System

Abstract

A system is provided.SOLUTION: The system includes a means for analyzing a message received from a user, a means for generating a plurality of illustrations and a one word message on the basis of an analysis result, a means for displaying a plurality of generated candidates so as to be selected by the user, and a means for transmitting the selected stamp.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Messaging applications play an important role in modern communication. However, while there are many existing stickers, they are limited to popular words and common phrases, making it difficult to find stickers that match specific situations or individual emotions. Furthermore, creating original stickers is not easy due to the high effort and technical barriers involved. This creates a challenge in that users have limited options for enjoying communication. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides the following means. We propose a system that includes a means for analyzing messages received from users, a means for generating multiple illustrations and short messages based on the analysis results, a means for displaying the generated candidates so that the user can select from them, and a means for sending the selected stamps. This system allows users to easily generate, select, and send original stamps that are optimal for specific occasions, broadening the scope of communication and making it more enjoyable.

[0006] "User" means an individual or group that uses the System to send messages and select and send stamps.

[0007] A "message" is text data that a user inputs and sends for communication purposes.

[0008] "Analysis" refers to the process of analyzing the content of the received message using natural language processing and extracting keywords and emotional information.

[0009] An "illustration" is a picture or drawing created to visually express a message or emotion.

[0010] A "one-line message" is a short piece of text that accompanies an illustration and serves to complement the meaning and emotion of the message.

[0011] "Generation" is the process of creating new illustrations or short messages based on the analysis results.

[0012] "Candidates" refer to combinations of multiple illustrations and short messages generated by the system, and represent options that users can select from.

[0013] "Display" refers to visually showing the generated stamp candidates to the user.

[0014] "Selection" refers to the action of the user selecting a specific stamp from the displayed stamp candidates.

[0015] "Send" is the act of sending data to convey the selected stamp to the other party. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] MODE FOR CARRYING OUT THE INVENTION

[0038] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. This system has the function of analyzing the user's message and generating an appropriate illustration and a short message to accompany it. Below, we will explain the operation of the system in detail from the perspectives of the server, terminal, and user.

[0039] Server Processing

[0040] 1. Receiving and parsing messages

[0041] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) to extract keywords and emotional information. For example, if a message is received saying "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted.

[0042] 2. Creating illustrations and short messages

[0043] The server generates an appropriate illustration and message based on the extracted keywords and emotional information. The generation is done using artificial intelligence (AI), and multiple candidates are created. For example, for the keyword "I'm getting late," a stamp is generated that combines an illustration of a sleeping cat with the message "I'm late, but I'm doing my best!"

[0044] 3. Submit your stamp suggestions

[0045] The server sends the generated stamp candidates to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation.

[0046] Terminal handling

[0047] 1. Receiving and displaying stamp candidates

[0048] The terminal receives the stamp candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface.

[0049] 2. Select and send stamps

[0050] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[0051] User operations

[0052] 1. Enter your message

[0053] The user opens the LINE application, types a message, and presses the send button. For example, they might type, "I'm going to be late today..."

[0054] 2. Select a stamp

[0055] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[0056] 3. Sending stamps

[0057] Once you have completed your selection, the stamp will appear on the other person's LINE chat screen.

[0058] Specific examples

[0059] For example, if a user sends a message saying, "I think I'll be late today...", the server analyzes this message and extracts the keyword "I'll be late". It then generates an illustration of a "sleeping cat" and a message saying, "I'm late, but I'll do my best!" This stamp is presented to the user along with other options such as "A rabbit looking at the clock" (Sorry I'm late!). The user selects "sleeping cat" and sends the stamp, and the original stamp is displayed to the recipient.

[0060] As described above, the present invention is a system that can be operated intuitively by the user and that makes communication more enjoyable and lively by providing original stamps suited to specific situations.

[0061] The processing flow will be explained below.

[0062] Program processing steps

[0063] User message entry and sending

[0064] Step 1:

[0065] The user opens the LINE application and types a message.

[0066] For example, a user types "I'm going to be late today..." and presses the send button.

[0067] Receiving and parsing messages

[0068] Step 2:

[0069] The terminal sends the message data (text, user ID, timestamp) entered by the user to the server.

[0070] Step 3:

[0071] The server analyzes the received message data.

[0072] Natural language processing (NLP) techniques are used to extract keywords (e.g., "slow") and emotional information (e.g., "fatigue") from messages.

[0073] Generate illustrations and short messages

[0074] Step 4:

[0075] The server's AI generates related illustrations and short messages based on the extracted keywords and emotional information.

[0076] For example, for the keyword "getting late," a stamp is generated that combines an illustration of a sleeping cat with a one-line message: "It's late, but do your best!"

[0077] Submit a stamp suggestion

[0078] Step 5:

[0079] The server organizes the generated stamp candidates and transmits them to the user's terminal.

[0080] For example, some possible phrases include "The cat is sleeping" (It's late, but do your best!) and "The rabbit is looking at the clock" (Sorry I'm late!).

[0081] Displaying and selecting stamp candidates

[0082] Step 6:

[0083] The terminal visually displays the received stamp candidates to the user.

[0084] To arrange stamp candidates on an interface so that the user can easily understand them.

[0085] Step 7:

[0086] The user selects the stamp they like by tapping on it from the displayed stamp candidates.

[0087] For example, select the "Cat Sleeping" stamp and press the send button.

[0088] Send selected stamps

[0089] Step 8:

[0090] The terminal sends the stamp data (stamp ID, user ID, timestamp) selected by the user to the server.

[0091] Step 9:

[0092] Based on the stamp selection data received by the server, the selected stamp is processed and information on the sender and destination is recorded.

[0093] Step 10:

[0094] The server transmits the stamp data to the other terminal.

[0095] Displaying stamps

[0096] Step 11:

[0097] The terminal on the other side displays the stamp data received from the server.

[0098] For example, the "Cat is sleeping" stamp (slow but good luck!) will appear on the other person's LINE chat screen.

[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] Conventional messaging applications require users to manually select stamps, which can be time-consuming and time-consuming to find the appropriate stamp. It can also be difficult to obtain the optimal stamp based on the content of a user's message, which can disrupt smooth communication. The purpose of this invention is to simplify user operations and improve the quality of communication by automatically generating and presenting the optimal stamp 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 analyzing a message received from a user, means for generating multiple illustrations and a short message based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, means for generating an illustration and a short message using a generative AI model, and means for inputting the illustration and the short message into the generative AI model based on a prompt sentence. This allows the server to automatically generate the optimal stamp based on the content of the user's message, allowing the user to easily select and send the stamp.

[0104] The "means for analyzing messages received from users" is a function for analyzing messages sent by users and extracting information such as meaning and emotion.

[0105] "Means for generating multiple illustrations and short messages based on the analysis results" refers to a function that uses AI to create multiple illustrations and accompanying short messages based on the information obtained through the analysis.

[0106] The "means for displaying a list of multiple candidates that can be selected by the user" is a function that displays multiple stamp candidates sent from the server on the terminal screen, allowing the user to select from among them.

[0107] The "means for transmitting the selected stamp" is a function for transmitting the stamp selected by the user to the other party's terminal.

[0108] A "generative AI model" is a model trained using artificial intelligence algorithms that generate illustrations and messages based on specific prompts.

[0109] The "means for inputting into the generative AI model based on the prompt sentence" is a function for inputting into the AI ​​model based on extracted keywords and emotional information, and generating an illustration and a short message as a result.

[0110] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. This system analyzes the user's message and generates appropriate illustrations and short messages, facilitating smooth communication.

[0111] Server Processing

[0112] The server receives messages sent by users. These received messages are analyzed using natural language processing (NLP) tools. For example, Python libraries such as NLTK and spaCy are used. As a result of the analysis, keywords and emotional information are extracted from the message. For example, from the message "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted.

[0113] The server then uses a generative AI model, based on the extracted keywords and emotional information, to generate an illustration and a short message. This generative AI model utilizes a pre-trained algorithm, such as GPT-3, and the prompt is input into the generative AI model.

[0114] Example prompt sentence:

[0115] User message: "Looks like I'm going to be late today..."

[0116] Keywords: ["running late", "tired"]

[0117] Emotion: ["fatigue"]

[0118] Generate an illustration and a short message.

[0119] Based on this prompt, the generative AI model generates multiple combinations of illustrations and one-line messages. For example, for the keyword "I'm getting late," it generates an illustration of a "sleeping cat" and the one-line message "It's late, but do your best!"

[0120] The generated stamp candidates are sent from the server to the user's device via the server's API, and multiple candidates are presented to the user.

[0121] Terminal handling

[0122] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The terminal provides an intuitive and easy-to-use GUI (Graphical User Interface). The user can then select the stamp they like from the displayed candidates.

[0123] When a user selects a stamp, the selection information is sent from the device to the server. This information includes the selected stamp ID and the user ID. Finally, the selected stamp is sent to the other device and displayed on the LINE chat screen.

[0124] User operations

[0125] The user opens the LINE application, types a message, and sends it. For example, they type "I'm going to be late today..." and press the send button. The server then displays multiple stamp candidates on the user's device. The user selects the stamp they like by tapping it. For example, if the user selects the "sleeping cat" stamp, that stamp will be sent to the other person and will appear on their LINE chat screen.

[0126] In this way, the system of the present invention can be operated intuitively by the user and makes communication more enjoyable and lively by providing original stamps suitable for specific situations.

[0127] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0128] Step 1:

[0129] Receiving messages (server)

[0130] The server receives a message sent by the user. This message also includes the user ID and message ID. The input is the text message entered by the user in the LINE application, and the output is structured data for storing this message in a database. Specifically, the server sends the received message to an API endpoint and stores it in the database.

[0131] Step 2:

[0132] Message analysis (server)

[0133] The server analyzes the received message. Natural language processing (NLP) tools are used for the analysis. The input is the received message text, and the output is extracted keywords and emotional information. For example, from the message "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted. Specifically, keywords and emotional information are extracted from the text using Python libraries such as NLTK and spaCy.

[0134] Step 3:

[0135] Prompt statement generation (server)

[0136] The server generates a prompt sentence to be input into the generative AI model based on the extracted keywords and emotional information. The input is the extracted keywords and emotional information, and the output is a prompt sentence suitable for the generative AI model. Specifically, it combines the keyword "I'm going to be late" with the emotional information "fatigue" to generate the prompt sentence: "User message: "I'm going to be late today..." Keywords: ["I'm going to be late", "Tired"] Emotion: ["Fatigue"] Generate an illustration and a short message."

[0137] Step 4:

[0138] Illustration and message generation (server)

[0139] The server inputs the generated prompt into a generative AI model to generate an illustration and a one-line message. The input is the generated prompt, and the output is a combination of multiple illustrations and one-line messages generated by the AI ​​model. Specifically, the prompt is input into a generative AI model such as GPT-3, generating an illustration of a "sleeping cat" and a message such as "You're slow, but keep trying!"

[0140] Step 5:

[0141] Sending stamp candidates (server)

[0142] The server sends the generated stamp candidates to the user's device. The input is multiple stamp candidates generated by the AI ​​model, and the output is the stamp candidates sent to the user's device. Specifically, the generated stamp candidates are sent to the user's device via API.

[0143] Step 6:

[0144] Receiving and displaying stamp candidates (device)

[0145] The terminal receives the stamp candidates sent from the server and displays them to the user. The input is the stamp candidates sent from the server, and the output is a list of stamp candidates displayed on the terminal. Specifically, the terminal receives the stamp candidates and displays them to the user using an intuitive GUI.

[0146] Step 7:

[0147] Stamp Selection (User)

[0148] The user selects the stamp they like from the displayed stamp candidates. The input is the stamp candidates visually confirmed by the user, and the output is the ID of the stamp selected by the user. Specifically, the user taps on the stamp they like to select it.

[0149] Step 8:

[0150] Send stamp selection information (device)

[0151] The terminal sends the stamp information selected by the user to the server. The input is the ID of the stamp selected by the user, and the output is the stamp selection information sent to the server. Specifically, the terminal sends the ID of the selected stamp to the server's API.

[0152] Step 9:

[0153] Sending stamps (server)

[0154] The server sends the stamp selected by the user to the other device. The input is the ID of the selected stamp and the user ID of the recipient, and the output is the stamp image sent to the other device. Specifically, the image data of the selected stamp is sent to the other device via API.

[0155] Step 10:

[0156] Displaying stamps (on the recipient's device)

[0157] The other device will display the received stamp on the LINE chat screen. The input is the received stamp image data, and the output is the stamp image displayed on the LINE chat screen. The specific operation is to display the received image data within the LINE application.

[0158] In this way, through a series of steps, the most suitable stamp based on the user's message is automatically generated, and the user can select and send it.

[0159] (Application example 1)

[0160] 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."

[0161] In modern messaging applications, users must manually select stickers to appropriately express their emotions and situations. This can be time-consuming and difficult to find. Furthermore, when there are too many sticker options, users can become overwhelmed. Furthermore, there is no mechanism for providing stickers that can quickly and accurately respond to a user's message. To solve these problems, a system is needed that can analyze a user's messages in real time, automatically generate appropriate stickers based on the analysis results, and present them to the user.

[0162] 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.

[0163] In this invention, the server includes means for analyzing messages received from users, means for generating multiple illustrations and short messages based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, and means for presenting the generated stamp candidates to the user in order of priority, thereby enabling the user to quickly and easily select and send the stamp that best suits the message content.

[0164] A "user" is a person who uses the system.

[0165] A "message" is text information sent by a user through a communication application.

[0166] The "analysis means" is a function that uses natural language processing technology to analyze messages received from users and extract keywords and emotional information.

[0167] An "illustration" is an image that visually expresses a user's emotions or situation.

[0168] A "one-line message" is a short piece of text that explains an emotion or situation in combination with an illustration.

[0169] "Means of generation" is a function that creates stamps by combining illustrations and short messages based on the analysis results.

[0170] The "display means" is a function that provides an interface that visually presents a plurality of candidates from among the generated stamps to the user and allows the user to select one.

[0171] The "transmission means" is a function for transmitting the stamp selected by the user to the recipient.

[0172] "Stamp candidates" are multiple stamp options that are generated based on the user's analysis of the message and presented to the user for selection.

[0173] The "order of priority" is a criterion for displaying the generated stamp candidates in the most appropriate order based on the content of the user's message and the situation.

[0174] This invention is a system that analyzes messages sent by users through messaging applications and generates and presents appropriate illustrations and short messages (stamps) based on the analysis results. Users can easily communicate by selecting from the presented stamp candidates.

[0175] Server Processing

[0176] Receiving and parsing messages

[0177] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) techniques to extract keywords and emotional information. The specific software used is the OpenAI API.

[0178] Generate illustrations and short messages

[0179] The server generates an appropriate illustration and a short message based on the extracted keywords and emotional information. The generation is done using artificial intelligence (AI), and multiple candidates are created. For example, if a user sends a message saying, "I'm going to be late today...", the keyword "I'm going to be late" is extracted, and a stamp is generated that combines an illustration of a sleeping cat with the message, "I'm late, but I'll do my best!"

[0180] Submit a stamp suggestion

[0181] The server sends the generated stamp candidates to the user's device. The stamp candidates are prioritized based on the user's message content and emotions, allowing the user to select the stamp that best suits the situation.

[0182] Terminal handling

[0183] Receiving and displaying stamp suggestions

[0184] The terminal receives the stamp candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface.

[0185] Select and send stamps

[0186] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp's ID, the user ID, and a timestamp.

[0187] User operations

[0188] Enter your message

[0189] A user opens a chat application, types a message, and hits send, for example, "I'm going to be late today..."

[0190] Select a stamp

[0191] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[0192] Sending stamps

[0193] Once you have completed your selection, the stamp will appear on the other person's chat screen.

[0194] Prompt Sentence Examples

[0195] Extract sentiment and keywords from the following messages:

[0196] Message: "Looks like I'll be late today..."

[0197] This system is expected to enable users to intuitively and quickly select and send stamps that suit the content of their messages, facilitating smooth communication.

[0198] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0199] Step 1:

[0200] The server gets the message received from the user. The input is the message sent by the user and the output is the received message data, which is kept for the next analysis step.

[0201] Step 2:

[0202] The server analyzes the received message using natural language processing technology. The input is the message data from step 1, and the output is the analyzed keywords and emotional information. The server uses OpenAI's API to extract important keywords and emotions from the message content. This analyzed information becomes the basic data for generating stamps.

[0203] Step 3:

[0204] The server generates multiple illustrations and short messages based on the analysis results. The input is the analysis information from step 2, and the output is the generated stamp candidates. The server uses an artificial intelligence model to generate multiple stamps that combine illustrations and short messages that match the extracted keywords and emotional information.

[0205] Step 4:

[0206] The server sends the generated stamp candidates to the terminal. The input is the stamp candidates from step 3, and the output is the stamp data sent to the terminal. The stamp candidates are sorted based on priority and presented in a format that makes it easy for the user to select.

[0207] Step 5:

[0208] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The input is the stamp data from step 4, and the output is the display to the user. The terminal provides an intuitive and easy-to-use user interface and presents multiple stamp candidates to the user.

[0209] Step 6:

[0210] The user selects the stamp they like from the displayed stamp candidates. The input is the stamp candidates displayed in step 5, and the output is the selected stamp information. The user selects a stamp with simple operations such as tapping or clicking, and the information is stored on the device.

[0211] Step 7:

[0212] The terminal sends the stamp selected by the user to the server. The input is the stamp information selected in step 6, and the output is the stamp information sent to the server. This information includes the stamp ID, user ID, timestamp, etc.

[0213] Step 8:

[0214] The server finally sends the selected stamp to the recipient. The input is the stamp information from step 7, and the output is the stamp sent to the recipient. This causes the selected stamp to be displayed on the recipient's chat screen.

[0215] The above processing steps realize a system in which appropriate stamps are automatically generated based on the user's message, and the user can easily select and send them.

[0216] 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.

[0217] MODE FOR CARRYING OUT THE INVENTION

[0218] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. Furthermore, by incorporating an emotion engine, the system enhances its functionality of recognizing the user's emotions and providing stamps that correspond to them. The system analyzes the user's message, extracts keywords containing emotional information, and generates an appropriate illustration and accompanying message. The operation of the system is specifically described below from the perspectives of the server, terminal, and user.

[0219] Server Processing

[0220] 1. Receiving and parsing messages

[0221] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) technology to extract keywords and emotional information. An emotion engine is used to recognize emotional information (e.g., "joy," "sadness," "anger," etc.) from the messages. For example, if a message is received saying, "I'm going to be late today...," keywords such as "I'm going to be late" and "I'm tired" and the emotional information of "fatigue" are extracted.

