation is not sufficiently automated, making it impossible to generate stamps that take into account the user's conversation content and emotions.

[1291] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1292] In this invention, the server includes means for users to register their favorite images and characters, means for saving the registered favorite images and characters, means for automatically generating stamps based on the conversation content and the emotion engine, means for presenting the generated stamps to the user terminal, and means for the user to select the presented stamps via the terminal, thereby enabling timely provision of stamps based on the user's preferences and emotions.

[1293] "User" refers to an individual or corporation that uses the system, and is the entity that primarily performs the operations of registering, selecting, and sending stamps.

[1294] "Images and characters" are visual expressions designated by users as their preferences, and are the materials used to generate stamps.

[1295] A "stamp" is an image or icon added to a message in digital communication to visually convey emotions or intentions.

[1296] A "generative AI model" is a model that uses artificial intelligence to automatically generate stamps based on user preferences and conversation content.

[1297] An "emotion engine" is a system or algorithm that analyzes the content of a user's conversation and recognizes the emotions contained within it.

[1298] The "database" is a system for storing and managing users' preferred images, characters, and related information such as conversation logs.

[1299] A "prompt" is text information that is input into a generative AI model and used to generate a specific stamp or response.

[1300] A "terminal" is a device used by a user to access and operate the system, such as a smartphone, tablet, or PC.

[1301] A "server" is a central computer system that operates and manages the entire system, and processes data and generates stamps in response to user requests.

[1302] "Interface" is a general term for the operation screen and input / output devices that allow users to interact with the system.

[1303] The system of the present invention allows users to register their favorite images and characters, and automatically generates stamps based on the content of the conversation and an emotion engine, thereby providing appropriate stamps to users. Specific embodiments of the system are described below.

[1304] Server Processing

[1305] Storing User Information and Preferences

[1306] The server receives the user's favorite images and character information sent from the device and stores it in a database. "MySQL" can be used as the database software. For example, information such as the user ID, favorite character, and registration date and time is stored.

[1307] Training an AI model

[1308] The server receives existing image data provided by the image creator and uses it as training data for the AI ​​model. The image data is tagged, for example, a cat image is tagged with "cat," "cute," and "smiling." Then, using TensorFlow and PyTorch, a stamp generation model is trained based on the conversation content and emotions.

[1309] Use of emotion engine

[1310] The server receives the user's conversation content sent from the device and uses an emotion engine to recognize the user's emotions from the content. The emotion engine can use tools such as Google Cloud Natural Language API or IBM Watson. This allows for highly accurate analysis of the user's emotions.

[1311] Stamp generation and presentation

[1312] The server uses an AI model to automatically generate appropriate stickers based on the recognized emotions and user preferences, and sends the generated sticker candidates to the user's device, where they are presented to the user.

[1313] Terminal handling

[1314] Providing a user interface

[1315] The device provides an interface for users to register their favorite images and characters, such as a form entry screen and an image selection screen, as well as an interface for displaying stamps based on the user's dialogue and emotions.

[1316] Sending and receiving data

[1317] The terminal transmits the user's input preference information to the server, transmits the user's interaction log to the server, conveys the user's interaction context and emotion information to the server, and receives the stamp list transmitted from the server and displays it to the user.

[1318] Selecting and Using Stamps

[1319] The terminal provides an interface for the user to select a desired stamp from the stamps presented and insert it into the conversation. The selected stamp is then sent from the terminal to the conversation partner.

[1320] User Actions

[1321] Register your preferences

[1322] The user launches the app on their device, inputs their favorite image or character, for example, "smiling dog," and sends it to the server.

[1323] Starting a conversation

[1324] The user opens a message exchange screen with the person they are talking to, enters a message such as "I had fun today," and sends it.

[1325] Emotion recognition

[1326] The server analyzes the received message and uses an emotion engine to identify the user's emotion. For example, it recognizes positive emotion from the message "I had fun today."

[1327] Checking and using stamps

[1328] The stamp candidates sent from the server are displayed on the user's device, and the user selects the appropriate stamp from the presented stamps and presses the select button.

[1329] Specific examples

[1330] 1. Register your favorite images and characters

[1331] User A registers "cat characters" as a preference. He enters "cat" into the device app and sends it to the server.

[1332] 2. Dialogue and Emotion Recognition

[1333] When User A sends a message saying "Work is done! Yay!", the server analyzes this message and uses an emotion engine to recognize positive emotions.

[1334] 3. Stamp creation and selection

[1335] The server generates a stamp of a happy cat using an AI model based on the recognized positive emotion. The server sends stamp candidates to the user's device, and User A selects the "happy cat" stamp and sends it to the person he or she is talking to.

[1336] Prompt Sentence Examples

[1337] 1. Register your preferences for designs and characters

[1338] "My favorite character is 'Cat'. Please register this information."

[1339] 2. Message sending for dialogue and emotion recognition

[1340] "Job done! Yay!"

[1341] 3. Using the generated stamp

[1342] Select "Joyful Cat" and send.

[1343] This system allows users to easily create stamps based on their preferences and emotions, allowing them to enjoy richer communication.

[1344] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1345] Step 1:

[1346] Users register their favorite images and characters

[1347] Input: The user inputs and sends their preferred image or character through the device interface.

[1348] How it works: The device receives information entered by the user through forms and selection screens and sends it to the server.

[1349] Output: The device sends the preference information entered by the user to the server, which receives this information.

[1350] Step 2:

[1351] Storing User Information and Preferences

[1352] Input: The user's preferred image and character information sent in Step 1.

[1353] Operation: The server stores the received information in a database. For example, it uses "MySQL" to register the user ID, favorite character, and registration date and time.

[1354] Output: The server sends a confirmation message to the device indicating that the save is complete.

[1355] Step 3:

[1356] Training an AI model

[1357] Input: Existing image data and tagging data provided by the image creator.

[1358] How it works: The server tags images and preprocesses the data. This preprocessed data is used to train a generative AI model using TensorFlow and PyTorch. The model learns to generate stickers based on the user's conversation content and emotions using the tag information.

[1359] Output: A fully trained generative AI model.

[1360] Step 4:

[1361] Receiving conversation content

[1362] Input: Message exchanges between the user and their interlocutor.

[1363] How it works: The device sends the messages the user sends to the server, which receives and stores them.

[1364] Output: The server is ready to parse and process the received conversation content.

[1365] Step 5:

[1366] Emotion recognition

[1367] Input: The conversation received in step 4.

[1368] How it works: The server uses an emotion engine to analyze the conversation and identify the user's emotions. For example, it uses Google Cloud Natural Language API or IBM Watson to analyze emotion data.

[1369] Output: Identified user sentiment data.

[1370] Step 6:

[1371] Stamp Generation

[1372] Input: Identified emotion data and user's preferred image or character information.

[1373] How it works: The server generates optimal stamps using a generative AI model. Emotional data and preference information are input to the generative AI model as prompts.

[1374] Output: The generated stamp candidates.

[1375] Step 7:

[1376] Sending and displaying stamps

[1377] Input: Generated stamp candidates.

[1378] Operation: The server sends the generated stamp candidates to the user terminal and displays them to the user. The terminal displays the stamp candidates in the user interface.

[1379] Output: User can see the stamp suggestions.

[1380] Step 8:

[1381] Select a stamp

[1382] Input: The stamp selected by the user.

[1383] How it works: The user selects the desired stamp from the ones presented and presses the "Send" button. The device then sends this selection to the server.

[1384] Output: The selected stamps are sent to the server.

[1385] Step 9:

[1386] Send Selected Stamps

[1387] Input: The stamp selected in step 8.

