system

Abstract

Provide a system. The method includes: receiving a text message entered by a user; means for analyzing keywords and phrases in the text message; A means for identifying emojis corresponding to the analyzed keywords or phrases; means for inserting the identified emoji into the text message; means for generating a message having emojis inserted therein; A means for sending the generated message to the user's terminal; A message processing system including:

Description

[Technical Field]

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

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

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

[0004] Text messages are frequently used in modern communication, but it is often difficult to fully convey emotions and nuances through mere text. This can result in misunderstandings and reduced communication effectiveness. This is particularly a serious problem in important business or personal communications. The present invention aims to solve this problem and provide a system for visually clearly conveying emotions and intentions in text messages. [Means for solving the problem]

[0005] The present invention provides a message processing system that receives a text message entered by a user, analyzes keywords and standard phrases in the message, and identifies and inserts corresponding emoji. Specifically, the system includes a means for receiving the message entered by the user, a means for analyzing the keywords and standard phrases in the message using a natural language processing library, a means for referencing a database or mapping list that identifies emoji corresponding to the analyzed keywords and standard phrases, a means for inserting the identified emoji into the message, and a means for generating a message with the inserted emoji and transmitting it in JSON format to the user's device. This system improves the legibility and emotional conveyance of text messages, thereby realizing smooth communication.

[0006] "User" means any person or entity that uses the System to enter and send text messages.

[0007] "Text Message" refers to a written message entered by a user into the system.

[0008] "Means for receiving" refers to the technical method or device for transferring the entered text message to the server and processing its content.

[0009] "Means for analyzing" refers to algorithms or programs used to identify and analyze keywords or phrases within received text messages.

[0010] "Keywords and phrases" are important words and phrases contained within a text message that indicate emotion or intent.

[0011] "Natural language processing library" refers to software tools and libraries used to analyze text data and understand its meaning and grammatical structure.

[0012] "Means of identification" refers to the technology or method for selecting the corresponding emoji based on the analysis results.

[0013] "Emoji" refers to symbols or icons inserted into text messages that visually express emotions or intentions.

[0014] "Database or mapping list" refers to a storage device or list for storing and retrieving emojis corresponding to keywords or phrases.

[0015] "Insertion means" refers to technology or programming that incorporates corresponding emojis at specific locations within a text message.

[0016] "Means for generating" refers to a method or apparatus for creating a new text message with an emoji inserted.

[0017] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and refers to a standard format for expressing data in a format that is easy for humans to read and machines to analyze.

[0018] "Terminal" means the electronic device used by a User to access the System and enter and view Messages. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, and identifies and inserts corresponding emoticons. This system improves the visibility and emotional conveyance of text message communications, thereby realizing smoother communication.

[0041] System configuration and operation

[0042] 1. User input:

[0043] The user types a text message into the chat tool's input field, for example, "Today was so much fun! Let's hang out again!"

[0044] The user sends the message by clicking the send button.

[0045] 2. Sending a message:

[0046] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint.

[0047] 3. Message received and parsed by the server:

[0048] The server receives the HTTP request and extracts the text message.

[0049] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0050] 4. Identify and insert emojis:

[0051] The server retrieves emojis corresponding to the identified keywords or phrases from a database or mapping list. For example, "It was fun" corresponds to the emoji "😊" and "Let's play" corresponds to the emoji "🎮."

[0052] The server then inserts the identified emoji into a text message and generates a new message, such as "Today was so much fun 😊. Let's hang out again 🎮!"

[0053] 5. Send a new message:

[0054] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[0055] 6. Displaying messages:

[0056] The terminal receives the HTTP response and parses the JSON format.

[0057] A new message appears in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0058] Specific examples

[0059] Situation

[0060] A user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!"

[0061] How it works

[0062] 1. User input and submission:

[0063] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[0064] 2. Sending a message from the device to the server:

[0065] The device sends a message in JSON format to the server.

[0066] 3. Receiving and parsing messages on the server:

[0067] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[0068] 4. Identify and insert emojis:

[0069] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play" and inserts them into the message.

[0070] Generate a new message: "Today was so much fun 😊. Let's play again 🎮!"

[0071] 5. Send a new message:

[0072] The server sends a new message to the device.

[0073] 6. Displaying messages in the terminal:

[0074] Your device will receive a new message and display it in the chat window.

[0075] This system allows users to effectively insert appropriate emojis into text messages, improving the quality of communication.

[0076] The processing flow will be explained below.

[0077] Step 1:

[0078] The user types a message, for example, "Today was so much fun! Let's hang out again!" into the chat tool's input field.

[0079] Step 2:

[0080] The user clicks the send button to send the entered text message.

[0081] Step 3:

[0082] The device packages the user-entered text message into JSON format.

[0083] Step 4:

[0084] The device sends a message as an HTTP POST request to the server endpoint.

[0085] Step 5:

[0086] The server receives the HTTP request and extracts the text message.

[0087] Step 6:

[0088] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0089] Step 7:

[0090] Based on the analysis results, the server refers to a database or mapping list to identify emojis that correspond to keywords or phrases.

[0091] Step 8:

[0092] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play."

[0093] Step 9:

[0094] The server then inserts the identified emoji into the appropriate position in the text message, for example, "Today was so much fun 😊. Let's hang out again 🎮!"

[0095] Step 10:

[0096] The server generates a new text message with the emoji inserted and repackages it into JSON format.

[0097] Step 11:

[0098] The server sends the generated new message to the user's device as an HTTP response.

[0099] Step 12:

[0100] The device receives the HTTP response and parses the JSON format.

[0101] Step 13:

[0102] The device displays a new message in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0103] Example 1

[0104] 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."

[0105] In recent years, communication using text messages has become very common, but there are issues with text alone, such as a lack of visibility and ability to convey emotions. This can lead to misunderstandings and impair smooth communication. To solve this problem and achieve richer and more effective communication, a system that can easily and automatically insert appropriate emojis into text messages is needed.

[0106] 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.

[0107] In this invention, the server includes means for receiving a text message entered by a user, means for analyzing keywords and set phrases in the text message, means for identifying emojis corresponding to the analyzed keywords and set phrases, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to the user's terminal, and means for displaying the generated message on the user's terminal. This allows the user to easily insert appropriate emojis into the text message, improving the visibility of communication and the ability to convey emotions, thereby enabling smoother communication.

[0108] "User" means a person who utilizes the System to enter, send, and receive text messages.

[0109] "Text message" refers to character string information that a user inputs and sends using a terminal.

[0110] "Keywords" refer to important words in a text message that convey a particular meaning or emotion.

[0111] "Phrases" refer to specific expressions or phrases that are frequently used in text messages.

[0112] "Analyzing" refers to analyzing text messages using natural language processing libraries and identifying keywords and phrases.

[0113] "Emoji" refers to small images or icons inserted into text messages that visually convey emotions or states.

[0114] "Inserting" refers to placing the identified emoji in the position of the corresponding keyword or phrase.

[0115] "Generating" refers to creating a new text message with the emoji inserted.

[0116] "Sending" refers to transferring the generated text message from the server to the user's terminal.

[0117] "Display" refers to displaying the generated text message on the screen of the user's terminal.

[0118] A "natural language processing library" refers to a software library that helps analyze and understand text data.

[0119] "JSON format" is an abbreviation for JavaScript Object Notation and refers to a lightweight data exchange format for representing structured data.

[0120] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a user uses to enter or receive text messages.

[0121] "Server" refers to the computer system that parses messages, identifies and inserts emojis, and creates and sends new messages.