[0222] 2. Creating illustrations and short messages

[0223] The server generates related illustrations and short messages based on the extracted keywords and emotional information. This generation uses artificial intelligence (AI) to create multiple stamp candidates. The priority of the stamp candidates to be generated is determined based on the recognition results of the emotion engine. For example, for the emotion "tired," a stamp combining an illustration of a "sleeping cat" and a short message such as "It's late, but do your best!" is generated.

[0224] 3. Submit your stamp suggestions

[0225] The server organizes the generated stamp candidates and sends them to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation. The most suitable candidates are displayed at the top based on a priority order based on emotional information.

[0226] Terminal handling

[0227] 1. Receiving and displaying stamp candidates

[0228] The device receives the sticker candidates sent from the server and visually displays them to the user. The display method is provided with an intuitive and easy-to-select interface. The stickers are prioritized based on emotion, so the most suitable ones are displayed first.

[0229] 2. Select and send stamps

[0230] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[0231] User operations

[0232] 1. Enter your message

[0233] The user opens the LINE application, types a message, and presses the send button. For example, they might type, "I'm going to be late today..."

[0234] 2. Select a stamp

[0235] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[0236] 3. Sending stamps

[0237] Once you have completed your selection, the stamp will appear on the other person's LINE chat screen.

[0238] Specific examples

[0239] For example, if a user sends a message saying, "I'm going to be late today...", the server analyzes the message and extracts keywords such as "I'm going to be late" and "I'm tired" as well as the emotional information of "fatigue".The server then generates an illustration of a "sleeping cat" and a message saying, "I'm late, but keep trying!" and presents them to the user along with other options.The user selects "sleeping cat" from the list and sends it, and the original stamp is displayed to the recipient.

[0240] As described above, the present invention is a system that can be intuitively operated by the user and makes communication more enjoyable and lively by providing original stamps that are best suited to specific situations and emotions.

[0241] The processing flow will be explained below.

[0242] MODE FOR CARRYING OUT THE INVENTION (PROCESSING STEPS)

[0243] User message entry and sending

[0244] Step 1:

[0245] The user opens the messaging application and types a message.

[0246] For example, a user types "I'm going to be late today..." and presses the send button.

[0247] Receiving and parsing messages

[0248] Step 2:

[0249] The terminal sends the message data (text, user ID, timestamp) entered by the user to the server.

[0250] Step 3:

[0251] The server analyzes the received message data.

[0252] Natural language processing (NLP) techniques are used to analyze messages and extract keywords (e.g., "slow") and emotional information (e.g., "fatigue").

[0253] Step 4:

[0254] The server uses an emotion engine to recognize emotion information from the extracted keywords and message content.

[0255] For example, the emotional information "fatigue" is recognized from "I'm going to be late today..."

[0256] Generate illustrations and short messages

[0257] Step 5:

[0258] The server's AI generates an appropriate illustration and a short message based on the extracted keywords and recognized emotional information.

[0259] For example, for the keyword "getting late" and the emotional information "fatigue," a stamp is generated that combines an illustration of a "sleeping cat" with a one-line message such as "It's late, but do your best!"

[0260] Step 6:

[0261] The server creates multiple stamp candidates and organizes them by prioritizing them based on emotional information.

[0262] For example, create suggestions such as "The cat is sleeping" (It's late, but do your best!) and "The rabbit is looking at the clock" (Sorry I'm late!) and prioritize them.

[0263] Submit a stamp suggestion

[0264] Step 7:

[0265] The server transmits the generated stamp candidates to the terminal.

[0266] Prioritize your search so that the best candidates are displayed at the top.

[0267] Displaying and selecting stamp candidates

[0268] Step 8:

[0269] The terminal visually displays the received stamp candidates to the user.

[0270] For example, the interface displays "A cat is sleeping" and "A rabbit is looking at the clock" in that order.

[0271] Step 9:

[0272] The user selects the stamp they like by tapping on it from the displayed stamp candidates.

[0273] For example, select the "Cat Sleeping" stamp and press the send button.

[0274] Send selected stamps

[0275] Step 10:

[0276] The terminal sends the stamp data (stamp ID, user ID, timestamp) selected by the user to the server.

[0277] Step 11:

[0278] Based on the stamp selection data received by the server, the selected stamp is processed and information on the sender and destination is recorded.

[0279] Step 12:

[0280] The server transmits the stamp data to the other terminal.

[0281] Displaying stamps

[0282] Step 13:

[0283] The terminal on the other side displays the stamp data received from the server.

[0284] For example, the "Cat is sleeping" stamp (slow but good luck!) will appear on the other person's LINE chat screen.

[0285] Example 2

[0286] 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."

[0287] In conventional messaging applications, users had to manually select stickers for messages they sent, making it difficult to quickly provide stickers that were optimal for specific situations or emotions. Furthermore, the lack of sticker suggestions based on the user's emotions made it difficult to make communication more personalized and smooth.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0289] In this invention, the server includes means for analyzing messages received from users and extracting keywords and emotional information, means for generating multiple illustrations and short messages based on the analysis results, means for prioritizing the generated multiple stamp candidates based on the emotional information and displaying them so that the user can select one, and means for transmitting the selected stamp. This makes it possible to automatically generate and provide stamps that are optimal for messages sent by users, thereby realizing more personalized communication.

[0290] A "User" is an individual or entity that sends or receives messages through a messaging application.

[0291] "Receiving" is the act of the server obtaining a message sent by a user.

[0292] A "message" is text information that a user sends through a messaging application.

[0293] "Analysis" is the process of breaking down the content of a received message and extracting meaning, keywords, and emotional information.

[0294] "Keywords" are words or phrases that carry significant meaning in a message.

[0295] "Emotion information" is data that represents the user's emotions extracted from the message.

[0296] "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language.

[0297] An "emotion engine" is software or hardware that analyzes and recognizes a user's emotions from the contents of a message.

[0298] "Illustration" refers to an image or picture used as a stamp.

[0299] A "one-line message" is a short text message that accompanies an illustration.

[0300] An "artificial intelligence model" is a computational model that learns from data and automates specific tasks.

[0301] "Stamp candidates" are multiple stamp options presented to the user.

[0302] "Priority" refers to the order in which stamp candidates are arranged based on emotion information.

[0303] A "selectable display" is an interface that allows the user to select one stamp from among multiple stamp candidates.

[0304] A "selected stamp" is a specific stamp that the user selects from among multiple stamp candidates.

[0305] "Send" is the act of sending the selected stamp from the server to the recipient's terminal.

[0306] A "system" is a set of hardware and software that integrates these means to provide a specific function.

[0307] MODE FOR CARRYING OUT THE INVENTION

[0308] The system of this invention automatically generates optimal stamps based on messages sent by users in a messaging application, allowing users to select and send them. Furthermore, by using an emotion engine, the system recognizes the user's emotions and provides corresponding stamps. The configuration and operation of this system are described in detail below.

[0309] Server Processing

[0310] 1. Receiving and parsing messages

[0311] The server receives messages sent by users. The messaging application used can be a commonly used messaging application, such as LINE or SNS Messenger.

[0312] Received messages are analyzed using natural language processing (NLP) technology. During this analysis, keywords and emotional information are extracted. By using an emotion engine, the system can recognize the user's emotions into categories such as "happiness," "sadness," and "anger."

[0313] Examples:

[0314] If a user sends a message saying "I'm going to be late today...", the server extracts keywords such as "I'm going to be late" and "I'm tired" as well as emotion information such as "fatigue".

[0315] 2. Creating illustrations and short messages

[0316] The server generates related illustrations and short messages based on the extracted keywords and emotional information, using an artificial intelligence (AI) model, specifically a generative AI model.

[0317] Based on the recognition results of the emotion engine, the priority of the stamp candidates to be generated is determined.

[0318] Examples:

[0319] For the emotion "tired," a stamp is generated that combines an illustration of a "sleeping cat" with a one-line message such as "It's late, but do your best!"

[0320] 3. Submit your stamp suggestions

[0321] The server sends the generated stamp candidates to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation. The most suitable candidates are displayed at the top based on a priority order based on emotion information.

[0322] Terminal handling

[0323] 1. Receiving and displaying stamp candidates

[0324] The device receives the sticker candidates sent from the server and visually displays them to the user. The display method is provided with an intuitive and easy-to-select interface. The stickers are prioritized based on emotion, so the most suitable ones are displayed first.

[0325] Examples:

[0326] The "sleeping cat" stamp will appear first on the device screen, followed by another stamp.

[0327] 2. Select and send stamps

[0328] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[0329] User operations

[0330] 1. Enter your message

[0331] The user opens the messaging application, types a message, and presses the send button.

[0332] Examples:

[0333] Type "I'm going to be late today..." and send it.

[0334] 2. Select a stamp

[0335] Stamp candidates sent from the server are displayed on the device, and the user can tap to select the stamp they like.

[0336] Examples:

[0337] Select the "Sleeping cat" stamp.

[0338] 3. Sending stamps

[0339] Once you have completed your selection, the stamp will appear on the other person's chat screen.

[0340] Prompt Sentence Examples

[0341] The following prompts can be fed into the generative AI model to explain the system's detailed behavior:

[0342] Messages sent by users are analyzed using natural language processing technology, and emotional information is extracted using an emotion engine. Based on this emotional information, AI is used to generate related illustrations and short messages. The generated stamp candidates are displayed to the user in a prioritized order, and a system is built that reflects the user's selection.

[0343] Through these steps, the system extracts emotions and keywords from the message entered by the user and provides the most appropriate stamps based on that, thereby realizing a more personalized communication experience.

[0344] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0345] Step 1:

[0346] Receiving messages

[0347] The server receives messages sent by users. The data received from the messaging application (input) is the text message typed by the user. This message data is passed to the server's parsing process (output).

[0348] Specific example of operation: When a user sends a message such as "I'm going to be late today..." in an application, this text data is sent to the server.

[0349] Step 2:

[0350] Message Parsing

[0351] The server analyzes the received message data using natural language processing (NLP) technology. The input is the received message data, and keywords and emotional information are extracted during the analysis process. The output is the extracted keywords and emotional information.

[0352] Specific example of operation: Analyze the message "I think I'll be late today..." and extract the keyword "I'll be late" and the emotional information "fatigue."

[0353] Step 3:

[0354] Generate illustrations and short messages

[0355] The server uses an artificial intelligence (AI) model to generate related illustrations and short messages based on the extracted keywords and emotional information. The input is the extracted keywords and emotional information, and the output is multiple stamp candidates.

[0356] Specific example of operation: In response to the emotional information "fatigue," an AI model is used to generate an illustration of a "sleeping cat" and a one-line message saying "You're slow, but keep trying!"

[0357] Step 4:

[0358] Prioritize and send sticker suggestions

[0359] The server prioritizes the generated stamp candidates based on emotion information and sends them to the user's device. The input is the generated stamp candidates, and the prioritized stamp candidates are sent to the device (output).

[0360] Specific example of operation: The generated "Cat sleeping" stamp is placed at the top, and multiple stamp candidates including it are sent to the user's device.

[0361] Step 5:

[0362] Receiving and displaying stamp suggestions

[0363] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The input is the stamp candidate data sent from the server, and the output is a list of stamp candidates displayed on the user interface.

[0364] Specific example of operation: The "Cat sleeping" stamp will be displayed on the device screen first, followed by other stamps.

[0365] Step 6:

[0366] Select a stamp

[0367] The user selects the stamp they like from the displayed stamp candidates. The input is multiple stamp candidates, and the output is the ID of the stamp selected by the user.

[0368] Specific example of operation: When the user taps the "sleeping cat" stamp, that stamp is selected.

[0369] Step 7:

[0370] Send selected stamps

[0371] The terminal sends the stamp information selected by the user to the server, which receives it and displays the stamp on the other party's chat screen. The input is the selected stamp ID, user ID, and timestamp, and the output is the stamp displayed on the other party's chat screen.

[0372] Specific example of operation: When a user selects the "sleeping cat" stamp, the information is sent to the server and displayed on the other person's chat screen.

[0373] (Application example 2)

[0374] 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."

[0375] Existing messaging applications lack functionality to help users quickly respond appropriately based on their emotions and the content of their messages. Furthermore, it can be time-consuming for users to select the most appropriate content (e.g., movies, music, articles, etc.) based on their emotions, which can lead to a decline in the quality of communication and engagement. This invention solves these problems by providing a function that automatically recommends the most appropriate stickers and content based on the user's message and emotions.

[0376] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a message received from a user, means for generating multiple illustrations and short messages based on the analysis results, means for displaying the multiple generated candidates so that the user can select one, means for sending the selected stamp, and means for recommending content based on the user's message and emotions. This enables the user to quickly receive appropriate stamps and content based on the message and emotions, thereby improving the quality of communication and engagement.

[0377] The "means for analyzing messages received from users" refers to a function that enables the platform to receive messages sent by users and analyze their contents using natural language processing technology.

[0378] The "means for generating multiple illustrations and short messages based on the analysis results" is a function that uses artificial intelligence technology to generate many candidate illustrations and suitable short messages based on the content and emotional information of the analyzed message.

[0379] The "means for displaying a selection from multiple generated candidates to the user" is an interface that displays the many generated stamp candidates on the user's terminal and allows the user to select the appropriate stamp from among them.

[0380] The "means for transmitting the selected stamp" is a function for transmitting the stamp selected by the user to the recipient user.

[0381] "Means for recommending content based on a user's message and emotions" refers to an evaluation and selection function that extracts the content of a user's message and emotional information, and then recommends the most appropriate content, such as movies, music, or articles, that correspond to them.

[0382] The system of the present invention is a content distribution service that automatically generates optimal stamps and content based on a user's message and emotions, allowing the user to select, send, and play them. This system has the functionality to operate on both the server and the user's terminal. The operation of the system will be specifically explained below from the perspectives of the server, the terminal, and the user.

[0383] Server Processing

[0384] 1. Receiving and parsing messages

[0385] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) techniques to extract keywords and emotional information. This analysis is performed using the Google Cloud Natural Language API. An emotional engine (e.g., IBM Watson's Tone Analyzer) is used to recognize emotional information (e.g., "stress," "joy," "sadness," etc.) from the messages.

[0386] 2. Creating illustrations and short messages

[0387] The server generates related illustrations and short messages based on the extracted keywords and emotion information. This generation uses artificial intelligence (AI) technology (e.g., OpenAI's GPT-3 and DALL-E). Based on the recognition results of the emotion engine, the server determines the priority of the sticker candidates to be generated.

[0388] 3. Content Recommendations

[0389] The server has an evaluation and selection function to recommend appropriate content (e.g., movies, music, articles, etc.) based on the corresponding message and emotional information. These contents are organized to prioritize the most appropriate content for the user.

[0390] 4. Submit sticker and content suggestions

[0391] The server organizes the generated stamps and content candidates and sends them to the user's device. By presenting multiple candidates, the user can select the stamps and content that best suit the situation.

[0392] Terminal handling

[0393] 1. Receiving and displaying stamps and content suggestions

[0394] The terminal receives the stamps and content candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface for the display method.

[0395] 2. Select stamps and content, and send and play them

[0396] When a user selects a stamp or content they like, the device sends the selection information to the server, including the stamp ID, content information, user ID, timestamp, etc. The content selected by the user is then played or provided immediately.

[0397] User operations

[0398] 1. Enter your message

[0399] A user opens the application, types a message, and hits send, for example, "I'm feeling very stressed today."

[0400] 2. Select stamps and content

[0401] The stamps and content candidates sent from the server are displayed on the device, and the user can select the stamps or content they like by tapping on them. For example, they can select "Relaxation Music."

[0402] 3. Sending stamps and playing content

[0403] Once the selection is complete, the stamp will appear on the other person's chat screen and the content will be played on the spot.

[0404] Examples of concrete examples and prompts

[0405] For example, if a user sends a message saying, "I'm feeling very stressed today," the server analyzes the message and extracts the keyword "stress" and the emotional information "negative." Potential content, such as relaxation music, nature videos, and soothing articles, are then generated and presented to the user. The user selects "relaxation music" from the list and plays it within the app.

[0406] Example prompt sentence:

[0407] User message: "I'm so stressed today"

[0408] Extracted keywords: ["stress"]

[0409] Extracted sentiment: ["Negative"]

[0410] Generate relevant content suggestions: "Relaxation Music", "Nature Videos", "Soothing Articles"

[0411] The user selects and plays relaxation music.

[0412] As described above, the system of the present invention can be operated intuitively by the user and makes communication more enjoyable and lively by providing stamps and content that are optimal for specific situations and emotions.

[0413] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0414] Step 1:

[0415] Receiving and parsing messages

[0416] The server receives messages sent by users. The received message text is given as input. The server uses natural language processing (NLP) techniques to analyze the message text. This analysis uses the Google Cloud Natural Language API to extract keywords and emotional information. An emotion engine (e.g., IBM Watson's Tone Analyzer) is used to recognize emotional information (e.g., "stress," "joy," "sadness," etc.) from the message. Data containing keywords and emotional information is generated as output.

[0417] Step 2:

[0418] Generate illustrations and short messages

[0419] The server receives the extracted keywords and emotion information as input and generates related illustrations and short messages using artificial intelligence (AI) technology, such as OpenAI's GPT-3 and DALL-E. Based on the recognition results of the emotion engine, the server determines the priority of the stamp candidates to be generated. The output is data containing multiple stamp candidates.

[0420] Step 3:

[0421] Content Recommendations

[0422] The server recommends appropriate content based on the message and emotional information. Extracted keywords and emotional information are given as input. AI technology is used to evaluate and select appropriate content (e.g., movies, music, articles, etc.). The output is data containing multiple content candidates.

[0423] Step 4:

[0424] Submit sticker and content suggestions

[0425] The server organizes the generated stamps and content candidates and sends them to the user's device. The generated stamps and content candidate data are given as input. The sent stamps and content candidates are displayed on the user's device as output.

[0426] Step 5:

[0427] Receive and display stamps and content suggestions

[0428] The terminal receives the stamps and content candidates sent from the server. The data received from the server is given as input. The terminal provides an intuitive and easy-to-select interface for the user, visually displaying the stamps and content candidates. As output, the displayed stamps and content candidates are provided to the user.

[0429] Step 6:

[0430] Selecting, sending, and playing stamps and content

[0431] The user selects the stamps and content they like. The terminal sends the selection information to the server. The input is the stamps and content information selected by the user. The output is the selected stamps displayed on the other party's chat screen and the content is played.

[0432] The above are the specific processing steps and operations of the system program that realizes this application example. This program allows users to intuitively select the most appropriate stamps and content based on their message and emotion, improving the quality of their communication.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] [Second embodiment]

[0437] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0438] 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.

[0439] 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).

[0440] 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.

[0441] 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.

[0442] 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).

