system

Abstract

Provide a system. A method for obtaining a message based on a user input; means for transmitting the retrieved messages to a server; means for analyzing the message at a server and extracting at least one keyword; a means for determining design requirements for a stamp based on the extracted keywords; means for generating new stamps based on the determined design requirements; means for transmitting the generated stamp to a user's terminal; A means to display the sent stamp on the chat screen, A system including:

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] The present invention aims to reduce the effort required for users to find appropriate stamps in messaging applications, making chat communication smoother and more enjoyable. Specifically, it aims to solve the following problems:

[0005] 1. The problem is that you can't find a stamp that perfectly matches the current conversation.

[0006] 2. A desire to use original stamps that no one else is using to liven up conversations.

[0007] 3. The problem is that people want to use stamps more to communicate in a more fun way, but existing stamps don't quite meet their needs. [Means for solving the problem]

[0008] In order to solve the above problems, the present invention provides the following means:

[0009] 1. Provide a means to retrieve messages based on user input.

[0010] 2. Provide a means for sending the retrieved messages to the server.

[0011] 3. The server is provided with means for analyzing the message and extracting at least one keyword.

[0012] 4. Provide a means for determining stamp design requirements based on the extracted keywords.

[0013] 5. Provide a means for generating new stamps based on determined design requirements.

[0014] 6. Provide a means for transmitting the generated stamp to the user's terminal.

[0015] 7. Provide a means to display sent stamps on the chat screen.

[0016] This allows users to easily use original stamps that match the content of their messages, making chats more fulfilling.

[0017] A "message" refers to text information that a user sends through a chat application.

[0018] "Terminal" refers to electronic devices such as computers, smartphones, and tablets used by users.

[0019] A "server" refers to a computer system that provides services to multiple terminals over a network.

[0020] "Natural language processing technology" refers to methods and technologies that enable computers to understand, interpret, and generate human language.

[0021] "Keywords" refer to important words or phrases extracted by analyzing the content of a message.

[0022] "Design requirements" refers to specifications regarding the appearance and components (e.g., facial expression, background, text) of the stamp to be generated.

[0023] "Image generation technology" refers to algorithms and methods for generating new images using computers.

[0024] "Stamps" refer to visual representations (usually small images or animations) used in chat applications. [Brief explanation of the drawings]

[0025] [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

[0026] 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.

[0027] First, the terms used in the following description will be explained.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] [First embodiment]

[0034] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0035] 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.

[0036] 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).

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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."

[0046] The present invention relates to a system that allows users to instantly create and use original stamps that are most suitable for messages in chat applications such as LINE. The program processing of this system is explained below in natural language.

[0047] System Overview

[0048] This system analyzes messages sent by users on the server and generates original stamps based on the analysis results. The generated stamps are then immediately sent to the user's device, where they can be sent via chat.

[0049] Program processing flow

[0050] 1. User sends message

[0051] A user opens a chat application such as LINE, types a message, and sends it. For example, a user sends a message such as "I had a great time today!"

[0052] 2. Message retrieval and sending by the device

[0053] The terminal receives the sent message and sends it to the server.

[0054] 3. Message Parsing by the Server

[0055] The server analyzes the received message using natural language processing technology. The analysis includes sentence structure analysis and sentiment analysis. For example, from the message "I had so much fun today!", keywords such as "fun," "today," and "thankful" are extracted.

[0056] 4. Keyword Extraction and Intention Estimation

[0057] The server extracts key keywords from the analysis results and uses them to infer the user's intention. In this case, the keywords "fun," "today," and "thankful" are extracted, and it is inferred that the user had a fun day and is grateful for it.

[0058] 5. Determine stamp requirements

[0059] The server determines the design requirements for the stamp based on the inferred intent. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0060] 6. Stamp Generation

[0061] The server uses image generation techniques (e.g., GANs or Style Transfer) to generate original stamps based on the determined design requirements.

[0062] 7. Sending stamps

[0063] The generated stamp is sent to the user's terminal and displayed on the chat screen.

[0064] 8. User confirmation and stamp sending

[0065] The user can check the generated stamps and send them in chat, allowing them to easily use original stamps that best suit the content of their messages.

[0066] Specific examples

[0067] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[0068] The device sends a message to the server.

[0069] The server analyzes the message and extracts keywords such as "fun," "today," and "thankful."

[0070] The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0071] The server sends the generated stamp to the terminal.

[0072] The user checks the stamp and, if there are no problems, sends it to the chat.

[0073] In this way, the system can instantly generate and send original stamps that are optimal for the content of a user's message, allowing users to always use stamps that are optimal for the conversation at hand, making communication more enjoyable and fulfilling.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[0077] Step 2:

[0078] The terminal receives the message sent by the user.

[0079] Step 3:

[0080] The terminal transmits the acquired message to the server.

[0081] Step 4:

[0082] The server receives the message.

[0083] Step 5:

[0084] The server analyzes the message using natural language processing techniques, including sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message like "I had so much fun today!" is broken down into the keywords "fun," "today," and "thankful."

[0085] Step 6:

[0086] The server extracts key keywords from the analysis results, such as "fun," "today," and "gratitude."

[0087] Step 7:

[0088] The server infers the user's intention based on the extracted keywords. For example, it may infer that the user had a good day and is expressing gratitude for it.

[0089] Step 8:

[0090] The server determines the design requirements for the stamp based on the inferred intent. In this case, the stamp includes elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0091] Step 9:

[0092] The server uses image generation techniques (e.g., Generative Adversarial Networks (GANs) or Style Transfer) to generate original stamps based on the determined design requirements.

[0093] Step 10:

[0094] The server sends the generated stamp to the terminal.

[0095] Step 11:

[0096] The stamp received by the terminal is displayed on the user's chat screen.

[0097] Step 12:

[0098] The user checks the generated stamp, and if there are no particular problems, selects the stamp and sends it to the chat.

[0099] Example 1

[0100] 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."

[0101] There is a need for a system that allows users to quickly generate and use stamps that are optimal for the content of their messages in chat applications. Existing methods require users to manually select stamps, which disrupts the flow of conversation. It can also take a long time for users to find a stamp that is appropriate for the content of their message. To solve this problem, there is a need for a system that automatically generates and provides stamps based on the user's message.

[0102] 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.

[0103] In this invention, the server includes means for acquiring information based on user input, means for transmitting the acquired information to the server, means for analyzing the information and extracting at least one keyword in the server, means for determining design requirements based on the extracted keyword, means for generating a new image based on the determined design requirements, means for transmitting the generated image to the user's device, and means for displaying the transmitted image on a display screen. This makes it possible to automatically and quickly generate and provide a stamp that is optimal for the content of a user's message.

[0104] A "user" is a person who uses the system to send a chat message and request the generation of a stamp.

[0105] "Input" refers to the act of a user sending a text message to a chat application.

[0106] "Information" refers to messages entered by users and other related data.

[0107] "Device" refers to the electronic device (e.g., smartphone, tablet, PC) that a user uses to access the chat application.

[0108] "Server" refers to a computer system that communicates with user devices over a network and performs processes such as parsing messages and generating stamps.

[0109] The term "means for acquiring" refers to the software and hardware configuration for acquiring input information from a user.

[0110] "Means for transmitting" refers to the software and hardware configuration for transmitting the acquired information to the server.

[0111] "Means for analyzing" refers to a software and hardware configuration that analyzes the transmitted information using natural language processing technology and extracts keywords.

[0112] "Keywords" refer to key words or phrases extracted from the analyzed information.

[0113] "Design requirements" refers to the conditions or requirements that determine the characteristics of the stamp to be generated (e.g., facial expression, background, text).

[0114] "Generating means" refers to a software and hardware configuration for generating new images (stamps) according to design requirements.

[0115] "Transmitting means" refers to the software and hardware configuration for transmitting the generated image to a user's device.

[0116] "Means for displaying" refers to the software and hardware configuration for displaying the transmitted image on the screen of the user's device.

[0117] The present invention relates to a system that analyzes messages sent by users using chat applications (e.g., LINE) and automatically generates original stamps based on the contents of the messages. Specific embodiments of the present invention are described below.

[0118] When a user opens a chat application, inputs a message, and sends it, the terminal receives the message and sends it to the server, attaching the user's identification information along with the message content.

[0119] The server analyzes the received message using natural language processing technology (e.g., BERT or GPT-3 (registered trademark)). As part of the analysis, the server analyzes the grammar and sentiment structure to extract key keywords. In this case, for example, keywords such as "fun," "today," and "thankful" are extracted from the message "I had so much fun today!"

[0120] The server infers the user's intent based on the extracted keywords and determines the appropriate design requirements for the stamp, including, for example, a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0121] To generate the stamps, the server uses image generation techniques (e.g., GANs or Style Transfer) to generate original stamps. As a specific example, StyleGAN is used to generate a stamp with the words "Thank you" written on it, featuring a smiling character with fireworks in the background. The stamps generated in this way are most suited to the user's intent.

[0122] The stamp data generated by the server is sent to the user's device. The device displays the received stamp on the chat application screen. The user checks the generated stamp and, if satisfied, sends it as a chat message.

[0123] This allows the present invention to automatically generate and instantly provide original stamps that are optimal for the content of a user's message. Users can intuitively use the stamps that are optimal for them without any special operations, making communication smoother and more enjoyable.

[0124] Examples of concrete examples and prompts

[0125] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[0126] 1. The device receives the message and sends it to the server.

[0127] 2. The server uses natural language processing technology to analyze the message and extract the keywords "fun," "today," and "thank you."

[0128] 3. The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0129] 4. The server sends the generated stamp to the device, which displays it on the chat screen.

[0130] 5. The user checks the stamp and sends it in the chat.

[0131] The specific prompt is as follows:

[0132] Analyze the message "Today was so much fun!" and generate a stamp that best suits that content. The stamp requirements should include a cheerful expression (e.g., a smiling face), a fun background (e.g., fireworks), and the text "Thank you."

[0133] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0134] Step 1:

[0135] A user opens a chat application, types a message, and sends it. The input is a text message such as "I had a great time today!" that the user sends on the chat application, and the output is the message data added to the device's sending queue. Specifically, when the user presses the send button, the message is stored in the device's sending queue.

[0136] Step 2:

[0137] The terminal reads the message from the sending queue and sends it to the server. The input is the user's message data obtained in the previous step, and the output is the message data sent to the server. The terminal sends the message content and the user's identification information to the server via the network.

[0138] Step 3:

[0139] The server analyzes the messages it receives using natural language processing technology. The input is the message data received by the server, and the output is the analyzed keyword data. The server uses generative AI models such as BERT and GPT-3 to perform grammar and sentiment analysis. Specifically, it extracts keywords such as "fun," "today," and "thankful" from the message "I had so much fun today!"

[0140] Step 4:

[0141] The server extracts key keywords from the analysis results and infers the user's intent based on them. The input is the analyzed keyword data, and the output is the inferred user intent. For example, based on the extracted keywords "fun," "today," and "thankful," the server infers that the user had a good day and is grateful for it.

[0142] Step 5:

[0143] The server determines the design requirements for the stamp based on the estimated intent. The input is the estimated user intent, and the output is the design requirement data. The design requirements include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0144] Step 6:

[0145] The server generates original stamps using image generation technology. The input is design requirement data, and the output is the generated stamp image data. The server uses technologies such as GANs and Style Transfer to generate stamps based on the determined design requirements. The specific process involves using StyleGAN to generate a stamp with a smiling character and the word "Thank you" written on it against a background of fireworks.

[0146] Step 7:

[0147] The server sends the generated stamp to the user's device. The input is the generated stamp image data, and the output is the stamp image data sent to the device. The server encodes the stamp in an appropriate data format (e.g. PNG, JPEG) and sends it to the device over the network.

[0148] Step 8:

[0149] The stamp received by the terminal is displayed on the chat screen. The input is the stamp image data sent to the terminal, and the output is the stamp image displayed on the chat screen. The user checks the generated stamp and, if satisfied, sends it as a chat message. Specifically, the user selects a stamp and presses the send button, and the stamp is then displayed to other chat participants.

[0150] By following the above steps, this system can automatically generate and quickly provide an original stamp that is optimal for the content of a user's message.

[0151] (Application example 1)

[0152] 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."

[0153] In customer support, responding quickly and appropriately to messages from users is important for improving customer satisfaction. However, current systems make it difficult to accurately understand users' emotions and intentions and provide an appropriate response immediately. This can result in delayed responses or inability to provide support that meets users' needs. Furthermore, this increases the burden on customer support staff, making it difficult to operate efficiently.

[0154] 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.

[0155] In this invention, the server includes means for acquiring a message based on a user's input, means for transmitting the acquired message to the server, means for analyzing the message in the server and extracting at least one keyword, means for determining stamp design requirements based on the extracted keyword, means for generating a new stamp based on the determined design requirements, means for transmitting the generated stamp to the user's terminal, means for displaying the transmitted stamp on a chat screen, and means for generating stamps and reaction images in response to the user's message and for efficiently supporting customers using a customer support chat application. This enables appropriate customer support to be provided in real time based on the user's message.

[0156] "User input" refers to the transmission of information or instructions given by the user via a communication terminal.

[0157] "Message" refers to text or other information sent based on user input.

[0158] A "server" refers to a computer system that stores and processes data over a network.

[0159] "Keywords" refer to important words and phrases extracted during message analysis.

[0160] A "stamp" is a type of image or emoji displayed in digital format and is used to express a user's emotions or intentions.

[0161] "Design Requirements" refers to the criteria that determine the specific features or elements (e.g., color, shape, text, etc.) of the stamp or image to be generated.

[0162] "Terminal" refers to communication devices such as smartphones and personal computers used by users.

[0163] "Chat screen" refers to an interface that allows users to exchange messages within a messaging application.

[0164] "Natural language processing technology" refers to computer technology for analyzing and understanding human language.

[0165] "Generative AI model" refers to a model that uses artificial intelligence techniques to generate new data (e.g., images, text).

[0166] "Customer support chat application" refers to a chat-style application that enables businesses to provide support to their customers.

[0167] The present invention relates to a system that generates original stamps and reaction images based on messages sent by users through a customer support chat application, and responds promptly and appropriately.

[0168] The following hardware and software are used to build the system:

[0169] Hardware

[0170] High-performance cloud servers (e.g., Amazon Web Services, Google Cloud Platform)

[0171] Smartphones and computers used by users

[0172] software

[0173] Natural Language Processing Libraries: SpaCy, NLTK, Google Cloud Natural Language API

[0174] Image generation technology: PyTorch, TENSORFLOW (registered trademark), GANs library

[0175] Chat support framework: Twilio, Dialogflow

[0176] System Operation

[0177] 1. Getting and sending messages

[0178] When a user sends a message through a customer support chat application, the device receives the message and sends it to the server, for example, "I'm worried because my item is late."

[0179] 2. Message Analysis

[0180] The server analyzes the received message using natural language processing technology (NLP library). Specifically, it performs sentiment analysis and sentence structure analysis to extract important keywords. In this example, the keywords extracted are "delay" and "worry."

[0181] 3. Determine design requirements

[0182] The server determines the design requirements for stamps and reaction images based on the extracted keywords, such as "a stamp that shows an intention to apologize" or "an expression that provides a sense of security."

[0183] 4. Stamp generation

[0184] Based on the determined design requirements, the server generates new stamps and reaction images using image generation techniques (e.g., GANs library), using a generative AI model.

[0185] 5. Sending and displaying stamps

[0186] The generated stamps and reaction images are sent from the server to the user's device and displayed on the chat screen within the customer support chat application, allowing the user to instantly check the generated images and receive appropriate support.

[0187] Specific examples

[0188] For example, if a user sends a message saying, "I'm worried because my item arrived late," the following prompt sentence is input to the generative AI model:

[0189] Prompt Sentence Examples

[0190] A user sends a message saying, "I'm worried about the delay in receiving my item." Generate a stamp expressing apology and relief.

[0191] Based on this prompt, the server generates a stamp with a calm, reassuring character saying, "I'm sorry, but please don't worry." The generated stamp is sent to the user's device and displayed on the chat screen. The user can view it and receive appropriate support.

[0192] As described above, the present invention can provide an appropriate response in real time based on the user's message, thereby improving customer satisfaction in customer support.

[0193] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0194] Program processing steps

[0195] Step 1:

[0196] User messaging

[0197] A user types and sends a message through a customer support chat application.

[0198] Input: A message entered by the user (e.g., "I'm worried about the delay in receiving my item.")

[0199] Output: The terminal gets the message

[0200] Step 2:

[0201] Retrieving and sending messages via the terminal

[0202] The terminal receives the message entered by the user and transmits the message to the server.

[0203] Input: User's message

[0204] Output: Message sent to the server

[0205] Step 3:

[0206] Message parsing by the server

[0207] The server analyzes the received message using natural language processing technology (NLP library).

[0208] Input: The message sent to the server

[0209] Data processing: sentence structure analysis, sentiment analysis

[0210] Output: Extracted keywords (e.g., "delay" and "worry")

[0211] Step 4:

[0212] Keyword extraction and intent estimation

[0213] The server extracts key keywords from the analysis results and uses them to infer the user's intent.

[0214] Input: Parsed message

[0215] Data calculation: Extraction of keywords, application of intent estimation algorithms

[0216] Output: Design requirements for stamps (e.g., "a stamp that shows the intention to apologize" or "an expression that provides a sense of security")

[0217] Step 5:

[0218] Determining design requirements

[0219] The server determines the design requirements for stamps and reaction images based on the keywords picked up.

[0220] Input: Extracted keywords and inferred intent

[0221] Data processing: Determining design requirements

[0222] Output: Specific design requirements (e.g., "smiling character" or "apology message")

[0223] Step 6:

[0224] Stamp generation using AI models

[0225] The server uses image generation technology (GANs and Style Transfer) to generate new stamps and reaction images. Specifically, it inputs a prompt sentence into a generative AI model and generates an image.

[0226] Input: Design Requirements

[0227] Data Computation: Image Generation with Generative AI Models

[0228] Output: Generated stamps and reaction images

[0229] Step 7:

[0230] Sending generated stamps

[0231] The generated stamps and reaction images are sent from the server to the user's device.

[0232] Input: Generated stamps and reaction images

[0233] Output: Stickers and reaction images sent to the user's device

[0234] Step 8:

[0235] Display on the chat screen

[0236] The stamps and reaction images received by the user's device are displayed on the chat screen, where the user can confirm them and continue interacting with the customer support representative.

[0237] Input: sent stamps and reaction images

[0238] Output: Stamps and reaction images displayed on the chat screen

[0239] These are the specific processing steps of the program that realizes the customer support chat application. Through this flow, users can receive prompt and appropriate support.

[0240] 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.