[1388] Operation: The server sends the selected stamp to the conversation partner. The terminal displays the selected stamp to the conversation partner.

[1389] Output: The stamp is sent to the person you are talking to and displayed.

[1390] This allows users to easily send stamps based on their preferences and emotions to their interlocutors, enabling richer communication.

[1391] (Application example 2)

[1392] 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."

[1393] Communication with customers in virtual stores is mainly text-based, resulting in limited emotional communication. Furthermore, it is difficult to respond flexibly to customer emotions, limiting the quality of service. Given this background, there is a need for a system that can appropriately recognize customer emotions in virtual stores and provide appropriate stamps to enable richer communication.

[1394] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1395] In this invention, the server includes means for a user to register their favorite pictures and characters, means for saving the registered favorite pictures and characters, means for automatically generating stamps based on conversation content and emotion analysis, means for presenting the generated stamps to the user, means for the user to select the presented stamps, emotion analysis means for recognizing emotions from the content of the user's message, and means for presenting stamps generated in accordance with the recognized emotions on the virtual store interface. This makes it possible to improve the quality of communication by recognizing customer emotions in the virtual store in real time and providing stamps in response to those emotions.

[1396] "User" refers to a person or company that uses the system to register their favorite designs or characters and generate and use stamps.

[1397] "Pictures and characters" are illustrations, images, symbols, etc. that users select as their preferences.

[1398] "Storage means" refers to a storage device or database for storing information about the images and characters registered by the user.

[1399] "Conversation content" refers to messages and text information sent by users on the system.

[1400] "Sentiment analysis" is the process of analyzing the content of a user's message to recognize their emotional state.

[1401] "Stamps" are emoticons or illustrations generated for users to use in their messages.

[1402] "Means for automatic generation" refers to the process by which the system automatically generates stamps based on the content of the user's conversation and sentiment analysis.

[1403] The "presentation means" is an interface for visually presenting the generated stamp to the user.

[1404] The "selection means" is an operation interface that allows the user to select the desired stamp from among the stamps presented.

[1405] "Emotion analysis tools" are algorithms or software that recognize emotions from users' messages.

[1406] A "virtual store" is an online store that offers products and services over the Internet.

[1407] An "AI model" is an artificial intelligence algorithm that generates stamps based on the content of the conversation and emotions.

[1408] The "virtual store interface" is the user interface through which customers interact with the system.

[1409] The system of the present invention allows users to register their favorite images and characters, and automatically generates and displays stamps based on conversation content and sentiment analysis. In implementing this system, the server, terminal, and user components work in conjunction with each other.

[1410] Server Processing

[1411] 1. Storing your information and preferences

[1412] The server receives the user's preferred designs and characters and stores them in a database. New designs and characters registered by the user are updated in real time.

[1413] 2. Training the AI ​​model

[1414] The server receives existing illustration data provided by the illustrator and uses it as training data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stickers based on the user's conversation content and emotions. Specific software used includes TensorFlow and PyTorch.

[1415] 3. Use of sentiment analysis engines

[1416] The server analyzes the user's conversation content and uses a sentiment analysis engine to recognize the user's emotions from the content. This engine analyzes emotions with high accuracy using natural language processing models (e.g., BERT and GPT-3).

[1417] 4. Stamp generation and presentation

[1418] Based on the user's message and the recognized emotion, the AI ​​model generates appropriate stickers. The generated sticker candidates are sent to the user's device and displayed. Generative Adversarial Networks (GANs) and DALL-E are used for generation.

[1419] Terminal handling

[1420] 1. Providing a user interface

[1421] The device provides an interface for users to register their favorite pictures and characters, as well as an interface that displays stamps based on the content of conversations and emotions.

[1422] 2. Data transmission and reception

[1423] The device sends the user's registration information and interaction log to the server, which then conveys the user's interaction context and emotional information to the server. The device also receives a stamp list sent from the server and displays it to the user.

[1424] 3. Selecting and Using Stamps

[1425] It provides an interface for users to select the desired stamp from the provided stamps, and the selected stamp is sent from the terminal to the interlocutor.

[1426] User Actions

[1427] 1. Register your preferences

[1428] Users can specify their favorite images and characters through the app on their device. For example, if a user likes "smiling dogs," they enter this information into the app and send it to the server.

[1429] 2. Starting a dialogue

[1430] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[1431] 3. Emotional Recognition

[1432] The server analyzes the received message and uses a sentiment analysis engine to identify the user's sentiment. For example, it recognizes positive sentiment from a message such as "I had fun today."

[1433] 4. Check and use stamps

[1434] The user selects an appropriate stamp from among the stamp candidates sent by the server based on the content of the conversation and the recognized emotion. For example, a "smiling dog" stamp is suggested for the message "I had fun today." The user selects this stamp, inserts it into the conversation, and sends it.

[1435] Specific examples

[1436] For example, if User A registers "cat characters" as a favorite and sends a message saying "Work is done! Yay!", the server will analyze this message and recognize the positive emotion. Based on this, a "joyful cat" stamp will be generated and presented to User A. User A can then select this stamp and send it to the person they are interacting with, achieving engaging, emotion-based communication.

[1437] Example prompt sentence:

[1438] A user sent a message saying, "I really liked this product!" Recognize the emotion from this message and generate an appropriate sticker based on the user's favorite character, "cat."

[1439] In this way, the system of the present invention automatically generates and provides stamps that correspond to the user's emotions, thereby improving the user experience in the virtual store.

[1440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1441] Step 1:

[1442] The server provides the terminal with an interface that allows users to register their favorite pictures and characters.

[1443] Input: User's preferred designs and character information

[1444] Output: Temporarily save registered information

[1445] Specific operation: The user inputs information such as "smiling dog" through the device interface, and the device temporarily stores this preference information.

[1446] Step 2:

[1447] The terminal transmits the user's registered favorite images and character information to the server.

[1448] Input: User preference information (e.g., "smiling dogs")

[1449] Output: Data sent to the server, confirmation message

[1450] Specific operation: The preference information is sent from the device to the server, which receives it and stores it in the database. After completion, a confirmation message is displayed on the device.

[1451] Step 3:

[1452] The server stores the registration information submitted by the user in a database.

[1453] Input: User preference information

[1454] Output: User preferences stored in a database

[1455] What happens: The server updates the database, storing the user's preferences, such as "smiling dogs."

[1456] Step 4:

[1457] The server provides an interface for analyzing the content of the user's conversation.

[1458] Input: A message that the user types

[1459] Output: Send message to server

[1460] Specific operation: The device sends the message entered by the user in the chat (e.g., "Today was fun") to the server.

[1461] Step 5:

[1462] The server analyzes the received message using a sentiment analysis engine.

[1463] Input: User's message

[1464] Output: Parsed emotion data

[1465] Specific operation: The server uses a natural language processing model (BERT or GPT-3) to analyze positive emotions from the message "I had fun today."

[1466] Step 6:

[1467] The server generates stamps based on the analyzed emotional data and the user's preferences.

[1468] Input: Emotion data, preferred picture information

[1469] Output: Generated stamp

[1470] Specific operation: Using AI models (TensorFlow, GANs, DALL-E), we generate "smiling dog" stamps that match positive emotions.

[1471] Step 7:

[1472] The server transmits the generated stamp to the terminal and presents it to the user.

[1473] Input: Generated stamp data

[1474] Output: Send stamp data to the terminal

[1475] Specific operation: The server sends the "smiling dog" stamp data to the terminal and displays the stamp on the display interface.

[1476] Step 8:

[1477] The terminal provides an interface for the user to select from the presented stamps.