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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."

[0449] MODE FOR CARRYING OUT THE INVENTION

[0450] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. This system has the function of analyzing the user's message and generating an appropriate illustration and a short message to accompany it. Below, we will explain the operation of the system in detail from the perspectives of the server, terminal, and user.

[0451] Server Processing

[0452] 1. Receiving and parsing messages

[0453] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) to extract keywords and emotional information. For example, if a message is received saying "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted.

[0454] 2. Creating illustrations and short messages

[0455] The server generates an appropriate illustration and message based on the extracted keywords and emotional information. The generation is done using artificial intelligence (AI), and multiple candidates are created. For example, for the keyword "I'm getting late," a stamp is generated that combines an illustration of a sleeping cat with the message "I'm late, but I'm doing my best!"

[0456] 3. Submit your stamp suggestions

[0457] The server sends the generated stamp candidates to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation.

[0458] Terminal handling

[0459] 1. Receiving and displaying stamp candidates

[0460] The terminal receives the stamp candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface.

[0461] 2. Select and send stamps

[0462] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[0463] User operations

[0464] 1. Enter your message

[0465] The user opens the LINE application, types a message, and presses the send button. For example, they might type, "I'm going to be late today..."

[0466] 2. Select a stamp

[0467] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[0468] 3. Sending stamps

[0469] Once you have completed your selection, the stamp will appear on the other person's LINE chat screen.

[0470] Specific examples

[0471] For example, if a user sends a message saying, "I think I'll be late today...", the server analyzes this message and extracts the keyword "I'll be late". It then generates an illustration of a "sleeping cat" and a message saying, "I'm late, but I'll do my best!" This stamp is presented to the user along with other options such as "A rabbit looking at the clock" (Sorry I'm late!). The user selects "sleeping cat" and sends the stamp, and the original stamp is displayed to the recipient.

[0472] As described above, the present invention is a system that can be operated intuitively by the user and that makes communication more enjoyable and lively by providing original stamps suited to specific situations.

[0473] The processing flow will be explained below.

[0474] Program processing steps

[0475] User message entry and sending

[0476] Step 1:

[0477] The user opens the LINE application and types a message.

[0478] For example, a user types "I'm going to be late today..." and presses the send button.

[0479] Receiving and parsing messages

[0480] Step 2:

[0481] The terminal sends the message data (text, user ID, timestamp) entered by the user to the server.

[0482] Step 3:

[0483] The server analyzes the received message data.

[0484] Natural language processing (NLP) techniques are used to extract keywords (e.g., "slow") and emotional information (e.g., "fatigue") from messages.

[0485] Generate illustrations and short messages

[0486] Step 4:

[0487] The server's AI generates related illustrations and short messages based on the extracted keywords and emotional information.

[0488] For example, for the keyword "getting late," a stamp is generated that combines an illustration of a sleeping cat with a one-line message: "It's late, but do your best!"

[0489] Submit a stamp suggestion

[0490] Step 5:

[0491] The server organizes the generated stamp candidates and transmits them to the user's terminal.

[0492] For example, some possible phrases include "The cat is sleeping" (It's late, but do your best!) and "The rabbit is looking at the clock" (Sorry I'm late!).

[0493] Displaying and selecting stamp candidates

[0494] Step 6:

[0495] The terminal visually displays the received stamp candidates to the user.

[0496] To arrange stamp candidates on an interface so that the user can easily understand them.

[0497] Step 7:

[0498] The user selects the stamp they like by tapping on it from the displayed stamp candidates.

[0499] For example, select the "Cat Sleeping" stamp and press the send button.

[0500] Send selected stamps

[0501] Step 8:

[0502] The terminal sends the stamp data (stamp ID, user ID, timestamp) selected by the user to the server.

[0503] Step 9:

[0504] Based on the stamp selection data received by the server, the selected stamp is processed and information on the sender and destination is recorded.

[0505] Step 10:

[0506] The server transmits the stamp data to the other terminal.

[0507] Displaying stamps

[0508] Step 11:

[0509] The terminal on the other side displays the stamp data received from the server.

[0510] For example, the "Cat is sleeping" stamp (slow but good luck!) will appear on the other person's LINE chat screen.

[0511] Example 1

[0512] 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."

[0513] Conventional messaging applications require users to manually select stamps, which can be time-consuming and time-consuming to find the appropriate stamp. It can also be difficult to obtain the optimal stamp based on the content of a user's message, which can disrupt smooth communication. The purpose of this invention is to simplify user operations and improve the quality of communication by automatically generating and presenting the optimal stamp based on the user's message.

[0514] 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.

[0515] In this invention, the server includes means for analyzing a message received from a user, means for generating multiple illustrations and a short message based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, means for generating an illustration and a short message using a generative AI model, and means for inputting the illustration and the short message into the generative AI model based on a prompt sentence. This allows the server to automatically generate the optimal stamp based on the content of the user's message, allowing the user to easily select and send the stamp.

[0516] The "means for analyzing messages received from users" is a function for analyzing messages sent by users and extracting information such as meaning and emotion.

[0517] "Means for generating multiple illustrations and short messages based on the analysis results" refers to a function that uses AI to create multiple illustrations and accompanying short messages based on the information obtained through the analysis.

[0518] The "means for displaying a list of multiple candidates that can be selected by the user" is a function that displays multiple stamp candidates sent from the server on the terminal screen, allowing the user to select from among them.

[0519] The "means for transmitting the selected stamp" is a function for transmitting the stamp selected by the user to the other party's terminal.

[0520] A "generative AI model" is a model trained using artificial intelligence algorithms that generate illustrations and messages based on specific prompts.

[0521] The "means for inputting into the generative AI model based on the prompt sentence" is a function for inputting into the AI ​​model based on extracted keywords and emotional information, and generating an illustration and a short message as a result.

[0522] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. This system analyzes the user's message and generates appropriate illustrations and short messages, facilitating smooth communication.

[0523] Server Processing

[0524] The server receives messages sent by users. These received messages are analyzed using natural language processing (NLP) tools. For example, Python libraries such as NLTK and spaCy are used. As a result of the analysis, keywords and emotional information are extracted from the message. For example, from the message "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted.

[0525] The server then uses a generative AI model, based on the extracted keywords and emotional information, to generate an illustration and a short message. This generative AI model utilizes a pre-trained algorithm, such as GPT-3, and the prompt is input into the generative AI model.

[0526] Example prompt sentence:

[0527] User message: "Looks like I'm going to be late today..."

[0528] Keywords: ["running late", "tired"]

[0529] Emotion: ["fatigue"]

[0530] Generate an illustration and a short message.

[0531] Based on this prompt, the generative AI model generates multiple combinations of illustrations and one-line messages. For example, for the keyword "I'm getting late," it generates an illustration of a "sleeping cat" and the one-line message "It's late, but do your best!"

[0532] The generated stamp candidates are sent from the server to the user's device via the server's API, and multiple candidates are presented to the user.

[0533] Terminal handling

[0534] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The terminal provides an intuitive and easy-to-use GUI (Graphical User Interface). The user can then select the stamp they like from the displayed candidates.

[0535] When a user selects a stamp, the selection information is sent from the device to the server. This information includes the selected stamp ID and the user ID. Finally, the selected stamp is sent to the other device and displayed on the LINE chat screen.

[0536] User operations

[0537] The user opens the LINE application, types a message, and sends it. For example, they type "I'm going to be late today..." and press the send button. The server then displays multiple stamp candidates on the user's device. The user selects the stamp they like by tapping it. For example, if the user selects the "sleeping cat" stamp, that stamp will be sent to the other person and will appear on their LINE chat screen.

[0538] In this way, the system of the present invention can be operated intuitively by the user and makes communication more enjoyable and lively by providing original stamps suitable for specific situations.

[0539] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0540] Step 1:

[0541] Receiving messages (server)

[0542] The server receives a message sent by the user. This message also includes the user ID and message ID. The input is the text message entered by the user in the LINE application, and the output is structured data for storing this message in a database. Specifically, the server sends the received message to an API endpoint and stores it in the database.

[0543] Step 2:

[0544] Message analysis (server)

[0545] The server analyzes the received message. Natural language processing (NLP) tools are used for the analysis. The input is the received message text, and the output is extracted keywords and emotional information. For example, from the message "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted. Specifically, keywords and emotional information are extracted from the text using Python libraries such as NLTK and spaCy.

[0546] Step 3:

[0547] Prompt statement generation (server)

[0548] The server generates a prompt sentence to be input into the generative AI model based on the extracted keywords and emotional information. The input is the extracted keywords and emotional information, and the output is a prompt sentence suitable for the generative AI model. Specifically, it combines the keyword "I'm going to be late" with the emotional information "fatigue" to generate the prompt sentence: "User message: "I'm going to be late today..." Keywords: ["I'm going to be late", "Tired"] Emotion: ["Fatigue"] Generate an illustration and a short message."

[0549] Step 4:

[0550] Illustration and message generation (server)

[0551] The server inputs the generated prompt into a generative AI model to generate an illustration and a one-line message. The input is the generated prompt, and the output is a combination of multiple illustrations and one-line messages generated by the AI ​​model. Specifically, the prompt is input into a generative AI model such as GPT-3, generating an illustration of a "sleeping cat" and a message such as "You're slow, but keep trying!"

[0552] Step 5:

[0553] Sending stamp candidates (server)

[0554] The server sends the generated stamp candidates to the user's device. The input is multiple stamp candidates generated by the AI ​​model, and the output is the stamp candidates sent to the user's device. Specifically, the generated stamp candidates are sent to the user's device via API.

[0555] Step 6:

[0556] Receiving and displaying stamp candidates (device)

[0557] The terminal receives the stamp candidates sent from the server and displays them to the user. The input is the stamp candidates sent from the server, and the output is a list of stamp candidates displayed on the terminal. Specifically, the terminal receives the stamp candidates and displays them to the user using an intuitive GUI.

[0558] Step 7:

[0559] Stamp Selection (User)

[0560] The user selects the stamp they like from the displayed stamp candidates. The input is the stamp candidates visually confirmed by the user, and the output is the ID of the stamp selected by the user. Specifically, the user taps on the stamp they like to select it.

[0561] Step 8:

[0562] Send stamp selection information (device)

[0563] The terminal sends the stamp information selected by the user to the server. The input is the ID of the stamp selected by the user, and the output is the stamp selection information sent to the server. Specifically, the terminal sends the ID of the selected stamp to the server's API.

[0564] Step 9:

[0565] Sending stamps (server)

[0566] The server sends the stamp selected by the user to the other device. The input is the ID of the selected stamp and the user ID of the recipient, and the output is the stamp image sent to the other device. Specifically, the image data of the selected stamp is sent to the other device via API.

[0567] Step 10:

[0568] Displaying stamps (on the recipient's device)

[0569] The other device will display the received stamp on the LINE chat screen. The input is the received stamp image data, and the output is the stamp image displayed on the LINE chat screen. The specific operation is to display the received image data within the LINE application.

[0570] In this way, through a series of steps, the most suitable stamp based on the user's message is automatically generated, and the user can select and send it.

[0571] (Application example 1)

[0572] 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."

[0573] In modern messaging applications, users must manually select stickers to appropriately express their emotions and situations. This can be time-consuming and difficult to find. Furthermore, when there are too many sticker options, users can become overwhelmed. Furthermore, there is no mechanism for providing stickers that can quickly and accurately respond to a user's message. To solve these problems, a system is needed that can analyze a user's messages in real time, automatically generate appropriate stickers based on the analysis results, and present them to the user.

[0574] 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.

[0575] In this invention, the server includes means for analyzing messages received from users, means for generating multiple illustrations and short messages based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, and means for presenting the generated stamp candidates to the user in order of priority, thereby enabling the user to quickly and easily select and send the stamp that best suits the message content.

[0576] A "user" is a person who uses the system.

[0577] A "message" is text information sent by a user through a communication application.

[0578] The "analysis means" is a function that uses natural language processing technology to analyze messages received from users and extract keywords and emotional information.

[0579] An "illustration" is an image that visually expresses a user's emotions or situation.

[0580] A "one-line message" is a short piece of text that explains an emotion or situation in combination with an illustration.

[0581] "Means of generation" is a function that creates stamps by combining illustrations and short messages based on the analysis results.

[0582] The "display means" is a function that provides an interface that visually presents a plurality of candidates from among the generated stamps to the user and allows the user to select one.

[0583] The "transmission means" is a function for transmitting the stamp selected by the user to the recipient.

[0584] "Stamp candidates" are multiple stamp options that are generated based on the user's analysis of the message and presented to the user for selection.

[0585] The "order of priority" is a criterion for displaying the generated stamp candidates in the most appropriate order based on the content of the user's message and the situation.

[0586] This invention is a system that analyzes messages sent by users through messaging applications and generates and presents appropriate illustrations and short messages (stamps) based on the analysis results. Users can easily communicate by selecting from the presented stamp candidates.

[0587] Server Processing

[0588] Receiving and parsing messages

[0589] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) techniques to extract keywords and emotional information. The specific software used is the OpenAI API.

[0590] Generate illustrations and short messages

[0591] The server generates an appropriate illustration and a short message based on the extracted keywords and emotional information. The generation is done using artificial intelligence (AI), and multiple candidates are created. For example, if a user sends a message saying, "I'm going to be late today...", the keyword "I'm going to be late" is extracted, and a stamp is generated that combines an illustration of a sleeping cat with the message, "I'm late, but I'll do my best!"

[0592] Submit a stamp suggestion

[0593] The server sends the generated stamp candidates to the user's device. The stamp candidates are prioritized based on the user's message content and emotions, allowing the user to select the stamp that best suits the situation.

[0594] Terminal handling

[0595] Receiving and displaying stamp suggestions

[0596] The terminal receives the stamp candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface.

[0597] Select and send stamps

[0598] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp's ID, the user ID, and a timestamp.

[0599] User operations

[0600] Enter your message

[0601] A user opens a chat application, types a message, and hits send, for example, "I'm going to be late today..."

[0602] Select a stamp

[0603] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[0604] Sending stamps

[0605] Once you have completed your selection, the stamp will appear on the other person's chat screen.

[0606] Prompt Sentence Examples

[0607] Extract sentiment and keywords from the following messages:

[0608] Message: "Looks like I'll be late today..."

[0609] This system is expected to enable users to intuitively and quickly select and send stamps that suit the content of their messages, facilitating smooth communication.

[0610] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0611] Step 1:

[0612] The server gets the message received from the user. The input is the message sent by the user and the output is the received message data, which is kept for the next analysis step.

[0613] Step 2:

[0614] The server analyzes the received message using natural language processing technology. The input is the message data from step 1, and the output is the analyzed keywords and emotional information. The server uses OpenAI's API to extract important keywords and emotions from the message content. This analyzed information becomes the basic data for generating stamps.

[0615] Step 3:

[0616] The server generates multiple illustrations and short messages based on the analysis results. The input is the analysis information from step 2, and the output is the generated stamp candidates. The server uses an artificial intelligence model to generate multiple stamps that combine illustrations and short messages that match the extracted keywords and emotional information.

[0617] Step 4:

[0618] The server sends the generated stamp candidates to the terminal. The input is the stamp candidates from step 3, and the output is the stamp data sent to the terminal. The stamp candidates are sorted based on priority and presented in a format that makes it easy for the user to select.

[0619] Step 5:

[0620] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The input is the stamp data from step 4, and the output is the display to the user. The terminal provides an intuitive and easy-to-use user interface and presents multiple stamp candidates to the user.

[0621] Step 6:

[0622] The user selects the stamp they like from the displayed stamp candidates. The input is the stamp candidates displayed in step 5, and the output is the selected stamp information. The user selects a stamp with simple operations such as tapping or clicking, and the information is stored on the device.

[0623] Step 7:

[0624] The terminal sends the stamp selected by the user to the server. The input is the stamp information selected in step 6, and the output is the stamp information sent to the server. This information includes the stamp ID, user ID, timestamp, etc.

[0625] Step 8:

[0626] The server finally sends the selected stamp to the recipient. The input is the stamp information from step 7, and the output is the stamp sent to the recipient. This causes the selected stamp to be displayed on the recipient's chat screen.

[0627] The above processing steps realize a system in which appropriate stamps are automatically generated based on the user's message, and the user can easily select and send them.

[0628] 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.

[0629] MODE FOR CARRYING OUT THE INVENTION

[0630] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. Furthermore, by incorporating an emotion engine, the system enhances its functionality of recognizing the user's emotions and providing stamps that correspond to them. The system analyzes the user's message, extracts keywords containing emotional information, and generates an appropriate illustration and accompanying message. The operation of the system is specifically described below from the perspectives of the server, terminal, and user.

[0631] Server Processing

[0632] 1. Receiving and parsing messages

[0633] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) technology to extract keywords and emotional information. An emotion engine is used to recognize emotional information (e.g., "joy," "sadness," "anger," etc.) from the messages. For example, if a message is received saying, "I'm going to be late today...," keywords such as "I'm going to be late" and "I'm tired" and the emotional information of "fatigue" are extracted.

[0634] 2. Creating illustrations and short messages

[0635] The server generates related illustrations and short messages based on the extracted keywords and emotional information. This generation uses artificial intelligence (AI) to create multiple stamp candidates. The priority of the stamp candidates to be generated is determined based on the recognition results of the emotion engine. For example, for the emotion "tired," a stamp combining an illustration of a "sleeping cat" and a short message such as "It's late, but do your best!" is generated.

[0636] 3. Submit your stamp suggestions

[0637] The server organizes the generated stamp candidates and sends them to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation. The most suitable candidates are displayed at the top based on a priority order based on emotional information.

[0638] Terminal handling

[0639] 1. Receiving and displaying stamp candidates

[0640] The device receives the sticker candidates sent from the server and visually displays them to the user. The display method is provided with an intuitive and easy-to-select interface. The stickers are prioritized based on emotion, so the most suitable ones are displayed first.

[0641] 2. Select and send stamps

[0642] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[0643] User operations

[0644] 1. Enter your message

[0645] The user opens the LINE application, types a message, and presses the send button. For example, they might type, "I'm going to be late today..."

[0646] 2. Select a stamp

[0647] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[0648] 3. Sending stamps

[0649] Once you have completed your selection, the stamp will appear on the other person's LINE chat screen.

[0650] Specific examples

[0651] For example, if a user sends a message saying, "I'm going to be late today...", the server analyzes the message and extracts keywords such as "I'm going to be late" and "I'm tired" as well as the emotional information of "fatigue".The server then generates an illustration of a "sleeping cat" and a message saying, "I'm late, but keep trying!" and presents them to the user along with other options.The user selects "sleeping cat" from the list and sends it, and the original stamp is displayed to the recipient.