[0241] This invention relates to a system that allows users to instantly create and use original stamps that are best suited to their messages in chat applications such as LINE. Furthermore, it provides a form that combines an emotion engine that recognizes the user's emotions and generates stamps based on that information.

[0242] System Overview

[0243] This system is characterized by analyzing messages sent by users on the server and generating original stamps based on the analysis results. In addition, an emotion engine recognizes the user's emotions and designs stamps based on that information, making it possible to generate more appropriate and emotionally rich stamps. The generated stamps are immediately sent to the user's device, where the user can send them in chats.

[0244] Program processing flow

[0245] 1. User sends message

[0246] The user opens a chat application such as LINE, enters "I had so much fun today!" in the message input field, and presses the send button.

[0247] 2. Message retrieval and sending by the device

[0248] The terminal receives the message sent by the user and sends the message to the server.

[0249] 3. Message analysis and emotion recognition by the server

[0250] The server analyzes the received message using natural language processing technology. This analysis includes sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message such as "I had so much fun today!" is broken down into the keywords "fun," "today," and "thankful." The emotion engine then analyzes the user's emotions and recognizes that they include feelings of joy and gratitude.

[0251] 4. Keyword Extraction and Intention Estimation

[0252] The server extracts key keywords from the analysis results and uses them to infer the user's intent. For example, if the keywords "fun," "today," and "thanks" are extracted, it is inferred that the user had a good day and is expressing gratitude for that.

[0253] 5. Determine stamp requirements

[0254] The server determines the design requirements for the stamp based on the estimated intent and the emotion information from the emotion engine. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0255] 6. Stamp Generation

[0256] The server uses image generation techniques (e.g., Generative Adversarial Networks (GANs) or Style Transfer) to generate original stamps based on the determined design requirements.

[0257] 7. Sending stamps

[0258] The generated stamp is sent to the user's terminal and displayed on the chat screen.

[0259] 8. User confirmation and stamp sending

[0260] The user can check the generated stamps and send them in chat. This allows users to easily use original stamps that best suit the content of their messages, and communicate with stamps that match their emotions.

[0261] Specific examples

[0262] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[0263] The device sends a message to the server.

[0264] The server analyzes the message and extracts keywords such as "fun," "today," and "thankful."

[0265] The emotion engine recognizes the user's emotion as "joy" from the message.

[0266] The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0267] The server sends the generated stamp to the terminal.

[0268] The user checks the stamp and, if there are no problems, sends it to the chat.

[0269] In this way, the system can instantly generate and send original stamps that best fit the content and emotion of a user's message, allowing users to always use stamps that best fit the conversation and emotion at the time, making communication more enjoyable and fulfilling.

[0270] The processing flow will be explained below.

[0271] Step 1:

[0272] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[0273] Step 2:

[0274] The terminal receives the message sent by the user.

[0275] Step 3:

[0276] The terminal transmits the acquired message to the server.

[0277] Step 4:

[0278] The server receives the message.

[0279] Step 5:

[0280] The server begins analyzing the message. It uses natural language processing technology to tokenize and syntactically analyze the sentence and extract key keywords. For example, from the message "I had so much fun today!", the keywords "fun," "today," and "thankful" are extracted.

[0281] Step 6:

[0282] The server uses an emotion engine to recognize the user's emotion. It identifies emotion categories (e.g., joy, sadness, anger, surprise, etc.) from words and phrases contained in the message. In this case, the emotion engine recognizes "joy."

[0283] Step 7:

[0284] The server infers the user's intention based on the analysis results and emotional information. For example, based on the keywords "fun," "today," and "gratitude" and the emotion "joy," it can infer that the user had a fun day and is grateful for it.

[0285] Step 8:

[0286] The server determines the design requirements for the stamp based on the estimated intent and emotion information. For example, the stamp may include a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0287] Step 9:

[0288] The server generates new stickers using image generation techniques (e.g., Generative Adversarial Networks (GANs) and Style Transfer). Based on the determined design requirements, a sticker with the words "Thank you" written on it and a smiling character with fireworks in the background is created.

[0289] Step 10:

[0290] The server sends the generated stamp to the user's terminal.

[0291] Step 11:

[0292] The stamp received by the terminal is displayed on the user's chat screen.

[0293] Step 12:

[0294] The user checks the generated stamps, selects one, and sends it in the chat.

[0295] This process allows users to quickly generate original stamps that best suit their message and emotion and use them in real time, making chat communication richer and more effective.

[0296] Example 2

[0297] 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."

[0298] Conventional chat applications require users to manually select appropriate stamps or emojis when sending messages, making communication cumbersome. Furthermore, the selection of stamps often does not adequately reflect the user's emotions or intentions, resulting in a reduction in the accuracy and effectiveness of the expression. This invention solves the above-mentioned problems by providing a system that automatically analyzes a user's message and the emotions behind it, and instantly generates and provides original stamps that are appropriate for the message.

[0299] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for acquiring a message based on a user's input; means for transmitting the acquired message to the server via a communication network; means for analyzing the message in the server using natural language processing technology and extracting at least one keyword; means for determining design requirements for a stamp based on the extracted keyword and emotional information analyzed by an emotion engine; means for using a generative AI model to generate a new stamp based on the determined design requirements; means for transmitting the generated stamp to the user's terminal; and means for displaying the transmitted stamp on a chat screen. This eliminates the need for the user to manually select a stamp, and enables the user to automatically obtain a stamp that best suits the message and the emotion behind it.

[0300] "User input" refers to messages or text information sent by a user through a chat application.

[0301] A "message" refers to a sentence or text data that a user sends through a chat application.

[0302] "Communications Network" means the Internet or other digital communications infrastructure used to transmit data from a device to a server or vice versa.

[0303] The term "server" refers to a central processing unit that performs various processes in a chat application, such as receiving messages, analyzing messages, and generating stamps.

[0304] "Natural language processing technology" refers to technology that allows a server to analyze text data and perform keyword extraction and emotion recognition.

[0305] "Keywords" refer to important words or phrases extracted from a message using natural language processing techniques.

[0306] "Emotion engine" refers to software or algorithms that analyze emotions from users' messages and provide that emotion information.

[0307] "Stamp design requirements" refer to the elements and attributes that should be included in stamps, which are determined based on the extracted keywords and emotional information.

[0308] "Generative AI Model" refers to an artificial intelligence model used to generate new stamps based on determined design requirements.

[0309] "Terminal" refers to a device such as a computer, smartphone, or tablet that a user uses to use a chat application.

[0310] The "chat screen" refers to an interface in a chat application where messages and stamps are displayed and which is operated by the user.

[0311] This invention relates to a system that allows users to instantly generate and use original stamps based on messages in chat applications. This system recognizes the user's emotions and combines them with an emotion engine to generate stamps based on that information, providing more appropriate and emotive stamps.

[0312] 1. Hardware and Software Used

[0313] Hardware:

[0314] Server: A server equipped with a high-performance central processing unit (including a CPU and GPU).

[0315] Device: The device on which a user uses a chat application, such as a computer, smartphone, or tablet.

[0316] software:

[0317] Chat application: Communication applications such as LINE.

[0318] Natural Language Processing technologies: NLP libraries (e.g. spaCy, NLTK).

[0319] Emotion engine: Software or algorithms for analyzing user emotions (e.g., IBM Watson®, Google Cloud Natural Language API).

[0320] Image generation techniques: Artificial intelligence models including Generative Adversarial Networks (GANs) and Style Transfer.

[0321] 2. Data processing and calculation

[0322] User sending message:

[0323] A user opens a chat application, enters text in the message input field, and presses the send button. For example, to send a message such as "I had so much fun today!"

[0324] Terminal message retrieval and sending:

[0325] The terminal receives the message sent by the user and transmits it to the server via the communication network, where the message is encrypted.

[0326] Server-based message parsing and emotion recognition:

[0327] The server analyzes the received message using natural language processing technology. This analysis includes sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message such as "I had so much fun today!" is broken down into the keywords "fun," "today," and "gratitude." The emotion engine then recognizes the user's emotions as "joy" or "gratitude."

[0328] Determining and generating stamp requirements:

[0329] The server determines the design requirements for the stamp based on the extracted keywords and emotional information. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you." Original stamps are generated using image generation techniques (e.g., GANs, Style Transfer).

[0330] Sending stamps and verifying users:

[0331] The generated stamp is sent to the user's device and displayed on the chat screen. The user checks the generated stamp and, if there are no problems, sends it via chat.

[0332] 3. Examples of concrete examples and prompts

[0333] For example, if a user sends a message saying "I had so much fun today!", the following will happen:

[0334] 1. A user sends a message on the LINE app saying, "Today was so much fun!"

[0335] 2. The device sends a message to the server.

[0336] 3. The server analyzes the message using NLP and extracts the keywords "fun," "today," and "gratitude."

[0337] 4. The emotion engine recognizes the emotions of "joy" and "gratitude" from the message.

[0338] 5. The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0339] 6. The server sends the generated stamp to the device.

[0340] 7. The user checks the stamps received in the LINE app and sends them in the chat.

[0341] Prompt Sentence Examples

[0342] Here is an example of a prompt you can enter into a generative AI model:

[0343] "Please generate an original stamp suitable for the following message."

[0344] Message: "Today was so much fun!"

[0345] This prompt sentence allows the user to instantly obtain an appropriate original stamp, and to communicate with a stamp that best suits the message content and emotion.

[0346] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0347] Step 1: User sends message

[0348] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[0349] Specific operation: A user uses a chat application on a smartphone or computer to enter a message in text format. The entered text data is sent.

[0350] Enter: Text message "Today was so much fun!"

[0351] Output: A trigger signal for a message to be sent from the terminal.

[0352] Step 2: Retrieving and sending messages using the device

[0353] The terminal receives the message sent by the user and transmits the message to the server via the communication network.

[0354] Specific operation: The device retrieves the message sent by the user and sends the message data in encrypted form to the server using the HTTPS protocol.

[0355] Input: The text message sent by the user

[0356] Output: Message data sent to the server in encrypted form

[0357] Step 3: Message analysis and emotion recognition by the server

[0358] The server analyzes the received message using natural language processing technology.

[0359] Specific operation: The server deserializes the message data, tokenizes and parses it using an NLP library (e.g., spaCy, NLTK), and extracts keywords. In addition, it analyzes the sentiment of the message using an emotion engine (e.g., IBM Watson, Google Cloud Natural Language API). For example, the keywords "fun," "today," and "gratitude" are extracted, along with the sentiment information of "joy."

[0360] Input: Message data in encrypted form

[0361] Output: Keywords ("fun," "today," "thankful") and emotional information ("joy")

[0362] Step 4: Determine stamp requirements

[0363] The server determines the design requirements of the stamp based on the extracted keywords and emotion information.

[0364] How it works: The server uses an algorithm to generate sticker concepts based on keywords and emotional information. For example, a sticker might have a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0365] Input: Keywords ("fun," "today," "thankful"), emotional information ("joy")

[0366] Output: Stamp design requirements (e.g. smiley face, fireworks, "thank you")

[0367] Step 5: Generate stamps

[0368] The server generates new stamps using image generation techniques.

[0369] How it works: The server uses techniques such as Generative Adversarial Networks (GANs) and Style Transfer to leverage the GPU to generate original stamps based on design requirements.

[0370] Input: Sticker design requirements (e.g. smiley face, fireworks, "thank you")

[0371] Output: Generated original stamp image data

[0372] Step 6: Send your sticker

[0373] The generated stamp is sent to the user's terminal.

[0374] What it does: The server compresses the generated stamp and quickly sends it to the user's device, where it decompresses the data and converts it into a displayable format.

[0375] Input: Generated original stamp image data

[0376] Output: Stamp data sent to the user's device

[0377] Step 7: User confirmation and stamp sending

[0378] The user checks the generated stamp and sends it in the chat.

[0379] Specific operation: The user visually confirms the generated stamp on the chat screen of the device and presses the "Send" button. The stamp is added to the chat log.

[0380] Input: Stamp data displayed on the terminal

[0381] Output: Stamp sent on the chat screen

[0382] (Application example 2)

[0383] 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."

[0384] In conventional chat systems, users had to manually select appropriate stamps based on their emotions and message content, making it difficult to communicate quickly and effectively. It was also difficult to automatically generate original content that accurately reflected emotions, making communication with users tend to be uniform and mechanical. In particular, in customer support, there was a need for a way to quickly and accurately convey users' emotions, such as dissatisfaction or joy.

[0385] 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.

[0386] In this invention, the server includes means for acquiring a message based on a user's input, means for transmitting the acquired message to the server, means for analyzing the message in the server and extracting at least one keyword, means for determining stamp design requirements based on the extracted keyword and emotion information, means for generating a new stamp based on the determined design requirements, means for transmitting the generated stamp to the user's terminal, means for displaying the transmitted stamp on a chat screen, means for recognizing the user's emotion, and means for generating an original stamp based on the recognized emotion. This makes it possible to automatically generate and transmit a stamp that is optimal for the message and emotion input by the user, thereby achieving fast and effective communication.

[0387] "User input" refers to messages or commands sent by a user via a keyboard or touchscreen, such as in a chat system.

[0388] The "means for obtaining a message" refers to hardware or software that has the function of extracting a message input by a user and passing it on to subsequent processing.

[0389] A "server" is a computer system that processes data and generates stamps via a network.

[0390] The "means for analyzing a message" refers to hardware or software that has the function of using natural language processing technology to understand a user's message and structurally divide its contents.

[0391] "Keyword extraction methods" refer to algorithms and techniques used to extract important words and phrases from the analysis results.

[0392] "Emotion information" refers to data that expresses the emotions contained in a user's message in numerical values ​​or categories.

[0393] "Stamp design requirements" are the standards or specifications that determine the appearance and content of the stamp to be generated.

[0394] "Means for generating new stickers" refers to generative AI models or technologies capable of creating images or animations based on determined design requirements.

[0395] "Means for transmitting stamps" refers to the communication protocols and techniques used to transmit the generated stamps to the user's terminal.

[0396] The "means for displaying on the chat screen" refers to software having a function for displaying the sent stamp on the chat application so that the user can check it.

[0397] "Means for recognizing emotions" refers to algorithms and technologies that estimate emotions from user input, facial expressions, etc., and output them as data.

[0398] "Means for generating original stamps" refers to technology or systems that allow for the creation of new stamps on the spot based on the user's emotions or keywords.

[0399] This invention relates to a system for enhancing communication with users in customer support for online shopping sites. Specifically, it is a system that automatically generates original stamps in response to users' messages and responds in a way that best suits their emotions.

[0400] System configuration

[0401] 1. Get user messages

[0402] Users input messages through the chat system, which are displayed on their terminals and sent to the server.

[0403] 2. Message Analysis and Emotion Recognition

[0404] The server analyzes the received message using natural language processing technology (e.g., TextBlob). The analysis includes tokenizing the sentence, parsing the syntax, and sentiment analysis. During this process, an emotion engine is activated to recognize the user's emotions and extract emotional information such as joy, anger, or dissatisfaction from the message.

[0405] 3. Keyword extraction and intent estimation

[0406] The server extracts key keywords from the analysis results and infers the user's intention. For example, from the message "Product delivery is delayed," the keywords "delivery" and "delay" are extracted, and the emotion engine recognizes dissatisfaction.

[0407] 4. Determine stamp requirements

[0408] The server determines the design requirements for a stamp based on the estimated intent and emotion information, such as the text "I'm sorry," a simple background, and a troubled face.

[0409] 5. Stamp generation

[0410] The server uses a generative AI model (e.g., Generative Adversarial Networks (GANs)) to generate original stamps based on the determined design requirements. The generated stamps are immediately prepared as binary data.

[0411] 6. Sending and displaying stamps

[0412] The generated stamp is sent to the user's device and displayed on the chat screen. The user checks the stamp, and if there are no problems, they can send it again to complete the communication.

[0413] Specific examples

[0414] For example, if a user enters the message "The delivery of the product is delayed," the system will act as follows:

[0415] A message saying "The delivery of the product is delayed" is sent from the terminal to the server.

[0416] The server analyzes the message and extracts the keywords "delivery" and "delay."

[0417] The emotion engine recognizes "dissatisfaction" from the message.

[0418] The server determines the design requirements for the stamp and generates a stamp containing the text "Sorry," a simple background, and a troubled facial expression.

[0419] The server sends the generated stamp to the terminal.

[0420] The device displays the stamp on the chat screen, and the user can check it and send it.

[0421] Prompt Sentence Examples

[0422] User message: "Item delivery is delayed"

[0423] Produced stamp: A stamp containing the text "Sorry"

[0424] Emotion: "Anger"

[0425] Background: "Simple"

[0426] Expression: "worried"

[0427] Through the above process, users can always use stamps that best suit the conversation and emotions they are feeling at the time, realizing a system that allows for smoother and more effective communication.

[0428] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0429] Step 1:

[0430] Users input messages through the chat system, which are displayed on the terminal and simultaneously sent to the server.

[0431] Input: A message entered by the user (e.g., "Your delivery is delayed.")

[0432] Output: Message sent from terminal to server

[0433] Step 2:

[0434] The server analyzes the received message, using natural language processing techniques (e.g., TextBlob) to tokenize the sentences, parse them syntactically, and analyze their sentiment, thereby understanding the message and extracting key keywords and sentiment information.

[0435] Input: User message sent from the terminal

[0436] Data processing: sentence tokenization, syntactic analysis, sentiment analysis

[0437] Output: Key keywords (e.g., "Delivery" and "Delay") and sentiment information (e.g., "Dissatisfied")

[0438] Step 3:

[0439] The server infers the user's intention based on the extracted keywords and emotional information. Based on the inferred intention, the design requirements for the stamp are determined, including the text to be displayed, the background, and the facial expression.

[0440] Input: Key keywords (e.g., "Delivery" or "Delay") and sentiment information (e.g., "Dissatisfied")

[0441] Data processing: Intent estimation and design requirement determination

[0442] Output: Sticker design requirements (e.g. "Sorry" text, simple background, worried face expression)

[0443] Step 4:

[0444] The server uses a generative AI model (e.g., Generative Adversarial Networks (GANs)) to generate original stamps based on the determined design requirements. The stamps are generated as image files and used for subsequent processing.

[0445] Input: Stamp design requirements

[0446] Data processing: Image generation using generative AI models

[0447] Output: Generated original stamp (e.g. stamp image file)

[0448] Step 5:

[0449] The server sends the generated stamp to the user's terminal, and transfers the stamp data to the terminal using a transmission protocol.

[0450] Input: Generated original stamp

[0451] Data processing: data encoding and transmission

[0452] Output: Stamp data sent to the terminal

[0453] Step 6:

[0454] The device displays the received stamps on the chat screen. The user can check the stamps and send them further to the chat if necessary, completing the communication.