[0122] MODE FOR CARRYING OUT THE INVENTION

[0123] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, and identifies and inserts corresponding emoticons. This system improves the visibility and emotional conveyance of text message communications, thereby realizing smoother communication.

[0124] Configuration and Operation

[0125] User Input

[0126] A user types a text message into the chat tool's input field and clicks the send button. For example, the user might type, "Today was so much fun! Let's hang out again!"

[0127] Sending a message

[0128] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint. Specifically, it converts the message into the format { "message": "Today was so much fun. Let's play again!"} and sends a POST request to https: / / example.com / api / messages.

[0129] Server receives and analyzes messages

[0130] The server receives an HTTP request and extracts the text message. For example, the extracted message might be {"message": "Today was so much fun. Let's hang out again!"}. The server then uses a natural language processing library to analyze the message and identify keywords and boilerplate phrases. Examples of natural language processing libraries that can be used include SpaCy and NLTK. The analysis results in the identification of "I had fun" and "Let's hang out."

[0131] Identifying and inserting emojis

[0132] The server retrieves emojis from a database or mapping list that correspond to the identified keywords or phrases. For example, it retrieves the emoji "😊" that corresponds to "I had fun" and the emoji "🎮" that corresponds to "Let's play." The server then inserts these emojis into the appropriate places and generates a new message. As a result, the text message is transformed into "Today was so much fun 😊. Let's play again 🎮!"

[0133] Sending a new message

[0134] The server then packages the new message into JSON format and sends it to the user's device as an HTTP response. Specifically, the server converts the new message into the format { "message": "Today was so much fun 😊. Let's play again 🎮!"} and returns it as a response.

[0135] Displaying messages

[0136] The device receives the HTTP response and parses the JSON format. The parsed message is displayed in the chat window. For example, a message like "Today was so much fun 😊. Let's play again 🎮!" is displayed.

[0137] Specific examples

[0138] For example, if a user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!", the system will analyze the message and insert appropriate emojis. Ultimately, the friend will see the message, "Today was so much fun! 😊 Let's hang out again! 🎮!" This improves the visibility of text messages and their ability to convey emotions, making communication more effective.

[0139] Prompt Sentence Examples

[0140] "If a user types 'I had so much fun today. Let's hang out again!', explain how you would insert an emoji."

[0141] This system allows users to easily insert appropriate emojis into text messages, improving the quality of communication.

[0142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0143] Step 1: User Input and Submission

[0144] The user enters a text message in the input field of the chat tool and clicks the send button. An example of input content is "Today was so much fun. Let's hang out again!". The text "Today was so much fun. Let's hang out again!" is given as input. Here, the user presses the enter key or clicks the send icon. This triggers the sending of the text message to the terminal as output.

[0145] Step 2: Sending a message

[0146] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint. The input is the text message entered by the user. Data processing converts the message to { "message": "Today was so much fun. Let's play again!"}. The output is an HTTP POST request containing the packaged JSON message.

[0147] Step 3: Server receives and analyzes the message

[0148] The server receives an HTTP request and extracts the text message. The input is an HTTP request in JSON format. Data processing involves extracting {"message": "Today was so much fun. Let's play again!"} from the request body to obtain the message. The output is the extracted text message. Next, the server uses a natural language processing library (for example, SpaCy or NLTK) to parse the text message. The input is the extracted text message. Data processing involves analyzing the message and identifying keywords such as "I had fun" or "Let's play." The output is the identified keywords.

[0149] Step 4: Identify and insert emojis

[0150] The server retrieves emojis from a database or mapping list that correspond to the identified keywords or phrases. The input is the identified keywords. The data processing involves retrieving the corresponding emojis from the database. For example, "😊" corresponds to "fun" and "🎮" corresponds to "let's play." The output is the corresponding emojis. The server then inserts these emojis into the appropriate places to generate a new message. The input is the original text message and the identified emojis. The data operation involves inserting the emojis to generate a new message, for example, "Today was so much fun 😊. Let's play again 🎮!" The output is the new message that is generated.

[0151] Step 5: Send a new message

[0152] The server packages the generated new message into JSON format again and sends it to the user's device as an HTTP response. The input is the generated new text message. For data processing, the new message is packaged into { "message": "Today was so much fun 😊. Let's play again 🎮!"}. The output is sent to the user's device as a JSON format HTTP response.

[0153] Step 6: Displaying messages

[0154] The terminal receives the HTTP response and parses the JSON format. The input is the HTTP response. As data processing, it extracts {"message": "Today was so much fun 😊. Let's hang out again 🎮!"} from the response body. The output is the extracted new message. Next, the terminal displays the new message in the user's chat window. The input is the extracted new message. As data processing, it converts it into a displayable format and displays it in the chat window. For example, the message "Today was so much fun 😊. Let's hang out again 🎮!" is displayed. This is the final output.

[0155] (Application example 1)

[0156] 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."

[0157] Traditional text message communication lacks visibility and the ability to convey emotions, and especially in virtual stores, the interaction between store staff and customers can feel robotic and unfriendly, which can lead to a poor user experience and negatively impact customer satisfaction and repeat business.

[0158] 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.

[0159] In this invention, the server includes means for receiving a text message input by a user, means for analyzing keywords and fixed phrases in the text message, means for identifying emojis corresponding to the analyzed keywords and fixed phrases, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to the user's terminal, and means installed in the smart glasses for realizing emotional dialogue in real time, thereby enabling the effective insertion of appropriate emojis into the text message and improving the quality of communication.

[0160] "User" means a person who uses the System to enter and send text messages.

[0161] A "text message" refers to a message consisting of characters and symbols entered by a user.

[0162] "Keywords" refer to important words contained within a text message that the system analyzes.

[0163] "Phrases" refer to specific patterns or phrases contained within text messages.

[0164] "Analysis" refers to the process of analyzing text messages to identify keywords and phrases.

[0165] "Emoji" refers to symbols or images inserted into text messages to visually express emotions.

[0166] A "server" refers to a computer system that receives, analyzes, and processes text messages sent from user terminals.

[0167] "Smart glasses" are wearable devices worn by users that have communication and display functions and can send and receive messages in real time.

[0168] "Real-time" refers to the property of providing a nearly instantaneous response.

[0169] The present invention relates to a message processing system that receives text messages entered by a user, analyzes keywords and phrases in the messages, and identifies and inserts corresponding emojis. This system is specialized for realizing emotionally rich interactions in real time using smart glasses. The following describes in detail the embodiments of the present invention.

[0170] System configuration and operation

[0171] 1. User input:

[0172] The user inputs a text message using the input interface of the smart glasses, for example, "Here are the latest sales! Check them out!" The input is temporarily stored in the smart glasses.

[0173] 2. Sending a message:

[0174] The smart glasses convert the text message entered by the user into JSON format and send it to the server as an HTTP POST request. The communication protocol used here is HTTP, and the data format is JSON.

[0175] 3. Message analysis:

[0176] The server parses the incoming HTTP request and extracts the text message, which is then analyzed using a natural language processing library (e.g., SpaCy) to identify keywords and phrases, such as "sale items" or "check it out."

[0177] 4. Identify and insert emojis:

[0178] The server retrieves emojis corresponding to the identified keywords or phrases from a database (e.g., SQLite) or mapping list. For example, "sale items" corresponds to the emoji "🛍️" and "check it out" corresponds to the emoji "👀". The server then inserts the identified emojis into a text message to generate a new message. For example, "Here are our latest sale items 🛍️! Check them out 👀!"