[0652] As described above, the present invention is a system that can be intuitively operated by the user and makes communication more enjoyable and lively by providing original stamps that are best suited to specific situations and emotions.

[0653] The processing flow will be explained below.

[0654] MODE FOR CARRYING OUT THE INVENTION (PROCESSING STEPS)

[0655] User message entry and sending

[0656] Step 1:

[0657] The user opens the messaging application and types a message.

[0658] For example, a user types "I'm going to be late today..." and presses the send button.

[0659] Receiving and parsing messages

[0660] Step 2:

[0661] The terminal sends the message data (text, user ID, timestamp) entered by the user to the server.

[0662] Step 3:

[0663] The server analyzes the received message data.

[0664] Natural language processing (NLP) techniques are used to analyze messages and extract keywords (e.g., "slow") and emotional information (e.g., "fatigue").

[0665] Step 4:

[0666] The server uses an emotion engine to recognize emotion information from the extracted keywords and message content.

[0667] For example, the emotional information "fatigue" is recognized from "I'm going to be late today..."

[0668] Generate illustrations and short messages

[0669] Step 5:

[0670] The server's AI generates an appropriate illustration and a short message based on the extracted keywords and recognized emotional information.

[0671] For example, for the keyword "getting late" and the emotional information "fatigue," a stamp is generated that combines an illustration of a "sleeping cat" with a one-line message such as "It's late, but do your best!"

[0672] Step 6:

[0673] The server creates multiple stamp candidates and organizes them by prioritizing them based on emotional information.

[0674] For example, create suggestions such as "The cat is sleeping" (It's late, but do your best!) and "The rabbit is looking at the clock" (Sorry I'm late!) and prioritize them.

[0675] Submit a stamp suggestion

[0676] Step 7:

[0677] The server transmits the generated stamp candidates to the terminal.

[0678] Prioritize your search so that the best candidates are displayed at the top.

[0679] Displaying and selecting stamp candidates

[0680] Step 8:

[0681] The terminal visually displays the received stamp candidates to the user.

[0682] For example, the interface displays "A cat is sleeping" and "A rabbit is looking at the clock" in that order.

[0683] Step 9:

[0684] The user selects the stamp they like by tapping on it from the displayed stamp candidates.

[0685] For example, select the "Cat Sleeping" stamp and press the send button.

[0686] Send selected stamps

[0687] Step 10:

[0688] The terminal sends the stamp data (stamp ID, user ID, timestamp) selected by the user to the server.

[0689] Step 11:

[0690] Based on the stamp selection data received by the server, the selected stamp is processed and information on the sender and destination is recorded.

[0691] Step 12:

[0692] The server transmits the stamp data to the other terminal.

[0693] Displaying stamps

[0694] Step 13:

[0695] The terminal on the other side displays the stamp data received from the server.

[0696] For example, the "Cat is sleeping" stamp (slow but good luck!) will appear on the other person's LINE chat screen.

[0697] Example 2

[0698] 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."

[0699] In conventional messaging applications, users had to manually select stickers for messages they sent, making it difficult to quickly provide stickers that were optimal for specific situations or emotions. Furthermore, the lack of sticker suggestions based on the user's emotions made it difficult to make communication more personalized and smooth.

[0700] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0701] In this invention, the server includes means for analyzing messages received from users and extracting keywords and emotional information, means for generating multiple illustrations and short messages based on the analysis results, means for prioritizing the generated multiple stamp candidates based on the emotional information and displaying them so that the user can select one, and means for transmitting the selected stamp. This makes it possible to automatically generate and provide stamps that are optimal for messages sent by users, thereby realizing more personalized communication.

[0702] A "User" is an individual or entity that sends or receives messages through a messaging application.

[0703] "Receiving" is the act of the server obtaining a message sent by a user.

[0704] A "message" is text information that a user sends through a messaging application.

[0705] "Analysis" is the process of breaking down the content of a received message and extracting meaning, keywords, and emotional information.

[0706] "Keywords" are words or phrases that carry significant meaning in a message.

[0707] "Emotion information" is data that represents the user's emotions extracted from the message.

[0708] "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language.

[0709] An "emotion engine" is software or hardware that analyzes and recognizes a user's emotions from the contents of a message.

[0710] "Illustration" refers to an image or picture used as a stamp.

[0711] A "one-line message" is a short text message that accompanies an illustration.

[0712] An "artificial intelligence model" is a computational model that learns from data and automates specific tasks.

[0713] "Stamp candidates" are multiple stamp options presented to the user.

[0714] "Priority" refers to the order in which stamp candidates are arranged based on emotion information.

[0715] A "selectable display" is an interface that allows the user to select one stamp from among multiple stamp candidates.

[0716] A "selected stamp" is a specific stamp that the user selects from among multiple stamp candidates.

[0717] "Send" is the act of sending the selected stamp from the server to the recipient's terminal.

[0718] A "system" is a set of hardware and software that integrates these means to provide a specific function.

[0719] MODE FOR CARRYING OUT THE INVENTION

[0720] The system of this invention automatically generates optimal stamps based on messages sent by users in a messaging application, allowing users to select and send them. Furthermore, by using an emotion engine, the system recognizes the user's emotions and provides corresponding stamps. The configuration and operation of this system are described in detail below.

[0721] Server Processing

[0722] 1. Receiving and parsing messages

[0723] The server receives messages sent by users. The messaging application used can be a commonly used messaging application, such as LINE or SNS Messenger.

[0724] Received messages are analyzed using natural language processing (NLP) technology. During this analysis, keywords and emotional information are extracted. By using an emotion engine, the system can recognize the user's emotions into categories such as "happiness," "sadness," and "anger."

[0725] Examples:

[0726] If a user sends a message saying "I'm going to be late today...", the server extracts keywords such as "I'm going to be late" and "I'm tired" as well as emotion information such as "fatigue".

[0727] 2. Creating illustrations and short messages

[0728] The server generates related illustrations and short messages based on the extracted keywords and emotional information, using an artificial intelligence (AI) model, specifically a generative AI model.

[0729] Based on the recognition results of the emotion engine, the priority of the stamp candidates to be generated is determined.

[0730] Examples:

[0731] For the emotion "tired," a stamp is generated that combines an illustration of a "sleeping cat" with a one-line message such as "It's late, but do your best!"

[0732] 3. Submit your stamp suggestions

[0733] The server sends the generated stamp candidates to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation. The most suitable candidates are displayed at the top based on a priority order based on emotion information.

[0734] Terminal handling

[0735] 1. Receiving and displaying stamp candidates

[0736] The device receives the sticker candidates sent from the server and visually displays them to the user. The display method is provided with an intuitive and easy-to-select interface. The stickers are prioritized based on emotion, so the most suitable ones are displayed first.

[0737] Examples:

[0738] The "sleeping cat" stamp will appear first on the device screen, followed by another stamp.

[0739] 2. Select and send stamps

[0740] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[0741] User operations

[0742] 1. Enter your message

[0743] The user opens the messaging application, types a message, and presses the send button.

[0744] Examples:

[0745] Type "I'm going to be late today..." and send it.

[0746] 2. Select a stamp

[0747] Stamp candidates sent from the server are displayed on the device, and the user can tap to select the stamp they like.

[0748] Examples:

[0749] Select the "Sleeping cat" stamp.

[0750] 3. Sending stamps

[0751] Once you have completed your selection, the stamp will appear on the other person's chat screen.

[0752] Prompt Sentence Examples

[0753] The following prompts can be fed into the generative AI model to explain the system's detailed behavior:

[0754] Messages sent by users are analyzed using natural language processing technology, and emotional information is extracted using an emotion engine. Based on this emotional information, AI is used to generate related illustrations and short messages. The generated stamp candidates are displayed to the user in a prioritized order, and a system is built that reflects the user's selection.

[0755] Through these steps, the system extracts emotions and keywords from the message entered by the user and provides the most appropriate stamps based on that, thereby realizing a more personalized communication experience.

[0756] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0757] Step 1:

[0758] Receiving messages

[0759] The server receives messages sent by users. The data received from the messaging application (input) is the text message typed by the user. This message data is passed to the server's parsing process (output).

[0760] Specific example of operation: When a user sends a message such as "I'm going to be late today..." in an application, this text data is sent to the server.

[0761] Step 2:

[0762] Message Parsing

[0763] The server analyzes the received message data using natural language processing (NLP) technology. The input is the received message data, and keywords and emotional information are extracted during the analysis process. The output is the extracted keywords and emotional information.

[0764] Specific example of operation: Analyze the message "I think I'll be late today..." and extract the keyword "I'll be late" and the emotional information "fatigue."

[0765] Step 3:

[0766] Generate illustrations and short messages

[0767] The server uses an artificial intelligence (AI) model to generate related illustrations and short messages based on the extracted keywords and emotional information. The input is the extracted keywords and emotional information, and the output is multiple stamp candidates.

[0768] Specific example of operation: In response to the emotional information "fatigue," an AI model is used to generate an illustration of a "sleeping cat" and a one-line message saying "You're slow, but keep trying!"

[0769] Step 4:

[0770] Prioritize and send sticker suggestions

[0771] The server prioritizes the generated stamp candidates based on emotion information and sends them to the user's device. The input is the generated stamp candidates, and the prioritized stamp candidates are sent to the device (output).

[0772] Specific example of operation: The generated "Cat sleeping" stamp is placed at the top, and multiple stamp candidates including it are sent to the user's device.

[0773] Step 5:

[0774] Receiving and displaying stamp suggestions

[0775] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The input is the stamp candidate data sent from the server, and the output is a list of stamp candidates displayed on the user interface.

[0776] Specific example of operation: The "Cat sleeping" stamp will be displayed on the device screen first, followed by other stamps.

[0777] Step 6:

[0778] Select a stamp

[0779] The user selects the stamp they like from the displayed stamp candidates. The input is multiple stamp candidates, and the output is the ID of the stamp selected by the user.

[0780] Specific example of operation: When the user taps the "sleeping cat" stamp, that stamp is selected.

[0781] Step 7:

[0782] Send selected stamps

[0783] The terminal sends the stamp information selected by the user to the server, which receives it and displays the stamp on the other party's chat screen. The input is the selected stamp ID, user ID, and timestamp, and the output is the stamp displayed on the other party's chat screen.

[0784] Specific example of operation: When a user selects the "sleeping cat" stamp, the information is sent to the server and displayed on the other person's chat screen.

[0785] (Application example 2)

[0786] 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."

[0787] Existing messaging applications lack functionality to help users quickly respond appropriately based on their emotions and the content of their messages. Furthermore, it can be time-consuming for users to select the most appropriate content (e.g., movies, music, articles, etc.) based on their emotions, which can lead to a decline in the quality of communication and engagement. This invention solves these problems by providing a function that automatically recommends the most appropriate stickers and content based on the user's message and emotions.

[0788] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a message received from a user, means for generating multiple illustrations and short messages based on the analysis results, means for displaying the multiple generated candidates so that the user can select one, means for sending the selected stamp, and means for recommending content based on the user's message and emotions. This enables the user to quickly receive appropriate stamps and content based on the message and emotions, thereby improving the quality of communication and engagement.

[0789] The "means for analyzing messages received from users" refers to a function that enables the platform to receive messages sent by users and analyze their contents using natural language processing technology.

[0790] The "means for generating multiple illustrations and short messages based on the analysis results" is a function that uses artificial intelligence technology to generate many candidate illustrations and suitable short messages based on the content and emotional information of the analyzed message.

[0791] The "means for displaying a selection from multiple generated candidates to the user" is an interface that displays the many generated stamp candidates on the user's terminal and allows the user to select the appropriate stamp from among them.

[0792] The "means for transmitting the selected stamp" is a function for transmitting the stamp selected by the user to the recipient user.

[0793] "Means for recommending content based on a user's message and emotions" refers to an evaluation and selection function that extracts the content of a user's message and emotional information, and then recommends the most appropriate content, such as movies, music, or articles, that correspond to them.

[0794] The system of the present invention is a content distribution service that automatically generates optimal stamps and content based on a user's message and emotions, allowing the user to select, send, and play them. This system has the functionality to operate on both the server and the user's terminal. The operation of the system will be specifically explained below from the perspectives of the server, the terminal, and the user.

[0795] Server Processing

[0796] 1. Receiving and parsing messages

[0797] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) techniques to extract keywords and emotional information. This analysis is performed using the Google Cloud Natural Language API. An emotional engine (e.g., IBM Watson's Tone Analyzer) is used to recognize emotional information (e.g., "stress," "joy," "sadness," etc.) from the messages.

[0798] 2. Creating illustrations and short messages

[0799] The server generates related illustrations and short messages based on the extracted keywords and emotion information. This generation uses artificial intelligence (AI) technology (e.g., OpenAI's GPT-3 and DALL-E). Based on the recognition results of the emotion engine, the server determines the priority of the sticker candidates to be generated.

[0800] 3. Content Recommendations

[0801] The server has an evaluation and selection function to recommend appropriate content (e.g., movies, music, articles, etc.) based on the corresponding message and emotional information. These contents are organized to prioritize the most appropriate content for the user.

[0802] 4. Submit sticker and content suggestions

[0803] The server organizes the generated stamps and content candidates and sends them to the user's device. By presenting multiple candidates, the user can select the stamps and content that best suit the situation.

[0804] Terminal handling

[0805] 1. Receiving and displaying stamps and content suggestions

[0806] The terminal receives the stamps and content candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface for the display method.

[0807] 2. Select stamps and content, and send and play them

[0808] When a user selects a stamp or content they like, the device sends the selection information to the server, including the stamp ID, content information, user ID, timestamp, etc. The content selected by the user is then played or provided immediately.

[0809] User operations

[0810] 1. Enter your message

[0811] A user opens the application, types a message, and hits send, for example, "I'm feeling very stressed today."

[0812] 2. Select stamps and content

[0813] The stamps and content candidates sent from the server are displayed on the device, and the user can select the stamps or content they like by tapping on them. For example, they can select "Relaxation Music."

[0814] 3. Sending stamps and playing content

[0815] Once the selection is complete, the stamp will appear on the other person's chat screen and the content will be played on the spot.

[0816] Examples of concrete examples and prompts

[0817] For example, if a user sends a message saying, "I'm feeling very stressed today," the server analyzes the message and extracts the keyword "stress" and the emotional information "negative." Potential content, such as relaxation music, nature videos, and soothing articles, are then generated and presented to the user. The user selects "relaxation music" from the list and plays it within the app.

[0818] Example prompt sentence:

[0819] User message: "I'm so stressed today"

[0820] Extracted keywords: ["stress"]

[0821] Extracted sentiment: ["Negative"]

[0822] Generate relevant content suggestions: "Relaxation Music", "Nature Videos", "Soothing Articles"

[0823] The user selects and plays relaxation music.

[0824] As described above, the system of the present invention can be operated intuitively by the user and makes communication more enjoyable and lively by providing stamps and content that are optimal for specific situations and emotions.

[0825] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0826] Step 1:

[0827] Receiving and parsing messages

[0828] The server receives messages sent by users. The received message text is given as input. The server uses natural language processing (NLP) techniques to analyze the message text. This analysis uses the Google Cloud Natural Language API to extract keywords and emotional information. An emotion engine (e.g., IBM Watson's Tone Analyzer) is used to recognize emotional information (e.g., "stress," "joy," "sadness," etc.) from the message. Data containing keywords and emotional information is generated as output.

[0829] Step 2:

[0830] Generate illustrations and short messages

[0831] The server receives the extracted keywords and emotion information as input and generates related illustrations and short messages using artificial intelligence (AI) technology, such as OpenAI's GPT-3 and DALL-E. Based on the recognition results of the emotion engine, the server determines the priority of the stamp candidates to be generated. The output is data containing multiple stamp candidates.

[0832] Step 3:

[0833] Content Recommendations

[0834] The server recommends appropriate content based on the message and emotional information. Extracted keywords and emotional information are given as input. AI technology is used to evaluate and select appropriate content (e.g., movies, music, articles, etc.). The output is data containing multiple content candidates.

[0835] Step 4:

[0836] Submit sticker and content suggestions

[0837] The server organizes the generated stamps and content candidates and sends them to the user's device. The generated stamps and content candidate data are given as input. The sent stamps and content candidates are displayed on the user's device as output.

[0838] Step 5:

[0839] Receive and display stamps and content suggestions

[0840] The terminal receives the stamps and content candidates sent from the server. The data received from the server is given as input. The terminal provides an intuitive and easy-to-select interface for the user, visually displaying the stamps and content candidates. As output, the displayed stamps and content candidates are provided to the user.

[0841] Step 6:

[0842] Selecting, sending, and playing stamps and content

[0843] The user selects the stamps and content they like. The terminal sends the selection information to the server. The input is the stamps and content information selected by the user. The output is the selected stamps displayed on the other party's chat screen and the content is played.

[0844] The above are the specific processing steps and operations of the system program that realizes this application example. This program allows users to intuitively select the most appropriate stamps and content based on their message and emotion, improving the quality of their communication.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] [Third embodiment]

[0849] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0850] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0851] 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).

[0852] 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.

[0853] 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.

[0854] 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).

[0855] 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. 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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."

[0861] MODE FOR CARRYING OUT THE INVENTION

[0862] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. This system has the function of analyzing the user's message and generating an appropriate illustration and a short message to accompany it. Below, we will explain the operation of the system in detail from the perspectives of the server, terminal, and user.

[0863] Server Processing

[0864] 1. Receiving and parsing messages

[0865] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) to extract keywords and emotional information. For example, if a message is received saying "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted.

[0866] 2. Creating illustrations and short messages

[0867] The server generates an appropriate illustration and message based on the extracted keywords and emotional information. The generation is done using artificial intelligence (AI), and multiple candidates are created. For example, for the keyword "I'm getting late," a stamp is generated that combines an illustration of a sleeping cat with the message "I'm late, but I'm doing my best!"

[0868] 3. Submit your stamp suggestions

[0869] The server sends the generated stamp candidates to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation.

[0870] Terminal handling

[0871] 1. Receiving and displaying stamp candidates

[0872] The terminal receives the stamp candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface.

[0873] 2. Select and send stamps

[0874] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[0875] User operations

[0876] 1. Enter your message

[0877] The user opens the LINE application, types a message, and presses the send button. For example, they might type, "I'm going to be late today..."

[0878] 2. Select a stamp

[0879] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[0880] 3. Sending stamps

[0881] Once you have completed your selection, the stamp will appear on the other person's LINE chat screen.

[0882] Specific examples

[0883] For example, if a user sends a message saying, "I think I'll be late today...", the server analyzes this message and extracts the keyword "I'll be late". It then generates an illustration of a "sleeping cat" and a message saying, "I'm late, but I'll do my best!" This stamp is presented to the user along with other options such as "A rabbit looking at the clock" (Sorry I'm late!). The user selects "sleeping cat" and sends the stamp, and the original stamp is displayed to the recipient.