[0455] Input: Stamp data sent to the terminal

[0456] Data processing: Decoding and display

[0457] Output: Stamp displayed on the chat screen

[0458] These processing steps automatically generate stamps that best suit the user's message and emotions, enabling fast and effective communication.

[0459] 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.

[0460] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0461] 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.

[0462] [Second embodiment]

[0463] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0464] 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.

[0465] 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).

[0466] 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.

[0467] 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.

[0468] 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).

[0469] 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.

[0470] 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.

[0471] 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.

[0472] 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.

[0473] 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.

[0474] 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."

[0475] The present invention relates to a system that allows users to instantly create and use original stamps that are most suitable for messages in chat applications such as LINE. The program processing of this system is explained below in natural language.

[0476] System Overview

[0477] This system analyzes messages sent by users on the server and generates original stamps based on the analysis results. The generated stamps are then immediately sent to the user's device, where they can be sent via chat.

[0478] Program processing flow

[0479] 1. User sends message

[0480] A user opens a chat application such as LINE, types a message, and sends it. For example, a user sends a message such as "I had a great time today!"

[0481] 2. Message retrieval and sending by the device

[0482] The terminal receives the sent message and sends it to the server.

[0483] 3. Message Parsing by the Server

[0484] The server analyzes the received message using natural language processing technology. The analysis includes sentence structure analysis and sentiment analysis. For example, from the message "I had so much fun today!", keywords such as "fun," "today," and "thankful" are extracted.

[0485] 4. Keyword Extraction and Intention Estimation

[0486] The server extracts key keywords from the analysis results and uses them to infer the user's intention. In this case, the keywords "fun," "today," and "thankful" are extracted, and it is inferred that the user had a fun day and is grateful for it.

[0487] 5. Determine stamp requirements

[0488] The server determines the design requirements for the stamp based on the inferred intent. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0489] 6. Stamp Generation

[0490] The server uses image generation techniques (e.g., GANs or Style Transfer) to generate original stamps based on the determined design requirements.

[0491] 7. Sending stamps

[0492] The generated stamp is sent to the user's terminal and displayed on the chat screen.

[0493] 8. User confirmation and stamp sending

[0494] The user can check the generated stamps and send them in chat, allowing them to easily use original stamps that best suit the content of their messages.

[0495] Specific examples

[0496] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[0497] The device sends a message to the server.

[0498] The server analyzes the message and extracts keywords such as "fun," "today," and "thankful."

[0499] The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0500] The server sends the generated stamp to the terminal.

[0501] The user checks the stamp and, if there are no problems, sends it to the chat.

[0502] In this way, the system can instantly generate and send original stamps that are optimal for the content of a user's message, allowing users to always use stamps that are optimal for the conversation at hand, making communication more enjoyable and fulfilling.

[0503] The processing flow will be explained below.

[0504] Step 1:

[0505] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[0506] Step 2:

[0507] The terminal receives the message sent by the user.

[0508] Step 3:

[0509] The terminal transmits the acquired message to the server.

[0510] Step 4:

[0511] The server receives the message.

[0512] Step 5:

[0513] The server analyzes the message using natural language processing techniques, including sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message like "I had so much fun today!" is broken down into the keywords "fun," "today," and "thankful."

[0514] Step 6:

[0515] The server extracts key keywords from the analysis results, such as "fun," "today," and "gratitude."

[0516] Step 7:

[0517] The server infers the user's intention based on the extracted keywords. For example, it may infer that the user had a good day and is expressing gratitude for it.

[0518] Step 8:

[0519] The server determines the design requirements for the stamp based on the inferred intent. In this case, the stamp includes elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0520] Step 9:

[0521] The server uses image generation techniques (e.g., Generative Adversarial Networks (GANs) or Style Transfer) to generate original stamps based on the determined design requirements.

[0522] Step 10:

[0523] The server sends the generated stamp to the terminal.

[0524] Step 11:

[0525] The stamp received by the terminal is displayed on the user's chat screen.

[0526] Step 12:

[0527] The user checks the generated stamp, and if there are no particular problems, selects the stamp and sends it to the chat.

[0528] Example 1

[0529] 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."

[0530] There is a need for a system that allows users to quickly generate and use stamps that are optimal for the content of their messages in chat applications. Existing methods require users to manually select stamps, which disrupts the flow of conversation. It can also take a long time for users to find a stamp that is appropriate for the content of their message. To solve this problem, there is a need for a system that automatically generates and provides stamps based on the user's message.

[0531] 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.

[0532] In this invention, the server includes means for acquiring information based on user input, means for transmitting the acquired information to the server, means for analyzing the information and extracting at least one keyword in the server, means for determining design requirements based on the extracted keyword, means for generating a new image based on the determined design requirements, means for transmitting the generated image to the user's device, and means for displaying the transmitted image on a display screen. This makes it possible to automatically and quickly generate and provide a stamp that is optimal for the content of a user's message.

[0533] A "user" is a person who uses the system to send a chat message and request the generation of a stamp.

[0534] "Input" refers to the act of a user sending a text message to a chat application.

[0535] "Information" refers to messages entered by users and other related data.

[0536] "Device" refers to the electronic device (e.g., smartphone, tablet, PC) that a user uses to access the chat application.

[0537] "Server" refers to a computer system that communicates with user devices over a network and performs processes such as parsing messages and generating stamps.

[0538] The term "means for acquiring" refers to the software and hardware configuration for acquiring input information from a user.

[0539] "Means for transmitting" refers to the software and hardware configuration for transmitting the acquired information to the server.

[0540] "Means for analyzing" refers to a software and hardware configuration that analyzes the transmitted information using natural language processing technology and extracts keywords.

[0541] "Keywords" refer to key words or phrases extracted from the analyzed information.

[0542] "Design requirements" refers to the conditions or requirements that determine the characteristics of the stamp to be generated (e.g., facial expression, background, text).

[0543] "Generating means" refers to a software and hardware configuration for generating new images (stamps) according to design requirements.

[0544] "Transmitting means" refers to the software and hardware configuration for transmitting the generated image to a user's device.

[0545] "Means for displaying" refers to the software and hardware configuration for displaying the transmitted image on the screen of the user's device.

[0546] The present invention relates to a system that analyzes messages sent by users using chat applications (e.g., LINE) and automatically generates original stamps based on the contents of the messages. Specific embodiments of the present invention are described below.

[0547] When a user opens a chat application, inputs a message, and sends it, the terminal receives the message and sends it to the server, attaching the user's identification information along with the message content.

[0548] The server analyzes the received message using natural language processing techniques (e.g., BERT or GPT-3). As part of the analysis, the server analyzes the grammar and sentiment structure to extract key keywords. In this case, for example, keywords such as "fun," "today," and "thankful" are extracted from the message "I had so much fun today!"

[0549] The server infers the user's intent based on the extracted keywords and determines the appropriate design requirements for the stamp, including, for example, a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0550] To generate the stamps, the server uses image generation techniques (e.g., GANs or Style Transfer) to generate original stamps. As a specific example, StyleGAN is used to generate a stamp with the words "Thank you" written on it, featuring a smiling character with fireworks in the background. The stamps generated in this way are most suited to the user's intent.

[0551] The stamp data generated by the server is sent to the user's device. The device displays the received stamp on the chat application screen. The user checks the generated stamp and, if satisfied, sends it as a chat message.

[0552] This allows the present invention to automatically generate and instantly provide original stamps that are optimal for the content of a user's message. Users can intuitively use the stamps that are optimal for them without any special operations, making communication smoother and more enjoyable.

[0553] Examples of concrete examples and prompts

[0554] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[0555] 1. The device receives the message and sends it to the server.

[0556] 2. The server uses natural language processing technology to analyze the message and extract the keywords "fun," "today," and "thank you."

[0557] 3. The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0558] 4. The server sends the generated stamp to the device, which displays it on the chat screen.

[0559] 5. The user checks the stamp and sends it in the chat.

[0560] The specific prompt is as follows:

[0561] Analyze the message "Today was so much fun!" and generate a stamp that best suits that content. The stamp requirements should include a cheerful expression (e.g., a smiling face), a fun background (e.g., fireworks), and the text "Thank you."

[0562] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0563] Step 1:

[0564] A user opens a chat application, types a message, and sends it. The input is a text message such as "I had a great time today!" that the user sends on the chat application, and the output is the message data added to the device's sending queue. Specifically, when the user presses the send button, the message is stored in the device's sending queue.

[0565] Step 2:

[0566] The terminal reads the message from the sending queue and sends it to the server. The input is the user's message data obtained in the previous step, and the output is the message data sent to the server. The terminal sends the message content and the user's identification information to the server via the network.

[0567] Step 3:

[0568] The server analyzes the messages it receives using natural language processing technology. The input is the message data received by the server, and the output is the analyzed keyword data. The server uses generative AI models such as BERT and GPT-3 to perform grammar and sentiment analysis. Specifically, it extracts keywords such as "fun," "today," and "thankful" from the message "I had so much fun today!"

[0569] Step 4:

[0570] The server extracts key keywords from the analysis results and infers the user's intent based on them. The input is the analyzed keyword data, and the output is the inferred user intent. For example, based on the extracted keywords "fun," "today," and "thankful," the server infers that the user had a good day and is grateful for it.

[0571] Step 5:

[0572] The server determines the design requirements for the stamp based on the estimated intent. The input is the estimated user intent, and the output is the design requirement data. The design requirements include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0573] Step 6:

[0574] The server generates original stamps using image generation technology. The input is design requirement data, and the output is the generated stamp image data. The server uses technologies such as GANs and Style Transfer to generate stamps based on the determined design requirements. The specific process involves using StyleGAN to generate a stamp with a smiling character and the word "Thank you" written on it against a background of fireworks.

[0575] Step 7:

[0576] The server sends the generated stamp to the user's device. The input is the generated stamp image data, and the output is the stamp image data sent to the device. The server encodes the stamp in an appropriate data format (e.g. PNG, JPEG) and sends it to the device over the network.

[0577] Step 8:

[0578] The stamp received by the terminal is displayed on the chat screen. The input is the stamp image data sent to the terminal, and the output is the stamp image displayed on the chat screen. The user checks the generated stamp and, if satisfied, sends it as a chat message. Specifically, the user selects a stamp and presses the send button, and the stamp is then displayed to other chat participants.

[0579] By following the above steps, this system can automatically generate and quickly provide an original stamp that is optimal for the content of a user's message.

[0580] (Application example 1)

[0581] 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."

[0582] In customer support, responding quickly and appropriately to messages from users is important for improving customer satisfaction. However, current systems make it difficult to accurately understand users' emotions and intentions and provide an appropriate response immediately. This can result in delayed responses or inability to provide support that meets users' needs. Furthermore, this increases the burden on customer support staff, making it difficult to operate efficiently.

[0583] 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.

[0584] In this invention, the server includes means for acquiring a message based on a user's input, means for transmitting the acquired message to the server, means for analyzing the message in the server and extracting at least one keyword, means for determining stamp design requirements based on the extracted keyword, means for generating a new stamp based on the determined design requirements, means for transmitting the generated stamp to the user's terminal, means for displaying the transmitted stamp on a chat screen, and means for generating stamps and reaction images in response to the user's message and for efficiently supporting customers using a customer support chat application. This enables appropriate customer support to be provided in real time based on the user's message.

[0585] "User input" refers to the transmission of information or instructions given by the user via a communication terminal.

[0586] "Message" refers to text or other information sent based on user input.

[0587] A "server" refers to a computer system that stores and processes data over a network.

[0588] "Keywords" refer to important words and phrases extracted during message analysis.

[0589] A "stamp" is a type of image or emoji displayed in digital format and is used to express a user's emotions or intentions.

[0590] "Design Requirements" refers to the criteria that determine the specific features or elements (e.g., color, shape, text, etc.) of the stamp or image to be generated.

[0591] "Terminal" refers to communication devices such as smartphones and personal computers used by users.

[0592] "Chat screen" refers to an interface that allows users to exchange messages within a messaging application.

[0593] "Natural language processing technology" refers to computer technology for analyzing and understanding human language.

[0594] "Generative AI model" refers to a model that uses artificial intelligence techniques to generate new data (e.g., images, text).

[0595] "Customer support chat application" refers to a chat-style application that enables businesses to provide support to their customers.

[0596] The present invention relates to a system that generates original stamps and reaction images based on messages sent by users through a customer support chat application, and responds promptly and appropriately.

[0597] The following hardware and software are used to build the system:

[0598] Hardware

[0599] High-performance cloud servers (e.g., Amazon Web Services, Google Cloud Platform)

[0600] Smartphones and computers used by users

[0601] software

[0602] Natural Language Processing Libraries: SpaCy, NLTK, Google Cloud Natural Language API

[0603] Image generation technology: PyTorch, TensorFlow, GANs library

[0604] Chat support framework: Twilio, Dialogflow

[0605] System Operation

[0606] 1. Getting and sending messages

[0607] When a user sends a message through a customer support chat application, the device receives the message and sends it to the server, for example, "I'm worried because my item is late."

[0608] 2. Message Analysis

[0609] The server analyzes the received message using natural language processing technology (NLP library). Specifically, it performs sentiment analysis and sentence structure analysis to extract important keywords. In this example, the keywords extracted are "delay" and "worry."

[0610] 3. Determine design requirements

[0611] The server determines the design requirements for stamps and reaction images based on the extracted keywords, such as "a stamp that shows an intention to apologize" or "an expression that provides a sense of security."

[0612] 4. Stamp generation

[0613] Based on the determined design requirements, the server generates new stamps and reaction images using image generation techniques (e.g., GANs library), using a generative AI model.

[0614] 5. Sending and displaying stamps

[0615] The generated stamps and reaction images are sent from the server to the user's device and displayed on the chat screen within the customer support chat application, allowing the user to instantly check the generated images and receive appropriate support.

[0616] Specific examples

[0617] For example, if a user sends a message saying, "I'm worried because my item arrived late," the following prompt sentence is input to the generative AI model:

[0618] Prompt Sentence Examples

[0619] A user sends a message saying, "I'm worried about the delay in receiving my item." Generate a stamp expressing apology and relief.

[0620] Based on this prompt, the server generates a stamp with a calm, reassuring character saying, "I'm sorry, but please don't worry." The generated stamp is sent to the user's device and displayed on the chat screen. The user can view it and receive appropriate support.

[0621] As described above, the present invention can provide an appropriate response in real time based on the user's message, thereby improving customer satisfaction in customer support.

[0622] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0623] Program processing steps

[0624] Step 1:

[0625] User messaging

[0626] A user types and sends a message through a customer support chat application.

[0627] Input: A message entered by the user (e.g., "I'm worried about the delay in receiving my item.")

[0628] Output: The terminal gets the message

[0629] Step 2:

[0630] Retrieving and sending messages via the terminal

[0631] The terminal receives the message entered by the user and transmits the message to the server.

[0632] Input: User's message

[0633] Output: Message sent to the server

[0634] Step 3:

[0635] Message parsing by the server

[0636] The server analyzes the received message using natural language processing technology (NLP library).

[0637] Input: The message sent to the server

[0638] Data processing: sentence structure analysis, sentiment analysis

[0639] Output: Extracted keywords (e.g., "delay" and "worry")

[0640] Step 4:

[0641] Keyword extraction and intent estimation

[0642] The server extracts key keywords from the analysis results and uses them to infer the user's intent.

[0643] Input: Parsed message

[0644] Data calculation: Extraction of keywords, application of intent estimation algorithms

[0645] Output: Design requirements for stamps (e.g., "a stamp that shows the intention to apologize" or "an expression that provides a sense of security")

[0646] Step 5:

[0647] Determining design requirements

[0648] The server determines the design requirements for stamps and reaction images based on the keywords picked up.

[0649] Input: Extracted keywords and inferred intent

[0650] Data processing: Determining design requirements

[0651] Output: Specific design requirements (e.g., "smiling character" or "apology message")

[0652] Step 6:

[0653] Stamp generation using AI models

[0654] The server uses image generation technology (GANs and Style Transfer) to generate new stamps and reaction images. Specifically, it inputs a prompt sentence into a generative AI model and generates an image.

[0655] Input: Design Requirements

[0656] Data Computation: Image Generation with Generative AI Models

[0657] Output: Generated stamps and reaction images

[0658] Step 7:

[0659] Sending generated stamps

[0660] The generated stamps and reaction images are sent from the server to the user's device.

[0661] Input: Generated stamps and reaction images

[0662] Output: Stickers and reaction images sent to the user's device

[0663] Step 8:

[0664] Display on the chat screen

[0665] The stamps and reaction images received by the user's device are displayed on the chat screen, where the user can confirm them and continue interacting with the customer support representative.

[0666] Input: sent stamps and reaction images

[0667] Output: Stamps and reaction images displayed on the chat screen

[0668] These are the specific processing steps of the program that realizes the customer support chat application. Through this flow, users can receive prompt and appropriate support.

[0669] 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.

[0670] This invention relates to a system that allows users to instantly create and use original stamps that are best suited to their messages in chat applications such as LINE. Furthermore, it provides a form that combines an emotion engine that recognizes the user's emotions and generates stamps based on that information.

[0671] System Overview

[0672] This system is characterized by analyzing messages sent by users on the server and generating original stamps based on the analysis results. In addition, an emotion engine recognizes the user's emotions and designs stamps based on that information, making it possible to generate more appropriate and emotionally rich stamps. The generated stamps are immediately sent to the user's device, where the user can send them in chats.

[0673] Program processing flow

[0674] 1. User sends message

[0675] The user opens a chat application such as LINE, enters "I had so much fun today!" in the message input field, and presses the send button.

[0676] 2. Message retrieval and sending by the device

[0677] The terminal receives the message sent by the user and sends the message to the server.

[0678] 3. Message analysis and emotion recognition by the server

[0679] The server analyzes the received message using natural language processing technology. This analysis includes sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message such as "I had so much fun today!" is broken down into the keywords "fun," "today," and "thankful." The emotion engine then analyzes the user's emotions and recognizes that they include feelings of joy and gratitude.

[0680] 4. Keyword Extraction and Intention Estimation

[0681] The server extracts key keywords from the analysis results and uses them to infer the user's intent. For example, if the keywords "fun," "today," and "thanks" are extracted, it is inferred that the user had a good day and is expressing gratitude for that.

[0682] 5. Determine stamp requirements

[0683] The server determines the design requirements for the stamp based on the estimated intent and the emotion information from the emotion engine. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0684] 6. Stamp Generation

[0685] The server uses image generation techniques (e.g., Generative Adversarial Networks (GANs) or Style Transfer) to generate original stamps based on the determined design requirements.

[0686] 7. Sending stamps

[0687] The generated stamp is sent to the user's terminal and displayed on the chat screen.