[0179] 5. Create and send a new message:

[0180] The server then packages the new generated message back into JSON format and sends it to the smart glasses as an HTTP response.

[0181] 6. Displaying messages:

[0182] The smart glasses parse the received HTTP response and extract the new message from the JSON formatted data, which is then displayed on the smart glasses' display, allowing users to continue communicating with appropriate emojis inserted into their text messages.

[0183] Specific examples

[0184] For example, if a customer in a virtual store sends a text message through their smart glasses saying, "Tell me what products are on sale," the server will identify the keyword "products on sale" and insert the corresponding emoji "🛒" into the message, which will generate a new message "Tell me what products are on sale 🛒" and display it on the customer's smart glasses.

[0185] Prompt Sentence Examples

[0186] Generate a program that reads "Here are the latest sale items! Check them out" and displays "Here are the latest sale items 🛍️! Check them out 👀" with an emoji inserted.

[0187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0188] Step 1:

[0189] A user inputs a text message using the input interface of the smart glasses. The input message is temporarily stored in the smart glasses. The input of this step is the text message input by the user, and the output is the text data temporarily stored in the smart glasses.

[0190] Step 2:

[0191] The smart glasses convert the stored text message into JSON format and send it as an HTTP POST request to the server. The input of this step is the stored text data, and the output is the data converted into JSON format. The smart glasses send this to the server using the HTTP protocol.

[0192] Step 3:

[0193] The server analyzes the received HTTP request and extracts the text message. It parses the received data to get the text message part. The input of this step is the JSON data sent from the smart glasses, and the output is the extracted text message.

[0194] Step 4:

[0195] The server analyzes the extracted text messages using a natural language processing library (e.g., SpaCy) to identify keywords and standard phrases. The data processing performed in this step is to identify keywords and standard phrases. The input of this step is the extracted text messages, and the output is the identified keywords and standard phrases.

[0196] Step 5:

[0197] The server retrieves emojis corresponding to the identified keywords or phrases from a database (e.g., SQLite) or mapping list. The input of this step is the identified keywords or phrases, and the output is the corresponding emojis. The server queries the database to retrieve the corresponding emojis.

[0198] Step 6:

[0199] The server inserts the identified emoji into the text message and generates a new message. The input of this step is the identified emoji and the original text message, and the output is the newly generated message. Specifically, string manipulation is used to insert the emoji at the appropriate position.

[0200] Step 7:

[0201] The server packages the generated new message into JSON format again and sends it to the smart glasses as an HTTP response. The input of this step is the generated message and the output is JSON format data, which the server sends to the smart glasses using the HTTP protocol.

[0202] Step 8:

[0203] The smart glasses parse the received HTTP response and extract the new message from the JSON formatted data. The input of this step is the JSON data sent from the server, and the output is the extracted new message, which the smart glasses then convert into a format for display.

[0204] Step 9:

[0205] The smart glasses display the extracted new message on the display. The input of this step is the extracted new message, and the output is the message displayed on the display, allowing the user to view the message with the emoji inserted.

[0206] 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.

[0207] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, recognizes emotions using an emotion engine, and identifies and inserts corresponding emojis. This system significantly improves the readability and emotional conveyance of text messages, enabling smoother and richer communication.

[0208] System configuration and operation

[0209] 1. User input:

[0210] The user types a text message into the chat tool's input field, for example, "Today was so much fun! Let's hang out again!"

[0211] The user sends the message by clicking the send button.

[0212] 2. Sending a message:

[0213] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint.

[0214] 3. Message received and parsed by the server:

[0215] The server receives the HTTP request and extracts the text message.

[0216] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0217] 4. Use of Emotion Engine:

[0218] The server uses an emotion engine to analyze the emotion of the entire text message, for example recognizing that the message expresses a positive emotion such as "fun."

[0219] 5. Identifying and Inserting Emojis:

[0220] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, the emoji "😊" corresponds to "It was fun," and the emoji "🎮" corresponds to "Let's play."

[0221] The server then inserts the identified emoji into a text message and generates a new message, such as "Today was so much fun 😊. Let's hang out again 🎮!"

[0222] 6. Send a new message:

[0223] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[0224] 7. Displaying messages:

[0225] The terminal receives the HTTP response and parses the JSON format.

[0226] A new message appears in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0227] Specific examples

[0228] Situation

[0229] A user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!"

[0230] How it works

[0231] 1. User input and submission:

[0232] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[0233] 2. Sending a message from the device to the server:

[0234] The device sends a message in JSON format to the server.

[0235] 3. Receiving and parsing messages on the server:

[0236] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[0237] 4. Use of Emotion Engine:

[0238] The server uses an emotion engine to recognize that the message expresses a positive emotion.

[0239] 5. Identifying and Inserting Emojis:

[0240] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play," and then selects appropriate emojis that express positive emotions.

[0241] Generate a new message: "Today was so much fun 😊. Let's play again 🎮!"

[0242] 6. Send a new message:

[0243] The server sends a new message to the device.

[0244] 7. Displaying messages in the terminal:

[0245] Your device will receive a new message and display it in the chat window.

[0246] This system allows users to effectively insert appropriate emojis that reflect their emotions into text messages, significantly improving the quality of communication.

[0247] The processing flow will be explained below.

[0248] Step 1:

[0249] The user types a message, for example, "Today was so much fun! Let's hang out again!" into the chat tool's input field.

[0250] Step 2:

[0251] The user clicks the send button to send the entered text message.

[0252] Step 3:

[0253] The device packages the user-entered text message into JSON format.

[0254] Step 4:

[0255] The device sends a message as an HTTP POST request to the server endpoint.

[0256] Step 5:

[0257] The server receives the HTTP request and extracts the text message.

[0258] Step 6:

[0259] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0260] Step 7:

[0261] The server uses an emotion engine to analyze the emotion of the entire text message, for example, recognizing that the message expresses a positive emotion such as "fun."

[0262] Step 8:

[0263] Based on the analysis results, the server retrieves emojis corresponding to keywords, phrases, and the emotion engine's recognition results from a database or mapping list.

[0264] Step 9:

[0265] The server identifies the emoji "😊" that corresponds to "It was fun," the emoji "😁" that corresponds to the positive emotion identified by the emotion engine, and the emoji "🎮" that corresponds to "Let's play."

[0266] Step 10:

[0267] The server then inserts the identified emoji into the appropriate position in the text message, for example, "Today was so much fun 😊😁. Let's hang out again 🎮!"

[0268] Step 11:

[0269] The server generates a new text message with the emoji inserted and repackages it into JSON format.

[0270] Step 12:

[0271] The server sends the generated new message to the user's device as an HTTP response.

[0272] Step 13:

[0273] The device receives the HTTP response and parses the JSON format.

[0274] Step 14:

[0275] The device displays a new message in the user's chat window: "Today was so much fun 😊😁. Let's hang out again 🎮!"

[0276] Example 2

[0277] 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."

[0278] In recent years, communication primarily based on text messages has rapidly spread, but there is a problem in that it is difficult to accurately convey emotions. This is because simple text alone cannot adequately convey the emotional nuances of a message, which can easily lead to misunderstandings and lack of communication between users. In addition, manually inserting emojis is time-consuming, which can detract from the user experience. There is a need for a system that can solve these issues and enable smoother and richer communication.

[0279] 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.