[0884] As described above, the present invention is a system that can be operated intuitively by the user and that makes communication more enjoyable and lively by providing original stamps suited to specific situations.

[0885] The processing flow will be explained below.

[0886] Program processing steps

[0887] User message entry and sending

[0888] Step 1:

[0889] The user opens the LINE application and types a message.

[0890] For example, a user types "I'm going to be late today..." and presses the send button.

[0891] Receiving and parsing messages

[0892] Step 2:

[0893] The terminal sends the message data (text, user ID, timestamp) entered by the user to the server.

[0894] Step 3:

[0895] The server analyzes the received message data.

[0896] Natural language processing (NLP) techniques are used to extract keywords (e.g., "slow") and emotional information (e.g., "fatigue") from messages.

[0897] Generate illustrations and short messages

[0898] Step 4:

[0899] The server's AI generates related illustrations and short messages based on the extracted keywords and emotional information.

[0900] For example, for the keyword "getting late," a stamp is generated that combines an illustration of a sleeping cat with a one-line message: "It's late, but do your best!"

[0901] Submit a stamp suggestion

[0902] Step 5:

[0903] The server organizes the generated stamp candidates and transmits them to the user's terminal.

[0904] For example, some possible phrases include "The cat is sleeping" (It's late, but do your best!) and "The rabbit is looking at the clock" (Sorry I'm late!).

[0905] Displaying and selecting stamp candidates

[0906] Step 6:

[0907] The terminal visually displays the received stamp candidates to the user.

[0908] To arrange stamp candidates on an interface so that the user can easily understand them.

[0909] Step 7:

[0910] The user selects the stamp they like by tapping on it from the displayed stamp candidates.

[0911] For example, select the "Cat Sleeping" stamp and press the send button.

[0912] Send selected stamps

[0913] Step 8:

[0914] The terminal sends the stamp data (stamp ID, user ID, timestamp) selected by the user to the server.

[0915] Step 9:

[0916] Based on the stamp selection data received by the server, the selected stamp is processed and information on the sender and destination is recorded.

[0917] Step 10:

[0918] The server transmits the stamp data to the other terminal.

[0919] Displaying stamps

[0920] Step 11:

[0921] The terminal on the other side displays the stamp data received from the server.

[0922] For example, the "Cat is sleeping" stamp (slow but good luck!) will appear on the other person's LINE chat screen.

[0923] Example 1

[0924] 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."

[0925] Conventional messaging applications require users to manually select stamps, which can be time-consuming and time-consuming to find the appropriate stamp. It can also be difficult to obtain the optimal stamp based on the content of a user's message, which can disrupt smooth communication. The purpose of this invention is to simplify user operations and improve the quality of communication by automatically generating and presenting the optimal stamp based on the user's message.

[0926] 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.

[0927] In this invention, the server includes means for analyzing a message received from a user, means for generating multiple illustrations and a short message based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, means for generating an illustration and a short message using a generative AI model, and means for inputting the illustration and the short message into the generative AI model based on a prompt sentence. This allows the server to automatically generate the optimal stamp based on the content of the user's message, allowing the user to easily select and send the stamp.

[0928] The "means for analyzing messages received from users" is a function for analyzing messages sent by users and extracting information such as meaning and emotion.

[0929] "Means for generating multiple illustrations and short messages based on the analysis results" refers to a function that uses AI to create multiple illustrations and accompanying short messages based on the information obtained through the analysis.

[0930] The "means for displaying multiple stamp candidates that can be selected by the user" is a function that displays multiple stamp candidates sent from the server on the terminal screen, allowing the user to select from them.

[0931] The "means for transmitting the selected stamp" is a function for transmitting the stamp selected by the user to the other party's terminal.

[0932] A "generative AI model" is a model trained using artificial intelligence algorithms that generates illustrations and messages based on specific prompts.

[0933] The "means for inputting into the generative AI model based on the prompt sentence" is a function for inputting into the AI ​​model based on extracted keywords and emotional information, and generating an illustration and a short message as a result.

[0934] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. This system analyzes the user's message and generates appropriate illustrations and short messages, facilitating smooth communication.

[0935] Server Processing

[0936] The server receives messages sent by users. These received messages are analyzed using natural language processing (NLP) tools. For example, Python libraries such as NLTK and spaCy are used. As a result of the analysis, keywords and emotional information are extracted from the message. For example, from the message "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted.

[0937] The server then uses a generative AI model, based on the extracted keywords and emotional information, to generate an illustration and a short message. This generative AI model utilizes a pre-trained algorithm, such as GPT-3, and the prompt is input into the generative AI model.

[0938] Example prompt sentence:

[0939] User message: "Looks like I'm going to be late today..."

[0940] Keywords: ["running late", "tired"]

[0941] Emotion: ["fatigue"]

[0942] Generate an illustration and a short message.

[0943] Based on this prompt, the generative AI model generates multiple combinations of illustrations and one-line messages. For example, for the keyword "I'm getting late," it generates an illustration of a "sleeping cat" and the one-line message "It's late, but do your best!"

[0944] The generated stamp candidates are sent from the server to the user's device via the server's API, and multiple candidates are presented to the user.

[0945] Terminal handling

[0946] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The terminal provides an intuitive and easy-to-use GUI (Graphical User Interface). The user can then select the stamp they like from the displayed candidates.

[0947] When a user selects a stamp, the selection information is sent from the device to the server. This information includes the selected stamp ID and the user ID. Finally, the selected stamp is sent to the other device and displayed on the LINE chat screen.

[0948] User operations

[0949] The user opens the LINE application, types a message, and sends it. For example, they type "I'm going to be late today..." and press the send button. The server then displays multiple stamp candidates on the user's device. The user selects the stamp they like by tapping it. For example, if the user selects the "sleeping cat" stamp, that stamp will be sent to the other person and will appear on their LINE chat screen.

[0950] In this way, the system of the present invention can be operated intuitively by the user and makes communication more enjoyable and lively by providing original stamps suited to specific situations.

[0951] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0952] Step 1:

[0953] Receiving messages (server)

[0954] The server receives a message sent by the user. This message also includes the user ID and message ID. The input is the text message entered by the user in the LINE application, and the output is structured data for storing this message in a database. Specifically, the server sends the received message to an API endpoint and stores it in the database.

[0955] Step 2:

[0956] Message analysis (server)

[0957] The server analyzes the received message. Natural language processing (NLP) tools are used for the analysis. The input is the received message text, and the output is extracted keywords and emotional information. For example, from the message "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted. Specifically, keywords and emotional information are extracted from the text using Python libraries such as NLTK and spaCy.

[0958] Step 3:

[0959] Prompt statement generation (server)

[0960] The server generates a prompt sentence to be input into the generative AI model based on the extracted keywords and emotional information. The input is the extracted keywords and emotional information, and the output is a prompt sentence suitable for the generative AI model. Specifically, it combines the keyword "I'm going to be late" with the emotional information "fatigue" to generate the prompt sentence: "User message: "I'm going to be late today..." Keywords: ["I'm going to be late", "Tired"] Emotion: ["Fatigue"] Generate an illustration and a short message."

[0961] Step 4:

[0962] Illustration and message generation (server)

[0963] The server inputs the generated prompt into a generative AI model to generate an illustration and a one-line message. The input is the generated prompt, and the output is a combination of multiple illustrations and one-line messages generated by the AI ​​model. Specifically, the prompt is input into a generative AI model such as GPT-3, generating an illustration of a "sleeping cat" and a message such as "You're slow, but keep trying!"

[0964] Step 5:

[0965] Sending stamp candidates (server)

[0966] The server sends the generated stamp candidates to the user's device. The input is multiple stamp candidates generated by the AI ​​model, and the output is the stamp candidates sent to the user's device. Specifically, the generated stamp candidates are sent to the user's device via API.

[0967] Step 6:

[0968] Receiving and displaying stamp candidates (device)

[0969] The terminal receives the stamp candidates sent from the server and displays them to the user. The input is the stamp candidates sent from the server, and the output is a list of stamp candidates displayed on the terminal. Specifically, the system receives the stamp candidates and displays them to the user using an intuitive GUI.

[0970] Step 7:

[0971] Stamp Selection (User)

[0972] The user selects the stamp they like from the displayed stamp candidates. The input is the stamp candidates visually confirmed by the user, and the output is the ID of the stamp selected by the user. Specifically, the user taps on the stamp they like to select it.

[0973] Step 8:

[0974] Send stamp selection information (device)

[0975] The terminal sends the stamp information selected by the user to the server. The input is the ID of the stamp selected by the user, and the output is the stamp selection information sent to the server. Specifically, the terminal sends the ID of the selected stamp to the server's API.

[0976] Step 9:

[0977] Sending stamps (server)

[0978] The server sends the stamp selected by the user to the other device. The input is the ID of the selected stamp and the user ID of the recipient, and the output is the stamp image sent to the other device. Specifically, the image data of the selected stamp is sent to the other device via API.

[0979] Step 10:

[0980] Displaying stamps (on the recipient's device)

[0981] The other device will display the received stamp on the LINE chat screen. The input is the received stamp image data, and the output is the stamp image displayed on the LINE chat screen. The specific operation is to display the received image data within the LINE application.

[0982] In this way, through a series of steps, the most suitable stamp based on the user's message is automatically generated, and the user can select and send it.

[0983] (Application example 1)

[0984] 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."

[0985] In modern messaging applications, users must manually select stickers to appropriately express their emotions and situations. This can be time-consuming and difficult to find. Furthermore, when there are too many sticker options, users can become overwhelmed. Furthermore, there is no mechanism for providing stickers that can quickly and accurately respond to a user's message. To solve these problems, a system is needed that can analyze a user's messages in real time, automatically generate appropriate stickers based on the analysis results, and present them to the user.

[0986] 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.

[0987] In this invention, the server includes means for analyzing messages received from users, means for generating multiple illustrations and short messages based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, and means for presenting the generated stamp candidates to the user in order of priority, thereby enabling the user to quickly and easily select and send the stamp that best suits the message content.

[0988] A "user" is a person who uses the system.

[0989] A "message" is text information sent by a user through a communication application.

[0990] The "analysis means" is a function that uses natural language processing technology to analyze messages received from users and extract keywords and emotional information.

[0991] An "illustration" is an image that visually expresses a user's emotions or situation.

[0992] A "one-line message" is a short piece of text that explains an emotion or situation in combination with an illustration.

[0993] "Means of generation" is a function that creates stamps by combining illustrations and short messages based on the analysis results.

[0994] The "display means" is a function that provides an interface that visually presents a plurality of candidates from among the generated stamps to the user and allows the user to select one.

[0995] The "transmission means" is a function for transmitting the stamp selected by the user to the recipient.

[0996] "Stamp candidates" are multiple stamp options that are generated based on the user's analysis of the message and presented to the user for selection.

[0997] The "order of priority" is a criterion for displaying the generated stamp candidates in the most appropriate order based on the content of the user's message and the situation.

[0998] This invention is a system that analyzes messages sent by users through messaging applications and generates and presents appropriate illustrations and short messages (stamps) based on the analysis results. Users can easily communicate by selecting from the presented stamp candidates.

[0999] Server Processing

[1000] Receiving and parsing messages

[1001] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) technology to extract keywords and emotional information. The specific software used is the OpenAI API.

[1002] Generate illustrations and short messages

[1003] The server generates an appropriate illustration and a short message based on the extracted keywords and emotional information. The generation is done using artificial intelligence (AI), and multiple candidates are created. For example, if a user sends a message saying, "I'm going to be late today...", the keyword "I'm going to be late" is extracted, and a stamp is generated that combines an illustration of a sleeping cat with the message, "I'm late, but I'll do my best!"

[1004] Submit a stamp suggestion

[1005] The server sends the generated stamp candidates to the user's device. The stamp candidates are prioritized based on the user's message content and emotions, allowing the user to select the stamp that best suits the situation.

[1006] Terminal handling

[1007] Receiving and displaying stamp suggestions

[1008] The terminal receives the stamp candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface.

[1009] Select and send stamps

[1010] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp's ID, the user ID, and a timestamp.

[1011] User operations

[1012] Enter your message

[1013] A user opens a chat application, types a message, and hits send, for example, "I'm going to be late today..."

[1014] Select a stamp

[1015] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[1016] Sending stamps

[1017] Once you have completed your selection, the stamp will appear on the other person's chat screen.

[1018] Prompt Sentence Examples

[1019] Extract sentiment and keywords from the following messages:

[1020] Message: "Looks like I'll be late today..."

[1021] This system is expected to enable users to intuitively and quickly select and send stamps that suit the content of their messages, facilitating smooth communication.

[1022] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1023] Step 1:

[1024] The server gets the message received from the user. The input is the message sent by the user and the output is the received message data, which is kept for the next analysis step.

[1025] Step 2:

[1026] The server analyzes the received message using natural language processing technology. The input is the message data from step 1, and the output is the analyzed keywords and emotional information. The server uses OpenAI's API to extract important keywords and emotions from the message content. This analyzed information becomes the basic data for generating stamps.

[1027] Step 3:

[1028] The server generates multiple illustrations and short messages based on the analysis results. The input is the analysis information from step 2, and the output is the generated stamp candidates. The server uses an artificial intelligence model to generate multiple stamps that combine illustrations and short messages that match the extracted keywords and emotional information.

[1029] Step 4:

[1030] The server sends the generated stamp candidates to the terminal. The input is the stamp candidates from step 3, and the output is the stamp data sent to the terminal. The stamp candidates are sorted based on priority and presented in a format that makes it easy for the user to select.

[1031] Step 5:

[1032] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The input is the stamp data from step 4, and the output is the display to the user. The terminal provides an intuitive and easy-to-use user interface and presents multiple stamp candidates to the user.

[1033] Step 6:

[1034] The user selects the stamp they like from the displayed stamp candidates. The input is the stamp candidates displayed in step 5, and the output is the selected stamp information. The user selects a stamp with simple operations such as tapping or clicking, and the information is stored on the device.

[1035] Step 7:

[1036] The terminal sends the stamp selected by the user to the server. The input is the stamp information selected in step 6, and the output is the stamp information sent to the server. This information includes the stamp ID, user ID, timestamp, etc.

[1037] Step 8:

[1038] The server finally sends the selected stamp to the recipient. The input is the stamp information from step 7, and the output is the stamp sent to the recipient. This causes the selected stamp to be displayed on the recipient's chat screen.

[1039] The above processing steps realize a system in which appropriate stamps are automatically generated based on the user's message, and the user can easily select and send them.

[1040] 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.

[1041] MODE FOR CARRYING OUT THE INVENTION

[1042] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. Furthermore, by incorporating an emotion engine, the system enhances its functionality of recognizing the user's emotions and providing stamps that correspond to them. The system analyzes the user's message, extracts keywords containing emotional information, and generates an appropriate illustration and accompanying message. The operation of the system is specifically described below from the perspectives of the server, terminal, and user.

[1043] Server Processing

[1044] 1. Receiving and parsing messages

[1045] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) technology to extract keywords and emotional information. An emotion engine is used to recognize emotional information (e.g., "joy," "sadness," "anger," etc.) from the messages. For example, if a message is received saying, "I'm going to be late today...," keywords such as "I'm going to be late" and "I'm tired" and the emotional information of "fatigue" are extracted.

[1046] 2. Creating illustrations and short messages

[1047] The server generates related illustrations and short messages based on the extracted keywords and emotional information. This generation uses artificial intelligence (AI) to create multiple stamp candidates. The priority of the stamp candidates to be generated is determined based on the recognition results of the emotion engine. For example, for the emotion "tired," a stamp combining an illustration of a "sleeping cat" and a short message such as "It's late, but do your best!" is generated.

[1048] 3. Submit your stamp suggestions

[1049] The server organizes the generated stamp candidates and sends them to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation. The most suitable candidates are displayed at the top based on a priority order based on emotional information.

[1050] Terminal handling

[1051] 1. Receiving and displaying stamp candidates

[1052] The device receives the sticker candidates sent from the server and visually displays them to the user. The display method is provided with an intuitive and easy-to-select interface. The stickers are prioritized based on emotion, so the most suitable ones are displayed first.

[1053] 2. Select and send stamps

[1054] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[1055] User operations

[1056] 1. Enter your message

[1057] The user opens the LINE application, types a message, and presses the send button. For example, they might type, "I'm going to be late today..."

[1058] 2. Select a stamp

[1059] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[1060] 3. Sending stamps

[1061] Once you have completed your selection, the stamp will appear on the other person's LINE chat screen.

[1062] Specific examples

[1063] For example, if a user sends a message saying, "I'm going to be late today...", the server analyzes the message and extracts keywords such as "I'm going to be late" and "I'm tired" as well as the emotional information of "fatigue".The server then generates an illustration of a "sleeping cat" and a message saying, "I'm late, but keep trying!" and presents them to the user along with other options.The user selects "sleeping cat" from the list and sends it, and the original stamp is displayed to the recipient.

[1064] As described above, the present invention is a system that can be intuitively operated by the user and makes communication more enjoyable and lively by providing original stamps that are best suited to specific situations and emotions.

[1065] The processing flow will be explained below.

[1066] MODE FOR CARRYING OUT THE INVENTION (PROCESSING STEPS)

[1067] User message entry and sending

[1068] Step 1:

[1069] The user opens the messaging application and types a message.

[1070] For example, a user types "I'm going to be late today..." and presses the send button.

[1071] Receiving and parsing messages

[1072] Step 2:

[1073] The terminal sends the message data (text, user ID, timestamp) entered by the user to the server.

[1074] Step 3:

[1075] The server analyzes the received message data.

[1076] Natural language processing (NLP) techniques are used to analyze messages and extract keywords (e.g., "slow") and emotional information (e.g., "fatigue").

[1077] Step 4:

[1078] The server uses an emotion engine to recognize emotion information from the extracted keywords and message content.

[1079] For example, the emotional information "fatigue" is recognized from "I'm going to be late today..."

[1080] Generate illustrations and short messages

[1081] Step 5:

[1082] The server's AI generates an appropriate illustration and a short message based on the extracted keywords and recognized emotional information.

[1083] For example, for the keyword "getting late" and the emotional information "fatigue," a stamp is generated that combines an illustration of a "sleeping cat" with a one-line message such as "It's late, but do your best!"

[1084] Step 6:

[1085] The server creates multiple stamp candidates and organizes them by prioritizing them based on emotional information.

[1086] For example, create suggestions such as "The cat is sleeping" (It's late, but do your best!) and "The rabbit is looking at the clock" (Sorry I'm late!) and prioritize them.