[0688] 8. User confirmation and stamp sending

[0689] The user can check the generated stamps and send them in chat. This allows users to easily use original stamps that best suit the content of their messages, and communicate with stamps that match their emotions.

[0690] Specific examples

[0691] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[0692] The device sends a message to the server.

[0693] The server analyzes the message and extracts keywords such as "fun," "today," and "thankful."

[0694] The emotion engine recognizes the user's emotion as "joy" from the message.

[0695] The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0696] The server sends the generated stamp to the terminal.

[0697] The user checks the stamp and, if there are no problems, sends it to the chat.

[0698] In this way, the system can instantly generate and send original stamps that best fit the content and emotion of a user's message, allowing users to always use stamps that best fit the conversation and emotion at the time, making communication more enjoyable and fulfilling.

[0699] The processing flow will be explained below.

[0700] Step 1:

[0701] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[0702] Step 2:

[0703] The terminal receives the message sent by the user.

[0704] Step 3:

[0705] The terminal transmits the acquired message to the server.

[0706] Step 4:

[0707] The server receives the message.

[0708] Step 5:

[0709] The server begins analyzing the message. It uses natural language processing technology to tokenize and syntactically analyze the sentence and extract key keywords. For example, from the message "I had so much fun today!", the keywords "fun," "today," and "thankful" are extracted.

[0710] Step 6:

[0711] The server uses an emotion engine to recognize the user's emotion. It identifies emotion categories (e.g., joy, sadness, anger, surprise, etc.) from words and phrases contained in the message. In this case, the emotion engine recognizes "joy."

[0712] Step 7:

[0713] The server infers the user's intention based on the analysis results and emotional information. For example, based on the keywords "fun," "today," and "gratitude" and the emotion "joy," it can infer that the user had a fun day and is grateful for it.

[0714] Step 8:

[0715] The server determines the design requirements for the stamp based on the estimated intent and emotion information. For example, the stamp may include a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0716] Step 9:

[0717] The server generates new stickers using image generation techniques (e.g., Generative Adversarial Networks (GANs) and Style Transfer). Based on the determined design requirements, a sticker with the words "Thank you" written on it and a smiling character with fireworks in the background is created.

[0718] Step 10:

[0719] The server sends the generated stamp to the user's terminal.

[0720] Step 11:

[0721] The stamp received by the terminal is displayed on the user's chat screen.

[0722] Step 12:

[0723] The user checks the generated stamps, selects one, and sends it in the chat.

[0724] This process allows users to quickly generate original stamps that best suit their message and emotion and use them in real time, making chat communication richer and more effective.

[0725] Example 2

[0726] 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."

[0727] Conventional chat applications require users to manually select appropriate stamps or emojis when sending messages, making communication cumbersome. Furthermore, the selection of stamps often does not adequately reflect the user's emotions or intentions, resulting in a reduction in the accuracy and effectiveness of the expression. This invention solves the above-mentioned problems by providing a system that automatically analyzes a user's message and the emotions behind it, and instantly generates and provides original stamps that are appropriate for the message.

[0728] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for acquiring a message based on a user's input; means for transmitting the acquired message to the server via a communication network; means for analyzing the message in the server using natural language processing technology and extracting at least one keyword; means for determining design requirements for a stamp based on the extracted keyword and emotional information analyzed by an emotion engine; means for using a generative AI model to generate a new stamp based on the determined design requirements; means for transmitting the generated stamp to the user's terminal; and means for displaying the transmitted stamp on a chat screen. This eliminates the need for the user to manually select a stamp, and enables the user to automatically obtain a stamp that best suits the message and the emotion behind it.

[0729] "User input" refers to messages or text information sent by a user through a chat application.

[0730] A "message" refers to a sentence or text data that a user sends through a chat application.

[0731] "Communications Network" means the Internet or other digital communications infrastructure used to transmit data from a device to a server or vice versa.

[0732] The term "server" refers to a central processing unit that performs various processes in a chat application, such as receiving messages, analyzing messages, and generating stamps.

[0733] "Natural language processing technology" refers to technology that allows a server to analyze text data and perform keyword extraction and emotion recognition.

[0734] "Keywords" refer to important words or phrases extracted from a message using natural language processing techniques.

[0735] "Emotion engine" refers to software or algorithms that analyze emotions from users' messages and provide that emotion information.

[0736] "Stamp design requirements" refer to the elements and attributes that should be included in stamps, which are determined based on the extracted keywords and emotional information.

[0737] "Generative AI Model" refers to an artificial intelligence model used to generate new stamps based on determined design requirements.

[0738] "Terminal" refers to a device such as a computer, smartphone, or tablet that a user uses to use a chat application.

[0739] The "chat screen" refers to an interface in a chat application where messages and stamps are displayed and which is operated by the user.

[0740] This invention relates to a system that allows users to instantly generate and use original stamps based on messages in chat applications. This system recognizes the user's emotions and combines them with an emotion engine to generate stamps based on that information, providing more appropriate and emotive stamps.

[0741] 1. Hardware and Software Used

[0742] Hardware:

[0743] Server: A server equipped with a high-performance central processing unit (including a CPU and GPU).

[0744] Device: The device on which a user uses a chat application, such as a computer, smartphone, or tablet.

[0745] software:

[0746] Chat application: Communication applications such as LINE.

[0747] Natural Language Processing technologies: NLP libraries (e.g. spaCy, NLTK).

[0748] Sentiment engine: Software or algorithms for analyzing user emotions (e.g., IBM Watson, Google Cloud Natural Language API).

[0749] Image generation techniques: Artificial intelligence models including Generative Adversarial Networks (GANs) and Style Transfer.

[0750] 2. Data processing and calculation

[0751] User sending message:

[0752] A user opens a chat application, enters text in the message input field, and presses the send button. For example, to send a message such as "I had so much fun today!"

[0753] Terminal message retrieval and sending:

[0754] The terminal receives the message sent by the user and transmits it to the server via the communication network, where the message is encrypted.

[0755] Server-based message parsing and emotion recognition:

[0756] The server analyzes the received message using natural language processing technology. This analysis includes sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message such as "I had so much fun today!" is broken down into the keywords "fun," "today," and "gratitude." The emotion engine then recognizes the user's emotions as "joy" or "gratitude."

[0757] Determining and generating stamp requirements:

[0758] The server determines the design requirements for the stamp based on the extracted keywords and emotional information. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you." Original stamps are generated using image generation techniques (e.g., GANs, Style Transfer).

[0759] Sending stamps and verifying users:

[0760] The generated stamp is sent to the user's device and displayed on the chat screen. The user checks the generated stamp and, if there are no problems, sends it via chat.

[0761] 3. Examples of concrete examples and prompts

[0762] For example, if a user sends a message saying "I had so much fun today!", the following will happen:

[0763] 1. A user sends a message on the LINE app saying, "Today was so much fun!"

[0764] 2. The device sends a message to the server.

[0765] 3. The server analyzes the message using NLP and extracts the keywords "fun," "today," and "gratitude."

[0766] 4. The emotion engine recognizes the emotions of "joy" and "gratitude" from the message.

[0767] 5. The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0768] 6. The server sends the generated stamp to the device.

[0769] 7. The user checks the stamps received in the LINE app and sends them in the chat.

[0770] Prompt Sentence Examples

[0771] Here is an example of a prompt you can enter into a generative AI model:

[0772] "Please generate an original stamp suitable for the following message."

[0773] Message: "Today was so much fun!"

[0774] This prompt sentence allows the user to instantly obtain an appropriate original stamp, and to communicate with a stamp that best suits the message content and emotion.

[0775] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0776] Step 1: User sends message

[0777] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[0778] Specific operation: A user uses a chat application on a smartphone or computer to enter a message in text format. The entered text data is sent.

[0779] Enter: Text message "Today was so much fun!"

[0780] Output: A trigger signal for a message to be sent from the terminal.

[0781] Step 2: Retrieving and sending messages using the device

[0782] The terminal receives the message sent by the user and transmits the message to the server via the communication network.

[0783] Specific operation: The device retrieves the message sent by the user and sends the message data in encrypted form to the server using the HTTPS protocol.

[0784] Input: The text message sent by the user

[0785] Output: Message data sent to the server in encrypted form

[0786] Step 3: Message analysis and emotion recognition by the server

[0787] The server analyzes the received message using natural language processing technology.

[0788] Specific operation: The server deserializes the message data, tokenizes and parses it using an NLP library (e.g., spaCy, NLTK), and extracts keywords. In addition, it analyzes the sentiment of the message using an emotion engine (e.g., IBM Watson, Google Cloud Natural Language API). For example, the keywords "fun," "today," and "gratitude" are extracted, along with the sentiment information of "joy."

[0789] Input: Message data in encrypted form

[0790] Output: Keywords ("fun," "today," "thankful") and emotional information ("joy")

[0791] Step 4: Determine stamp requirements

[0792] The server determines the design requirements of the stamp based on the extracted keywords and emotion information.

[0793] How it works: The server uses an algorithm to generate sticker concepts based on keywords and emotional information. For example, a sticker might have a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0794] Input: Keywords ("fun," "today," "thankful"), emotional information ("joy")

[0795] Output: Stamp design requirements (e.g. smiley face, fireworks, "thank you")

[0796] Step 5: Generate stamps

[0797] The server generates new stamps using image generation techniques.

[0798] How it works: The server uses techniques such as Generative Adversarial Networks (GANs) and Style Transfer to leverage the GPU to generate original stamps based on design requirements.

[0799] Input: Sticker design requirements (e.g. smiley face, fireworks, "thank you")

[0800] Output: Generated original stamp image data

[0801] Step 6: Send your sticker

[0802] The generated stamp is sent to the user's terminal.

[0803] What it does: The server compresses the generated stamp and quickly sends it to the user's device, where it decompresses the data and converts it into a displayable format.

[0804] Input: Generated original stamp image data

[0805] Output: Stamp data sent to the user's device

[0806] Step 7: User confirmation and stamp sending

[0807] The user checks the generated stamp and sends it in the chat.

[0808] Specific operation: The user visually confirms the generated stamp on the chat screen of the device and presses the "Send" button. The stamp is added to the chat log.

[0809] Input: Stamp data displayed on the terminal

[0810] Output: Stamp sent on the chat screen

[0811] (Application example 2)

[0812] 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."

[0813] In conventional chat systems, users had to manually select appropriate stamps based on their emotions and message content, making it difficult to communicate quickly and effectively. It was also difficult to automatically generate original content that accurately reflected emotions, making communication with users tend to be uniform and mechanical. In particular, in customer support, there was a need for a way to quickly and accurately convey users' emotions, such as dissatisfaction or joy.

[0814] 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.

[0815] In this invention, the server includes means for acquiring a message based on a user's input, means for transmitting the acquired message to the server, means for analyzing the message in the server and extracting at least one keyword, means for determining stamp design requirements based on the extracted keyword and emotion information, means for generating a new stamp based on the determined design requirements, means for transmitting the generated stamp to the user's terminal, means for displaying the transmitted stamp on a chat screen, means for recognizing the user's emotion, and means for generating an original stamp based on the recognized emotion. This makes it possible to automatically generate and transmit a stamp that is optimal for the message and emotion input by the user, thereby achieving fast and effective communication.

[0816] "User input" refers to messages or commands sent by a user via a keyboard or touchscreen, such as in a chat system.

[0817] The "means for obtaining a message" refers to hardware or software that has the function of extracting a message input by a user and passing it on to subsequent processing.

[0818] A "server" is a computer system that processes data and generates stamps via a network.

[0819] The "means for analyzing a message" refers to hardware or software that has the function of using natural language processing technology to understand a user's message and structurally divide its contents.

[0820] "Keyword extraction methods" refer to algorithms and techniques used to extract important words and phrases from the analysis results.

[0821] "Emotion information" refers to data that expresses the emotions contained in a user's message in numerical values ​​or categories.

[0822] "Stamp design requirements" are the standards or specifications that determine the appearance and content of the stamp to be generated.

[0823] "Means for generating new stickers" refers to generative AI models or technologies capable of creating images or animations based on determined design requirements.

[0824] "Means for transmitting stamps" refers to the communication protocols and techniques used to transmit the generated stamps to the user's terminal.

[0825] The "means for displaying on the chat screen" refers to software having a function for displaying the sent stamp on the chat application so that the user can check it.

[0826] "Means for recognizing emotions" refers to algorithms and technologies that estimate emotions from user input, facial expressions, etc., and output them as data.

[0827] "Means for generating original stamps" refers to technology or systems that allow for the creation of new stamps on the spot based on the user's emotions or keywords.

[0828] This invention relates to a system for enhancing communication with users in customer support for online shopping sites. Specifically, it is a system that automatically generates original stamps in response to users' messages and responds in a way that best suits their emotions.

[0829] System configuration

[0830] 1. Get user messages

[0831] Users input messages through the chat system, which are displayed on their terminals and sent to the server.

[0832] 2. Message Analysis and Emotion Recognition

[0833] The server analyzes the received message using natural language processing technology (e.g., TextBlob). The analysis includes tokenizing the sentence, parsing the syntax, and sentiment analysis. During this process, an emotion engine is activated to recognize the user's emotions and extract emotional information such as joy, anger, or dissatisfaction from the message.

[0834] 3. Keyword extraction and intent estimation

[0835] The server extracts key keywords from the analysis results and infers the user's intention. For example, from the message "Product delivery is delayed," the keywords "delivery" and "delay" are extracted, and the emotion engine recognizes dissatisfaction.

[0836] 4. Determine stamp requirements

[0837] The server determines the design requirements for a stamp based on the estimated intent and emotion information, such as the text "I'm sorry," a simple background, and a troubled face.

[0838] 5. Stamp generation

[0839] The server uses a generative AI model (e.g., Generative Adversarial Networks (GANs)) to generate original stamps based on the determined design requirements. The generated stamps are immediately prepared as binary data.

[0840] 6. Sending and displaying stamps

[0841] The generated stamp is sent to the user's device and displayed on the chat screen. The user checks the stamp, and if there are no problems, they can send it again to complete the communication.

[0842] Specific examples

[0843] For example, if a user enters the message "The delivery of the product is delayed," the system will act as follows:

[0844] A message saying "The delivery of the product is delayed" is sent from the terminal to the server.

[0845] The server analyzes the message and extracts the keywords "delivery" and "delay."

[0846] The emotion engine recognizes "dissatisfaction" from the message.

[0847] The server determines the design requirements for the stamp and generates a stamp containing the text "Sorry," a simple background, and a troubled facial expression.

[0848] The server sends the generated stamp to the terminal.

[0849] The device displays the stamp on the chat screen, and the user can check it and send it.

[0850] Prompt Sentence Examples

[0851] User message: "Item delivery is delayed"

[0852] Produced stamp: A stamp containing the text "Sorry"

[0853] Emotion: "Anger"

[0854] Background: "Simple"

[0855] Expression: "worried"

[0856] Through the above process, users can always use stamps that best suit the conversation and emotions they are feeling at the time, realizing a system that allows for smoother and more effective communication.

[0857] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0858] Step 1:

[0859] Users input messages through the chat system, which are displayed on the terminal and simultaneously sent to the server.

[0860] Input: A message entered by the user (e.g., "Your delivery is delayed.")

[0861] Output: Message sent from terminal to server

[0862] Step 2:

[0863] The server analyzes the received message, using natural language processing techniques (e.g., TextBlob) to tokenize the sentences, parse them syntactically, and analyze their sentiment, thereby understanding the message and extracting key keywords and sentiment information.

[0864] Input: User message sent from the terminal

[0865] Data processing: sentence tokenization, syntactic analysis, sentiment analysis

[0866] Output: Key keywords (e.g., "Delivery" and "Delay") and sentiment information (e.g., "Dissatisfied")

[0867] Step 3:

[0868] The server infers the user's intention based on the extracted keywords and emotional information. Based on the inferred intention, the design requirements for the stamp are determined, including the text to be displayed, the background, and the facial expression.

[0869] Input: Key keywords (e.g., "Delivery" or "Delay") and sentiment information (e.g., "Dissatisfied")

[0870] Data processing: Intent estimation and design requirement determination

[0871] Output: Sticker design requirements (e.g. "Sorry" text, simple background, worried face expression)

[0872] Step 4:

[0873] The server uses a generative AI model (e.g., Generative Adversarial Networks (GANs)) to generate original stamps based on the determined design requirements. The stamps are generated as image files and used for subsequent processing.

[0874] Input: Stamp design requirements

[0875] Data processing: Image generation using generative AI models

[0876] Output: Generated original stamp (e.g. stamp image file)

[0877] Step 5:

[0878] The server sends the generated stamp to the user's terminal, and transfers the stamp data to the terminal using a transmission protocol.

[0879] Input: Generated original stamp

[0880] Data processing: data encoding and transmission

[0881] Output: Stamp data sent to the terminal

[0882] Step 6:

[0883] The device displays the received stamps on the chat screen. The user can check the stamps and send them further to the chat if necessary, completing the communication.

[0884] Input: Stamp data sent to the terminal

[0885] Data processing: Decoding and display

[0886] Output: Stamp displayed on the chat screen

[0887] These processing steps automatically generate stamps that best suit the user's message and emotions, enabling fast and effective communication.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] [Third embodiment]

[0892] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0893] 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.

[0894] 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).

[0895] 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.

[0896] 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.

[0897] 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).

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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."

[0904] The present invention relates to a system that allows users to instantly create and use original stamps that are most suitable for messages in chat applications such as LINE. The program processing of this system is explained below in natural language.

[0905] System Overview

[0906] This system analyzes messages sent by users on the server and generates original stamps based on the analysis results. The generated stamps are then immediately sent to the user's device, where they can be sent via chat.

[0907] Program processing flow

[0908] 1. User sends message

[0909] A user opens a chat application such as LINE, types a message, and sends it. For example, a user sends a message such as "I had a great time today!"

[0910] 2. Message retrieval and sending by the device

[0911] The terminal receives the sent message and sends it to the server.

[0912] 3. Message Parsing by the Server

[0913] The server analyzes the received message using natural language processing technology. The analysis includes sentence structure analysis and sentiment analysis. For example, from the message "I had so much fun today!", keywords such as "fun," "today," and "thankful" are extracted.

[0914] 4. Keyword Extraction and Intention Estimation

[0915] The server extracts key keywords from the analysis results and uses them to infer the user's intention. In this case, the keywords "fun," "today," and "thankful" are extracted, and it is inferred that the user had a fun day and is grateful for it.

[0916] 5. Determine stamp requirements

[0917] The server determines the design requirements for the stamp based on the inferred intent. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0918] 6. Stamp Generation

[0919] The server uses image generation techniques (e.g., GANs or Style Transfer) to generate original stamps based on the determined design requirements.

[0920] 7. Sending stamps

[0921] The generated stamp is sent to the user's terminal and displayed on the chat screen.