[0280] In this invention, the server includes means for receiving a text message entered by a user, means for analyzing keywords and fixed phrases in the text message, means for recognizing emotions in the analyzed text message, means for identifying emojis corresponding to the recognized emotions based on the identified emotions, means for inserting the identified emojis into the text message, and means for transmitting the generated message to the user's terminal. This allows the user to automatically insert emojis that reflect emotions into messages, thereby reducing misunderstandings about emotions and enabling richer communication.

[0281] "User" means a person who uses the System to enter and send text messages.

[0282] "Text Message" means textual information entered by a User and sent and received through the System.

[0283] "Keywords" are important words or phrases within a text message that are identified and analyzed by the system.

[0284] A "fixed phrase" is a phrase or expression that has a certain pattern and is included in a text message and is the subject of analysis.

[0285] "Emotion" refers to the psychological nuances or states expressed in text messages, and can be classified as positive, negative, neutral, etc.

[0286] "Emoji" refers to small images or icons used to visually represent emotions or concepts.

[0287] "Natural language processing libraries" refers to software tools and frameworks used to analyze text messages.

[0288] "JSON format" is an abbreviation for JavaScript Object Notation and refers to a lightweight data format used for data exchange.

[0289] An "HTTP POST request" is a type of HTTP method for sending data to a web server, and is primarily used for data submission.

[0290] MODE FOR CARRYING OUT THE INVENTION

[0291] The present invention is a message processing system that receives a text message entered by a user, analyzes keywords and fixed phrases in the message, recognizes emotions using an emotion engine, and identifies and inserts corresponding emojis to improve the readability and emotional communication of the text message. This system is configured by combining hardware and software.

[0292] Hardware and software used

[0293] Hardware:

[0294] User device (e.g. smartphone, PC)

[0295] Server (e.g. cloud server, dedicated server)

[0296] software:

[0297] Natural language processing libraries (e.g., SpaCy, NLTK)

[0298] Sentiment Analysis Engine

[0299] Database or Mapping List

[0300] Communication protocol (e.g. HTTP, JSON)

[0301] How the system is implemented

[0302] 1. User Input

[0303] The user enters a text message into the chat tool's input field and clicks the send button. For example, the user can enter "I had a great time today. Let's hang out again!"

[0304] 2. Sending a Message

[0305] The device packages the text message entered by the user into JSON format and sends it to the server endpoint as an HTTP POST request, which transfers the message data to the server.

[0306] 3. Message Reception and Analysis by the Server

[0307] The server unpacks the received HTTP request and extracts the text message. It then uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases. For example, "It was fun" or "Let's play" might be identified.

[0308] 4. Use of Emotion Engine

[0309] The server uses an emotion engine to analyze the emotion of the entire text message, for example recognizing that the message expresses a positive emotion such as "fun."

[0310] 5. Identifying and Inserting Emojis

[0311] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, the emoji "😊" corresponds to "fun" and the emoji "🎮" corresponds to "let's play." The server then inserts the identified emojis into a text message to generate a new message. For example, "Today was so much fun 😊. Let's play again 🎮!"

[0312] 6. Send a new message

[0313] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[0314] 7. Displaying Messages

[0315] The device unpacks the received HTTP response and parses the message from the JSON format. The new message is then displayed in the user's chat window.

[0316] Specific examples

[0317] If a user wants to send a message to a friend saying, "I had a great time today. Let's hang out again!", the system works as follows:

[0318] 1. User input and submission

[0319] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[0320] 2. Sending a message from the device to the server

[0321] The device sends a message in JSON format to the server.

[0322] 3. Receiving and analyzing messages on the server

[0323] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[0324] 4. Use of Emotion Engine

[0325] The server uses an emotion engine to recognize that the message expresses a positive emotion.

[0326] 5. Identifying and Inserting Emojis

[0327] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play," and generates a new message: "Today was so much fun 😊. Let's play again 🎮!"

[0328] 6. Send a new message

[0329] The server sends a new message to the device.

[0330] 7. Displaying messages on the terminal

[0331] Your device will receive a new message and display it in the chat window.

[0332] This system allows users to effectively insert emojis that reflect their emotions into text messages, significantly improving the quality of communication.

[0333] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0334] Step 1:

[0335] A user enters a text message into the chat tool's input field and clicks the send button. For example, "I had a great time today. Let's hang out again!" The input in this case is the user's text message, and the output is the click event of the send button.

[0336] Step 2:

[0337] The device receives the text message entered by the user when the send button is clicked. The device then packages the text message in JSON format and sends it as an HTTP POST request to the specified endpoint on the server. The input is the user's text message, and the output is message data in JSON format. This process converts the text message into JSON format and sends it to the server.

[0338] Step 3:

[0339] The server receives the HTTP POST request and retrieves the message data in JSON format. After extracting the text message from the retrieved data, it uses a natural language processing library (e.g., SpaCy or NLTK) to analyze the text message and identify keywords and standard phrases. The input is the message data in JSON format, and the output is the analyzed keywords and standard phrases. Specifically, it identifies keywords such as "It was fun" and "Let's play."

[0340] Step 4:

[0341] The server uses a sentiment analysis engine to analyze the sentiment of the entire text message. For example, it recognizes the positive sentiment of "fun" from the message "Today was so much fun. Let's hang out again!" The input is the text message, and the output is the recognized sentiment (e.g., positive). This process identifies the sentiment of the message.

[0342] Step 5:

[0343] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, "I had fun" corresponds to the emoji "😊" and "Let's play" corresponds to the emoji "🎮". Next, a new message is generated by inserting the identified emojis into a text message. The input is the analyzed keywords and emotions, and the output is the identified emojis and a new text message (e.g., "I had a lot of fun today 😊. Let's play again 🎮!").

[0344] Step 6:

[0345] The server repackages the generated new message into JSON format and sends it as an HTTP response to the user's device. The input is the new text message and the output is JSON formatted data. This process sends the new message to the device.

[0346] Step 7:

[0347] The device receives the HTTP response and parses the JSON-formatted data. The resulting new message is displayed in the user's chat window. The input is JSON-formatted data, and the output is a new message (e.g., "Today was so much fun 😊. Let's play again 🎮!") that is displayed in the user's chat window. This allows the user to visually confirm the new message.

[0348] The above are the specific processing steps and flow of the system. This system allows users to easily send text messages that reflect their emotions, thereby improving the quality of communication.

[0349] (Application example 2)

[0350] 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."

[0351] With conventional messaging systems, it is difficult to convey emotions in text-based communication, making it difficult to accurately grasp the other person's intentions and emotions. Furthermore, in brick-and-mortar stores, communication with customers tends to be emotionless and monotonous, which can lead to a decrease in customer satisfaction. To solve these problems, there is a need for a way to reflect emotions in text messages and convey them in a visually easy-to-understand format.

[0352] 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 receiving a text message entered by a user, means for analyzing keywords and set phrases in the text message, means for recognizing emotions in the text message using an emotion engine, means for identifying emojis corresponding to the analyzed keywords and set phrases and the recognized emotions, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to a user's terminal, means for displaying the generated message on the user's device, and means corresponding to an application installed on a smartphone, smart glasses, a head-mounted display, or a robot. This makes it possible to easily reflect emotions in a text message and convey them in a visually easy-to-understand manner.

[0353] "User" means a person who uses a system or device to input and send text messages.

[0354] "Text message" refers to a message in the form of a string of characters that is entered and sent by a user.

[0355] "Keywords" refer to important words that appear in a text message and have a particular meaning or sentiment.

[0356] A "fixed phrase" is a commonly used expression or phrase.