[1087] Submit a stamp suggestion

[1088] Step 7:

[1089] The server transmits the generated stamp candidates to the terminal.

[1090] Prioritize your search so that the best candidates are displayed at the top.

[1091] Displaying and selecting stamp candidates

[1092] Step 8:

[1093] The terminal visually displays the received stamp candidates to the user.

[1094] For example, the interface displays "A cat is sleeping" and "A rabbit is looking at the clock" in that order.

[1095] Step 9:

[1096] The user selects the stamp they like by tapping on it from the displayed stamp candidates.

[1097] For example, select the "Cat Sleeping" stamp and press the send button.

[1098] Send selected stamps

[1099] Step 10:

[1100] The terminal sends the stamp data (stamp ID, user ID, timestamp) selected by the user to the server.

[1101] Step 11:

[1102] Based on the stamp selection data received by the server, the selected stamp is processed and information on the sender and destination is recorded.

[1103] Step 12:

[1104] The server transmits the stamp data to the other terminal.

[1105] Displaying stamps

[1106] Step 13:

[1107] The terminal on the other side displays the stamp data received from the server.

[1108] For example, the "Cat is sleeping" stamp (slow but good luck!) will appear on the other person's LINE chat screen.

[1109] Example 2

[1110] 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."

[1111] In conventional messaging applications, users had to manually select stickers for messages they sent, making it difficult to quickly provide stickers that were optimal for specific situations or emotions. Furthermore, the lack of sticker suggestions based on the user's emotions made it difficult to make communication more personalized and smooth.

[1112] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1113] In this invention, the server includes means for analyzing messages received from users and extracting keywords and emotional information, means for generating multiple illustrations and short messages based on the analysis results, means for prioritizing the generated multiple stamp candidates based on the emotional information and displaying them so that the user can select one, and means for transmitting the selected stamp. This makes it possible to automatically generate and provide stamps that are optimal for messages sent by users, thereby realizing more personalized communication.

[1114] A "User" is an individual or entity that sends or receives messages through a messaging application.

[1115] "Receiving" is the act of the server obtaining a message sent by a user.

[1116] A "message" is text information that a user sends through a messaging application.

[1117] "Analysis" is the process of breaking down the content of a received message and extracting meaning, keywords, and emotional information.

[1118] "Keywords" are words or phrases that carry significant meaning in a message.

[1119] "Emotion information" is data that represents the user's emotions extracted from the message.

[1120] "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language.

[1121] An "emotion engine" is software or hardware that analyzes and recognizes a user's emotions from the content of a message.

[1122] "Illustration" refers to an image or picture used as a stamp.

[1123] A "one-line message" is a short text message that accompanies an illustration.

[1124] An "artificial intelligence model" is a computational model that learns from data and automates specific tasks.

[1125] "Stamp candidates" are multiple stamp options presented to the user.

[1126] "Priority" refers to the order in which stamp candidates are arranged based on emotion information.

[1127] A "selectable display" is an interface that allows the user to select one stamp from among multiple stamp candidates.

[1128] A "selected stamp" is a specific stamp that the user selects from among multiple stamp candidates.

[1129] "Send" is the act of sending the selected stamp from the server to the recipient's terminal.

[1130] A "system" is a set of hardware and software that integrates these means to provide a specific function.

[1131] MODE FOR CARRYING OUT THE INVENTION

[1132] The system of this invention automatically generates optimal stamps based on messages sent by users in a messaging application, allowing users to select and send them. Furthermore, by using an emotion engine, the system recognizes the user's emotions and provides corresponding stamps. The configuration and operation of this system are described in detail below.

[1133] Server Processing

[1134] 1. Receiving and parsing messages

[1135] The server receives messages sent by users. The messaging application used can be a commonly used messaging application, such as LINE or SNS Messenger.

[1136] Received messages are analyzed using natural language processing (NLP) technology. During this analysis, keywords and emotional information are extracted. By using an emotion engine, the system can recognize the user's emotions into categories such as "happiness," "sadness," and "anger."

[1137] Examples:

[1138] If a user sends a message saying "I'm going to be late today...", the server extracts keywords such as "I'm going to be late" and "I'm tired" as well as emotion information such as "fatigue".

[1139] 2. Creating illustrations and short messages

[1140] The server generates related illustrations and short messages based on the extracted keywords and emotional information, using an artificial intelligence (AI) model, specifically a generative AI model.

[1141] Based on the recognition results of the emotion engine, the priority of the stamp candidates to be generated is determined.

[1142] Examples:

[1143] For the emotion "tired," a stamp is generated that combines an illustration of a "sleeping cat" with a one-line message such as "It's late, but do your best!"

[1144] 3. Submit your stamp suggestions

[1145] The server sends the generated stamp candidates to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation. The most suitable candidates are displayed at the top based on a priority order based on emotion information.

[1146] Terminal handling

[1147] 1. Receiving and displaying stamp candidates

[1148] The device receives the sticker candidates sent from the server and visually displays them to the user. The display method is provided with an intuitive and easy-to-select interface. The stickers are prioritized based on emotion, so the most suitable ones are displayed first.

[1149] Examples:

[1150] The "sleeping cat" stamp will appear first on the device screen, followed by another stamp.

[1151] 2. Select and send stamps

[1152] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[1153] User operations

[1154] 1. Enter your message

[1155] The user opens the messaging application, types a message, and presses the send button.

[1156] Examples:

[1157] Type "I'm going to be late today..." and send it.

[1158] 2. Select a stamp

[1159] Stamp candidates sent from the server are displayed on the device, and the user can tap to select the stamp they like.

[1160] Examples:

[1161] Select the "Sleeping cat" stamp.

[1162] 3. Sending stamps

[1163] Once you have completed your selection, the stamp will appear on the other person's chat screen.

[1164] Prompt Sentence Examples

[1165] The following prompts can be fed into the generative AI model to explain the system's detailed behavior:

[1166] Messages sent by users are analyzed using natural language processing technology, and emotional information is extracted using an emotion engine. Based on this emotional information, AI is used to generate related illustrations and short messages. The generated stamp candidates are displayed to the user in a prioritized order, and a system is built that reflects the user's selection.

[1167] Through these steps, the system extracts emotions and keywords from the message entered by the user and provides the most appropriate stamps based on that, thereby realizing a more personalized communication experience.

[1168] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1169] Step 1:

[1170] Receiving messages

[1171] The server receives messages sent by users. The data received from the messaging application (input) is the text message typed by the user. This message data is passed to the server's parsing process (output).

[1172] Specific example of operation: When a user sends a message such as "I'm going to be late today..." in an application, this text data is sent to the server.

[1173] Step 2:

[1174] Message Parsing

[1175] The server analyzes the received message data using natural language processing (NLP) technology. The input is the received message data, and keywords and emotional information are extracted during the analysis process. The output is the extracted keywords and emotional information.

[1176] Specific example of operation: Analyze the message "I think I'll be late today..." and extract the keyword "I'll be late" and the emotional information "fatigue."

[1177] Step 3:

[1178] Generate illustrations and short messages

[1179] The server uses an artificial intelligence (AI) model to generate related illustrations and short messages based on the extracted keywords and emotional information. The input is the extracted keywords and emotional information, and the output is multiple stamp candidates.

[1180] Specific example of operation: In response to the emotional information "fatigue," an AI model is used to generate an illustration of a "sleeping cat" and a one-line message saying "You're slow, but keep trying!"

[1181] Step 4:

[1182] Prioritize and send sticker suggestions

[1183] The server prioritizes the generated stamp candidates based on emotion information and sends them to the user's device. The input is the generated stamp candidates, and the prioritized stamp candidates are sent to the device (output).

[1184] Specific example of operation: The generated "Cat sleeping" stamp is placed at the top, and multiple stamp candidates including it are sent to the user's device.

[1185] Step 5:

[1186] Receiving and displaying stamp suggestions

[1187] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The input is the stamp candidate data sent from the server, and the output is a list of stamp candidates displayed on the user interface.

[1188] Specific example of operation: The "Cat sleeping" stamp will be displayed on the device screen first, followed by other stamps.

[1189] Step 6:

[1190] Select a stamp

[1191] The user selects the stamp they like from the displayed stamp candidates. The input is multiple stamp candidates, and the output is the ID of the stamp selected by the user.

[1192] Specific example of operation: When the user taps the "sleeping cat" stamp, that stamp is selected.

[1193] Step 7:

[1194] Send selected stamps

[1195] The terminal sends the stamp information selected by the user to the server, which receives it and displays the stamp on the other party's chat screen. The input is the selected stamp ID, user ID, and timestamp, and the output is the stamp displayed on the other party's chat screen.

[1196] Specific example of operation: When a user selects the "sleeping cat" stamp, the information is sent to the server and displayed on the other person's chat screen.

[1197] (Application example 2)

[1198] 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."

[1199] Existing messaging applications lack functionality to help users quickly respond appropriately based on their emotions and the content of their messages. Furthermore, it can be time-consuming for users to select the most appropriate content (e.g., movies, music, articles, etc.) based on their emotions, which can lead to a decline in the quality of communication and engagement. This invention solves these problems by providing a function that automatically recommends the most appropriate stickers and content based on the user's message and emotions.

[1200] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a message received from a user, means for generating multiple illustrations and short messages based on the analysis results, means for displaying the multiple generated candidates so that the user can select one, means for sending the selected stamp, and means for recommending content based on the user's message and emotions. This enables the user to quickly receive appropriate stamps and content based on the message and emotions, thereby improving the quality of communication and engagement.

[1201] The "means for analyzing messages received from users" refers to a function that enables the platform to receive messages sent by users and analyze their contents using natural language processing technology.

[1202] The "means for generating multiple illustrations and short messages based on the analysis results" is a function that uses artificial intelligence technology to generate many candidate illustrations and suitable short messages based on the content and emotional information of the analyzed message.

[1203] The "means for displaying a selection from multiple generated candidates to the user" is an interface that displays the many generated stamp candidates on the user's terminal and allows the user to select the appropriate stamp from among them.

[1204] The "means for transmitting the selected stamp" is a function for transmitting the stamp selected by the user to the recipient user.

[1205] "Means for recommending content based on a user's message and emotions" refers to an evaluation and selection function that extracts the content of a user's message and emotional information, and then recommends the most appropriate content, such as movies, music, or articles, that correspond to them.

[1206] The system of the present invention is a content distribution service that automatically generates optimal stamps and content based on a user's message and emotions, allowing the user to select, send, and play them. This system has the functionality to operate on both the server and the user's terminal. The operation of the system will be specifically explained below from the perspectives of the server, the terminal, and the user.

[1207] Server Processing

[1208] 1. Receiving and parsing messages

[1209] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) techniques to extract keywords and emotional information. This analysis is performed using the Google Cloud Natural Language API. An emotional engine (e.g., IBM Watson's Tone Analyzer) is used to recognize emotional information (e.g., "stress," "joy," "sadness," etc.) from the messages.

[1210] 2. Creating illustrations and short messages

[1211] The server generates related illustrations and short messages based on the extracted keywords and emotion information. This generation uses artificial intelligence (AI) technology (e.g., OpenAI's GPT-3 and DALL-E). Based on the recognition results of the emotion engine, the server determines the priority of the sticker candidates to be generated.

[1212] 3. Content Recommendations

[1213] The server has an evaluation and selection function to recommend appropriate content (e.g., movies, music, articles, etc.) based on the corresponding message and emotional information. These contents are organized to prioritize the most appropriate content for the user.

[1214] 4. Submit sticker and content suggestions

[1215] The server organizes the generated stamps and content candidates and sends them to the user's device. By presenting multiple candidates, the user can select the stamps and content that best suit the situation.

[1216] Terminal handling

[1217] 1. Receiving and displaying stamps and content suggestions

[1218] The terminal receives the stamps and content candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface for the display method.

[1219] 2. Select stamps and content, and send and play them

[1220] When a user selects a stamp or content they like, the device sends the selection information to the server, including the stamp ID, content information, user ID, timestamp, etc. The content selected by the user is then played or provided immediately.

[1221] User operations

[1222] 1. Enter your message

[1223] A user opens the application, types a message, and hits send, for example, "I'm feeling very stressed today."

[1224] 2. Select stamps and content

[1225] The stamps and content candidates sent from the server are displayed on the device, and the user can select the stamps or content they like by tapping on them. For example, they can select "Relaxation Music."

[1226] 3. Sending stamps and playing content

[1227] Once the selection is complete, the stamp will appear on the other person's chat screen and the content will be played on the spot.

[1228] Examples of concrete examples and prompts

[1229] For example, if a user sends a message saying, "I'm feeling very stressed today," the server analyzes the message and extracts the keyword "stress" and the emotional information "negative." Potential content, such as relaxation music, nature videos, and soothing articles, are then generated and presented to the user. The user selects "relaxation music" from the list and plays it within the app.

[1230] Example prompt sentence:

[1231] User message: "I'm so stressed today"

[1232] Extracted keywords: ["stress"]

[1233] Extracted sentiment: ["Negative"]

[1234] Generate relevant content suggestions: "Relaxation Music", "Nature Videos", "Soothing Articles"

[1235] The user selects and plays relaxation music.

[1236] As described above, the system of the present invention can be operated intuitively by the user and makes communication more enjoyable and lively by providing stamps and content that are optimal for specific situations and emotions.

[1237] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1238] Step 1:

[1239] Receiving and parsing messages

[1240] The server receives messages sent by users. The received message text is given as input. The server uses natural language processing (NLP) techniques to analyze the message text. This analysis uses the Google Cloud Natural Language API to extract keywords and emotional information. An emotion engine (e.g., IBM Watson's Tone Analyzer) is used to recognize emotional information (e.g., "stress," "joy," "sadness," etc.) from the message. Data containing keywords and emotional information is generated as output.

[1241] Step 2:

[1242] Generate illustrations and short messages

[1243] The server receives the extracted keywords and emotion information as input and generates related illustrations and short messages using artificial intelligence (AI) technology, such as OpenAI's GPT-3 and DALL-E. Based on the recognition results of the emotion engine, the server determines the priority of the stamp candidates to be generated. The output is data containing multiple stamp candidates.

[1244] Step 3:

[1245] Content Recommendations

[1246] The server recommends appropriate content based on the message and emotional information. Extracted keywords and emotional information are given as input. AI technology is used to evaluate and select appropriate content (e.g., movies, music, articles, etc.). The output is data containing multiple content candidates.

[1247] Step 4:

[1248] Submit sticker and content suggestions

[1249] The server organizes the generated stamps and content candidates and sends them to the user's device. The generated stamps and content candidate data are given as input. The sent stamps and content candidates are displayed on the user's device as output.

[1250] Step 5:

[1251] Receive and display stamps and content suggestions

[1252] The terminal receives the stamps and content candidates sent from the server. The data received from the server is given as input. The terminal provides an intuitive and easy-to-select interface for the user, visually displaying the stamps and content candidates. As output, the displayed stamps and content candidates are provided to the user.

[1253] Step 6:

[1254] Selecting, sending, and playing stamps and content

[1255] The user selects the stamps and content they like. The terminal sends the selection information to the server. The input is the stamps and content information selected by the user. The output is the selected stamps displayed on the other party's chat screen and the content is played.

[1256] The above are the specific processing steps and operations of the system program that realizes this application example. This program allows users to intuitively select the most appropriate stamps and content based on their message and emotion, improving the quality of their communication.

[1257] 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.

[1258] 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.

[1259] 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.

[1260] [Fourth embodiment]

[1261] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1262] 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.

[1263] 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).

[1264] 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.

[1265] 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.

[1266] 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).

[1267] 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. 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.

[1268] 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.

[1269] 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.

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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."

[1274] MODE FOR CARRYING OUT THE INVENTION

[1275] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. This system has the function of analyzing the user's message and generating an appropriate illustration and a short message to accompany it. Below, we will explain the operation of the system in detail from the perspectives of the server, terminal, and user.

[1276] Server Processing

[1277] 1. Receiving and parsing messages

[1278] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) to extract keywords and emotional information. For example, if a message is received saying "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted.

[1279] 2. Creating illustrations and short messages

[1280] The server generates an appropriate illustration and message based on the extracted keywords and emotional information. The generation is done using artificial intelligence (AI), and multiple candidates are created. For example, for the keyword "I'm getting late," a stamp is generated that combines an illustration of a sleeping cat with the message "I'm late, but I'm doing my best!"

[1281] 3. Submit your stamp suggestions

[1282] The server sends the generated stamp candidates to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation.

[1283] Terminal handling

[1284] 1. Receiving and displaying stamp candidates

[1285] The terminal receives the stamp candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface.

[1286] 2. Select and send stamps

[1287] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[1288] User operations

[1289] 1. Enter your message

[1290] The user opens the LINE application, types a message, and presses the send button. For example, they might type, "I'm going to be late today..."

[1291] 2. Select a stamp

[1292] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[1293] 3. Sending stamps

[1294] Once you have completed your selection, the stamp will appear on the other person's LINE chat screen.

[1295] Specific examples

[1296] For example, if a user sends a message saying, "I think I'll be late today...", the server analyzes this message and extracts the keyword "I'll be late". It then generates an illustration of a "sleeping cat" and a message saying, "I'm late, but I'll do my best!" This stamp is presented to the user along with other options such as "A rabbit looking at the clock" (Sorry I'm late!). The user selects "sleeping cat" and sends the stamp, and the original stamp is displayed to the recipient.

[1297] As described above, the present invention is a system that can be operated intuitively by the user and that makes communication more enjoyable and lively by providing original stamps suited to specific situations.

[1298] The processing flow will be explained below.

[1299] Program processing steps

[1300] User message entry and sending

[1301] Step 1:

[1302] The user opens the LINE application and types a message.

[1303] For example, a user types "I'm going to be late today..." and presses the send button.

[1304] Receiving and parsing messages

[1305] Step 2:

[1306] The terminal sends the message data (text, user ID, timestamp) entered by the user to the server.

[1307] Step 3:

[1308] The server analyzes the received message data.

[1309] Natural language processing (NLP) techniques are used to extract keywords (e.g., "slow") and emotional information (e.g., "fatigue") from messages.

[1310] Generate illustrations and short messages

[1311] Step 4:

[1312] The server's AI generates related illustrations and short messages based on the extracted keywords and emotional information.

[1313] For example, for the keyword "getting late," a stamp is generated that combines an illustration of a sleeping cat with a one-line message: "It's late, but do your best!"

[1314] Submit a stamp suggestion

[1315] Step 5:

[1316] The server organizes the generated stamp candidates and transmits them to the user's terminal.

[1317] For example, some possible phrases include "The cat is sleeping" (It's late, but do your best!) and "The rabbit is looking at the clock" (Sorry I'm late!).