[0922] 8. User confirmation and stamp sending

[0923] The user can check the generated stamps and send them in chat, allowing them to easily use original stamps that best suit the content of their messages.

[0924] Specific examples

[0925] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[0926] The device sends a message to the server.

[0927] The server analyzes the message and extracts keywords such as "fun," "today," and "thankful."

[0928] The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0929] The server sends the generated stamp to the terminal.

[0930] The user checks the stamp and, if there are no problems, sends it to the chat.

[0931] In this way, the system can instantly generate and send original stamps that are optimal for the content of a user's message, allowing users to always use stamps that are optimal for the conversation at hand, making communication more enjoyable and fulfilling.

[0932] The processing flow will be explained below.

[0933] Step 1:

[0934] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[0935] Step 2:

[0936] The terminal receives the message sent by the user.

[0937] Step 3:

[0938] The terminal transmits the acquired message to the server.

[0939] Step 4:

[0940] The server receives the message.

[0941] Step 5:

[0942] The server analyzes the message using natural language processing techniques, including sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message like "I had so much fun today!" is broken down into the keywords "fun," "today," and "thankful."

[0943] Step 6:

[0944] The server extracts key keywords from the analysis results, such as "fun," "today," and "gratitude."

[0945] Step 7:

[0946] The server infers the user's intention based on the extracted keywords. For example, it may infer that the user had a good day and is expressing gratitude for it.

[0947] Step 8:

[0948] The server determines the design requirements for the stamp based on the inferred intent. In this case, the stamp includes elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0949] Step 9:

[0950] The server uses image generation techniques (e.g., Generative Adversarial Networks (GANs) or Style Transfer) to generate original stamps based on the determined design requirements.

[0951] Step 10:

[0952] The server sends the generated stamp to the terminal.

[0953] Step 11:

[0954] The stamp received by the terminal is displayed on the user's chat screen.

[0955] Step 12:

[0956] The user checks the generated stamp, and if there are no particular problems, selects the stamp and sends it to the chat.

[0957] Example 1

[0958] 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."

[0959] There is a need for a system that allows users to quickly generate and use stamps that are optimal for the content of their messages in chat applications. Existing methods require users to manually select stamps, which disrupts the flow of conversation. It can also take a long time for users to find a stamp that is appropriate for the content of their message. To solve this problem, there is a need for a system that automatically generates and provides stamps based on the user's message.

[0960] 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.

[0961] In this invention, the server includes means for acquiring information based on user input, means for transmitting the acquired information to the server, means for analyzing the information and extracting at least one keyword in the server, means for determining design requirements based on the extracted keyword, means for generating a new image based on the determined design requirements, means for transmitting the generated image to the user's device, and means for displaying the transmitted image on a display screen. This makes it possible to automatically and quickly generate and provide a stamp that is optimal for the content of a user's message.

[0962] A "user" is a person who uses the system to send a chat message and request the generation of a stamp.

[0963] "Input" refers to the act of a user sending a text message to a chat application.

[0964] "Information" refers to messages entered by users and other related data.

[0965] "Device" refers to the electronic device (e.g., smartphone, tablet, PC) that a user uses to access the chat application.

[0966] "Server" refers to a computer system that communicates with user devices over a network and performs processes such as parsing messages and generating stamps.

[0967] The term "means for acquiring" refers to the software and hardware configuration for acquiring input information from a user.

[0968] "Means for transmitting" refers to the software and hardware configuration for transmitting the acquired information to the server.

[0969] "Means for analyzing" refers to a software and hardware configuration that analyzes the transmitted information using natural language processing technology and extracts keywords.

[0970] "Keywords" refer to key words or phrases extracted from the analyzed information.

[0971] "Design requirements" refers to the conditions or requirements that determine the characteristics of the stamp to be generated (e.g., facial expression, background, text).

[0972] "Generating means" refers to a software and hardware configuration for generating new images (stamps) according to design requirements.

[0973] "Transmitting means" refers to the software and hardware configuration for transmitting the generated image to a user's device.

[0974] "Means for displaying" refers to the software and hardware configuration for displaying the transmitted image on the screen of the user's device.

[0975] The present invention relates to a system that analyzes messages sent by users using chat applications (e.g., LINE) and automatically generates original stamps based on the contents of the messages. Specific embodiments of the present invention are described below.

[0976] When a user opens a chat application, inputs a message, and sends it, the terminal receives the message and sends it to the server, attaching the user's identification information along with the message content.

[0977] The server analyzes the received message using natural language processing techniques (e.g., BERT or GPT-3). As part of the analysis, the server analyzes the grammar and sentiment structure to extract key keywords. In this case, for example, keywords such as "fun," "today," and "thankful" are extracted from the message "I had so much fun today!"

[0978] The server infers the user's intent based on the extracted keywords and determines the appropriate design requirements for the stamp, including, for example, a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[0979] To generate the stamps, the server uses image generation techniques (e.g., GANs or Style Transfer) to generate original stamps. As a specific example, StyleGAN is used to generate a stamp with the words "Thank you" written on it, featuring a smiling character with fireworks in the background. The stamps generated in this way are most suited to the user's intent.

[0980] The stamp data generated by the server is sent to the user's device. The device displays the received stamp on the chat application screen. The user checks the generated stamp and, if satisfied, sends it as a chat message.

[0981] This allows the present invention to automatically generate and instantly provide original stamps that are optimal for the content of a user's message. Users can intuitively use the stamps that are optimal for them without any special operations, making communication smoother and more enjoyable.

[0982] Examples of concrete examples and prompts

[0983] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[0984] 1. The device receives the message and sends it to the server.

[0985] 2. The server uses natural language processing technology to analyze the message and extract the keywords "fun," "today," and "thank you."

[0986] 3. The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[0987] 4. The server sends the generated stamp to the device, which displays it on the chat screen.

[0988] 5. The user checks the stamp and sends it in the chat.

[0989] The specific prompt is as follows:

[0990] Analyze the message "Today was so much fun!" and generate a stamp that best suits that content. The stamp requirements should include a cheerful expression (e.g., a smiling face), a fun background (e.g., fireworks), and the text "Thank you."

[0991] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0992] Step 1:

[0993] A user opens a chat application, types a message, and sends it. The input is a text message such as "I had a great time today!" that the user sends on the chat application, and the output is the message data added to the device's sending queue. Specifically, when the user presses the send button, the message is stored in the device's sending queue.

[0994] Step 2:

[0995] The terminal reads the message from the sending queue and sends it to the server. The input is the user's message data obtained in the previous step, and the output is the message data sent to the server. The terminal sends the message content and the user's identification information to the server via the network.

[0996] Step 3:

[0997] The server analyzes the messages it receives using natural language processing technology. The input is the message data received by the server, and the output is the analyzed keyword data. The server uses generative AI models such as BERT and GPT-3 to perform grammar and sentiment analysis. Specifically, it extracts keywords such as "fun," "today," and "thankful" from the message "I had so much fun today!"

[0998] Step 4:

[0999] The server extracts key keywords from the analysis results and infers the user's intent based on them. The input is the analyzed keyword data, and the output is the inferred user intent. For example, based on the extracted keywords "fun," "today," and "thankful," the server infers that the user had a good day and is grateful for it.

[1000] Step 5:

[1001] The server determines the design requirements for the stamp based on the estimated intent. The input is the estimated user intent, and the output is the design requirement data. The design requirements include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1002] Step 6:

[1003] The server generates original stamps using image generation technology. The input is design requirement data, and the output is the generated stamp image data. The server uses technologies such as GANs and Style Transfer to generate stamps based on the determined design requirements. The specific process involves using StyleGAN to generate a stamp with a smiling character and the word "Thank you" written on it against a background of fireworks.

[1004] Step 7:

[1005] The server sends the generated stamp to the user's device. The input is the generated stamp image data, and the output is the stamp image data sent to the device. The server encodes the stamp in an appropriate data format (e.g. PNG, JPEG) and sends it to the device over the network.

[1006] Step 8:

[1007] The stamp received by the terminal is displayed on the chat screen. The input is the stamp image data sent to the terminal, and the output is the stamp image displayed on the chat screen. The user checks the generated stamp and, if satisfied, sends it as a chat message. Specifically, the user selects a stamp and presses the send button, and the stamp is then displayed to other chat participants.

[1008] By following the above steps, this system can automatically generate and quickly provide an original stamp that is optimal for the content of a user's message.

[1009] (Application example 1)

[1010] 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."

[1011] In customer support, responding quickly and appropriately to messages from users is important for improving customer satisfaction. However, current systems make it difficult to accurately understand users' emotions and intentions and provide an appropriate response immediately. This can result in delayed responses or inability to provide support that meets users' needs. Furthermore, this increases the burden on customer support staff, making it difficult to operate efficiently.

[1012] 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.

[1013] In this invention, the server includes means for acquiring a message based on a user's input, means for transmitting the acquired message to the server, means for analyzing the message in the server and extracting at least one keyword, means for determining stamp design requirements based on the extracted keyword, means for generating a new stamp based on the determined design requirements, means for transmitting the generated stamp to the user's terminal, means for displaying the transmitted stamp on a chat screen, and means for generating stamps and reaction images in response to the user's message and for efficiently supporting customers using a customer support chat application. This enables appropriate customer support to be provided in real time based on the user's message.

[1014] "User input" refers to the transmission of information or instructions given by the user via a communication terminal.

[1015] "Message" refers to text or other information sent based on user input.

[1016] A "server" refers to a computer system that stores and processes data over a network.

[1017] "Keywords" refer to important words and phrases extracted during message analysis.

[1018] A "stamp" is a type of image or emoji displayed in digital format and is used to express a user's emotions or intentions.

[1019] "Design Requirements" refers to the criteria that determine the specific features or elements (e.g., color, shape, text, etc.) of the stamp or image to be generated.

[1020] "Terminal" refers to communication devices such as smartphones and personal computers used by users.

[1021] "Chat screen" refers to an interface that allows users to exchange messages within a messaging application.

[1022] "Natural language processing technology" refers to computer technology for analyzing and understanding human language.

[1023] "Generative AI model" refers to a model that uses artificial intelligence techniques to generate new data (e.g., images, text).

[1024] "Customer support chat application" refers to a chat-style application that enables businesses to provide support to their customers.

[1025] The present invention relates to a system that generates original stamps and reaction images based on messages sent by users through a customer support chat application, and responds promptly and appropriately.

[1026] The following hardware and software are used to build the system:

[1027] Hardware

[1028] High-performance cloud servers (e.g., Amazon Web Services, Google Cloud Platform)

[1029] Smartphones and computers used by users

[1030] software

[1031] Natural Language Processing Libraries: SpaCy, NLTK, Google Cloud Natural Language API

[1032] Image generation technology: PyTorch, TensorFlow, GANs library

[1033] Chat support framework: Twilio, Dialogflow

[1034] System Operation

[1035] 1. Getting and sending messages

[1036] When a user sends a message through a customer support chat application, the device receives the message and sends it to the server, for example, "I'm worried because my item is late."

[1037] 2. Message Analysis

[1038] The server analyzes the received message using natural language processing technology (NLP library). Specifically, it performs sentiment analysis and sentence structure analysis to extract important keywords. In this example, the keywords extracted are "delay" and "worry."

[1039] 3. Determine design requirements

[1040] The server determines the design requirements for stamps and reaction images based on the extracted keywords, such as "a stamp that shows an intention to apologize" or "an expression that provides a sense of security."

[1041] 4. Stamp generation

[1042] Based on the determined design requirements, the server generates new stamps and reaction images using image generation techniques (e.g., GANs library), using a generative AI model.

[1043] 5. Sending and displaying stamps

[1044] The generated stamps and reaction images are sent from the server to the user's device and displayed on the chat screen within the customer support chat application, allowing the user to instantly check the generated images and receive appropriate support.

[1045] Specific examples

[1046] For example, if a user sends a message saying, "I'm worried because my item arrived late," the following prompt sentence is input to the generative AI model:

[1047] Prompt Sentence Examples

[1048] A user sends a message saying, "I'm worried about the delay in receiving my item." Generate a stamp expressing apology and relief.

[1049] Based on this prompt, the server generates a stamp with a calm, reassuring character saying, "I'm sorry, but please don't worry." The generated stamp is sent to the user's device and displayed on the chat screen. The user can view it and receive appropriate support.

[1050] As described above, the present invention can provide an appropriate response in real time based on the user's message, thereby improving customer satisfaction in customer support.

[1051] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1052] Program processing steps

[1053] Step 1:

[1054] User messaging

[1055] A user types and sends a message through a customer support chat application.

[1056] Input: A message entered by the user (e.g., "I'm worried about the delay in receiving my item.")

[1057] Output: The terminal gets the message

[1058] Step 2:

[1059] Retrieving and sending messages via the terminal

[1060] The terminal receives the message entered by the user and transmits the message to the server.

[1061] Input: User's message

[1062] Output: Message sent to the server

[1063] Step 3:

[1064] Message parsing by the server

[1065] The server analyzes the received message using natural language processing technology (NLP library).

[1066] Input: The message sent to the server

[1067] Data processing: sentence structure analysis, sentiment analysis

[1068] Output: Extracted keywords (e.g., "delay" and "worry")

[1069] Step 4:

[1070] Keyword extraction and intent estimation

[1071] The server extracts key keywords from the analysis results and uses them to infer the user's intent.

[1072] Input: Parsed message

[1073] Data calculation: Extraction of keywords, application of intent estimation algorithms

[1074] Output: Design requirements for stamps (e.g., "a stamp that shows the intention to apologize" or "an expression that provides a sense of security")

[1075] Step 5:

[1076] Determining design requirements

[1077] The server determines the design requirements for stamps and reaction images based on the keywords picked up.

[1078] Input: Extracted keywords and inferred intent

[1079] Data processing: Determining design requirements

[1080] Output: Specific design requirements (e.g., "smiling character" or "apology message")

[1081] Step 6:

[1082] Stamp generation using AI models

[1083] The server uses image generation technology (GANs and Style Transfer) to generate new stamps and reaction images. Specifically, it inputs a prompt sentence into a generative AI model and generates an image.

[1084] Input: Design Requirements

[1085] Data Computation: Image Generation with Generative AI Models

[1086] Output: Generated stamps and reaction images

[1087] Step 7:

[1088] Sending generated stamps

[1089] The generated stamps and reaction images are sent from the server to the user's device.

[1090] Input: Generated stamps and reaction images

[1091] Output: Stickers and reaction images sent to the user's device

[1092] Step 8:

[1093] Display on the chat screen

[1094] The stamps and reaction images received by the user's device are displayed on the chat screen, where the user can confirm them and continue interacting with the customer support representative.

[1095] Input: sent stamps and reaction images

[1096] Output: Stamps and reaction images displayed on the chat screen

[1097] These are the specific processing steps of the program that realizes the customer support chat application. Through this flow, users can receive prompt and appropriate support.

[1098] 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.

[1099] This invention relates to a system that allows users to instantly create and use original stamps that are best suited to their messages in chat applications such as LINE. Furthermore, it provides a form that combines an emotion engine that recognizes the user's emotions and generates stamps based on that information.

[1100] System Overview

[1101] This system is characterized by analyzing messages sent by users on the server and generating original stamps based on the analysis results. In addition, an emotion engine recognizes the user's emotions and designs stamps based on that information, making it possible to generate more appropriate and emotionally rich stamps. The generated stamps are immediately sent to the user's device, where the user can send them in chats.

[1102] Program processing flow

[1103] 1. User sends message

[1104] The user opens a chat application such as LINE, enters "I had so much fun today!" in the message input field, and presses the send button.

[1105] 2. Message retrieval and sending by the device

[1106] The terminal receives the message sent by the user and sends the message to the server.

[1107] 3. Message analysis and emotion recognition by the server

[1108] The server analyzes the received message using natural language processing technology. This analysis includes sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message such as "I had so much fun today!" is broken down into the keywords "fun," "today," and "thankful." The emotion engine then analyzes the user's emotions and recognizes that they include feelings of joy and gratitude.

[1109] 4. Keyword Extraction and Intention Estimation

[1110] The server extracts key keywords from the analysis results and uses them to infer the user's intent. For example, if the keywords "fun," "today," and "thanks" are extracted, it is inferred that the user had a good day and is expressing gratitude for that.

[1111] 5. Determine stamp requirements

[1112] The server determines the design requirements for the stamp based on the estimated intent and the emotion information from the emotion engine. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1113] 6. Stamp Generation

[1114] The server uses image generation techniques (e.g., Generative Adversarial Networks (GANs) or Style Transfer) to generate original stamps based on the determined design requirements.

[1115] 7. Sending stamps

[1116] The generated stamp is sent to the user's terminal and displayed on the chat screen.

[1117] 8. User confirmation and stamp sending

[1118] The user can check the generated stamps and send them in chat. This allows users to easily use original stamps that best suit the content of their messages, and communicate with stamps that match their emotions.

[1119] Specific examples

[1120] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[1121] The device sends a message to the server.

[1122] The server analyzes the message and extracts keywords such as "fun," "today," and "thankful."

[1123] The emotion engine recognizes the user's emotion as "joy" from the message.

[1124] The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[1125] The server sends the generated stamp to the terminal.

[1126] The user checks the stamp and, if there are no problems, sends it to the chat.

[1127] In this way, the system can instantly generate and send original stamps that best fit the content and emotion of a user's message, allowing users to always use stamps that best fit the conversation and emotion at the time, making communication more enjoyable and fulfilling.

[1128] The processing flow will be explained below.

[1129] Step 1:

[1130] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[1131] Step 2:

[1132] The terminal receives the message sent by the user.

[1133] Step 3:

[1134] The terminal transmits the acquired message to the server.

[1135] Step 4:

[1136] The server receives the message.

[1137] Step 5:

[1138] The server begins analyzing the message. It uses natural language processing technology to tokenize and syntactically analyze the sentence and extract key keywords. For example, from the message "I had so much fun today!", the keywords "fun," "today," and "thankful" are extracted.

[1139] Step 6:

[1140] The server uses an emotion engine to recognize the user's emotion. It identifies emotion categories (e.g., joy, sadness, anger, surprise, etc.) from words and phrases contained in the message. In this case, the emotion engine recognizes "joy."

[1141] Step 7:

[1142] The server infers the user's intention based on the analysis results and emotional information. For example, based on the keywords "fun," "today," and "gratitude" and the emotion "joy," it can infer that the user had a fun day and is grateful for it.

[1143] Step 8:

[1144] The server determines the design requirements for the stamp based on the estimated intent and emotion information. For example, the stamp may include a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1145] Step 9:

[1146] The server generates new stickers using image generation techniques (e.g., Generative Adversarial Networks (GANs) and Style Transfer). Based on the determined design requirements, a sticker with the words "Thank you" written on it and a smiling character with fireworks in the background is created.