[1478] Input: Presented stamp

[1479] Output: User selection data

[1480] Specific behavior: The user selects the "smiling dog" sticker that is displayed.

[1481] Step 9:

[1482] The terminal operates to transmit the stamp selected by the user to the interlocutor.

[1483] Input: User's stamp selection data

[1484] Output: Send stamp to the person you are talking to

[1485] Specific operation: The device sends the "smiling dog" stamp selected by the user to the person it is talking to.

[1486] In this way, stamps are generated and displayed in real time according to the user's conversation content and emotions, enabling richer communication.

[1487] 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.

[1488] 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.

[1489] 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.

[1490] [Fourth embodiment]

[1491] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1492] 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.

[1493] 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).

[1494] 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.

[1495] 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.

[1496] 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).

[1497] 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.

[1498] 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.

[1499] 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.

[1500] 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.

[1501] 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.

[1502] 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.

[1503] 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."

[1504] To implement the system of the present invention, three main entities work together: the server, the terminal, and the user. This system allows users to register their favorite pictures and characters, and then uses that information to automatically generate stamps based on the content of the conversation, providing appropriate stamps to the user.

[1505] Server Processing

[1506] 1. Storing your information and preferences

[1507] The server receives the information about the preferred designs and characters sent by the user and stores it in a database, allowing the system to accumulate the user's registered preferences.

[1508] 2. Training the AI ​​model

[1509] The server receives existing illustration data provided by the illustrator and uses it as learning data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stamps based on the user's conversation content.

[1510] 3. Stamp generation and presentation

[1511] When a user's message is received, the server analyzes the content, selects appropriate images and characters, and generates stamps. The generated stamp candidates are sent to the user's device and displayed.

[1512] Terminal handling

[1513] 1. Providing a user interface

[1514] The device provides an interface for users to register their favorite pictures and characters, as well as an interface for displaying stamps according to the flow of conversation.

[1515] 2. Data transmission and reception

[1516] The device sends the user's registration information and interaction log to the server, which conveys the user's interaction context to the server. The device receives the stamp list sent from the server and displays it to the user.

[1517] 3. Selecting and Using Stamps

[1518] The system provides an interface for users to select the desired stamp from the provided stamps and insert it into the conversation. The selected stamp is then sent from the device to the conversation partner.

[1519] User Actions

[1520] 1. Register your preferences

[1521] Users can specify their favorite designs and characters through the app on their device. For example, if a user likes a "smiling cat," they enter this information into the app and send it to the server.

[1522] 2. Starting a dialogue

[1523] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[1524] 3. Check and use stamps

[1525] The user selects an appropriate stamp from the list of stamp candidates sent by the server based on the content of the conversation. For example, a "smiling cat" stamp is suggested for the message "Today was fun." The user selects this stamp, inserts it into the conversation, and sends it.

[1526] Specific examples

[1527] 1. Register your favorite designs and characters

[1528] User A registers "dog characters" as a preference. He enters this information into the device app and sends it to the server.

[1529] 2. Interaction and stamp generation

[1530] When user A sends the message "good night," the server analyzes this message and generates a stamp of a dog saying "good night."

[1531] 3. Check and Use

[1532] User A checks the stamp list sent from the server, selects the "Goodnight Dog" stamp and sends it to the person he or she is talking to.

[1533] This system allows users to freely create stamps that suit their preferences and enjoy rich communication.

[1534] The processing flow will be explained below.

[1535] The process steps for users to register their favorite designs and characters and use stamps during conversations

[1536] Step 1: Users register their favorite designs and characters

[1537] 1. User: Enter your favorite image or character into the device app. For example, "dog character."

[1538] 2. Terminal: Converts the user's input preferences into data packets.

[1539] 3. Terminal: Sends the converted data packets to the server.

[1540] Step 2: The server stores the user information

[1541] 1. Server: Analyzes data packets received from users and extracts their preferred images and character information.

[1542] 2. Server: Stores the extracted information in a database.

[1543] Step 3: Train the AI ​​model

[1544] 1. Illustrator: Upload an existing illustration to the server as learning data.

[1545] 2. Server: Stores the received illustration data in a database and performs preprocessing (size adjustment, noise removal, etc.).

[1546] 3. Server: Trains the AI ​​model using the preprocessed illustration data, properly tags each illustration, and generates stickers for the corresponding user conversations.

[1547] Step 4: User initiates interaction

[1548] 1. User: Sends a message to the person they are interacting with through the app, for example, "I had a great time today."

[1549] 2. Terminal: Converts the user's message into data packets and sends them to the server.

[1550] Step 5: The server generates and presents the stamp

[1551] 1. Server: Analyzes the received message data and understands the conversation content.

[1552] 2. Server: Taking into account the analysis results and the user's preferred designs and character information, the server uses an AI model to generate appropriate stamps.

[1553] 3. Server: Arranges the generated stamp candidates into a list and sends it to the user's device.

[1554] Step 6: Your device will display suggested stickers

[1555] 1. Terminal: The stamp list data received from the server is displayed on the user interface, visually presenting multiple stamps in thumbnail format.

[1556] 2. User: Select the desired stamp from the presented stamp list.

[1557] Step 7: User selects sticker and sends it

[1558] 1. User: Selects the "Smiling Dog" stamp from the presented stamps and sends it to the person he or she is talking to.

[1559] 2. Terminal: Converts the selected stamp data into a data packet and sends it to the other terminal.

[1560] In this way, users, devices, and servers work together to enable users to easily create stamps based on their preferences and enjoy rich communication.

[1561] Example 1

[1562] 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."

[1563] In conventional messaging systems, users must manually select emojis and stickers, making it difficult to quickly find the right stickers that match their individual preferences. This disrupts the flow of conversation and detracts from the user experience. Furthermore, there is no automated method for identifying stickers based on individual user preferences, requiring constant manual intervention. Therefore, there is a need to improve user convenience and enable richer communication.

[1564] 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.

[1565] In this invention, the server includes means for a user to register visual information and characters that the user likes, means for saving the registered visual information and characters that the user likes, means for automatically generating digital emojis based on the content of a conversation, means for presenting the generated digital emojis to the user, and means for the user to select the presented digital emojis. This allows the user to quickly find digital emojis that match their preferences, enabling smoother communication without interrupting the flow of conversation.

[1566] "User" means an individual or organization that uses the system to register their preferred visual information or characters and communicates through messaging services.

[1567] "Visual information" refers to visual content such as favorite images, designs, characters, etc. registered by users.

[1568] "Character" refers to an image of a specific person, animal, fictional creature, or other character that a user likes.

[1569] "Digital Emoji" are system-generated illustrations or icons for use in messages.

[1570] An "artificial intelligence model" is a software program that includes machine learning algorithms to analyze user preferences and conversational content and generate digital emojis based on that analysis.

[1571] An "image provider" is an individual or organization that provides existing images to be used as training data for an artificial intelligence model.

[1572] "Conversation content" refers to the content of text messages and discussions exchanged between users via messaging services.

[1573] "Messaging Service" refers to an application or platform that allows users to send and receive text messages.

[1574] "Server" refers to the computer system that stores and manages user preference information and generated digital emojis, and generates digital emojis as needed.

[1575] This system allows users to register their preferred visual information and characters, and then automatically generates and presents digital emojis based on that information in response to the content of the conversation. To implement this system, three main entities work together: a server, a terminal, and a user.

[1576] Server Processing

[1577] 1. Storing your information and preferences

[1578] The server receives the visual information and character data that the user sends from their device and stores it in a database. Databases such as MySQL and PostgreSQL can be used for efficient information management.