[1318] Displaying and selecting stamp candidates

[1319] Step 6:

[1320] The terminal visually displays the received stamp candidates to the user.

[1321] To arrange stamp candidates on an interface so that the user can easily understand them.

[1322] Step 7:

[1323] The user selects the stamp they like by tapping on it from the displayed stamp candidates.

[1324] For example, select the "Cat Sleeping" stamp and press the send button.

[1325] Send selected stamps

[1326] Step 8:

[1327] The terminal sends the stamp data (stamp ID, user ID, timestamp) selected by the user to the server.

[1328] Step 9:

[1329] Based on the stamp selection data received by the server, the selected stamp is processed and information on the sender and destination is recorded.

[1330] Step 10:

[1331] The server transmits the stamp data to the other terminal.

[1332] Displaying stamps

[1333] Step 11:

[1334] The terminal on the other side displays the stamp data received from the server.

[1335] For example, the "Cat is sleeping" stamp (slow but good luck!) will appear on the other person's LINE chat screen.

[1336] Example 1

[1337] 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."

[1338] Conventional messaging applications require users to manually select stamps, which can be time-consuming and time-consuming to find the appropriate stamp. It can also be difficult to obtain the optimal stamp based on the content of a user's message, which can disrupt smooth communication. The purpose of this invention is to simplify user operations and improve the quality of communication by automatically generating and presenting the optimal stamp based on the user's message.

[1339] 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.

[1340] In this invention, the server includes means for analyzing a message received from a user, means for generating multiple illustrations and a short message based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, means for generating an illustration and a short message using a generative AI model, and means for inputting the illustration and the short message into the generative AI model based on a prompt sentence. This allows the server to automatically generate the optimal stamp based on the content of the user's message, allowing the user to easily select and send the stamp.

[1341] The "means for analyzing messages received from users" is a function for analyzing messages sent by users and extracting information such as meaning and emotion.

[1342] "Means for generating multiple illustrations and short messages based on the analysis results" refers to a function that uses AI to create multiple illustrations and accompanying short messages based on the information obtained through the analysis.

[1343] The "means for displaying a list of multiple candidates that can be selected by the user" is a function that displays multiple stamp candidates sent from the server on the terminal screen, allowing the user to select from among them.

[1344] The "means for transmitting the selected stamp" is a function for transmitting the stamp selected by the user to the other party's terminal.

[1345] A "generative AI model" is a model trained using artificial intelligence algorithms that generates illustrations and messages based on specific prompts.

[1346] The "means for inputting into the generative AI model based on the prompt sentence" is a function for inputting into the AI ​​model based on extracted keywords and emotional information, and generating an illustration and a short message as a result.

[1347] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. This system analyzes the user's message and generates appropriate illustrations and short messages, facilitating smooth communication.

[1348] Server Processing

[1349] The server receives messages sent by users. These received messages are analyzed using natural language processing (NLP) tools. For example, Python libraries such as NLTK and spaCy are used. As a result of the analysis, keywords and emotional information are extracted from the message. For example, from the message "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted.

[1350] The server then uses a generative AI model, which utilizes a pre-trained algorithm such as GPT-3, to generate an illustration and a short message based on the extracted keywords and emotional information. The prompt is then input to the generative AI model.

[1351] Example prompt sentence:

[1352] User message: "Looks like I'm going to be late today..."

[1353] Keywords: ["running late", "tired"]

[1354] Emotion: ["fatigue"]

[1355] Generate an illustration and a short message.

[1356] Based on this prompt, the generative AI model generates multiple combinations of illustrations and one-line messages. For example, for the keyword "I'm getting late," it generates an illustration of a "sleeping cat" and the one-line message "It's late, but do your best!"

[1357] The generated stamp candidates are sent from the server to the user's device via the server's API, and multiple candidates are presented to the user.

[1358] Terminal handling

[1359] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The terminal provides an intuitive and easy-to-use GUI (Graphical User Interface). The user can then select the stamp they like from the displayed candidates.

[1360] When a user selects a stamp, the selection information is sent from the device to the server. This information includes the selected stamp ID and the user ID. Finally, the selected stamp is sent to the other device and displayed on the LINE chat screen.

[1361] User operations

[1362] The user opens the LINE application, types a message, and sends it. For example, they type "I'm going to be late today..." and press the send button. The server then displays multiple stamp candidates on the user's device. The user selects the stamp they like by tapping it. For example, if the user selects the "sleeping cat" stamp, that stamp will be sent to the other person and will appear on their LINE chat screen.

[1363] In this way, the system of the present invention can be operated intuitively by the user and makes communication more enjoyable and lively by providing original stamps suited to specific situations.

[1364] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1365] Step 1:

[1366] Receiving messages (server)

[1367] The server receives a message sent by the user. This message also includes the user ID and message ID. The input is the text message entered by the user in the LINE application, and the output is structured data for storing this message in a database. Specifically, the server sends the received message to an API endpoint and stores it in the database.

[1368] Step 2:

[1369] Message analysis (server)

[1370] The server analyzes the received message. Natural language processing (NLP) tools are used for the analysis. The input is the received message text, and the output is extracted keywords and emotional information. For example, from the message "I'm going to be late today...", keywords such as "I'm going to be late" and "I'm tired" and emotional information such as "fatigue" are extracted. Specifically, keywords and emotional information are extracted from the text using Python libraries such as NLTK and spaCy.

[1371] Step 3:

[1372] Prompt statement generation (server)

[1373] The server generates a prompt sentence to be input into the generative AI model based on the extracted keywords and emotional information. The input is the extracted keywords and emotional information, and the output is a prompt sentence suitable for the generative AI model. Specifically, it combines the keyword "I'm going to be late" with the emotional information "fatigue" to generate the prompt sentence: "User message: "I'm going to be late today..." Keywords: ["I'm going to be late", "Tired"] Emotion: ["Fatigue"] Generate an illustration and a short message."

[1374] Step 4:

[1375] Illustration and message generation (server)

[1376] The server inputs the generated prompt into a generative AI model to generate an illustration and a one-line message. The input is the generated prompt, and the output is a combination of multiple illustrations and one-line messages generated by the AI ​​model. Specifically, the prompt is input into a generative AI model such as GPT-3, generating an illustration of a "sleeping cat" and a message such as "You're slow, but keep trying!"

[1377] Step 5:

[1378] Sending stamp candidates (server)

[1379] The server sends the generated stamp candidates to the user's device. The input is multiple stamp candidates generated by the AI ​​model, and the output is the stamp candidates sent to the user's device. Specifically, the generated stamp candidates are sent to the user's device via API.

[1380] Step 6:

[1381] Receiving and displaying stamp candidates (device)

[1382] The terminal receives the stamp candidates sent from the server and displays them to the user. The input is the stamp candidates sent from the server, and the output is a list of stamp candidates displayed on the terminal. Specifically, the system receives the stamp candidates and displays them to the user using an intuitive GUI.

[1383] Step 7:

[1384] Stamp Selection (User)

[1385] The user selects the stamp they like from the displayed stamp candidates. The input is the stamp candidates visually confirmed by the user, and the output is the ID of the stamp selected by the user. Specifically, the user taps on the stamp they like to select it.

[1386] Step 8:

[1387] Send stamp selection information (device)

[1388] The terminal sends the stamp information selected by the user to the server. The input is the ID of the stamp selected by the user, and the output is the stamp selection information sent to the server. Specifically, the terminal sends the ID of the selected stamp to the server's API.

[1389] Step 9:

[1390] Sending stamps (server)

[1391] The server sends the stamp selected by the user to the other device. The input is the ID of the selected stamp and the user ID of the recipient, and the output is the stamp image sent to the other device. Specifically, the image data of the selected stamp is sent to the other device via API.

[1392] Step 10:

[1393] Displaying stamps (on the recipient's device)

[1394] The other device will display the received stamp on the LINE chat screen. The input is the received stamp image data, and the output is the stamp image displayed on the LINE chat screen. The specific operation is to display the received image data within the LINE application.

[1395] In this way, through a series of steps, the most suitable stamp based on the user's message is automatically generated, and the user can select and send it.

[1396] (Application example 1)

[1397] 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."

[1398] In modern messaging applications, users must manually select stickers to appropriately express their emotions and situations. This can be time-consuming and difficult to find. Furthermore, when there are too many sticker options, users can become overwhelmed. Furthermore, there is no mechanism for providing stickers that can quickly and accurately respond to a user's message. To solve these problems, a system is needed that can analyze a user's messages in real time, automatically generate appropriate stickers based on the analysis results, and present them to the user.

[1399] 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.

[1400] In this invention, the server includes means for analyzing messages received from users, means for generating multiple illustrations and short messages based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, and means for presenting the generated stamp candidates to the user in order of priority, thereby enabling the user to quickly and easily select and send the stamp that best suits the message content.

[1401] A "user" is a person who uses the system.

[1402] A "message" is text information sent by a user through a communication application.

[1403] The "analysis means" is a function that uses natural language processing technology to analyze messages received from users and extract keywords and emotional information.

[1404] An "illustration" is an image that visually expresses a user's emotions or situation.

[1405] A "one-line message" is a short piece of text that explains an emotion or situation in combination with an illustration.

[1406] "Means of generation" is a function that creates stamps by combining illustrations and short messages based on the analysis results.

[1407] The "display means" is a function that provides an interface that visually presents a plurality of candidates from among the generated stamps to the user and allows the user to select one.

[1408] The "transmission means" is a function for transmitting the stamp selected by the user to the recipient.

[1409] "Stamp candidates" are multiple stamp options that are generated based on the user's analysis of the message and presented to the user for selection.

[1410] The "order of priority" is a criterion for displaying the generated stamp candidates in the most appropriate order based on the content of the user's message and the situation.

[1411] This invention is a system that analyzes messages sent by users through messaging applications and generates and presents appropriate illustrations and short messages (stamps) based on the analysis results. Users can easily communicate by selecting from the presented stamp candidates.

[1412] Server Processing

[1413] Receiving and parsing messages

[1414] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) technology to extract keywords and emotional information. The specific software used is the OpenAI API.

[1415] Generate illustrations and short messages

[1416] The server generates an appropriate illustration and a short message based on the extracted keywords and emotional information. The generation is done using artificial intelligence (AI), and multiple candidates are created. For example, if a user sends a message saying, "I'm going to be late today...", the keyword "I'm going to be late" is extracted, and a stamp is generated that combines an illustration of a sleeping cat with the message, "I'm late, but I'll do my best!"

[1417] Submit a stamp suggestion

[1418] The server sends the generated stamp candidates to the user's device. The stamp candidates are prioritized based on the user's message content and emotions, allowing the user to select the stamp that best suits the situation.

[1419] Terminal handling

[1420] Receiving and displaying stamp suggestions

[1421] The terminal receives the stamp candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface.

[1422] Select and send stamps

[1423] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp's ID, the user ID, and a timestamp.

[1424] User operations

[1425] Enter your message

[1426] A user opens a chat application, types a message, and hits send, for example, "I'm going to be late today..."

[1427] Select a stamp

[1428] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[1429] Sending stamps

[1430] Once you have completed your selection, the stamp will appear on the other person's chat screen.

[1431] Prompt Sentence Examples

[1432] Extract sentiment and keywords from the following messages:

[1433] Message: "Looks like I'll be late today..."

[1434] This system is expected to enable users to intuitively and quickly select and send stamps that suit the content of their messages, facilitating smooth communication.

[1435] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1436] Step 1:

[1437] The server gets the message received from the user. The input is the message sent by the user and the output is the received message data, which is kept for the next analysis step.

[1438] Step 2:

[1439] The server analyzes the received message using natural language processing technology. The input is the message data from step 1, and the output is the analyzed keywords and emotional information. The server uses OpenAI's API to extract important keywords and emotions from the message content. This analyzed information becomes the basic data for generating stamps.

[1440] Step 3:

[1441] The server generates multiple illustrations and short messages based on the analysis results. The input is the analysis information from step 2, and the output is the generated stamp candidates. The server uses an artificial intelligence model to generate multiple stamps that combine illustrations and short messages that match the extracted keywords and emotional information.

[1442] Step 4:

[1443] The server sends the generated stamp candidates to the terminal. The input is the stamp candidates from step 3, and the output is the stamp data sent to the terminal. The stamp candidates are sorted based on priority and presented in a format that makes it easy for the user to select.

[1444] Step 5:

[1445] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The input is the stamp data from step 4, and the output is the display to the user. The terminal provides an intuitive and easy-to-use user interface and presents multiple stamp candidates to the user.

[1446] Step 6:

[1447] The user selects the stamp they like from the displayed stamp candidates. The input is the stamp candidates displayed in step 5, and the output is the selected stamp information. The user selects a stamp with simple operations such as tapping or clicking, and the information is stored on the device.

[1448] Step 7:

[1449] The terminal sends the stamp selected by the user to the server. The input is the stamp information selected in step 6, and the output is the stamp information sent to the server. This information includes the stamp ID, user ID, timestamp, etc.

[1450] Step 8:

[1451] The server finally sends the selected stamp to the recipient. The input is the stamp information from step 7, and the output is the stamp sent to the recipient. This causes the selected stamp to be displayed on the recipient's chat screen.

[1452] The above processing steps realize a system in which appropriate stamps are automatically generated based on the user's message, and the user can easily select and send them.

[1453] 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.

[1454] MODE FOR CARRYING OUT THE INVENTION

[1455] The system of the present invention automatically generates optimal stamps based on a user's message in a messaging application, allowing the user to select and send them. Furthermore, by incorporating an emotion engine, the system enhances its functionality of recognizing the user's emotions and providing stamps that correspond to them. The system analyzes the user's message, extracts keywords containing emotional information, and generates an appropriate illustration and accompanying message. The operation of the system is specifically described below from the perspectives of the server, terminal, and user.

[1456] Server Processing

[1457] 1. Receiving and parsing messages

[1458] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) technology to extract keywords and emotional information. An emotion engine is used to recognize emotional information (e.g., "joy," "sadness," "anger," etc.) from the messages. For example, if a message is received saying, "I'm going to be late today...," keywords such as "I'm going to be late" and "I'm tired" and the emotional information of "fatigue" are extracted.

[1459] 2. Creating illustrations and short messages

[1460] The server generates related illustrations and short messages based on the extracted keywords and emotional information. This generation uses artificial intelligence (AI) to create multiple stamp candidates. The priority of the stamp candidates to be generated is determined based on the recognition results of the emotion engine. For example, for the emotion "tired," a stamp combining an illustration of a "sleeping cat" and a short message such as "It's late, but do your best!" is generated.

[1461] 3. Submit your stamp suggestions

[1462] The server organizes the generated stamp candidates and sends them to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation. The most suitable candidates are displayed at the top based on a priority order based on emotional information.

[1463] Terminal handling

[1464] 1. Receiving and displaying stamp candidates

[1465] The device receives the sticker candidates sent from the server and visually displays them to the user. The display method is provided with an intuitive and easy-to-select interface. The stickers are prioritized based on emotion, so the most suitable ones are displayed first.

[1466] 2. Select and send stamps

[1467] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[1468] User operations

[1469] 1. Enter your message

[1470] The user opens the LINE application, types a message, and presses the send button. For example, they might type, "I'm going to be late today..."

[1471] 2. Select a stamp

[1472] The stamp candidates sent from the server are displayed on the device, and the user can select the stamp they like by tapping it. For example, they can select the "sleeping cat" stamp.

[1473] 3. Sending stamps

[1474] Once you have completed your selection, the stamp will appear on the other person's LINE chat screen.

[1475] Specific examples

[1476] For example, if a user sends a message saying, "I'm going to be late today...", the server analyzes the message and extracts keywords such as "I'm going to be late" and "I'm tired" as well as the emotional information of "fatigue".The server then generates an illustration of a "sleeping cat" and a message saying, "I'm late, but keep trying!" and presents them to the user along with other options.The user selects "sleeping cat" from the list and sends it, and the original stamp is displayed to the recipient.

[1477] As described above, the present invention is a system that can be intuitively operated by the user and makes communication more enjoyable and lively by providing original stamps that are best suited to specific situations and emotions.

[1478] The processing flow will be explained below.

[1479] MODE FOR CARRYING OUT THE INVENTION (PROCESSING STEPS)

[1480] User message entry and sending

[1481] Step 1:

[1482] The user opens the messaging application and types a message.

[1483] For example, a user types "I'm going to be late today..." and presses the send button.

[1484] Receiving and parsing messages

[1485] Step 2:

[1486] The terminal sends the message data (text, user ID, timestamp) entered by the user to the server.

[1487] Step 3:

[1488] The server analyzes the received message data.

[1489] Natural language processing (NLP) techniques are used to analyze messages and extract keywords (e.g., "slow") and emotional information (e.g., "fatigue").

[1490] Step 4:

[1491] The server uses an emotion engine to recognize emotion information from the extracted keywords and message content.

[1492] For example, the emotional information "fatigue" is recognized from "I'm going to be late today..."

[1493] Generate illustrations and short messages

[1494] Step 5:

[1495] The server's AI generates an appropriate illustration and a short message based on the extracted keywords and recognized emotional information.

[1496] For example, for the keyword "getting late" and the emotional information "fatigue," a stamp is generated that combines an illustration of a "sleeping cat" with a one-line message such as "It's late, but do your best!"

[1497] Step 6:

[1498] The server creates multiple stamp candidates and organizes them by prioritizing them based on emotional information.

[1499] For example, create suggestions such as "The cat is sleeping" (It's late, but do your best!) and "The rabbit is looking at the clock" (Sorry I'm late!) and prioritize them.

[1500] Submit a stamp suggestion

[1501] Step 7:

[1502] The server transmits the generated stamp candidates to the terminal.

[1503] Prioritize your search so that the best candidates are displayed at the top.

[1504] Displaying and selecting stamp candidates

[1505] Step 8:

[1506] The terminal visually displays the received stamp candidates to the user.

[1507] For example, the interface displays "A cat is sleeping" and "A rabbit is looking at the clock" in that order.

[1508] Step 9:

[1509] The user selects the stamp they like by tapping on it from the displayed stamp candidates.

[1510] For example, select the "Cat Sleeping" stamp and press the send button.

[1511] Send selected stamps

[1512] Step 10:

[1513] The terminal sends the stamp data (stamp ID, user ID, timestamp) selected by the user to the server.

[1514] Step 11:

[1515] Based on the stamp selection data received by the server, the selected stamp is processed and information on the sender and destination is recorded.

[1516] Step 12:

[1517] The server transmits the stamp data to the other terminal.

[1518] Displaying stamps

[1519] Step 13:

[1520] The terminal on the other side displays the stamp data received from the server.

[1521] For example, the "Cat is sleeping" stamp (slow but good luck!) will appear on the other person's LINE chat screen.