[0357] "Emotion engine" refers to a software component for analyzing and recognizing emotions from input text messages.

[0358] "Emoji" refers to small icons inserted into text messages to visually express emotions or concepts.

[0359] A "natural language processing library" refers to a software tool used to analyze text data and identify keywords and phrases.

[0360] A "smartphone" refers to a mobile information terminal that has multiple functions, including voice communication capabilities, Internet access, and application execution.

[0361] "Smart glasses" are a wearable device in the shape of glasses that has the ability to display information and connect to the Internet.

[0362] A "head-mounted display" refers to a display device worn on the head to display visual information and digital content.

[0363] "Robot" refers to a mechanical device that performs automated operation or interaction and is programmed to perform specific tasks or interactions.

[0364] This invention is a system that analyzes text messages entered by a user, recognizes emotions, and inserts appropriate emoticons. This system uses the following hardware and software configuration.

[0365] First, a user types and sends a text message from a device such as a smartphone, smart glasses, head-mounted display, or robot. When the user sends a message such as "Do you have any recommendations for me today?", the text message is packaged in JSON format and sent to the server.

[0366] The server then processes the received text message using the following software:

[0367] 1. Use a natural language processing library (e.g., SpaCy, NLTK) to analyze text messages and identify keywords and boilerplate phrases.

[0368] 2. Recognize the sentiment of the message using an emotion engine (e.g., Google® Cloud Natural Language API).

[0369] Based on the analysis results, emojis corresponding to keywords, phrases, and recognized emotions are retrieved from a database or mapping list. For example, "🛍" is identified for "recommended items." Then, the identified emojis are inserted into a text message to generate a new message: "Do you have any recommendations for me today? 🛍?"

[0370] The generated message is then packaged in JSON format and sent to the user's device for display, allowing users to visually express emotions in their text messages, making communication smoother and richer.

[0371] Specific examples of hardware and software used

[0372] Hardware:

[0373] Smartphones (iOS and ANDROID (registered trademark) devices)

[0374] Smart Glasses

[0375] head-mounted display

[0376] Robots (e.g. Pepper)

[0377] software:

[0378] Natural language processing libraries: SpaCy, NLTK

[0379] Sentiment analysis engine: Google Cloud Natural Language API

[0380] Database: MySQL (registered trademark), Firebase Realtime Database

[0381] Application framework: Flutter (registered trademark), React Native

[0382] Examples of concrete examples and prompts

[0383] A concrete example is when a user sends a message to a friend saying, "What do you have for me today?" This message is parsed to detect emotion and generate a new message with the appropriate emoji inserted: "What do you have for me today? 🛍?"

[0384] Example prompt sentence:

[0385] Based on the message entered by the customer, analyze the sentiment and create a reply with appropriate emojis.

[0386] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0387] Step 1:

[0388] A user types a text message into a device (e.g., smartphone, smart glasses, head-mounted display, robot) and clicks the "Send" button. The input is "Do you have any recommendations for me today?". This causes the text message typed by the user to be captured within the device.

[0389] Step 2:

[0390] The device packages the captured text message into JSON format and sends it to the server as an HTTP POST request. The input data is the text message and the user's ID, and the output data is the HTTP request sent to the server.

[0391] Step 3:

[0392] The server receives an HTTP request and extracts the text message. The input data is message data in JSON format, and the output data is the extracted text message. Specifically, the server analyzes the received data and extracts the string portion of the text message.

[0393] Step 4:

[0394] The server uses natural language processing libraries (SpaCy or NLTK) to analyze text messages and identify keywords and phrases. The input data is the extracted text message, and the output data is the identified keywords and phrases. Specific operations include tokenizing the text, tagging parts of speech, and dependency analysis.

[0395] Step 5:

[0396] The server uses an emotion engine (such as the Google Cloud Natural Language API) to recognize the emotion of a text message. The input data is a text message containing identified keywords and phrases, and the output data is the emotion type (e.g., positive, negative, neutral). Specific operations include calculating an emotion score for the entire message and classifying it.

[0397] Step 6:

[0398] The server retrieves the analysis results and emojis corresponding to the emotions from a database or mapping list. The input data are the identified keywords and emotion types, and the output data are the corresponding emojis. Specifically, the server searches for and retrieves the corresponding emojis from the database.

[0399] Step 7:

[0400] The server inserts the identified emoji into the text message to generate a new message. The input data is the original text message and the corresponding emoji, and the output data is the new message with the inserted emoji. The specific operation is to insert the emoji into a specific position in the text.

[0401] Step 8:

[0402] The server then packages the new message into JSON format and sends it to the user's device as an HTTP response. The input data is the new text message, and the output data is the JSON response. Specifically, the server converts the message into a JSON object and sends it.

[0403] Step 9:

[0404] The terminal receives the HTTP response and parses the JSON format. The input data is the received JSON response, and the output data is the parsed new text message. Specifically, the terminal parses the response data and extracts the text portion.

[0405] Step 10:

[0406] The terminal displays the parsed new message on the user's device. The input data is the parsed new message, and the output data is the message displayed in the user's chat window. A specific operation is to render the message in a user interface.

[0407] 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.

[0408] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0409] 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.

[0410] [Second embodiment]

[0411] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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."

[0423] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, and identifies and inserts corresponding emoticons. This system improves the visibility and emotional conveyance of text message communications, thereby realizing smoother communication.

[0424] System configuration and operation

[0425] 1. User input:

[0426] The user types a text message into the chat tool's input field, for example, "Today was so much fun! Let's hang out again!"

[0427] The user sends the message by clicking the send button.

[0428] 2. Sending a message:

[0429] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint.

[0430] 3. Message received and parsed by the server:

[0431] The server receives the HTTP request and extracts the text message.

[0432] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0433] 4. Identify and insert emojis:

[0434] The server retrieves emojis corresponding to the identified keywords or phrases from a database or mapping list. For example, "It was fun" corresponds to the emoji "😊" and "Let's play" corresponds to the emoji "🎮."

[0435] The server then inserts the identified emoji into a text message and generates a new message, such as "Today was so much fun 😊. Let's hang out again 🎮!"

[0436] 5. Send a new message:

[0437] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[0438] 6. Displaying messages:

[0439] The terminal receives the HTTP response and parses the JSON format.

[0440] A new message appears in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0441] Specific examples

[0442] Situation

[0443] A user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!"

[0444] How it works

[0445] 1. User input and submission:

[0446] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[0447] 2. Sending a message from the device to the server:

[0448] The device sends a message in JSON format to the server.

[0449] 3. Receiving and parsing messages on the server:

[0450] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[0451] 4. Identify and insert emojis:

[0452] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play" and inserts them into the message.

[0453] Generate a new message: "Today was so much fun 😊. Let's play again 🎮!"

[0454] 5. Send a new message:

[0455] The server sends a new message to the device.

[0456] 6. Displaying messages in the terminal:

[0457] Your device will receive a new message and display it in the chat window.

[0458] This system allows users to effectively insert appropriate emojis into text messages, improving the quality of communication.

[0459] The processing flow will be explained below.

[0460] Step 1:

[0461] The user types a message, for example, "Today was so much fun! Let's hang out again!" into the chat tool's input field.

[0462] Step 2:

[0463] The user clicks the send button to send the entered text message.

[0464] Step 3:

[0465] The device packages the user-entered text message into JSON format.

[0466] Step 4:

[0467] The device sends a message as an HTTP POST request to the server endpoint.

[0468] Step 5:

[0469] The server receives the HTTP request and extracts the text message.