[1579] 2. Training the AI ​​model

[1580] The server receives existing visual data provided by image providers and uses it as training data for an AI model. Using machine learning frameworks such as TensorFlow and PyTorch, it trains a model that can tag images based on visual information and generate digital emojis that adapt to the user's conversation.

[1581] 3. Digital Emoji Generation and Presentation

[1582] Upon receiving a user's message, the server uses NLP technology to analyze its content and generate digital emojis based on appropriate visual information and characters. The generated digital emoji candidates are packaged in JSON format and sent to the user's device.

[1583] Terminal handling

[1584] 1. Providing a user interface

[1585] The device provides an interface for users to register their favorite visual information and characters. Users can easily register visual information using a smartphone app or web app. It also provides an interface that displays digital emojis as the conversation progresses.

[1586] 2. Data transmission and reception

[1587] The device sends the visual information data and conversation log entered by the user to the server using an HTTP POST request. The server then receives a list of digital emoji candidates and displays them to the user.

[1588] 3. Selection and Use of Digital Emojis

[1589] The user selects the desired digital emoji from the provided ones and uses the interface to insert them into the conversation. The selected digital emoji is then sent to the other person via the terminal.

[1590] User Actions

[1591] 1. Register your preferences

[1592] Users can specify their preferred visual information and characters through the app on their device. For example, if a user likes a "smiling cat," they enter this information in the app's input field and send it to the server.

[1593] 2. Starting a dialogue

[1594] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[1595] 3. Checking and using digital emojis

[1596] The user can select an appropriate digital emoji from the candidates sent by the server. For example, in response to the message "I had a great day," a digital emoji of a "smiling cat" is suggested. The user selects this emoji and sends it to the person they are speaking with.

[1597] Specific examples

[1598] 1. Register your favorite visual information and characters

[1599] User A registers "dog characters" as a preference. He enters this information into the device app and sends it to the server.

[1600] 2. Interaction and Digital Emoji Generation

[1601] When User A sends the message "good night," the server parses the message and generates a digital emoji of a dog saying "good night."

[1602] 3. Check and Use

[1603] User A checks the list of digital emojis sent from the server, selects the digital emoji "Goodnight dog" and sends it to the person he is talking to.

[1604] Prompt Sentence Examples

[1605] 1. "Please register dog characters as your favorite."

[1606] 2. "What did you have for lunch today?"

[1607] 3. "What emoji is appropriate for saying thank you?"

[1608] This system allows users to freely create digital emojis according to their preferences and enjoy richer communication. The AI ​​model also provides high-quality digital emojis that match the user's preferences.

[1609] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1610] System processing steps

[1611] Step 1:

[1612] The user opens the application on their device and registers their preferred visual information and characters. The user enters "smiling cat" as their preference and presses the send button. At this time, the device packages the entered information as JSON-formatted data. The input is visual information such as "smiling cat," and the output is JSON-formatted data.

[1613] Step 2:

[1614] The terminal sends the packaged JSON data to the server using an HTTP POST request: the input is the packaged JSON data, and the output is an HTTP request to the server's endpoint.

[1615] Step 3:

[1616] The server receives the HTTP request and parses the JSON data. The parsed results are saved in a database. The input is JSON data, and the output is visual information data saved in the database. The specific operation is to execute an INSERT query against MySQL.

[1617] Step 4:

[1618] The server acquires existing visual information data provided by the image provider. It uses this data to train an AI model. The input is the visual information data provided by the image provider, and the output is the trained AI model. Specifically, the machine learning algorithm is trained using TensorFlow and PyTorch.

[1619] Step 5:

[1620] A user starts a message exchange with a conversation partner, for example, sending a message such as "I had fun today." The input is the text message "I had fun today," and the output is the message sent from the terminal to the server.

[1621] Step 6:

[1622] The server receives the user's message and analyzes the message content using NLP techniques. The input is the text message and the output is the analysis result. Specific operations include text analysis using spaCy and Transformers.

[1623] Step 7:

[1624] Based on the analysis results, the server selects appropriate visual information and characters to generate a digital emoji. This process uses a trained AI model. The input is the analysis results and the trained model, and the output is a digital emoji. Specific operations include running the AI ​​model's inference engine.

[1625] Step 8:

[1626] The server packages the generated digital emoji candidates in JSON format and sends them to the user's device. The input is the digital emoji, and the output is an HTTP response to the user's device. The specific operations include generating and sending data in JSON format.

[1627] Step 9:

[1628] The device analyzes the received digital emoji candidates and displays them on the user interface. The input is digital emoji data in JSON format, and the output is digital emoji candidates displayed on the user interface.

[1629] Step 10:

[1630] The user selects the desired digital emoji from the presented ones and inserts it into the conversation. For example, they select the digital emoji "smiling cat" and press the send button. The input is the user's selection, and the output is the transmission of the digital emoji to the conversation partner.

[1631] In this way, the user, device, and server all work together to create a system that can quickly and smoothly generate and display digital emojis based on the user's preferences.

[1632] (Application example 1)

[1633] 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."

[1634] In traditional brick-and-mortar stores, it was difficult to provide personalized suggestions tailored to individual customer preferences and needs, resulting in limited means for improving customer satisfaction. Furthermore, effective use of visual elements such as stamps and illustrations was also limited, leading to a tendency for dialogue with customers to be monotonous.

[1635] 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.

[1636] In this invention, the server includes a means for users to register their favorite designs and characters, a means for saving the registered favorite designs and characters, and a means for automatically generating stamps based on the content of conversations, which enables personalized suggestions to be made based on the content of customer conversations in physical stores.

[1637] A "user" is a user of the system who registers their preferred designs and characters to receive personalized services.

[1638] "Pictures and characters" refer to the illustrations and image designs that users prefer to register, and are the visual elements that form the basis for generating stamps.

[1639] "Stamps" are emojis or images used during conversations to visually express users' emotions and messages.

[1640] "Automatically generating stickers" refers to the process of using AI models and algorithms to create appropriate stickers based on the user's conversation content and registration information.

[1641] "Presenting" refers to the act of showing the generated stamp to the user.

[1642] "Selecting" refers to the act of the user choosing the stamp that best suits their taste from the ones presented.

[1643] A "physical store" refers to a commercial or service facility that exists in a physical location and where customers can visit in person to receive services.

[1644] "Customers" refer to shoppers who visit physical stores or service users and who receive personalized offers.

[1645] "Personalized offers" refers to individualized service and product proposals tailored to the customer's preferences and needs.

[1646] "Training an AI model" refers to the process of using illustrations and data to teach an artificial intelligence model and strengthen it to work effectively for a specific task.

[1647] "Content Creator" refers to a person or organization that creates illustrations or other visual content and provides it to the System.

[1648] "Existing illustrations" refer to visual materials previously created by content creators and provided for use as training data.

[1649] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[1650] Server Processing

[1651] 1. Storing your information and preferences

[1652] The server receives the user's registered favorite images and characters and stores them in a database. This allows the user to change their favorite information as many times as they like, and the system always keeps the latest user preferences.

[1653] 2. Training the AI ​​model

[1654] The server collects existing illustration data provided by content creators and uses it to train an AI model that is trained to generate stickers based on the tagged data and the user's conversation content. This process uses deep learning frameworks such as TensorFlow and PyTorch.

[1655] 3. Stamp generation and presentation

[1656] The server analyzes the user's message and generates appropriate stickers based on the user's preferences and the content of the conversation. The generated sticker candidates are sent to the user's device and displayed. Specifically, for example, a prompt phrase such as "new item arrival with a blue cat character" is input into the generative AI model to generate an appropriate sticker.