[1147] Step 10:

[1148] The server sends the generated stamp to the user's terminal.

[1149] Step 11:

[1150] The stamp received by the terminal is displayed on the user's chat screen.

[1151] Step 12:

[1152] The user checks the generated stamps, selects one, and sends it in the chat.

[1153] This process allows users to quickly generate original stamps that best suit their message and emotion and use them in real time, making chat communication richer and more effective.

[1154] Example 2

[1155] 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."

[1156] Conventional chat applications require users to manually select appropriate stamps or emojis when sending messages, making communication cumbersome. Furthermore, the selection of stamps often does not adequately reflect the user's emotions or intentions, resulting in a reduction in the accuracy and effectiveness of the expression. This invention solves the above-mentioned problems by providing a system that automatically analyzes a user's message and the emotions behind it, and instantly generates and provides original stamps that are appropriate for the message.

[1157] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for acquiring a message based on a user's input; means for transmitting the acquired message to the server via a communication network; means for analyzing the message in the server using natural language processing technology and extracting at least one keyword; means for determining design requirements for a stamp based on the extracted keyword and emotional information analyzed by an emotion engine; means for using a generative AI model to generate a new stamp based on the determined design requirements; means for transmitting the generated stamp to the user's terminal; and means for displaying the transmitted stamp on a chat screen. This eliminates the need for the user to manually select a stamp, and enables the user to automatically obtain a stamp that best suits the message and the emotion behind it.

[1158] "User input" refers to messages or text information sent by a user through a chat application.

[1159] A "message" refers to a sentence or text data that a user sends through a chat application.

[1160] "Communications Network" means the Internet or other digital communications infrastructure used to transmit data from a device to a server or vice versa.

[1161] The term "server" refers to a central processing unit that performs various processes in a chat application, such as receiving messages, analyzing messages, and generating stamps.

[1162] "Natural language processing technology" refers to technology that allows a server to analyze text data and perform keyword extraction and emotion recognition.

[1163] "Keywords" refer to important words or phrases extracted from a message using natural language processing techniques.

[1164] "Emotion engine" refers to software or algorithms that analyze emotions from users' messages and provide that emotion information.

[1165] "Stamp design requirements" refer to the elements and attributes that should be included in stamps, which are determined based on the extracted keywords and emotional information.

[1166] "Generative AI Model" refers to an artificial intelligence model used to generate new stamps based on determined design requirements.

[1167] "Terminal" refers to a device such as a computer, smartphone, or tablet that a user uses to use a chat application.

[1168] The "chat screen" refers to an interface in a chat application where messages and stamps are displayed and which is operated by the user.

[1169] This invention relates to a system that allows users to instantly generate and use original stamps based on messages in chat applications. This system recognizes the user's emotions and combines them with an emotion engine to generate stamps based on that information, providing more appropriate and emotive stamps.

[1170] 1. Hardware and Software Used

[1171] Hardware:

[1172] Server: A server equipped with a high-performance central processing unit (including a CPU and GPU).

[1173] Device: The device on which a user uses a chat application, such as a computer, smartphone, or tablet.

[1174] software:

[1175] Chat application: Communication applications such as LINE.

[1176] Natural Language Processing technologies: NLP libraries (e.g. spaCy, NLTK).

[1177] Sentiment engine: Software or algorithms for analyzing user emotions (e.g., IBM Watson, Google Cloud Natural Language API).

[1178] Image generation techniques: Artificial intelligence models including Generative Adversarial Networks (GANs) and Style Transfer.

[1179] 2. Data processing and calculation

[1180] User sending message:

[1181] A user opens a chat application, enters text in the message input field, and presses the send button. For example, to send a message such as "I had so much fun today!"

[1182] Terminal message retrieval and sending:

[1183] The terminal receives the message sent by the user and transmits it to the server via the communication network, where the message is encrypted.

[1184] Server-based message parsing and emotion recognition:

[1185] The server analyzes the received message using natural language processing technology. This analysis includes sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message such as "I had so much fun today!" is broken down into the keywords "fun," "today," and "gratitude." The emotion engine then recognizes the user's emotions as "joy" or "gratitude."

[1186] Determining and generating stamp requirements:

[1187] The server determines the design requirements for the stamp based on the extracted keywords and emotional information. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you." Original stamps are generated using image generation techniques (e.g., GANs, Style Transfer).

[1188] Sending stamps and verifying users:

[1189] The generated stamp is sent to the user's device and displayed on the chat screen. The user checks the generated stamp and, if there are no problems, sends it via chat.

[1190] 3. Examples of concrete examples and prompts

[1191] For example, if a user sends a message saying "I had so much fun today!", the following will happen:

[1192] 1. A user sends a message on the LINE app saying, "Today was so much fun!"

[1193] 2. The device sends a message to the server.

[1194] 3. The server analyzes the message using NLP and extracts the keywords "fun," "today," and "gratitude."

[1195] 4. The emotion engine recognizes the emotions of "joy" and "gratitude" from the message.

[1196] 5. The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[1197] 6. The server sends the generated stamp to the device.

[1198] 7. The user checks the stamps received in the LINE app and sends them in the chat.

[1199] Prompt Sentence Examples

[1200] Here is an example of a prompt you can enter into a generative AI model:

[1201] "Please generate an original stamp suitable for the following message."

[1202] Message: "Today was so much fun!"

[1203] This prompt sentence allows the user to instantly obtain an appropriate original stamp, and to communicate with a stamp that best suits the message content and emotion.

[1204] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1205] Step 1: User sends message

[1206] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[1207] Specific operation: A user uses a chat application on a smartphone or computer to enter a message in text format. The entered text data is sent.

[1208] Enter: Text message "Today was so much fun!"

[1209] Output: A trigger signal for a message to be sent from the terminal.

[1210] Step 2: Retrieving and sending messages using the device

[1211] The terminal receives the message sent by the user and transmits the message to the server via the communication network.

[1212] Specific operation: The device retrieves the message sent by the user and sends the message data in encrypted form to the server using the HTTPS protocol.

[1213] Input: The text message sent by the user

[1214] Output: Message data sent to the server in encrypted form

[1215] Step 3: Message analysis and emotion recognition by the server

[1216] The server analyzes the received message using natural language processing technology.

[1217] Specific operation: The server deserializes the message data, tokenizes and parses it using an NLP library (e.g., spaCy, NLTK), and extracts keywords. In addition, it analyzes the sentiment of the message using an emotion engine (e.g., IBM Watson, Google Cloud Natural Language API). For example, the keywords "fun," "today," and "gratitude" are extracted, along with the sentiment information of "joy."

[1218] Input: Message data in encrypted form

[1219] Output: Keywords ("fun," "today," "thankful") and emotional information ("joy")

[1220] Step 4: Determine stamp requirements

[1221] The server determines the design requirements of the stamp based on the extracted keywords and emotion information.

[1222] How it works: The server uses an algorithm to generate sticker concepts based on keywords and emotional information. For example, a sticker might have a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1223] Input: Keywords ("fun," "today," "thankful"), emotional information ("joy")

[1224] Output: Stamp design requirements (e.g. smiley face, fireworks, "thank you")

[1225] Step 5: Generate stamps

[1226] The server generates new stamps using image generation techniques.

[1227] How it works: The server uses techniques such as Generative Adversarial Networks (GANs) and Style Transfer to leverage the GPU to generate original stamps based on design requirements.

[1228] Input: Sticker design requirements (e.g. smiley face, fireworks, "thank you")

[1229] Output: Generated original stamp image data

[1230] Step 6: Send your sticker

[1231] The generated stamp is sent to the user's terminal.

[1232] What it does: The server compresses the generated stamp and quickly sends it to the user's device, where it decompresses the data and converts it into a displayable format.

[1233] Input: Generated original stamp image data

[1234] Output: Stamp data sent to the user's device

[1235] Step 7: User confirmation and stamp sending

[1236] The user checks the generated stamp and sends it in the chat.

[1237] Specific operation: The user visually confirms the generated stamp on the chat screen of the device and presses the "Send" button. The stamp is added to the chat log.

[1238] Input: Stamp data displayed on the terminal

[1239] Output: Stamp sent on the chat screen

[1240] (Application example 2)

[1241] 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."

[1242] In conventional chat systems, users had to manually select appropriate stamps based on their emotions and message content, making it difficult to communicate quickly and effectively. It was also difficult to automatically generate original content that accurately reflected emotions, making communication with users tend to be uniform and mechanical. In particular, in customer support, there was a need for a way to quickly and accurately convey users' emotions, such as dissatisfaction or joy.

[1243] 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.

[1244] In this invention, the server includes means for acquiring a message based on a user's input, means for transmitting the acquired message to the server, means for analyzing the message in the server and extracting at least one keyword, means for determining stamp design requirements based on the extracted keyword and emotion information, means for generating a new stamp based on the determined design requirements, means for transmitting the generated stamp to the user's terminal, means for displaying the transmitted stamp on a chat screen, means for recognizing the user's emotion, and means for generating an original stamp based on the recognized emotion. This makes it possible to automatically generate and transmit a stamp that is optimal for the message and emotion input by the user, thereby achieving fast and effective communication.

[1245] "User input" refers to messages or commands sent by a user via a keyboard or touchscreen, such as in a chat system.

[1246] The "means for obtaining a message" refers to hardware or software that has the function of extracting a message input by a user and passing it on to subsequent processing.

[1247] A "server" is a computer system that processes data and generates stamps via a network.

[1248] The "means for analyzing a message" refers to hardware or software that has the function of using natural language processing technology to understand a user's message and structurally divide its contents.

[1249] "Keyword extraction methods" refer to algorithms and techniques used to extract important words and phrases from the analysis results.

[1250] "Emotion information" refers to data that expresses the emotions contained in a user's message in numerical values ​​or categories.

[1251] "Stamp design requirements" are the standards or specifications that determine the appearance and content of the stamp to be generated.

[1252] "Means for generating new stickers" refers to generative AI models or technologies capable of creating images or animations based on determined design requirements.

[1253] "Means for transmitting stamps" refers to the communication protocols and techniques used to transmit the generated stamps to the user's terminal.

[1254] The "means for displaying on the chat screen" refers to software having a function for displaying the sent stamp on the chat application so that the user can check it.

[1255] "Means for recognizing emotions" refers to algorithms and technologies that estimate emotions from user input, facial expressions, etc., and output them as data.

[1256] "Means for generating original stamps" refers to technology or systems that allow for the creation of new stamps on the spot based on the user's emotions or keywords.

[1257] This invention relates to a system for enhancing communication with users in customer support for online shopping sites. Specifically, it is a system that automatically generates original stamps in response to users' messages and responds in a way that best suits their emotions.

[1258] System configuration

[1259] 1. Get user messages

[1260] Users input messages through the chat system, which are displayed on their terminals and sent to the server.

[1261] 2. Message Analysis and Emotion Recognition

[1262] The server analyzes the received message using natural language processing technology (e.g., TextBlob). The analysis includes tokenizing the sentence, parsing the syntax, and sentiment analysis. During this process, an emotion engine is activated to recognize the user's emotions and extract emotional information such as joy, anger, or dissatisfaction from the message.

[1263] 3. Keyword extraction and intent estimation

[1264] The server extracts key keywords from the analysis results and infers the user's intention. For example, from the message "Product delivery is delayed," the keywords "delivery" and "delay" are extracted, and the emotion engine recognizes dissatisfaction.

[1265] 4. Determine stamp requirements

[1266] The server determines the design requirements for a stamp based on the estimated intent and emotion information, such as the text "I'm sorry," a simple background, and a troubled face.

[1267] 5. Stamp generation

[1268] The server uses a generative AI model (e.g., Generative Adversarial Networks (GANs)) to generate original stamps based on the determined design requirements. The generated stamps are immediately prepared as binary data.

[1269] 6. Sending and displaying stamps

[1270] The generated stamp is sent to the user's device and displayed on the chat screen. The user checks the stamp, and if there are no problems, they can send it again to complete the communication.

[1271] Specific examples

[1272] For example, if a user enters the message "The delivery of the product is delayed," the system will act as follows:

[1273] A message saying "The delivery of the product is delayed" is sent from the terminal to the server.

[1274] The server analyzes the message and extracts the keywords "delivery" and "delay."

[1275] The emotion engine recognizes "dissatisfaction" from the message.

[1276] The server determines the design requirements for the stamp and generates a stamp containing the text "Sorry," a simple background, and a troubled facial expression.

[1277] The server sends the generated stamp to the terminal.

[1278] The device displays the stamp on the chat screen, and the user can check it and send it.

[1279] Prompt Sentence Examples

[1280] User message: "Item delivery is delayed"

[1281] Produced stamp: A stamp containing the text "Sorry"

[1282] Emotion: "Anger"

[1283] Background: "Simple"

[1284] Expression: "worried"

[1285] Through the above process, users can always use stamps that best suit the conversation and emotions they are feeling at the time, realizing a system that allows for smoother and more effective communication.

[1286] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1287] Step 1:

[1288] Users input messages through the chat system, which are displayed on the terminal and simultaneously sent to the server.

[1289] Input: A message entered by the user (e.g., "Your delivery is delayed.")

[1290] Output: Message sent from terminal to server

[1291] Step 2:

[1292] The server analyzes the received message, using natural language processing techniques (e.g., TextBlob) to tokenize the sentences, parse them syntactically, and analyze their sentiment, thereby understanding the message and extracting key keywords and sentiment information.

[1293] Input: User message sent from the terminal

[1294] Data processing: sentence tokenization, syntactic analysis, sentiment analysis

[1295] Output: Key keywords (e.g., "Delivery" and "Delay") and sentiment information (e.g., "Dissatisfied")

[1296] Step 3:

[1297] The server infers the user's intention based on the extracted keywords and emotional information. Based on the inferred intention, the design requirements for the stamp are determined, including the text to be displayed, the background, and the facial expression.

[1298] Input: Key keywords (e.g., "Delivery" or "Delay") and sentiment information (e.g., "Dissatisfied")

[1299] Data processing: Intent estimation and design requirement determination

[1300] Output: Sticker design requirements (e.g. "Sorry" text, simple background, worried face expression)

[1301] Step 4:

[1302] The server uses a generative AI model (e.g., Generative Adversarial Networks (GANs)) to generate original stamps based on the determined design requirements. The stamps are generated as image files and used for subsequent processing.

[1303] Input: Stamp design requirements

[1304] Data processing: Image generation using generative AI models

[1305] Output: Generated original stamp (e.g. stamp image file)

[1306] Step 5:

[1307] The server sends the generated stamp to the user's terminal, and transfers the stamp data to the terminal using a transmission protocol.

[1308] Input: Generated original stamp

[1309] Data processing: data encoding and transmission

[1310] Output: Stamp data sent to the terminal

[1311] Step 6:

[1312] The device displays the received stamps on the chat screen. The user can check the stamps and send them further to the chat if necessary, completing the communication.

[1313] Input: Stamp data sent to the terminal

[1314] Data processing: Decoding and display

[1315] Output: Stamp displayed on the chat screen

[1316] These processing steps automatically generate stamps that best suit the user's message and emotions, enabling fast and effective communication.

[1317] 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.

[1318] 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.

[1319] 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.

[1320] [Fourth embodiment]

[1321] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1322] 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.

[1323] 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).

[1324] 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.

[1325] 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.

[1326] 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).

[1327] 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.

[1328] 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.

[1329] 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.

[1330] 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.

[1331] 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.

[1332] 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.

[1333] 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."

[1334] The present invention relates to a system that allows users to instantly create and use original stamps that are most suitable for messages in chat applications such as LINE. The program processing of this system is explained below in natural language.

[1335] System Overview

[1336] This system analyzes messages sent by users on the server and generates original stamps based on the analysis results. The generated stamps are then immediately sent to the user's device, where they can be sent via chat.

[1337] Program processing flow

[1338] 1. User sends message

[1339] A user opens a chat application such as LINE, types a message, and sends it. For example, a user sends a message such as "I had a great time today!"

[1340] 2. Message retrieval and sending by the device

[1341] The terminal receives the sent message and sends it to the server.

[1342] 3. Message Parsing by the Server

[1343] The server analyzes the received message using natural language processing technology. The analysis includes sentence structure analysis and sentiment analysis. For example, from the message "I had so much fun today!", keywords such as "fun," "today," and "thankful" are extracted.

[1344] 4. Keyword Extraction and Intention Estimation

[1345] The server extracts key keywords from the analysis results and uses them to infer the user's intention. In this case, the keywords "fun," "today," and "thankful" are extracted, and it is inferred that the user had a fun day and is grateful for it.

[1346] 5. Determine stamp requirements

[1347] The server determines the design requirements for the stamp based on the inferred intent. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1348] 6. Stamp Generation

[1349] The server uses image generation techniques (e.g., GANs or Style Transfer) to generate original stamps based on the determined design requirements.

[1350] 7. Sending stamps

[1351] The generated stamp is sent to the user's terminal and displayed on the chat screen.

[1352] 8. User confirmation and stamp sending

[1353] The user can check the generated stamps and send them in chat, allowing them to easily use original stamps that best suit the content of their messages.

[1354] Specific examples

[1355] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[1356] The device sends a message to the server.

[1357] The server analyzes the message and extracts keywords such as "fun," "today," and "thankful."

[1358] The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[1359] The server sends the generated stamp to the terminal.

[1360] The user checks the stamp and, if there are no problems, sends it to the chat.

[1361] In this way, the system can instantly generate and send original stamps that are optimal for the content of a user's message, allowing users to always use stamps that are optimal for the conversation at hand, making communication more enjoyable and fulfilling.

[1362] The processing flow will be explained below.

[1363] Step 1:

[1364] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[1365] Step 2:

[1366] The terminal receives the message sent by the user.

[1367] Step 3:

[1368] The terminal transmits the acquired message to the server.

[1369] Step 4:

[1370] The server receives the message.

[1371] Step 5:

[1372] The server analyzes the message using natural language processing techniques, including sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message like "I had so much fun today!" is broken down into the keywords "fun," "today," and "thankful."

[1373] Step 6:

[1374] The server extracts key keywords from the analysis results, such as "fun," "today," and "gratitude."

[1375] Step 7:

[1376] The server infers the user's intention based on the extracted keywords. For example, it may infer that the user had a good day and is expressing gratitude for it.

[1377] Step 8:

[1378] The server determines the design requirements for the stamp based on the inferred intent. In this case, the stamp includes elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1379] Step 9:

[1380] The server uses image generation techniques (e.g., Generative Adversarial Networks (GANs) or Style Transfer) to generate original stamps based on the determined design requirements.

[1381] Step 10:

[1382] The server sends the generated stamp to the terminal.