[1522] Example 2

[1523] 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."

[1524] In conventional messaging applications, users had to manually select stickers for messages they sent, making it difficult to quickly provide stickers that were optimal for specific situations or emotions. Furthermore, the lack of sticker suggestions based on the user's emotions made it difficult to make communication more personalized and smooth.

[1525] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1526] In this invention, the server includes means for analyzing messages received from users and extracting keywords and emotional information, means for generating multiple illustrations and short messages based on the analysis results, means for prioritizing the generated multiple stamp candidates based on the emotional information and displaying them so that the user can select one, and means for transmitting the selected stamp. This makes it possible to automatically generate and provide stamps that are optimal for messages sent by users, thereby realizing more personalized communication.

[1527] A "User" is an individual or entity that sends or receives messages through a messaging application.

[1528] "Receiving" is the act of the server obtaining a message sent by a user.

[1529] A "message" is text information that a user sends through a messaging application.

[1530] "Analysis" is the process of breaking down the content of a received message and extracting meaning, keywords, and emotional information.

[1531] "Keywords" are words or phrases that carry significant meaning in a message.

[1532] "Emotion information" is data that represents the user's emotions extracted from the message.

[1533] "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language.

[1534] An "emotion engine" is software or hardware that analyzes and recognizes a user's emotions from the content of a message.

[1535] "Illustration" refers to an image or picture used as a stamp.

[1536] A "one-line message" is a short text message that accompanies an illustration.

[1537] An "artificial intelligence model" is a computational model that learns from data and automates specific tasks.

[1538] "Stamp candidates" are multiple stamp options presented to the user.

[1539] "Priority" refers to the order in which stamp candidates are arranged based on emotion information.

[1540] A "selectable display" is an interface that allows the user to select one stamp from among multiple stamp candidates.

[1541] A "selected stamp" is a specific stamp that the user selects from among multiple stamp candidates.

[1542] "Send" is the act of sending the selected stamp from the server to the recipient's terminal.

[1543] A "system" is a set of hardware and software that integrates these means to provide a specific function.

[1544] MODE FOR CARRYING OUT THE INVENTION

[1545] The system of this invention automatically generates optimal stamps based on messages sent by users in a messaging application, allowing users to select and send them. Furthermore, by using an emotion engine, the system recognizes the user's emotions and provides corresponding stamps. The configuration and operation of this system are described in detail below.

[1546] Server Processing

[1547] 1. Receiving and parsing messages

[1548] The server receives messages sent by users. The messaging application used can be a commonly used messaging application, such as LINE or SNS Messenger.

[1549] Received messages are analyzed using natural language processing (NLP) technology. During this analysis, keywords and emotional information are extracted. By using an emotion engine, the system can recognize the user's emotions into categories such as "happiness," "sadness," and "anger."

[1550] Examples:

[1551] If a user sends a message saying "I'm going to be late today...", the server extracts keywords such as "I'm going to be late" and "I'm tired" as well as emotion information such as "fatigue".

[1552] 2. Creating illustrations and short messages

[1553] The server generates related illustrations and short messages based on the extracted keywords and emotional information, using an artificial intelligence (AI) model, specifically a generative AI model.

[1554] Based on the recognition results of the emotion engine, the priority of the stamp candidates to be generated is determined.

[1555] Examples:

[1556] For the emotion "tired," a stamp is generated that combines an illustration of a "sleeping cat" with a one-line message such as "It's late, but do your best!"

[1557] 3. Submit your stamp suggestions

[1558] The server sends the generated stamp candidates to the user's device. By presenting multiple candidates, the user can select the stamp that best suits the situation. The most suitable candidates are displayed at the top based on a priority order based on emotion information.

[1559] Terminal handling

[1560] 1. Receiving and displaying stamp candidates

[1561] The device receives the sticker candidates sent from the server and visually displays them to the user. The display method is provided with an intuitive and easy-to-select interface. The stickers are prioritized based on emotion, so the most suitable ones are displayed first.

[1562] Examples:

[1563] The "sleeping cat" stamp will appear first on the device screen, followed by another stamp.

[1564] 2. Select and send stamps

[1565] When a user selects a stamp they like, the device sends the selection information to the server, including the stamp ID, user ID, and timestamp.

[1566] User operations

[1567] 1. Enter your message

[1568] The user opens the messaging application, types a message, and presses the send button.

[1569] Examples:

[1570] Type "I'm going to be late today..." and send it.

[1571] 2. Select a stamp

[1572] Stamp candidates sent from the server are displayed on the device, and the user can tap to select the stamp they like.

[1573] Examples:

[1574] Select the "Sleeping cat" stamp.

[1575] 3. Sending stamps

[1576] Once you have completed your selection, the stamp will appear on the other person's chat screen.

[1577] Prompt Sentence Examples

[1578] The following prompts can be fed into the generative AI model to explain the system's detailed behavior:

[1579] Messages sent by users are analyzed using natural language processing technology, and emotional information is extracted using an emotion engine. Based on this emotional information, AI is used to generate related illustrations and short messages. The generated stamp candidates are displayed to the user in a prioritized order, and a system is built that reflects the user's selection.

[1580] Through these steps, the system extracts emotions and keywords from the message entered by the user and provides the most appropriate stamps based on these, thereby realizing a more personalized communication experience.

[1581] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1582] Step 1:

[1583] Receiving messages

[1584] The server receives messages sent by users. The data received from the messaging application (input) is the text message typed by the user. This message data is passed to the server's parsing process (output).

[1585] Specific example of operation: When a user sends a message such as "I'm going to be late today..." in an application, this text data is sent to the server.

[1586] Step 2:

[1587] Message Parsing

[1588] The server analyzes the received message data using natural language processing (NLP) technology. The input is the received message data, and keywords and emotional information are extracted during the analysis process. The output is the extracted keywords and emotional information.

[1589] Specific example of operation: Analyze the message "I think I'll be late today..." and extract the keyword "I'll be late" and the emotional information "fatigue."

[1590] Step 3:

[1591] Generate illustrations and short messages

[1592] The server uses an artificial intelligence (AI) model to generate related illustrations and short messages based on the extracted keywords and emotional information. The input is the extracted keywords and emotional information, and the output is multiple stamp candidates.

[1593] Specific example of operation: In response to the emotional information "fatigue," an AI model is used to generate an illustration of a "sleeping cat" and a one-line message saying "You're slow, but keep trying!"

[1594] Step 4:

[1595] Prioritize and send sticker suggestions

[1596] The server prioritizes the generated stamp candidates based on emotion information and sends them to the user's device. The input is the generated stamp candidates, and the prioritized stamp candidates are sent to the device (output).

[1597] Specific example of operation: The generated "Cat sleeping" stamp is placed at the top, and multiple stamp candidates including it are sent to the user's device.

[1598] Step 5:

[1599] Receiving and displaying stamp suggestions

[1600] The terminal receives the stamp candidates sent from the server and visually displays them to the user. The input is the stamp candidate data sent from the server, and the output is a list of stamp candidates displayed on the user interface.

[1601] Specific example of operation: The "Cat sleeping" stamp will be displayed on the device screen first, followed by other stamps.

[1602] Step 6:

[1603] Select a stamp

[1604] The user selects the stamp they like from the displayed stamp candidates. The input is multiple stamp candidates, and the output is the ID of the stamp selected by the user.

[1605] Specific example of operation: When the user taps the "sleeping cat" stamp, that stamp is selected.

[1606] Step 7:

[1607] Send selected stamps

[1608] The terminal sends the stamp information selected by the user to the server, which receives it and displays the stamp on the other party's chat screen. The input is the selected stamp ID, user ID, and timestamp, and the output is the stamp displayed on the other party's chat screen.

[1609] Specific example of operation: When a user selects the "sleeping cat" stamp, the information is sent to the server and displayed on the other person's chat screen.

[1610] (Application example 2)

[1611] 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."

[1612] Existing messaging applications lack functionality to help users quickly respond appropriately based on their emotions and the content of their messages. Furthermore, selecting the most appropriate content (e.g., movies, music, articles, etc.) based on emotions can be time-consuming, potentially reducing the quality of communication and engagement. This invention solves these issues by providing a function that automatically recommends the most appropriate stickers and content based on the user's message and emotions.

[1613] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing a message received from a user, means for generating multiple illustrations and short messages based on the analysis results, means for displaying the generated candidates so that the user can select one, means for sending the selected stamp, and means for recommending content based on the user's message and emotions. This enables the user to quickly receive appropriate stamps and content based on the message and emotions, thereby improving the quality of communication and engagement.

[1614] The "means for analyzing messages received from users" refers to a function that enables the platform to receive messages sent by users and analyze their contents using natural language processing technology.

[1615] The "means for generating multiple illustrations and one-line messages based on the analysis results" is a function that uses artificial intelligence technology to generate many candidate illustrations and suitable one-line messages based on the content and emotional information of the analyzed message.

[1616] The "means for displaying a selection from multiple generated candidates to the user" is an interface that displays the many generated stamp candidates on the user's terminal and allows the user to select the appropriate stamp from among them.

[1617] The "means for transmitting the selected stamp" is a function for transmitting the stamp selected by the user to the recipient user.

[1618] "Means for recommending content based on a user's message and emotions" refers to an evaluation and selection function that extracts the content of a user's message and emotional information, and then recommends the most appropriate content, such as movies, music, or articles, that correspond to them.

[1619] The system of the present invention is a content distribution service that automatically generates optimal stamps and content based on a user's message and emotions, allowing the user to select, send, and play them. This system has the functionality to operate on both the server and the user's terminal. The operation of the system will be specifically explained below from the perspectives of the server, the terminal, and the user.

[1620] Server Processing

[1621] 1. Receiving and parsing messages

[1622] The server receives messages sent by users. The received messages are analyzed using natural language processing (NLP) techniques to extract keywords and emotional information. This analysis is performed using the Google Cloud Natural Language API. An emotional engine (e.g., IBM Watson's Tone Analyzer) is used to recognize emotional information (e.g., "stress," "joy," "sadness," etc.) from the messages.

[1623] 2. Creating illustrations and short messages

[1624] The server generates related illustrations and short messages based on the extracted keywords and emotion information. This generation uses artificial intelligence (AI) technology (e.g., OpenAI's GPT-3 and DALL-E). Based on the recognition results of the emotion engine, the server determines the priority of the sticker candidates to be generated.

[1625] 3. Content Recommendations

[1626] The server has an evaluation and selection function to recommend appropriate content (e.g., movies, music, articles, etc.) based on the corresponding message and emotional information. These contents are organized to prioritize the most appropriate content for the user.

[1627] 4. Submit sticker and content suggestions

[1628] The server organizes the generated stamps and content candidates and sends them to the user's device. By presenting multiple candidates, the user can select the stamps and content that best suit the situation.

[1629] Terminal handling

[1630] 1. Receiving and displaying stamps and content suggestions

[1631] The terminal receives the stamps and content candidates sent from the server and visually displays them to the user, providing an intuitive and easy-to-select interface for the display method.

[1632] 2. Select stamps and content, and send and play them

[1633] When a user selects a stamp or content they like, the device sends the selection information to the server, including the stamp ID, content information, user ID, timestamp, etc. The content selected by the user is then played or provided immediately.

[1634] User operations

[1635] 1. Enter your message

[1636] A user opens the application, types a message, and hits send, for example, "I'm feeling very stressed today."

[1637] 2. Select stamps and content

[1638] The stamps and content candidates sent from the server are displayed on the device, and the user can select the stamps or content they like by tapping on them. For example, they can select "Relaxation Music."

[1639] 3. Sending stamps and playing content

[1640] Once the selection is complete, the stamp will appear on the other person's chat screen and the content will be played on the spot.

[1641] Examples of specific examples and prompts

[1642] For example, if a user sends a message saying, "I'm feeling very stressed today," the server analyzes the message and extracts the keyword "stress" and the emotional information "negative." Potential content, such as relaxation music, nature videos, and soothing articles, are then generated and presented to the user. The user selects "relaxation music" from the list and plays it within the app.

[1643] Example prompt sentence:

[1644] User message: "I'm so stressed today"

[1645] Extracted keywords: ["stress"]

[1646] Extracted sentiment: ["Negative"]

[1647] Generate relevant content suggestions: "Relaxation Music", "Nature Videos", "Soothing Articles"

[1648] The user selects and plays relaxation music.

[1649] As described above, the system of the present invention can be operated intuitively by the user and makes communication more enjoyable and lively by providing stamps and content that are optimal for specific situations and emotions.

[1650] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1651] Step 1:

[1652] Receiving and parsing messages

[1653] The server receives messages sent by users. The received message text is given as input. The server uses natural language processing (NLP) techniques to analyze the message text. This analysis uses the Google Cloud Natural Language API to extract keywords and emotional information. An emotion engine (e.g., IBM Watson's Tone Analyzer) is used to recognize emotional information (e.g., "stress," "joy," "sadness," etc.) from the message. Data containing keywords and emotional information is generated as output.

[1654] Step 2:

[1655] Generate illustrations and short messages

[1656] The server receives the extracted keywords and emotion information as input and generates related illustrations and short messages using artificial intelligence (AI) technology, such as OpenAI's GPT-3 and DALL-E. Based on the recognition results of the emotion engine, the server determines the priority of the stamp candidates to be generated. The output is data containing multiple stamp candidates.

[1657] Step 3:

[1658] Content Recommendations

[1659] The server recommends appropriate content based on the message and emotional information. Extracted keywords and emotional information are given as input. AI technology is used to evaluate and select appropriate content (e.g., movies, music, articles, etc.). The output is data containing multiple content candidates.

[1660] Step 4:

[1661] Submit sticker and content suggestions

[1662] The server organizes the generated stamps and content candidates and sends them to the user's device. The generated stamps and content candidate data are given as input. The sent stamps and content candidates are displayed on the user's device as output.

[1663] Step 5:

[1664] Receive and display stamps and content suggestions

[1665] The terminal receives the stamps and content candidates sent from the server. The data received from the server is given as input. The terminal provides an intuitive and easy-to-select interface for the user, visually displaying the stamps and content candidates. As output, the displayed stamps and content candidates are provided to the user.

[1666] Step 6:

[1667] Selecting, sending, and playing stamps and content

[1668] The user selects the stamps and content they like. The terminal sends the selection information to the server. The input is the stamps and content information selected by the user. The output is the selected stamps displayed on the other party's chat screen and the content is played.

[1669] The above are the specific processing steps and operations of the system program that realizes this application example. This program allows users to intuitively select the most appropriate stamps and content based on their message and emotion, improving the quality of their communication.

[1670] 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.

[1671] 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.

[1672] 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.

[1673] 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.

[1674] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1675] 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.

[1676] 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).

[1677] 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.

[1678] 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."

[1679] 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.

[1680] 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).

[1681] 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.

[1682] 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.

[1683] 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.

[1684] 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.

[1685] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1686] 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.

[1687] 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.

[1688] 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.

[1689] 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.

[1690] 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.

[1691] The following is further disclosed regarding the above embodiment.

[1692] (Claim 1)

[1693] means for analyzing messages received from users;

[1694] A means for generating multiple illustrations and short messages based on the analysis results;

[1695] a display means for displaying the generated candidates so that the user can select one from the plurality of candidates;

[1696] means for transmitting the selected stamp;

[1697] A system including:

[1698] (Claim 2)

[1699] 10. The system of claim 1, wherein natural language processing is used to analyze the message.

[1700] (Claim 3)

[1701] The system of claim 1 uses artificial intelligence to generate the illustrations and one-line messages.

[1702] "Example 1"

[1703] (Claim 1)

[1704] means for analyzing messages received from users;

[1705] A means for generating multiple illustrations and short messages based on the analysis results;

[1706] a display means for displaying the generated candidates so that the user can select one from the plurality of candidates;

[1707] means for transmitting the selected stamp;

[1708] A means to generate illustrations and short messages using a generative AI model;

[1709] a means for providing input to a generative AI model based on the prompt sentence;

[1710] A system including:

[1711] (Claim 2)

[1712] 10. The system of claim 1, wherein natural language processing is used to analyze the message.

[1713] (Claim 3)

[1714] 10. The system of claim 1, further comprising means for generating a prompt sentence based on a user's message and inputting the prompt sentence into the generative AI model.

[1715] "Application Example 1"

[1716] (Claim 1)

[1717] means for analyzing messages received from users;

[1718] A means for generating multiple illustrations and short messages based on the analysis results;

[1719] a display means for displaying the generated candidates so that the user can select one from the plurality of candidates;

[1720] means for transmitting the selected stamp;

[1721] means for presenting the generated stamp candidates to a user in order of priority;

[1722] A system including:

[1723] (Claim 2)

[1724] 10. The system of claim 1, wherein natural language processing is used to analyze the message.

[1725] (Claim 3)

[1726] The system of claim 1 uses artificial intelligence to generate the illustrations and one-line messages.

[1727] "Example 2: Combining Emotion Engines"

[1728] (Claim 1)

[1729] means for analyzing messages received from users and extracting keywords and emotion information;

[1730] A means for generating multiple illustrations and short messages based on the analysis results;

[1731] a means for prioritizing the generated stamp candidates based on emotion information and displaying them so that the user can select one;

[1732] means for transmitting the selected stamp;

[1733] A system including:

[1734] (Claim 2)

[1735] 10. The system of claim 1, wherein natural language processing techniques are used to analyze the messages.

[1736] (Claim 3)

[1737] The system of claim 1, wherein an artificial intelligence model is used to generate the illustrations and one-line messages.

[1738] "Application example 2 when combining emotion engines"

[1739] (Claim 1)

[1740] means for analyzing messages received from users;

[1741] A means for generating multiple illustrations and short messages based on the analysis results;

[1742] a display means for displaying the generated candidates so that the user can select one from the plurality of candidates;

[1743] means for transmitting the selected stamp;

[1744] means for recommending content based on a user's messages and emotions;

[1745] A system including:

[1746] (Claim 2)

[1747] 10. The system of claim 1, wherein natural language processing is used to analyze the message.

[1748] (Claim 3)

[1749] The system of claim 1 uses artificial intelligence to generate the illustrations and one-line messages.

[1750] (Claim 4)

[1751] 10. The system of claim 1, wherein the system uses artificial intelligence to recommend appropriate content based on the extracted emotion information. [Explanation of symbols]

[1752] 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 analyzing messages received from users; A means for generating multiple illustrations and short messages based on the analysis results; a display means for displaying the generated candidates so that the user can select one from the plurality of candidates; means for transmitting the selected stamp; A system including:

2. 10. The system of claim 1, wherein natural language processing is used to analyze the message.

3. The system of claim 1, wherein the illustrations and one-line messages are generated using artificial intelligence.

Images