[1657] Terminal handling

[1658] 1. Providing a user interface

[1659] The device provides an interface for users to register their favorite pictures and characters, as well as an interface for displaying stamps during conversations. It is implemented as an application for smartphones and tablets.

[1660] 2. Data transmission and reception

[1661] The device sends the user's registration information and interaction log to the server. This conveys the user's interaction context to the server, which then generates stamps based on that information. The device receives the generated stamp list and displays it to the user.

[1662] 3. Selecting and Using Stamps

[1663] The user selects the desired stamp from the list of stamp candidates presented by the server through the terminal interface, and the selected stamp is inserted into the message and sent to the other party.

[1664] User Actions

[1665] 1. Register your preferences

[1666] Users use the device interface to specify their preferred image or character, such as "a smiling cat" or "I like blue items," and then input this information into the app and send it to the server.

[1667] 2. Starting a dialogue

[1668] Users can interact with store staff or AI chatbots in physical stores, for example by sending messages such as "Have new products arrived?"

[1669] 3. Check and use stamps

[1670] The user selects an appropriate stamp from the list of stamp candidates sent by the server. For example, the "Blue Cat" stamp is suggested for the message "Have new items arrived?" The user selects this stamp, inserts it into the conversation, and sends it.

[1671] Software and Hardware Requirements

[1672] Software used:

[1673] Server software: Linux (e.g., Ubuntu 20.04), Flask web framework, PostgreSQL database

[1674] AI model training: TensorFlow or PyTorch

[1675] Terminal applications: iOS app (Swift), Android app (Kotlin)

[1676] Hardware used:

[1677] Server hardware: High-performance server machine (e.g., Dell PowerEdge series)

[1678] Device: iOS or Android smartphone or tablet

[1679] Specific examples

[1680] If User A registers "Smiling Cat" as a preference, the server stores this. When User A sends a message to a physical store asking "Have new items arrived?", the server analyzes this message and inputs the prompt "New items arrived with a smiling cat character" into the AI ​​model. The AI ​​model generates an appropriate stamp and sends it to the device. User A selects the "Smiling Cat" stamp and sends it to the store clerk or chatbot, achieving personalized communication.

[1681] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1682] Step 1:

[1683] Registering user preferences

[1684] The server receives the user's favorite images and characters sent from the device, stores this information in a database, and updates the user's favorite list.

[1685] Input: User preference information (e.g., "smiling cats," "blue items")

[1686] Output: User preference information stored in a database

[1687] Step 2:

[1688] Collecting learning data and training AI models

[1689] The server collects existing illustration data provided by content creators, labels it, and trains the AI ​​model, using deep learning frameworks such as TensorFlow and PyTorch to enable the model to generate appropriate stamps.

[1690] Input: Existing illustration data and label information

[1691] Output: A trained AI model

[1692] Step 3:

[1693] Message parsing and prompt generation

[1694] The server receives the user's interactive message sent from the device and analyzes its content. Based on the analysis results, it generates a prompt sentence and inputs it into the AI ​​model. For example, if the message is "Have new items arrived?", it generates the prompt sentence "new item arrival with a smiling cat character."

[1695] Input: User interaction message

[1696] Output: Generated prompt statement

[1697] Step 4:

[1698] Stamp Generation

[1699] The server inputs the generated prompt into the AI ​​model to generate a corresponding stamp. The AI ​​model analyzes the prompt and outputs a stamp that combines an appropriate image and character.

[1700] Input: Generated prompt text

[1701] Output: Generated stamp

[1702] Step 5:

[1703] Stamp list presentation

[1704] The server sends the generated stamp list to the device and presents it to the user, who can then view the stamps displayed through the device interface.

[1705] Input: Generated stamp list

[1706] Output: Stamp list displayed on the device

[1707] Step 6:

[1708] Selecting and Using Stamps

[1709] The user selects the desired stamp from a list of stamps presented to them using the terminal interface, and the selected stamp is inserted into the message and sent to the interlocutor.

[1710] Input: User selects stamp

[1711] Output: Send selected stamps

[1712] Through the above processing steps, appropriate stamps are automatically generated based on the content of the user's dialogue, realizing personalized communication.

[1713] 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.

[1714] The system of the present invention allows users to register their favorite pictures and characters, and automatically generates stamps based on the content of the conversation and an emotion engine, thereby providing users with appropriate stamps.

[1715] Server Processing

[1716] 1. Storing your information and preferences

[1717] The server receives information about the preferred designs and characters sent by the user and stores it in a database.

[1718] 2. Training the AI ​​model

[1719] The server receives existing illustration data provided by the illustrator and uses it as training data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stickers based on the user's conversation content and emotions.

[1720] 3. Use of Emotion Engine

[1721] The server analyzes the content of the user's conversation and uses an emotion engine to recognize the user's emotions from that content. The emotion engine uses multiple language models and emotion recognition algorithms to analyze the user's emotions with high accuracy.

[1722] 4. Stamp generation and presentation

[1723] Based on the user's message and the perceived emotion, the AI ​​model generates appropriate stickers, which are then sent to the user's device for display.

[1724] Terminal handling

[1725] 1. Providing a user interface

[1726] The device provides an interface for users to register their favorite pictures and characters, as well as an interface that displays stamps based on the content of conversations and emotions.

[1727] 2. Data transmission and reception

[1728] The device sends the user's registration information and interaction log to the server, which then conveys the user's interaction context and emotional information to the server. The device also receives a stamp list sent from the server and displays it to the user.

[1729] 3. Selecting and Using Stamps

[1730] The system provides an interface for users to select the desired stamp from the provided stamps and insert it into the conversation. The selected stamp is then sent from the device to the conversation partner.

[1731] User Actions

[1732] 1. Register your preferences

[1733] Users can specify their favorite images and characters through the app on their device. For example, if a user likes "smiling dogs," they enter this information into the app and send it to the server.

[1734] 2. Starting a dialogue

[1735] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[1736] 3. Emotional Recognition

[1737] The server analyzes the received message and uses an emotion engine to identify the user's emotion. For example, it recognizes positive emotion from the message "I had fun today."

[1738] 4. Check and use stamps

[1739] The user selects an appropriate stamp from among the stamp candidates sent by the server based on the content of the conversation and the recognized emotion. For example, a "smiling dog" stamp is suggested for the message "I had fun today." The user selects this stamp, inserts it into the conversation, and sends it.

[1740] Specific examples

[1741] 1. Register your favorite designs and characters

[1742] User A registers "cat characters" as a preference. He enters this information into the device app and sends it to the server.

[1743] 2. Dialogue and Emotion Recognition

[1744] When User A sends a message saying "Work is done! Yay!", the server analyzes this message and uses an emotion engine to recognize positive emotions.

[1745] 3. Stamp creation and selection

[1746] The server uses an AI model to generate a "joyful cat" stamp based on the recognized positive emotion.

[1747] The server sends stamp candidates to the user's device, and User A selects the "Joyful Cat" stamp and sends it to the person he or she is talking to.

[1748] This system allows users to easily create stamps based on their preferences and emotions, allowing them to enjoy richer communication.

[1749] The processing flow will be explained below.

[1750] The processing steps from when the user registers their favorite pictures or characters to when the emotion engine is used to generate stamps during a conversation

[1751] Step 1: Users register their favorite designs and characters

[1752] 1. User: Enter your favorite image or character into the device app. For example, "dog character."

[1753] 2. Terminal: Converts the user's input preferences into data packets.

[1754] 3. Terminal: Sends the converted data packets to the server.

[1755] Step 2: The server stores the user information

[1756] 1. Server: Analyzes data packets received from users and extracts their preferred images and character information.