[1383] Step 11:

[1384] The stamp received by the terminal is displayed on the user's chat screen.

[1385] Step 12:

[1386] The user checks the generated stamp, and if there are no particular problems, selects the stamp and sends it to the chat.

[1387] Example 1

[1388] 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."

[1389] There is a need for a system that allows users to quickly generate and use stamps that are optimal for the content of their messages in chat applications. Existing methods require users to manually select stamps, which disrupts the flow of conversation. It can also take a long time for users to find a stamp that is appropriate for the content of their message. To solve this problem, there is a need for a system that automatically generates and provides stamps based on the user's message.

[1390] 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.

[1391] In this invention, the server includes means for acquiring information based on user input, means for transmitting the acquired information to the server, means for analyzing the information and extracting at least one keyword in the server, means for determining design requirements based on the extracted keyword, means for generating a new image based on the determined design requirements, means for transmitting the generated image to the user's device, and means for displaying the transmitted image on a display screen. This makes it possible to automatically and quickly generate and provide a stamp that is optimal for the content of a user's message.

[1392] A "user" is a person who uses the system to send a chat message and request the generation of a stamp.

[1393] "Input" refers to the act of a user sending a text message to a chat application.

[1394] "Information" refers to messages entered by users and other related data.

[1395] "Device" refers to the electronic device (e.g., smartphone, tablet, PC) that a user uses to access the chat application.

[1396] "Server" refers to a computer system that communicates with user devices over a network and performs processes such as parsing messages and generating stamps.

[1397] The term "means for acquiring" refers to the software and hardware configuration for acquiring input information from a user.

[1398] "Means for transmitting" refers to the software and hardware configuration for transmitting the acquired information to the server.

[1399] "Means for analyzing" refers to a software and hardware configuration that analyzes the transmitted information using natural language processing technology and extracts keywords.

[1400] "Keywords" refer to key words or phrases extracted from the analyzed information.

[1401] "Design requirements" refers to the conditions or requirements that determine the characteristics of the stamp to be generated (e.g., facial expression, background, text).

[1402] "Generating means" refers to a software and hardware configuration for generating new images (stamps) according to design requirements.

[1403] "Transmitting means" refers to the software and hardware configuration for transmitting the generated image to a user's device.

[1404] "Means for displaying" refers to the software and hardware configuration for displaying the transmitted image on the screen of the user's device.

[1405] The present invention relates to a system that analyzes messages sent by users using chat applications (e.g., LINE) and automatically generates original stamps based on the contents of the messages. Specific embodiments of the present invention are described below.

[1406] When a user opens a chat application, inputs a message, and sends it, the terminal receives the message and sends it to the server, attaching the user's identification information along with the message content.

[1407] The server analyzes the received message using natural language processing techniques (e.g., BERT or GPT-3). As part of the analysis, the server analyzes the grammar and sentiment structure to extract key keywords. In this case, for example, keywords such as "fun," "today," and "thankful" are extracted from the message "I had so much fun today!"

[1408] The server infers the user's intent based on the extracted keywords and determines the appropriate design requirements for the stamp, including, for example, a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1409] To generate the stamps, the server uses image generation techniques (e.g., GANs or Style Transfer) to generate original stamps. As a specific example, StyleGAN is used to generate a stamp with the words "Thank you" written on it, featuring a smiling character with fireworks in the background. The stamps generated in this way are most suited to the user's intent.

[1410] The stamp data generated by the server is sent to the user's device. The device displays the received stamp on the chat application screen. The user checks the generated stamp and, if satisfied, sends it as a chat message.

[1411] This allows the present invention to automatically generate and instantly provide original stamps that are optimal for the content of a user's message. Users can intuitively use the stamps that are optimal for them without any special operations, making communication smoother and more enjoyable.

[1412] Examples of concrete examples and prompts

[1413] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[1414] 1. The device receives the message and sends it to the server.

[1415] 2. The server uses natural language processing technology to analyze the message and extract the keywords "fun," "today," and "thank you."

[1416] 3. The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[1417] 4. The server sends the generated stamp to the device, which displays it on the chat screen.

[1418] 5. The user checks the stamp and sends it in the chat.

[1419] The specific prompt is as follows:

[1420] Analyze the message "Today was so much fun!" and generate a stamp that best suits that content. The stamp requirements should include a cheerful expression (e.g., a smiling face), a fun background (e.g., fireworks), and the text "Thank you."

[1421] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1422] Step 1:

[1423] A user opens a chat application, types a message, and sends it. The input is a text message such as "I had a great time today!" that the user sends on the chat application, and the output is the message data added to the device's sending queue. Specifically, when the user presses the send button, the message is stored in the device's sending queue.

[1424] Step 2:

[1425] The terminal reads the message from the sending queue and sends it to the server. The input is the user's message data obtained in the previous step, and the output is the message data sent to the server. The terminal sends the message content and the user's identification information to the server via the network.

[1426] Step 3:

[1427] The server analyzes the messages it receives using natural language processing technology. The input is the message data received by the server, and the output is the analyzed keyword data. The server uses generative AI models such as BERT and GPT-3 to perform grammar and sentiment analysis. Specifically, it extracts keywords such as "fun," "today," and "thankful" from the message "I had so much fun today!"

[1428] Step 4:

[1429] The server extracts key keywords from the analysis results and infers the user's intent based on them. The input is the analyzed keyword data, and the output is the inferred user intent. For example, based on the extracted keywords "fun," "today," and "thankful," the server infers that the user had a good day and is grateful for it.

[1430] Step 5:

[1431] The server determines the design requirements for the stamp based on the estimated intent. The input is the estimated user intent, and the output is the design requirement data. The design requirements include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1432] Step 6:

[1433] The server generates original stamps using image generation technology. The input is design requirement data, and the output is the generated stamp image data. The server uses technologies such as GANs and Style Transfer to generate stamps based on the determined design requirements. The specific process involves using StyleGAN to generate a stamp with a smiling character and the word "Thank you" written on it against a background of fireworks.

[1434] Step 7:

[1435] The server sends the generated stamp to the user's device. The input is the generated stamp image data, and the output is the stamp image data sent to the device. The server encodes the stamp in an appropriate data format (e.g. PNG, JPEG) and sends it to the device over the network.

[1436] Step 8:

[1437] The stamp received by the terminal is displayed on the chat screen. The input is the stamp image data sent to the terminal, and the output is the stamp image displayed on the chat screen. The user checks the generated stamp and, if satisfied, sends it as a chat message. Specifically, the user selects a stamp and presses the send button, and the stamp is then displayed to other chat participants.

[1438] By following the above steps, this system can automatically generate and quickly provide an original stamp that is optimal for the content of a user's message.

[1439] (Application example 1)

[1440] 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."

[1441] In customer support, responding quickly and appropriately to messages from users is important for improving customer satisfaction. However, current systems make it difficult to accurately understand users' emotions and intentions and provide an appropriate response immediately. This can result in delayed responses or inability to provide support that meets users' needs. Furthermore, this increases the burden on customer support staff, making it difficult to operate efficiently.

[1442] 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.

[1443] In this invention, the server includes means for acquiring a message based on a user's input, means for transmitting the acquired message to the server, means for analyzing the message in the server and extracting at least one keyword, means for determining stamp design requirements based on the extracted keyword, means for generating a new stamp based on the determined design requirements, means for transmitting the generated stamp to the user's terminal, means for displaying the transmitted stamp on a chat screen, and means for generating stamps and reaction images in response to the user's message and for efficiently supporting customers using a customer support chat application. This enables appropriate customer support to be provided in real time based on the user's message.

[1444] "User input" refers to the transmission of information or instructions given by the user via a communication terminal.

[1445] "Message" refers to text or other information sent based on user input.

[1446] A "server" refers to a computer system that stores and processes data over a network.

[1447] "Keywords" refer to important words and phrases extracted during message analysis.

[1448] A "stamp" is a type of image or emoji displayed in digital format and is used to express a user's emotions or intentions.

[1449] "Design Requirements" refers to the criteria that determine the specific features or elements (e.g., color, shape, text, etc.) of the stamp or image to be generated.

[1450] "Terminal" refers to communication devices such as smartphones and personal computers used by users.

[1451] "Chat screen" refers to an interface that allows users to exchange messages within a messaging application.

[1452] "Natural language processing technology" refers to computer technology for analyzing and understanding human language.

[1453] "Generative AI model" refers to a model that uses artificial intelligence techniques to generate new data (e.g., images, text).

[1454] "Customer support chat application" refers to a chat-style application that enables businesses to provide support to their customers.

[1455] The present invention relates to a system that generates original stamps and reaction images based on messages sent by users through a customer support chat application, and responds promptly and appropriately.

[1456] The following hardware and software are used to build the system:

[1457] Hardware

[1458] High-performance cloud servers (e.g., Amazon Web Services, Google Cloud Platform)

[1459] Smartphones and computers used by users

[1460] software

[1461] Natural Language Processing Libraries: SpaCy, NLTK, Google Cloud Natural Language API

[1462] Image generation technology: PyTorch, TensorFlow, GANs library

[1463] Chat support framework: Twilio, Dialogflow

[1464] System Operation

[1465] 1. Getting and sending messages

[1466] When a user sends a message through a customer support chat application, the device receives the message and sends it to the server, for example, "I'm worried because my item is late."

[1467] 2. Message Analysis

[1468] The server analyzes the received message using natural language processing technology (NLP library). Specifically, it performs sentiment analysis and sentence structure analysis to extract important keywords. In this example, the keywords extracted are "delay" and "worry."

[1469] 3. Determine design requirements

[1470] The server determines the design requirements for stamps and reaction images based on the extracted keywords, such as "a stamp that shows an intention to apologize" or "an expression that provides a sense of security."

[1471] 4. Stamp generation

[1472] Based on the determined design requirements, the server generates new stamps and reaction images using image generation techniques (e.g., GANs library), using a generative AI model.

[1473] 5. Sending and displaying stamps

[1474] The generated stamps and reaction images are sent from the server to the user's device and displayed on the chat screen within the customer support chat application, allowing the user to instantly check the generated images and receive appropriate support.

[1475] Specific examples

[1476] For example, if a user sends a message saying, "I'm worried because my item arrived late," the following prompt sentence is input to the generative AI model:

[1477] Prompt Sentence Examples

[1478] A user sends a message saying, "I'm worried about the delay in receiving my item." Generate a stamp expressing apology and relief.

[1479] Based on this prompt, the server generates a stamp with a calm, reassuring character saying, "I'm sorry, but please don't worry." The generated stamp is sent to the user's device and displayed on the chat screen. The user can view it and receive appropriate support.

[1480] As described above, the present invention can provide an appropriate response in real time based on the user's message, thereby improving customer satisfaction in customer support.

[1481] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1482] Program processing steps

[1483] Step 1:

[1484] User messaging

[1485] A user types and sends a message through a customer support chat application.

[1486] Input: A message entered by the user (e.g., "I'm worried about the delay in receiving my item.")

[1487] Output: The terminal gets the message

[1488] Step 2:

[1489] Retrieving and sending messages via the terminal

[1490] The terminal receives the message entered by the user and transmits the message to the server.

[1491] Input: User's message

[1492] Output: Message sent to the server

[1493] Step 3:

[1494] Message parsing by the server

[1495] The server analyzes the received message using natural language processing technology (NLP library).

[1496] Input: The message sent to the server

[1497] Data processing: sentence structure analysis, sentiment analysis

[1498] Output: Extracted keywords (e.g., "delay" and "worry")

[1499] Step 4:

[1500] Keyword extraction and intent estimation

[1501] The server extracts key keywords from the analysis results and uses them to infer the user's intent.

[1502] Input: Parsed message

[1503] Data calculation: Extraction of keywords, application of intent estimation algorithms

[1504] Output: Design requirements for stamps (e.g., "a stamp that shows the intention to apologize" or "an expression that provides a sense of security")

[1505] Step 5:

[1506] Determining design requirements

[1507] The server determines the design requirements for stamps and reaction images based on the keywords picked up.

[1508] Input: Extracted keywords and inferred intent

[1509] Data processing: Determining design requirements

[1510] Output: Specific design requirements (e.g., "smiling character" or "apology message")

[1511] Step 6:

[1512] Stamp generation using AI models

[1513] The server uses image generation technology (GANs and Style Transfer) to generate new stamps and reaction images. Specifically, it inputs a prompt sentence into a generative AI model and generates an image.

[1514] Input: Design Requirements

[1515] Data Computation: Image Generation with Generative AI Models

[1516] Output: Generated stamps and reaction images

[1517] Step 7:

[1518] Sending generated stamps

[1519] The generated stamps and reaction images are sent from the server to the user's device.

[1520] Input: Generated stamps and reaction images

[1521] Output: Stickers and reaction images sent to the user's device

[1522] Step 8:

[1523] Display on the chat screen

[1524] The stamps and reaction images received by the user's device are displayed on the chat screen, where the user can confirm them and continue interacting with the customer support representative.

[1525] Input: sent stamps and reaction images

[1526] Output: Stamps and reaction images displayed on the chat screen

[1527] These are the specific processing steps of the program that realizes the customer support chat application. Through this flow, users can receive prompt and appropriate support.

[1528] 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.

[1529] This invention relates to a system that allows users to instantly create and use original stamps that are best suited to their messages in chat applications such as LINE. Furthermore, it provides a form that combines an emotion engine that recognizes the user's emotions and generates stamps based on that information.

[1530] System Overview

[1531] This system is characterized by analyzing messages sent by users on the server and generating original stamps based on the analysis results. In addition, an emotion engine recognizes the user's emotions and designs stamps based on that information, making it possible to generate more appropriate and emotionally rich stamps. The generated stamps are immediately sent to the user's device, where the user can send them in chats.

[1532] Program processing flow

[1533] 1. User sends message

[1534] The user opens a chat application such as LINE, enters "I had so much fun today!" in the message input field, and presses the send button.

[1535] 2. Message retrieval and sending by the device

[1536] The terminal receives the message sent by the user and sends the message to the server.

[1537] 3. Message analysis and emotion recognition by the server

[1538] The server analyzes the received message using natural language processing technology. This analysis includes sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message such as "I had so much fun today!" is broken down into the keywords "fun," "today," and "thankful." The emotion engine then analyzes the user's emotions and recognizes that they include feelings of joy and gratitude.

[1539] 4. Keyword Extraction and Intention Estimation

[1540] The server extracts key keywords from the analysis results and uses them to infer the user's intent. For example, if the keywords "fun," "today," and "thanks" are extracted, it is inferred that the user had a good day and is expressing gratitude for that.

[1541] 5. Determine stamp requirements

[1542] The server determines the design requirements for the stamp based on the estimated intent and the emotion information from the emotion engine. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1543] 6. Stamp Generation

[1544] The server uses image generation techniques (e.g., Generative Adversarial Networks (GANs) or Style Transfer) to generate original stamps based on the determined design requirements.

[1545] 7. Sending stamps

[1546] The generated stamp is sent to the user's terminal and displayed on the chat screen.

[1547] 8. User confirmation and stamp sending

[1548] The user can check the generated stamps and send them in chat. This allows users to easily use original stamps that best suit the content of their messages, and communicate with stamps that match their emotions.

[1549] Specific examples

[1550] For example, if a user sends a message saying "I had so much fun today!", it will look like this:

[1551] The device sends a message to the server.

[1552] The server analyzes the message and extracts keywords such as "fun," "today," and "thankful."

[1553] The emotion engine recognizes the user's emotion as "joy" from the message.

[1554] The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[1555] The server sends the generated stamp to the terminal.

[1556] The user checks the stamp and, if there are no problems, sends it to the chat.

[1557] In this way, the system can instantly generate and send original stamps that best fit the content and emotion of a user's message, allowing users to always use stamps that best fit the conversation and emotion at the time, making communication more enjoyable and fulfilling.

[1558] The processing flow will be explained below.

[1559] Step 1:

[1560] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[1561] Step 2:

[1562] The terminal receives the message sent by the user.

[1563] Step 3:

[1564] The terminal transmits the acquired message to the server.

[1565] Step 4:

[1566] The server receives the message.

[1567] Step 5:

[1568] The server begins analyzing the message. It uses natural language processing technology to tokenize and syntactically analyze the sentence and extract key keywords. For example, from the message "I had so much fun today!", the keywords "fun," "today," and "thankful" are extracted.

[1569] Step 6:

[1570] The server uses an emotion engine to recognize the user's emotion. It identifies emotion categories (e.g., joy, sadness, anger, surprise, etc.) from words and phrases contained in the message. In this case, the emotion engine recognizes "joy."

[1571] Step 7:

[1572] The server infers the user's intention based on the analysis results and emotional information. For example, based on the keywords "fun," "today," and "gratitude" and the emotion "joy," it can infer that the user had a fun day and is grateful for it.

[1573] Step 8:

[1574] The server determines the design requirements for the stamp based on the estimated intent and emotion information. For example, the stamp may include a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1575] Step 9:

[1576] The server generates new stickers using image generation techniques (e.g., Generative Adversarial Networks (GANs) and Style Transfer). Based on the determined design requirements, a sticker with the words "Thank you" written on it and a smiling character with fireworks in the background is created.

[1577] Step 10:

[1578] The server sends the generated stamp to the user's terminal.

[1579] Step 11:

[1580] The stamp received by the terminal is displayed on the user's chat screen.

[1581] Step 12:

[1582] The user checks the generated stamps, selects one, and sends it in the chat.

[1583] This process allows users to quickly generate original stamps that best suit their message and emotion and use them in real time, making chat communication richer and more effective.

[1584] Example 2

[1585] 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."

[1586] Conventional chat applications require users to manually select appropriate stamps or emojis when sending messages, making communication cumbersome. Furthermore, the selection of stamps often does not adequately reflect the user's emotions or intentions, resulting in a reduction in the accuracy and effectiveness of the expression. This invention solves the above-mentioned problems by providing a system that automatically analyzes a user's message and the emotions behind it, and instantly generates and provides original stamps that are appropriate for the message.

[1587] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for acquiring a message based on a user's input; means for transmitting the acquired message to the server via a communication network; means for analyzing the message in the server using natural language processing technology and extracting at least one keyword; means for determining design requirements for a stamp based on the extracted keyword and emotional information analyzed by an emotion engine; means for using a generative AI model to generate a new stamp based on the determined design requirements; means for transmitting the generated stamp to the user's terminal; and means for displaying the transmitted stamp on a chat screen. This eliminates the need for the user to manually select a stamp, and enables the user to automatically obtain a stamp that best suits the message and the emotion behind it.

[1588] "User input" refers to messages or text information sent by a user through a chat application.

[1589] A "message" refers to a sentence or text data that a user sends through a chat application.

[1590] "Communications Network" means the Internet or other digital communications infrastructure used to transmit data from a device to a server or vice versa.