[0470] Step 6:

[0471] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0472] Step 7:

[0473] Based on the analysis results, the server refers to a database or mapping list to identify emojis that correspond to keywords or phrases.

[0474] Step 8:

[0475] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play."

[0476] Step 9:

[0477] The server then inserts the identified emoji into the appropriate position in the text message, for example, "Today was so much fun 😊. Let's hang out again 🎮!"

[0478] Step 10:

[0479] The server generates a new text message with the emoji inserted and repackages it into JSON format.

[0480] Step 11:

[0481] The server sends the generated new message to the user's device as an HTTP response.

[0482] Step 12:

[0483] The device receives the HTTP response and parses the JSON format.

[0484] Step 13:

[0485] The device displays a new message in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0486] Example 1

[0487] 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."

[0488] In recent years, communication using text messages has become very common, but there are issues with text alone, such as a lack of visibility and ability to convey emotions. This can lead to misunderstandings and impair smooth communication. To solve this problem and achieve richer and more effective communication, a system that can easily and automatically insert appropriate emojis into text messages is needed.

[0489] 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.

[0490] In this invention, the server includes means for receiving a text message entered by a user, means for analyzing keywords and set phrases in the text message, means for identifying emojis corresponding to the analyzed keywords and set phrases, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to the user's terminal, and means for displaying the generated message on the user's terminal. This allows the user to easily insert appropriate emojis into the text message, improving the visibility of communication and the ability to convey emotions, thereby enabling smoother communication.

[0491] "User" means a person who utilizes the System to enter, send, and receive text messages.

[0492] "Text message" refers to character string information that a user inputs and sends using a terminal.

[0493] "Keywords" refer to important words in a text message that convey a particular meaning or emotion.

[0494] "Phrases" refer to specific expressions or phrases that are frequently used in text messages.

[0495] "Analyzing" refers to analyzing text messages using natural language processing libraries and identifying keywords and phrases.

[0496] "Emoji" refers to small images or icons inserted into text messages that visually convey emotions or states.

[0497] "Inserting" refers to placing the identified emoji in the position of the corresponding keyword or phrase.

[0498] "Generating" refers to creating a new text message with the emoji inserted.

[0499] "Sending" refers to transferring the generated text message from the server to the user's terminal.

[0500] "Display" refers to displaying the generated text message on the screen of the user's terminal.

[0501] A "natural language processing library" refers to a software library that helps analyze and understand text data.

[0502] "JSON format" is an abbreviation for JavaScript Object Notation and refers to a lightweight data exchange format for representing structured data.

[0503] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a user uses to enter or receive text messages.

[0504] "Server" refers to the computer system that parses messages, identifies and inserts emojis, and creates and sends new messages.

[0505] MODE FOR CARRYING OUT THE INVENTION

[0506] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, and identifies and inserts corresponding emoticons. This system improves the visibility and emotional conveyance of text message communications, thereby realizing smoother communication.

[0507] Configuration and Operation

[0508] User Input

[0509] A user types a text message into the chat tool's input field and clicks the send button. For example, the user might type, "Today was so much fun! Let's hang out again!"

[0510] Sending a message

[0511] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint. Specifically, it converts the message into the format { "message": "Today was so much fun. Let's play again!"} and sends a POST request to https: / / example.com / api / messages.

[0512] Server receives and analyzes messages

[0513] The server receives an HTTP request and extracts the text message. For example, the extracted message might be {"message": "Today was so much fun. Let's hang out again!"}. The server then uses a natural language processing library to analyze the message and identify keywords and boilerplate phrases. Examples of natural language processing libraries that can be used include SpaCy and NLTK. The analysis results in the identification of "I had fun" and "Let's hang out."

[0514] Identifying and inserting emojis

[0515] The server retrieves emojis from a database or mapping list that correspond to the identified keywords or phrases. For example, it retrieves the emoji "😊" that corresponds to "I had fun" and the emoji "🎮" that corresponds to "Let's play." The server then inserts these emojis into the appropriate places and generates a new message. As a result, the text message is transformed into "Today was so much fun 😊. Let's play again 🎮!"

[0516] Sending a new message

[0517] The server then packages the new message into JSON format and sends it to the user's device as an HTTP response. Specifically, the server converts the new message into the format { "message": "Today was so much fun 😊. Let's play again 🎮!"} and returns it as a response.

[0518] Displaying messages

[0519] The device receives the HTTP response and parses the JSON format. The parsed message is displayed in the chat window. For example, a message like "Today was so much fun 😊. Let's play again 🎮!" is displayed.

[0520] Specific examples

[0521] For example, if a user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!", the system will analyze the message and insert appropriate emojis. Ultimately, the friend will see the message, "Today was so much fun! 😊 Let's hang out again! 🎮!" This improves the visibility of text messages and their ability to convey emotions, making communication more effective.

[0522] Prompt Sentence Examples

[0523] "If a user types 'I had so much fun today. Let's hang out again!', explain how you would insert an emoji."

[0524] This system allows users to easily insert appropriate emojis into text messages, improving the quality of communication.

[0525] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0526] Step 1: User Input and Submission

[0527] The user enters a text message in the input field of the chat tool and clicks the send button. An example of input content is "Today was so much fun. Let's hang out again!". The text "Today was so much fun. Let's hang out again!" is given as input. Here, the user presses the enter key or clicks the send icon. This triggers the sending of the text message to the terminal as output.

[0528] Step 2: Sending a message

[0529] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint. The input is the text message entered by the user. Data processing converts the message to { "message": "Today was so much fun. Let's play again!"}. The output is an HTTP POST request containing the packaged JSON message.

[0530] Step 3: Server receives and analyzes the message

[0531] The server receives an HTTP request and extracts the text message. The input is an HTTP request in JSON format. Data processing involves extracting {"message": "Today was so much fun. Let's play again!"} from the request body to obtain the message. The output is the extracted text message. Next, the server uses a natural language processing library (for example, SpaCy or NLTK) to parse the text message. The input is the extracted text message. Data processing involves analyzing the message and identifying keywords such as "I had fun" or "Let's play." The output is the identified keywords.

[0532] Step 4: Identify and insert emojis

[0533] The server retrieves emojis from a database or mapping list that correspond to the identified keywords or phrases. The input is the identified keywords. The data processing involves retrieving the corresponding emojis from the database. For example, "😊" corresponds to "fun" and "🎮" corresponds to "let's play." The output is the corresponding emojis. The server then inserts these emojis into the appropriate places to generate a new message. The input is the original text message and the identified emojis. The data operation involves inserting the emojis to generate a new message, for example, "Today was so much fun 😊. Let's play again 🎮!" The output is the new message that is generated.

[0534] Step 5: Send a new message

[0535] The server packages the generated new message into JSON format again and sends it to the user's device as an HTTP response. The input is the generated new text message. For data processing, the new message is packaged into { "message": "Today was so much fun 😊. Let's play again 🎮!"}. The output is sent to the user's device as a JSON format HTTP response.

[0536] Step 6: Displaying messages

[0537] The terminal receives the HTTP response and parses the JSON format. The input is the HTTP response. As data processing, it extracts {"message": "Today was so much fun 😊. Let's hang out again 🎮!"} from the response body. The output is the extracted new message. Next, the terminal displays the new message in the user's chat window. The input is the extracted new message. As data processing, it converts it into a displayable format and displays it in the chat window. For example, the message "Today was so much fun 😊. Let's hang out again 🎮!" is displayed. This is the final output.