[1757] 2. Server: Stores the extracted information in a database.

[1758] Step 3: Train the AI ​​model

[1759] 1. Illustrator: Upload an existing illustration to the server as learning data.

[1760] 2. Server: Stores the received illustration data in a database and performs preprocessing (size adjustment, noise removal, etc.).

[1761] 3. Server: Trains the AI ​​model using the preprocessed illustration data, properly tags each illustration, and generates stickers for the corresponding user conversation and emotion.

[1762] Step 4: User initiates interaction

[1763] 1. User: Sends a message to the person they are interacting with through the app, for example, "I had a great time today."

[1764] 2. Terminal: Converts the user's message into data packets and sends them to the server.

[1765] Step 5: The emotion engine recognizes the user's emotions

[1766] 1. Server: Analyzes the received message data.

[1767] 2. Server: Recognizes the user's emotion from the message content using an emotion engine. For example, recognize positive emotion from the message "I had fun today."

[1768] Step 6: The server generates and presents the stamp

[1769] 1. Server: Using an AI model, the server generates appropriate stamps based on the analysis results, the user's preferred designs, character information, and recognized emotions.

[1770] 2. Server: Arranges the generated stamp candidates into a list and sends it to the user's device.

[1771] Step 7: Your device will display sticker suggestions

[1772] 1. Terminal: The stamp list received from the server is displayed on the user interface, visually presenting multiple stamps in thumbnail format.

[1773] 2. User: Select the desired stamp from the presented stamp list.

[1774] Step 8: User selects sticker and sends it

[1775] 1. User: Selects the "Smiling Dog" stamp from the presented stamps and sends it to the person he or she is talking to.

[1776] 2. Terminal: Converts the selected stamp data into a data packet and sends it to the other terminal.

[1777] In this way, the user, device, server, and emotion engine work together to enable users to easily create stamps based on their preferences and emotions, and enjoy rich communication.

[1778] Example 2

[1779] 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."

[1780] Conventional stamp generation systems have had problems such as making it difficult for users to easily select stamps that match their preferences, and not being able to provide appropriate stamps based on emotions in a timely manner. Furthermore, stamp generation is not sufficiently automated, making it impossible to generate stamps that take into account the user's conversation content and emotions.

[1781] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1782] In this invention, the server includes means for users to register their favorite images and characters, means for saving the registered favorite images and characters, means for automatically generating stamps based on the conversation content and the emotion engine, means for presenting the generated stamps to the user terminal, and means for the user to select the presented stamps via the terminal, thereby enabling timely provision of stamps based on the user's preferences and emotions.

[1783] "User" refers to an individual or corporation that uses the system, and is the entity that primarily performs the operations of registering, selecting, and sending stamps.

[1784] "Images and characters" are visual expressions designated by users as their preferences, and are the materials used to generate stamps.

[1785] A "stamp" is an image or icon added to a message in digital communication to visually convey emotions or intentions.

[1786] A "generative AI model" is a model that uses artificial intelligence to automatically generate stamps based on user preferences and conversation content.

[1787] An "emotion engine" is a system or algorithm that analyzes the content of a user's conversation and recognizes the emotions contained within it.

[1788] The "database" is a system for storing and managing users' preferred images, characters, and related information such as conversation logs.

[1789] A "prompt" is text information that is input into a generative AI model and used to generate a specific stamp or response.

[1790] A "terminal" is a device used by a user to access and operate the system, such as a smartphone, tablet, or PC.

[1791] A "server" is a central computer system that operates and manages the entire system, and processes data and generates stamps in response to user requests.

[1792] "Interface" is a general term for the operation screen and input / output devices that allow users to interact with the system.

[1793] The system of the present invention allows users to register their favorite images and characters, and automatically generates stamps based on the content of the conversation and an emotion engine, thereby providing appropriate stamps to users. Specific embodiments of the system are described below.

[1794] Server Processing

[1795] Storing User Information and Preferences

[1796] The server receives the user's favorite images and character information sent from the device and stores it in a database. "MySQL" can be used as the database software. For example, information such as the user ID, favorite character, and registration date and time is stored.

[1797] Training an AI model

[1798] The server receives existing image data provided by the image creator and uses it as training data for the AI ​​model. The image data is tagged, for example, a cat image is tagged with "cat," "cute," and "smiling." Then, using TensorFlow and PyTorch, a stamp generation model is trained based on the conversation content and emotions.

[1799] Use of emotion engine

[1800] The server receives the user's conversation content sent from the device and uses an emotion engine to recognize the user's emotions from the content. The emotion engine can use tools such as Google Cloud Natural Language API or IBM Watson. This allows for highly accurate analysis of the user's emotions.

[1801] Stamp generation and presentation

[1802] The server uses an AI model to automatically generate appropriate stickers based on the recognized emotions and user preferences, and sends the generated sticker candidates to the user's device, where they are presented to the user.

[1803] Terminal handling

[1804] Providing a user interface

[1805] The device provides an interface for users to register their favorite images and characters, such as a form entry screen and an image selection screen, as well as an interface for displaying stamps based on the user's dialogue and emotions.

[1806] Sending and receiving data

[1807] The terminal transmits the user's input preference information to the server, transmits the user's interaction log to the server, conveys the user's interaction context and emotion information to the server, and receives the stamp list transmitted from the server and displays it to the user.

[1808] Selecting and Using Stamps

[1809] The terminal provides an interface for the user to select a desired stamp from the stamps presented and insert it into the conversation. The selected stamp is then sent from the terminal to the conversation partner.

[1810] User Actions

[1811] Register your preferences

[1812] The user launches the app on their device, inputs their favorite image or character, for example, "smiling dog," and sends it to the server.

[1813] Starting a conversation

[1814] The user opens a message exchange screen with the person they are talking to, enters a message such as "I had fun today," and sends it.

[1815] Emotion recognition

[1816] The server analyzes the received message and uses an emotion engine to identify the user's emotion. For example, it recognizes positive emotion from the message "I had fun today."

[1817] Checking and using stamps

[1818] The stamp candidates sent from the server are displayed on the user's device, and the user selects the appropriate stamp from the presented stamps and presses the select button.

[1819] Specific examples

[1820] 1. Register your favorite images and characters

[1821] User A registers "cat characters" as a preference. He enters "cat" into the device app and sends it to the server.

[1822] 2. Dialogue and Emotion Recognition

[1823] When User A sends a message saying "Work is done! Yay!", the server analyzes this message and uses an emotion engine to recognize positive emotions.

[1824] 3. Stamp creation and selection

[1825] The server generates a stamp of a happy cat using an AI model based on the recognized positive emotion. The server sends stamp candidates to the user's device, and User A selects the "happy cat" stamp and sends it to the person he or she is talking to.

[1826] Prompt Sentence Examples

[1827] 1. Register your preferences for designs and characters

[1828] "My favorite character is 'Cat'. Please register this information."

[1829] 2. Message sending for dialogue and emotion recognition

[1830] "Job done! Yay!"

[1831] 3. Using the generated stamp

[1832] Select "Joyful Cat" and send.

[1833] This system allows users to easily create stamps based on their preferences and emotions, allowing them to enjoy richer communication.

[1834] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1835] Step 1:

[1836] Users register their favorite images and characters

[1837] Input: The user inputs and sends their preferred image or character through the device interface.

[1838] How it works: The device receives information entered by the user through forms and selection screens and sends it to the server.

[1839] Output: The device sends the preference information entered by the user to the server, which receives this information.

[1840] Step 2:

[1841] Storing User Information and Preferences

[1842] Input: The user's preferred image and character information sent in Step 1.