[1591] The term "server" refers to a central processing unit that performs various processes in a chat application, such as receiving messages, analyzing messages, and generating stamps.

[1592] "Natural language processing technology" refers to technology that allows a server to analyze text data and perform keyword extraction and emotion recognition.

[1593] "Keywords" refer to important words or phrases extracted from a message using natural language processing techniques.

[1594] "Emotion engine" refers to software or algorithms that analyze emotions from users' messages and provide that emotion information.

[1595] "Stamp design requirements" refer to the elements and attributes that should be included in stamps, which are determined based on the extracted keywords and emotional information.

[1596] "Generative AI Model" refers to an artificial intelligence model used to generate new stamps based on determined design requirements.

[1597] "Terminal" refers to a device such as a computer, smartphone, or tablet that a user uses to use a chat application.

[1598] The "chat screen" refers to an interface in a chat application where messages and stamps are displayed and which is operated by the user.

[1599] This invention relates to a system that allows users to instantly generate and use original stamps based on messages in chat applications. This system recognizes the user's emotions and combines them with an emotion engine to generate stamps based on that information, providing more appropriate and emotive stamps.

[1600] 1. Hardware and Software Used

[1601] Hardware:

[1602] Server: A server equipped with a high-performance central processing unit (including a CPU and GPU).

[1603] Device: The device on which a user uses a chat application, such as a computer, smartphone, or tablet.

[1604] software:

[1605] Chat application: Communication applications such as LINE.

[1606] Natural Language Processing technologies: NLP libraries (e.g. spaCy, NLTK).

[1607] Sentiment engine: Software or algorithms for analyzing user emotions (e.g., IBM Watson, Google Cloud Natural Language API).

[1608] Image generation techniques: Artificial intelligence models including Generative Adversarial Networks (GANs) and Style Transfer.

[1609] 2. Data processing and calculation

[1610] User sending message:

[1611] A user opens a chat application, enters text in the message input field, and presses the send button. For example, to send a message such as "I had so much fun today!"

[1612] Terminal message retrieval and sending:

[1613] The terminal receives the message sent by the user and transmits it to the server via the communication network, where the message is encrypted.

[1614] Server-based message parsing and emotion recognition:

[1615] The server analyzes the received message using natural language processing technology. This analysis includes sentence tokenization, syntactic analysis, and sentiment analysis. For example, a message such as "I had so much fun today!" is broken down into the keywords "fun," "today," and "gratitude." The emotion engine then recognizes the user's emotions as "joy" or "gratitude."

[1616] Determining and generating stamp requirements:

[1617] The server determines the design requirements for the stamp based on the extracted keywords and emotional information. For example, the stamp may include elements such as a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you." Original stamps are generated using image generation techniques (e.g., GANs, Style Transfer).

[1618] Sending stamps and verifying users:

[1619] The generated stamp is sent to the user's device and displayed on the chat screen. The user checks the generated stamp and, if there are no problems, sends it via chat.

[1620] 3. Examples of concrete examples and prompts

[1621] For example, if a user sends a message saying "I had so much fun today!", the following will happen:

[1622] 1. A user sends a message on the LINE app saying, "Today was so much fun!"

[1623] 2. The device sends a message to the server.

[1624] 3. The server analyzes the message using NLP and extracts the keywords "fun," "today," and "gratitude."

[1625] 4. The emotion engine recognizes the emotions of "joy" and "gratitude" from the message.

[1626] 5. The server determines the design requirements for the stamp and generates a stamp with a smiling character saying "Thank you" against a background of fireworks.

[1627] 6. The server sends the generated stamp to the device.

[1628] 7. The user checks the stamps received in the LINE app and sends them in the chat.

[1629] Prompt Sentence Examples

[1630] Here is an example of a prompt you can enter into a generative AI model:

[1631] "Please generate an original stamp suitable for the following message."

[1632] Message: "Today was so much fun!"

[1633] This prompt sentence allows the user to instantly obtain an appropriate original stamp, and to communicate with a stamp that best suits the message content and emotion.

[1634] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1635] Step 1: User sends message

[1636] A user opens a chat application, types "I had so much fun today!" in the message input field, and presses the send button.

[1637] Specific operation: A user uses a chat application on a smartphone or computer to enter a message in text format. The entered text data is sent.

[1638] Enter: Text message "Today was so much fun!"

[1639] Output: A trigger signal for a message to be sent from the terminal.

[1640] Step 2: Retrieving and sending messages using the device

[1641] The terminal receives the message sent by the user and transmits the message to the server via the communication network.

[1642] Specific operation: The device retrieves the message sent by the user and sends the message data in encrypted form to the server using the HTTPS protocol.

[1643] Input: The text message sent by the user

[1644] Output: Message data sent to the server in encrypted form

[1645] Step 3: Message analysis and emotion recognition by the server

[1646] The server analyzes the received message using natural language processing technology.

[1647] Specific operation: The server deserializes the message data, tokenizes and parses it using an NLP library (e.g., spaCy, NLTK), and extracts keywords. In addition, it analyzes the sentiment of the message using an emotion engine (e.g., IBM Watson, Google Cloud Natural Language API). For example, the keywords "fun," "today," and "gratitude" are extracted, along with the sentiment information of "joy."

[1648] Input: Message data in encrypted form

[1649] Output: Keywords ("fun," "today," "thankful") and emotional information ("joy")

[1650] Step 4: Determine stamp requirements

[1651] The server determines the design requirements of the stamp based on the extracted keywords and emotion information.

[1652] How it works: The server uses an algorithm to generate sticker concepts based on keywords and emotional information. For example, a sticker might have a cheerful expression (e.g., a smile), a fun background (e.g., fireworks), and the text "Thank you."

[1653] Input: Keywords ("fun," "today," "thankful"), emotional information ("joy")

[1654] Output: Stamp design requirements (e.g. smiley face, fireworks, "thank you")

[1655] Step 5: Generate stamps

[1656] The server generates new stamps using image generation techniques.

[1657] How it works: The server uses techniques such as Generative Adversarial Networks (GANs) and Style Transfer to leverage the GPU to generate original stamps based on design requirements.

[1658] Input: Sticker design requirements (e.g. smiley face, fireworks, "thank you")

[1659] Output: Generated original stamp image data

[1660] Step 6: Send your sticker

[1661] The generated stamp is sent to the user's terminal.

[1662] What it does: The server compresses the generated stamp and quickly sends it to the user's device, where it decompresses the data and converts it into a displayable format.

[1663] Input: Generated original stamp image data

[1664] Output: Stamp data sent to the user's device

[1665] Step 7: User confirmation and stamp sending

[1666] The user checks the generated stamp and sends it in the chat.

[1667] Specific operation: The user visually confirms the generated stamp on the chat screen of the device and presses the "Send" button. The stamp is added to the chat log.

[1668] Input: Stamp data displayed on the terminal

[1669] Output: Stamp sent on the chat screen

[1670] (Application example 2)

[1671] 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."

[1672] In conventional chat systems, users had to manually select appropriate stamps based on their emotions and message content, making it difficult to communicate quickly and effectively. It was also difficult to automatically generate original content that accurately reflected emotions, making communication with users tend to be uniform and mechanical. In particular, in customer support, there was a need for a way to quickly and accurately convey users' emotions, such as dissatisfaction or joy.

[1673] 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.

[1674] In this invention, the server includes means for acquiring a message based on a user's input, means for transmitting the acquired message to the server, means for analyzing the message in the server and extracting at least one keyword, means for determining stamp design requirements based on the extracted keyword and emotion information, means for generating a new stamp based on the determined design requirements, means for transmitting the generated stamp to the user's terminal, means for displaying the transmitted stamp on a chat screen, means for recognizing the user's emotion, and means for generating an original stamp based on the recognized emotion. This makes it possible to automatically generate and transmit a stamp that is optimal for the message and emotion input by the user, thereby achieving fast and effective communication.

[1675] "User input" refers to messages or commands sent by a user via a keyboard or touchscreen, such as in a chat system.

[1676] The "means for obtaining a message" refers to hardware or software that has the function of extracting a message input by a user and passing it on to subsequent processing.

[1677] A "server" is a computer system that processes data and generates stamps via a network.

[1678] The "means for analyzing a message" refers to hardware or software that has the function of using natural language processing technology to understand a user's message and structurally divide its contents.

[1679] "Keyword extraction methods" refer to algorithms and techniques used to extract important words and phrases from the analysis results.

[1680] "Emotion information" refers to data that expresses the emotions contained in a user's message in numerical values ​​or categories.

[1681] "Stamp design requirements" are the standards or specifications that determine the appearance and content of the stamp to be generated.

[1682] "Means for generating new stickers" refers to generative AI models or technologies capable of creating images or animations based on determined design requirements.

[1683] "Means for transmitting stamps" refers to the communication protocols and techniques used to transmit the generated stamps to the user's terminal.

[1684] The "means for displaying on the chat screen" refers to software having a function for displaying the sent stamp on the chat application so that the user can check it.

[1685] "Means for recognizing emotions" refers to algorithms and technologies that estimate emotions from user input, facial expressions, etc., and output them as data.

[1686] "Means for generating original stamps" refers to technology or systems that allow for the creation of new stamps on the spot based on the user's emotions or keywords.

[1687] This invention relates to a system for enhancing communication with users in customer support for online shopping sites. Specifically, it is a system that automatically generates original stamps in response to users' messages and responds in a way that best suits their emotions.

[1688] System configuration

[1689] 1. Get user messages

[1690] Users input messages through the chat system, which are displayed on their terminals and sent to the server.

[1691] 2. Message Analysis and Emotion Recognition

[1692] The server analyzes the received message using natural language processing technology (e.g., TextBlob). The analysis includes tokenizing the sentence, parsing the syntax, and sentiment analysis. During this process, an emotion engine is activated to recognize the user's emotions and extract emotional information such as joy, anger, or dissatisfaction from the message.

[1693] 3. Keyword extraction and intent estimation

[1694] The server extracts key keywords from the analysis results and infers the user's intention. For example, from the message "Product delivery is delayed," the keywords "delivery" and "delay" are extracted, and the emotion engine recognizes dissatisfaction.

[1695] 4. Determine stamp requirements

[1696] The server determines the design requirements for a stamp based on the estimated intent and emotion information, such as the text "I'm sorry," a simple background, and a troubled face.

[1697] 5. Stamp generation

[1698] The server uses a generative AI model (e.g., Generative Adversarial Networks (GANs)) to generate original stamps based on the determined design requirements. The generated stamps are immediately prepared as binary data.

[1699] 6. Sending and displaying stamps

[1700] The generated stamp is sent to the user's device and displayed on the chat screen. The user checks the stamp, and if there are no problems, they can send it again to complete the communication.

[1701] Specific examples

[1702] For example, if a user enters the message "The delivery of the product is delayed," the system will act as follows:

[1703] A message saying "The delivery of the product is delayed" is sent from the terminal to the server.

[1704] The server analyzes the message and extracts the keywords "delivery" and "delay."

[1705] The emotion engine recognizes "dissatisfaction" from the message.

[1706] The server determines the design requirements for the stamp and generates a stamp containing the text "Sorry," a simple background, and a troubled facial expression.

[1707] The server sends the generated stamp to the terminal.

[1708] The device displays the stamp on the chat screen, and the user can check it and send it.

[1709] Prompt Sentence Examples

[1710] User message: "Item delivery is delayed"

[1711] Produced stamp: A stamp containing the text "Sorry"

[1712] Emotion: "Anger"

[1713] Background: "Simple"

[1714] Expression: "worried"

[1715] Through the above process, users can always use stamps that best suit the conversation and emotions they are feeling at the time, realizing a system that allows for smoother and more effective communication.

[1716] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1717] Step 1:

[1718] Users input messages through the chat system, which are displayed on the terminal and simultaneously sent to the server.

[1719] Input: A message entered by the user (e.g., "Your delivery is delayed.")

[1720] Output: Message sent from terminal to server

[1721] Step 2:

[1722] The server analyzes the received message, using natural language processing techniques (e.g., TextBlob) to tokenize the sentences, parse them syntactically, and analyze their sentiment, thereby understanding the message and extracting key keywords and sentiment information.

[1723] Input: User message sent from the terminal

[1724] Data processing: sentence tokenization, syntactic analysis, sentiment analysis

[1725] Output: Key keywords (e.g., "Delivery" and "Delay") and sentiment information (e.g., "Dissatisfied")

[1726] Step 3:

[1727] The server infers the user's intention based on the extracted keywords and emotional information. Based on the inferred intention, the design requirements for the stamp are determined, including the text to be displayed, the background, and the facial expression.

[1728] Input: Key keywords (e.g., "Delivery" or "Delay") and sentiment information (e.g., "Dissatisfied")

[1729] Data processing: Intent estimation and design requirement determination

[1730] Output: Sticker design requirements (e.g. "Sorry" text, simple background, worried face expression)

[1731] Step 4:

[1732] The server uses a generative AI model (e.g., Generative Adversarial Networks (GANs)) to generate original stamps based on the determined design requirements. The stamps are generated as image files and used for subsequent processing.

[1733] Input: Stamp design requirements

[1734] Data processing: Image generation using generative AI models

[1735] Output: Generated original stamp (e.g. stamp image file)

[1736] Step 5:

[1737] The server sends the generated stamp to the user's terminal, and transfers the stamp data to the terminal using a transmission protocol.

[1738] Input: Generated original stamp

[1739] Data processing: data encoding and transmission

[1740] Output: Stamp data sent to the terminal

[1741] Step 6:

[1742] The device displays the received stamps on the chat screen. The user can check the stamps and send them further to the chat if necessary, completing the communication.

[1743] Input: Stamp data sent to the terminal

[1744] Data processing: Decoding and display

[1745] Output: Stamp displayed on the chat screen

[1746] These processing steps automatically generate stamps that best suit the user's message and emotions, enabling fast and effective communication.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] 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.

[1751] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1752] 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.

[1753] 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).

[1754] 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.

[1755] 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."

[1756] 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.

[1757] 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).

[1758] 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.

[1759] 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.

[1760] 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.

[1761] 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.

[1762] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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 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.

[1763] 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.

[1764] 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.

[1765] 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.

[1766] 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.

[1767] 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.

[1768] The following is further disclosed regarding the above embodiment.

[1769] (Claim 1)

[1770] means for obtaining a message based on user input;

[1771] means for transmitting the retrieved messages to a server;

[1772] means for analyzing the message at a server and extracting at least one keyword;

[1773] a means for determining design requirements for a stamp based on the extracted keywords;

[1774] means for generating new stamps based on the determined design requirements;

[1775] means for transmitting the generated stamp to a user's terminal;

[1776] A means to display the sent stamp on the chat screen,

[1777] A system including:

[1778] (Claim 2)

[1779] 2. The system according to claim 1, wherein natural language processing techniques are used to analyze the message.

[1780] (Claim 3)

[1781] 10. The system of claim 1, wherein image generation techniques are used to generate the stamps.

[1782] "Example 1"

[1783] (Claim 1)

[1784] means for obtaining information based on user input;

[1785] means for transmitting the acquired information to a server;

[1786] A means for analyzing the information in a server and extracting at least one keyword;

[1787] A means for determining design requirements based on the extracted keywords;

[1788] means for generating new images based on the determined design requirements;

[1789] means for transmitting the generated image to a user device;

[1790] means for displaying the transmitted image on a display screen;

[1791] A system including:

[1792] (Claim 2)

[1793] 2. The system according to claim 1, wherein natural language processing techniques are used to analyze the information.

[1794] (Claim 3)

[1795] The system of claim 1, wherein a generation technique is used to generate the image.

[1796] "Application Example 1"

[1797] (Claim 1)

[1798] means for obtaining a message based on user input;

[1799] means for transmitting the retrieved messages to a server;

[1800] means for analyzing the message at a server and extracting at least one keyword;

[1801] a means for determining design requirements for a stamp based on the extracted keywords;

[1802] means for generating new stamps based on the determined design requirements;

[1803] means for transmitting the generated stamp to a user's terminal;

[1804] A means to display the sent stamp on the chat screen,

[1805] A means for generating stamps and reaction images in response to user messages and efficiently responding to customers in a customer support chat application;

[1806] A system including:

[1807] (Claim 2)

[1808] 2. The system according to claim 1, wherein natural language processing techniques are used to analyze the message.

[1809] (Claim 3)

[1810] The system of claim 1, characterized in that a generative AI model is used to generate the stamps and reaction images.

[1811] "Example 2: Combining Emotion Engines"

[1812] (Claim 1)

[1813] means for obtaining a message based on user input;

[1814] means for transmitting the retrieved message to a server via a communication network;

[1815] a means for analyzing the message in a server using natural language processing technology and extracting at least one keyword;

[1816] a means for determining design requirements for stamps based on the extracted keywords and the emotion information analyzed by the emotion engine;

[1817] a means for using a generative AI model to generate new stamps based on the determined design requirements;

[1818] means for transmitting the generated stamp to a user's terminal;

[1819] A means to display the sent stamp on the chat screen,

[1820] A system including:

[1821] (Claim 2)

[1822] 2. The system according to claim 1, wherein natural language processing technology is used to analyze the message, and emotion recognition is performed by an emotion engine.

[1823] (Claim 3)

[1824] The system of claim 1, wherein image generation techniques such as Generative Adversarial Networks (GANs) and Style Transfer are used to generate the stamps.

[1825] "Application example 2 when combining emotion engines"

[1826] (Claim 1)

[1827] means for obtaining a message based on user input;

[1828] means for transmitting the retrieved messages to a server;

[1829] means for analyzing the message at a server and extracting at least one keyword;

[1830] a means for determining design requirements for stamps based on the extracted keywords and emotion information;

[1831] means for generating new stamps based on the determined design requirements;

[1832] means for transmitting the generated stamp to a user's terminal;

[1833] A means to display the sent stamp on the chat screen,

[1834] means for recognizing a user's emotion;

[1835] A means for generating an original stamp based on the recognized emotion;

[1836] A system including:

[1837] (Claim 2)

[1838] 2. The system according to claim 1, wherein natural language processing techniques are used to analyze the message.

[1839] (Claim 3)

[1840] The system of claim 1, wherein the stamps are generated using a generative AI model. [Explanation of symbols]

[1841] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for obtaining a message based on user input; means for transmitting the retrieved messages to a server; means for analyzing the message at a server and extracting at least one keyword; a means for determining design requirements for a stamp based on the extracted keywords; means for generating new stamps based on the determined design requirements; means for transmitting the generated stamp to a user's terminal; A means to display the sent stamp on the chat screen, A system including:

2. 2. The system of claim 1, wherein natural language processing techniques are used to analyze the message.

3. The system of claim 1, wherein image generation techniques are used to generate the stamps.

Images