[0538] (Application example 1)

[0539] 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."

[0540] Traditional text message communication lacks visibility and the ability to convey emotions, and especially in virtual stores, the interaction between store staff and customers can feel robotic and unfriendly, which can lead to a poor user experience and negatively impact customer satisfaction and repeat business.

[0541] 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.

[0542] In this invention, the server includes means for receiving a text message input by a user, means for analyzing keywords and fixed phrases in the text message, means for identifying emojis corresponding to the analyzed keywords and fixed phrases, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to the user's terminal, and means installed in the smart glasses for realizing emotional dialogue in real time, thereby enabling the effective insertion of appropriate emojis into the text message and improving the quality of communication.

[0543] "User" means a person who uses the System to enter and send text messages.

[0544] A "text message" refers to a message consisting of characters and symbols entered by a user.

[0545] "Keywords" refer to important words contained within a text message that the system analyzes.

[0546] "Phrases" refer to specific patterns or phrases contained within text messages.

[0547] "Analysis" refers to the process of analyzing text messages to identify keywords and phrases.

[0548] "Emoji" refers to symbols or images inserted into text messages to visually express emotions.

[0549] A "server" refers to a computer system that receives, analyzes, and processes text messages sent from user terminals.

[0550] "Smart glasses" are wearable devices worn by users that have communication and display functions and can send and receive messages in real time.

[0551] "Real-time" refers to the property of providing a nearly instantaneous response.

[0552] The present invention relates to a message processing system that receives text messages entered by a user, analyzes keywords and phrases in the messages, and identifies and inserts corresponding emojis. This system is specialized for realizing emotionally rich interactions in real time using smart glasses. The following describes in detail the embodiments of the present invention.

[0553] System configuration and operation

[0554] 1. User input:

[0555] The user inputs a text message using the input interface of the smart glasses, for example, "Here are the latest sales! Check them out!" The input is temporarily stored in the smart glasses.

[0556] 2. Sending a message:

[0557] The smart glasses convert the text message entered by the user into JSON format and send it to the server as an HTTP POST request. The communication protocol used here is HTTP, and the data format is JSON.

[0558] 3. Message analysis:

[0559] The server parses the incoming HTTP request and extracts the text message, which is then analyzed using a natural language processing library (e.g., SpaCy) to identify keywords and phrases, such as "sale items" or "check it out."

[0560] 4. Identify and insert emojis:

[0561] The server retrieves emojis corresponding to the identified keywords or phrases from a database (e.g., SQLite) or mapping list. For example, "sale items" corresponds to the emoji "🛍️" and "check it out" corresponds to the emoji "👀". The server then inserts the identified emojis into a text message to generate a new message. For example, "Here are our latest sale items 🛍️! Check them out 👀!"

[0562] 5. Create and send a new message:

[0563] The server then packages the new generated message back into JSON format and sends it to the smart glasses as an HTTP response.

[0564] 6. Displaying messages:

[0565] The smart glasses parse the received HTTP response and extract the new message from the JSON formatted data, which is then displayed on the smart glasses' display, allowing users to continue communicating with appropriate emojis inserted into their text messages.

[0566] Specific examples

[0567] For example, if a customer in a virtual store sends a text message through their smart glasses saying, "Tell me what products are on sale," the server will identify the keyword "products on sale" and insert the corresponding emoji "🛒" into the message, which will generate a new message "Tell me what products are on sale 🛒" and display it on the customer's smart glasses.

[0568] Prompt Sentence Examples

[0569] Generate a program that reads "Here are the latest sale items! Check them out" and displays "Here are the latest sale items 🛍️! Check them out 👀" with an emoji inserted.

[0570] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0571] Step 1:

[0572] A user inputs a text message using the input interface of the smart glasses. The input message is temporarily stored in the smart glasses. The input of this step is the text message input by the user, and the output is the text data temporarily stored in the smart glasses.

[0573] Step 2:

[0574] The smart glasses convert the stored text message into JSON format and send it as an HTTP POST request to the server. The input of this step is the stored text data, and the output is the data converted into JSON format. The smart glasses send this to the server using the HTTP protocol.

[0575] Step 3:

[0576] The server analyzes the received HTTP request and extracts the text message. It parses the received data to get the text message part. The input of this step is the JSON data sent from the smart glasses, and the output is the extracted text message.

[0577] Step 4:

[0578] The server analyzes the extracted text messages using a natural language processing library (e.g., SpaCy) to identify keywords and standard phrases. The data processing performed in this step is to identify keywords and standard phrases. The input of this step is the extracted text messages, and the output is the identified keywords and standard phrases.

[0579] Step 5:

[0580] The server retrieves emojis corresponding to the identified keywords or phrases from a database (e.g., SQLite) or mapping list. The input of this step is the identified keywords or phrases, and the output is the corresponding emojis. The server queries the database to retrieve the corresponding emojis.

[0581] Step 6:

[0582] The server inserts the identified emoji into the text message and generates a new message. The input of this step is the identified emoji and the original text message, and the output is the newly generated message. Specifically, string manipulation is used to insert the emoji at the appropriate position.

[0583] Step 7:

[0584] The server packages the generated new message into JSON format again and sends it to the smart glasses as an HTTP response. The input of this step is the generated message and the output is JSON format data, which the server sends to the smart glasses using the HTTP protocol.

[0585] Step 8:

[0586] The smart glasses parse the received HTTP response and extract the new message from the JSON formatted data. The input of this step is the JSON data sent from the server, and the output is the extracted new message, which the smart glasses then convert into a format for display.

[0587] Step 9:

[0588] The smart glasses display the extracted new message on the display. The input of this step is the extracted new message, and the output is the message displayed on the display, allowing the user to view the message with the emoji inserted.

[0589] 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.

[0590] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, recognizes emotions using an emotion engine, and identifies and inserts corresponding emojis. This system significantly improves the readability and emotional conveyance of text messages, enabling smoother and richer communication.

[0591] System configuration and operation

[0592] 1. User input:

[0593] The user types a text message into the chat tool's input field, for example, "Today was so much fun! Let's hang out again!"

[0594] The user sends the message by clicking the send button.

[0595] 2. Sending a message:

[0596] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint.

[0597] 3. Message received and parsed by the server:

[0598] The server receives the HTTP request and extracts the text message.

[0599] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0600] 4. Use of Emotion Engine:

[0601] The server uses an emotion engine to analyze the emotion of the entire text message, for example recognizing that the message expresses a positive emotion such as "fun."

[0602] 5. Identifying and Inserting Emojis:

[0603] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, the emoji "😊" corresponds to "It was fun," and the emoji "🎮" corresponds to "Let's play."

[0604] The server then inserts the identified emoji into a text message and generates a new message, such as "Today was so much fun 😊. Let's hang out again 🎮!"

[0605] 6. Send a new message:

[0606] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[0607] 7. Displaying messages:

[0608] The terminal receives the HTTP response and parses the JSON format.

[0609] A new message appears in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0610] Specific examples

[0611] Situation

[0612] A user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!"

[0613] How it works

[0614] 1. User input and submission:

[0615] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[0616] 2. Sending a message from the device to the server:

[0617] The device sends a message in JSON format to the server.

[0618] 3. Receiving and parsing messages on the server:

[0619] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[0620] 4. Use of Emotion Engine:

[0621] The server uses an emotion engine to recognize that the message expresses a positive emotion.

[0622] 5. Identifying and Inserting Emojis:

[0623] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play," and then selects appropriate emojis that express positive emotions.