[1843] Operation: The server stores the received information in a database. For example, it uses "MySQL" to register the user ID, favorite character, and registration date and time.

[1844] Output: The server sends a confirmation message to the device indicating that the save is complete.

[1845] Step 3:

[1846] Training an AI model

[1847] Input: Existing image data and tagging data provided by the image creator.

[1848] How it works: The server tags images and preprocesses the data. This preprocessed data is used to train a generative AI model using TensorFlow and PyTorch. The model learns to generate stickers based on the user's conversation content and emotions using the tag information.

[1849] Output: A fully trained generative AI model.

[1850] Step 4:

[1851] Receiving conversation content

[1852] Input: Message exchanges between the user and their interlocutor.

[1853] How it works: The device sends the messages the user sends to the server, which receives and stores them.

[1854] Output: The server is ready to parse and process the received conversation content.

[1855] Step 5:

[1856] Emotion recognition

[1857] Input: The conversation received in step 4.

[1858] How it works: The server uses an emotion engine to analyze the conversation and identify the user's emotions. For example, it uses Google Cloud Natural Language API or IBM Watson to analyze emotion data.

[1859] Output: Identified user sentiment data.

[1860] Step 6:

[1861] Stamp Generation

[1862] Input: Identified emotion data and user's preferred image or character information.

[1863] How it works: The server generates optimal stamps using a generative AI model. Emotional data and preference information are input to the generative AI model as prompts.

[1864] Output: The generated stamp candidates.

[1865] Step 7:

[1866] Sending and displaying stamps

[1867] Input: Generated stamp candidates.

[1868] Operation: The server sends the generated stamp candidates to the user terminal and displays them to the user. The terminal displays the stamp candidates in the user interface.

[1869] Output: User can see the stamp suggestions.

[1870] Step 8:

[1871] Select a stamp

[1872] Input: The stamp selected by the user.

[1873] How it works: The user selects the desired stamp from the ones presented and presses the "Send" button. The device then sends this selection to the server.

[1874] Output: The selected stamps are sent to the server.

[1875] Step 9:

[1876] Send Selected Stamps

[1877] Input: The stamp selected in step 8.

[1878] Operation: The server sends the selected stamp to the conversation partner. The terminal displays the selected stamp to the conversation partner.

[1879] Output: The stamp is sent to the person you are talking to and displayed.

[1880] This allows users to easily send stamps based on their preferences and emotions to their interlocutors, enabling richer communication.

[1881] (Application example 2)

[1882] 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."

[1883] Communication with customers in virtual stores is mainly text-based, resulting in limited emotional communication. Furthermore, it is difficult to respond flexibly to customer emotions, limiting the quality of service. Given this background, there is a need for a system that can appropriately recognize customer emotions in virtual stores and provide appropriate stamps to enable richer communication.

[1884] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1885] In this invention, the server includes means for a user to register their favorite pictures and characters, means for saving the registered favorite pictures and characters, means for automatically generating stamps based on conversation content and emotion analysis, means for presenting the generated stamps to the user, means for the user to select the presented stamps, emotion analysis means for recognizing emotions from the content of the user's message, and means for presenting stamps generated in accordance with the recognized emotions on the virtual store interface. This makes it possible to improve the quality of communication by recognizing customer emotions in the virtual store in real time and providing stamps in response to those emotions.

[1886] "User" refers to a person or company that uses the system to register their favorite designs or characters and generate and use stamps.

[1887] "Pictures and characters" are illustrations, images, symbols, etc. that users select as their preferences.

[1888] "Storage means" refers to a storage device or database for storing information about the images and characters registered by the user.

[1889] "Conversation content" refers to messages and text information sent by users on the system.

[1890] "Sentiment analysis" is the process of analyzing the content of a user's message to recognize their emotional state.

[1891] "Stamps" are emoticons or illustrations generated for users to use in their messages.

[1892] "Means for automatic generation" refers to the process by which the system automatically generates stamps based on the content of the user's conversation and sentiment analysis.

[1893] The "presentation means" is an interface for visually presenting the generated stamp to the user.

[1894] The "selection means" is an operation interface that allows the user to select the desired stamp from among the stamps presented.

[1895] "Emotion analysis tools" are algorithms or software that recognize emotions from users' messages.

[1896] A "virtual store" is an online store that offers products and services over the Internet.

[1897] An "AI model" is an artificial intelligence algorithm that generates stamps based on the content of the conversation and emotions.

[1898] The "virtual store interface" is the user interface through which customers interact with the system.

[1899] The system of the present invention allows users to register their favorite images and characters, and automatically generates and displays stamps based on conversation content and sentiment analysis. In implementing this system, the server, terminal, and user components work in conjunction with each other.

[1900] Server Processing

[1901] 1. Storing your information and preferences

[1902] The server receives the user's preferred designs and characters and stores them in a database. New designs and characters registered by the user are updated in real time.

[1903] 2. Training the AI ​​model

[1904] The server receives existing illustration data provided by the illustrator and uses it as training data for the AI ​​model. It tags the illustration data and trains the model to generate appropriate stickers based on the user's conversation content and emotions. Specific software used includes TensorFlow and PyTorch.

[1905] 3. Use of sentiment analysis engines

[1906] The server analyzes the user's conversation content and uses a sentiment analysis engine to recognize the user's emotions from the content. This engine analyzes emotions with high accuracy using natural language processing models (e.g., BERT and GPT-3).

[1907] 4. Stamp generation and presentation

[1908] Based on the user's message and the recognized emotion, the AI ​​model generates appropriate stickers. The generated sticker candidates are sent to the user's device and displayed. Generative Adversarial Networks (GANs) and DALL-E are used for generation.

[1909] Terminal handling

[1910] 1. Providing a user interface

[1911] The device provides an interface for users to register their favorite pictures and characters, as well as an interface that displays stamps based on the content of conversations and emotions.

[1912] 2. Data transmission and reception

[1913] The device sends the user's registration information and interaction log to the server, which then conveys the user's interaction context and emotional information to the server. The device also receives a stamp list sent from the server and displays it to the user.

[1914] 3. Selecting and Using Stamps

[1915] It provides an interface for users to select the desired stamp from the provided stamps, and the selected stamp is sent from the terminal to the interlocutor.

[1916] User Actions

[1917] 1. Register your preferences

[1918] Users can specify their favorite images and characters through the app on their device. For example, if a user likes "smiling dogs," they enter this information into the app and send it to the server.

[1919] 2. Starting a dialogue

[1920] The user initiates a message exchange with the other person, for example, sending a message saying, "I had a great time today."

[1921] 3. Emotional Recognition

[1922] The server analyzes the received message and uses a sentiment analysis engine to identify the user's sentiment. For example, it recognizes positive sentiment from a message such as "I had fun today."

[1923] 4. Check and use stamps

[1924] The user selects an appropriate stamp from among the stamp candidates sent by the server based on the content of the conversation and the recognized emotion. For example, a "smiling dog" stamp is suggested for the message "I had fun today." The user selects this stamp, inserts it into the conversation, and sends it.

[1925] Specific examples

[1926] For example, if User A registers "cat characters" as a favorite and sends a message saying "Work is done! Yay!", the server will analyze this message and recognize the positive emotion. Based on this, a "joyful cat" stamp will be generated and presented to User A. User A can then select this stamp and send it to the person they are interacting with, achieving engaging, emotion-based communication.

[1927] Example prompt sentence:

[1928] A user sent a message saying, "I really liked this product!" Recognize the emotion from this message and generate an appropriate sticker based on the user's favorite character, "cat."

[1929] In this way, the system of the present invention automatically generates and provides stamps that correspond to the user's emotions, thereby improving the user experience in the virtual store.

[1930] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1931] Step 1:

[1932] The server provides the terminal with an interface that allows users to register their favorite pictures and characters.

[1933] Input: User's preferred designs and character information

[1934] Output: Temporarily save registered information

[1935] Specific operation: The user inputs information such as "smiling dog" through the device interface, and the device temporarily stores this preference information.

[1936] Step 2:

[1937] The terminal transmits the user's registered favorite images and character information to the server.

[1938] Input: User preference information (e.g., "smiling dogs")

[1939] Output: Data sent to the server, confirmation message

[1940] Specific operation: The preference information is sent from the device to the server, which receives it and stores it in the database. After completion, a confirmation message is displayed on the device.

[1941] Step 3:

[1942] The server stores the registration information submitted by the user in a database.

[1943] Input: User preference information

[1944] Output: User preferences stored in a database

[1945] What happens: The server updates the database, storing the user's preferences, such as "smiling dogs."

[1946] Step 4:

[1947] The server provides an interface for analyzing the content of the user's conversation.

[1948] Input: A message that the user types

[1949] Output: Send message to server

[1950] Specific operation: The device sends the message entered by the user in the chat (e.g., "Today was fun") to the server.

[1951] Step 5:

[1952] The server analyzes the received message using a sentiment analysis engine.

[1953] Input: User's message

[1954] Output: Parsed emotion data

[1955] Specific operation: The server uses a natural language processing model (BERT or GPT-3) to analyze positive emotions from the message "I had fun today."

[1956] Step 6:

[1957] The server generates stamps based on the analyzed emotional data and the user's preferences.

[1958] Input: Emotion data, preferred picture information

[1959] Output: Generated stamp

[1960] Specific operation: Using AI models (TensorFlow, GANs, DALL-E), we generate "smiling dog" stamps that match positive emotions.

[1961] Step 7:

[1962] The server transmits the generated stamp to the terminal and presents it to the user.

[1963] Input: Generated stamp data

[1964] Output: Send stamp data to the terminal

[1965] Specific operation: The server sends the "smiling dog" stamp data to the terminal and displays the stamp on the display interface.

[1966] Step 8:

[1967] The terminal provides an interface for the user to select from the presented stamps.

[1968] Input: Presented stamp

[1969] Output: User selection data

[1970] Specific behavior: The user selects the "smiling dog" sticker that is displayed.

[1971] Step 9:

[1972] The terminal operates to transmit the stamp selected by the user to the interlocutor.

[1973] Input: User's stamp selection data

[1974] Output: Send stamp to the person you are talking to

[1975] Specific operation: The device sends the "smiling dog" stamp selected by the user to the person it is talking to.

[1976] In this way, stamps are generated and displayed in real time according to the user's conversation content and emotions, enabling richer communication.

[1977] 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.

[1978] 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.

[1979] 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.

[1980] 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.

[1981] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1982] 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.

[1983] 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).

[1984] 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.

[1985] 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."

[1986] 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.

[1987] 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).

[1988] 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.

[1989] 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.

[1990] 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.

[1991] 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.

[1992] 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.

[1993] 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.

[1994] 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.

[1995] 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.

[1996] 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.

[1997] 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.

[1998] The following is further disclosed regarding the above embodiment.

[1999] (Claim 1)

[2000] A means for users to register their favorite designs and characters,

[2001] A way to save your favorite registered designs and characters,

[2002] A means for automatically generating stamps based on the content of a conversation;

[2003] means for presenting the generated stamp to a user;

[2004] a means for a user to select a presented stamp;

[2005] A system including:

[2006] (Claim 2)

[2007] 10. The system of claim 1, further comprising means for training an AI model that generates stamps based on user-registered preferred designs and characters.

[2008] (Claim 3)

[2009] 10. The system of claim 1, further comprising means for utilizing existing illustrations provided by an illustration creator as training data.

[2010] "Example 1"

[2011] (Claim 1)

[2012] A means for users to register their preferred visual information and characters,

[2013] A means for storing registered preferred visual information and characters;

[2014] means for automatically generating digital emojis based on the content of a conversation;

[2015] a means for presenting the generated digital emoji to a user;

[2016] a means for a user to select a presented digital emoji;

[2017] A system including:

[2018] (Claim 2)

[2019] 10. The system of claim 1, further comprising means for training an artificial intelligence model to generate digital emojis based on user-registered preferred visual information and characters.

[2020] (Claim 3)

[2021] 10. The system of claim 1, further comprising means for utilizing existing images provided by an image provider as training data.

[2022] "Application Example 1"

[2023] (Claim 1)

[2024] A means for users to register their favorite designs and characters,

[2025] A way to save your favorite registered designs and characters,

[2026] A means for automatically generating stamps based on the content of a conversation;

[2027] means for presenting the generated stamp to a user;

[2028] a means for a user to select a presented stamp;

[2029] A means for providing personalized recommendations based on customer interactions in a physical store;

[2030] A system including:

[2031] (Claim 2)

[2032] 10. The system of claim 1, further comprising means for training an AI model that generates stamps based on user-registered preferred designs and characters.

[2033] (Claim 3)

[2034] 10. The system of claim 1, further comprising means for utilizing existing illustrations provided by content creators as training data.

[2035] "Example 2: Combining Emotion Engines"

[2036] (Claim 1)

[2037] A means for users to register their favorite images and characters,

[2038] A way to save your favorite images and characters,

[2039] A means for automatically generating stamps based on the conversation content and emotion engine;

[2040] A means for presenting the generated stamp on a user terminal;

[2041] A means for the user to select the stamps presented through the terminal;

[2042] A system including:

[2043] (Claim 2)

[2044] 10. The system of claim 1, further comprising means for recognizing a user's emotion using an emotion engine and presenting appropriate stamps to the user based on the recognized emotion.

[2045] (Claim 3)

[2046] 10. The system of claim 1, further comprising means for training a generative AI model that generates stamps based on preferred images and characters registered by a user.

[2047] (Claim 4)

[2048] 10. The system of claim 1, further comprising means for utilizing existing images provided by image creators as training data.

[2049] (Claim 5)

[2050] The system of claim 1, further comprising means for inputting stamp candidates as prompt sentences to the generative AI model based on the user's conversation content analyzed by the emotion engine.

[2051] "Application example 2 when combining emotion engines"

[2052] (Claim 1)

[2053] A means for users to register their favorite designs and characters,

[2054] A way to save your favorite registered designs and characters,

[2055] means for automatically generating stamps based on conversation content and sentiment analysis;

[2056] means for presenting the generated stamp to a user;

[2057] a means for a user to select a presented stamp;

[2058] an emotion analysis means for recognizing emotions from the content of a user's message;

[2059] a means for presenting stamps generated according to the recognized emotions on an interface of a virtual store;

[2060] A system including:

[2061] (Claim 2)

[2062] 10. The system of claim 1, further comprising means for training an AI model that generates stamps based on user-registered preferred designs and characters.

[2063] (Claim 3)

[2064] 10. The system of claim 1, further comprising means for utilizing existing illustrations provided by an illustration creator as training data. [Explanation of symbols]

[2065] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to register their favorite designs and characters, A way to save your favorite registered designs and characters, A means for automatically generating stamps based on the content of a conversation; means for presenting the generated stamp to a user; a means for a user to select a presented stamp; A system including:

2. The system of claim 1 , further comprising means for training an AI model that generates stamps based on user-registered favorite images and characters.

3. The system according to claim 1 , further comprising means for utilizing existing illustrations provided by an illustration creator as learning data.

Images