[0624] Generate a new message: "Today was so much fun 😊. Let's play again 🎮!"

[0625] 6. Send a new message:

[0626] The server sends a new message to the device.

[0627] 7. Displaying messages in the terminal:

[0628] Your device will receive a new message and display it in the chat window.

[0629] This system allows users to effectively insert appropriate emojis that reflect their emotions into text messages, significantly improving the quality of communication.

[0630] The processing flow will be explained below.

[0631] Step 1:

[0632] The user types a message, for example, "Today was so much fun! Let's hang out again!" into the chat tool's input field.

[0633] Step 2:

[0634] The user clicks the send button to send the entered text message.

[0635] Step 3:

[0636] The device packages the user-entered text message into JSON format.

[0637] Step 4:

[0638] The device sends a message as an HTTP POST request to the server endpoint.

[0639] Step 5:

[0640] The server receives the HTTP request and extracts the text message.

[0641] Step 6:

[0642] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0643] Step 7:

[0644] The server uses an emotion engine to analyze the emotion of the entire text message, for example, recognizing that the message expresses a positive emotion such as "fun."

[0645] Step 8:

[0646] Based on the analysis results, the server retrieves emojis corresponding to keywords, phrases, and the emotion engine's recognition results from a database or mapping list.

[0647] Step 9:

[0648] The server identifies the emoji "😊" that corresponds to "It was fun," the emoji "😁" that corresponds to the positive emotion identified by the emotion engine, and the emoji "🎮" that corresponds to "Let's play."

[0649] Step 10:

[0650] The server then inserts the identified emoji into the appropriate position in the text message, for example, "Today was so much fun 😊😁. Let's hang out again 🎮!"

[0651] Step 11:

[0652] The server generates a new text message with the emoji inserted and repackages it into JSON format.

[0653] Step 12:

[0654] The server sends the generated new message to the user's device as an HTTP response.

[0655] Step 13:

[0656] The device receives the HTTP response and parses the JSON format.

[0657] Step 14:

[0658] The device displays a new message in the user's chat window: "Today was so much fun 😊😁. Let's hang out again 🎮!"

[0659] Example 2

[0660] 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."

[0661] In recent years, communication primarily based on text messages has rapidly spread, but there is a problem in that it is difficult to accurately convey emotions. This is because simple text alone cannot adequately convey the emotional nuances of a message, which can easily lead to misunderstandings and lack of communication between users. In addition, manually inserting emojis is time-consuming, which can detract from the user experience. There is a need for a system that can solve these issues and enable smoother and richer communication.

[0662] 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.

[0663] In this invention, the server includes means for receiving a text message entered by a user, means for analyzing keywords and fixed phrases in the text message, means for recognizing emotions in the analyzed text message, means for identifying emojis corresponding to the recognized emotions based on the identified emotions, means for inserting the identified emojis into the text message, and means for transmitting the generated message to the user's terminal. This allows the user to automatically insert emojis that reflect emotions into messages, thereby reducing misunderstandings about emotions and enabling richer communication.

[0664] "User" means a person who uses the System to enter and send text messages.

[0665] "Text Message" means textual information entered by a User and sent and received through the System.

[0666] "Keywords" are important words or phrases within a text message that are identified and analyzed by the system.

[0667] A "fixed phrase" is a phrase or expression that has a certain pattern and is included in a text message and is the subject of analysis.

[0668] "Emotion" refers to the psychological nuances or states expressed in text messages, and can be classified as positive, negative, neutral, etc.

[0669] "Emoji" refers to small images or icons used to visually represent emotions or concepts.

[0670] "Natural language processing libraries" refers to software tools and frameworks used to analyze text messages.

[0671] "JSON format" is an abbreviation for JavaScript Object Notation and refers to a lightweight data format used for data exchange.

[0672] An "HTTP POST request" is a type of HTTP method for sending data to a web server, and is primarily used for data submission.

[0673] MODE FOR CARRYING OUT THE INVENTION

[0674] The present invention is a message processing system that receives a text message entered by a user, analyzes keywords and fixed phrases in the message, recognizes emotions using an emotion engine, and identifies and inserts corresponding emojis to improve the readability and emotional communication of the text message. This system is configured by combining hardware and software.

[0675] Hardware and software used

[0676] Hardware:

[0677] User device (e.g. smartphone, PC)

[0678] Server (e.g. cloud server, dedicated server)

[0679] software:

[0680] Natural language processing libraries (e.g., SpaCy, NLTK)

[0681] Sentiment Analysis Engine

[0682] Database or Mapping List

[0683] Communication protocol (e.g. HTTP, JSON)

[0684] How the system is implemented

[0685] 1. User Input

[0686] The user enters a text message into the chat tool's input field and clicks the send button. For example, the user can enter "I had a great time today. Let's hang out again!"

[0687] 2. Sending a Message

[0688] The device packages the text message entered by the user into JSON format and sends it to the server endpoint as an HTTP POST request, which transfers the message data to the server.

[0689] 3. Message Reception and Analysis by the Server

[0690] The server unpacks the received HTTP request and extracts the text message. It then uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases. For example, "It was fun" or "Let's play" might be identified.

[0691] 4. Use of Emotion Engine

[0692] The server uses an emotion engine to analyze the emotion of the entire text message, for example recognizing that the message expresses a positive emotion such as "fun."

[0693] 5. Identifying and Inserting Emojis

[0694] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, the emoji "😊" corresponds to "fun" and the emoji "🎮" corresponds to "let's play." The server then inserts the identified emojis into a text message to generate a new message. For example, "Today was so much fun 😊. Let's play again 🎮!"

[0695] 6. Send a new message

[0696] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[0697] 7. Displaying Messages

[0698] The device unpacks the received HTTP response and parses the message from the JSON format. The new message is then displayed in the user's chat window.

[0699] Specific examples

[0700] If a user wants to send a message to a friend saying, "I had a great time today. Let's hang out again!", the system works as follows:

[0701] 1. User input and submission

[0702] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[0703] 2. Sending a message from the device to the server

[0704] The device sends a message in JSON format to the server.

[0705] 3. Receiving and analyzing messages on the server

[0706] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[0707] 4. Use of Emotion Engine

[0708] The server uses an emotion engine to recognize that the message expresses a positive emotion.

[0709] 5. Identifying and Inserting Emojis

[0710] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play," and generates a new message: "Today was so much fun 😊. Let's play again 🎮!"

[0711] 6. Send a new message

[0712] The server sends a new message to the device.

[0713] 7. Displaying messages on the terminal

[0714] Your device will receive a new message and display it in the chat window.

[0715] This system allows users to effectively insert emojis that reflect their emotions into text messages, significantly improving the quality of communication.

[0716] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0717] Step 1:

[0718] A user enters a text message into the chat tool's input field and clicks the send button. For example, "I had a great time today. Let's hang out again!" The input in this case is the user's text message, and the output is the click event of the send button.

[0719] Step 2:

[0720] The device receives the text message entered by the user when the send button is clicked. The device then packages the text message in JSON format and sends it as an HTTP POST request to the specified endpoint on the server. The input is the user's text message, and the output is message data in JSON format. This process converts the text message into JSON format and sends it to the server.

[0721] Step 3:

[0722] The server receives the HTTP POST request and retrieves the message data in JSON format. After extracting the text message from the retrieved data, it uses a natural language processing library (e.g., SpaCy or NLTK) to analyze the text message and identify keywords and standard phrases. The input is the message data in JSON format, and the output is the analyzed keywords and standard phrases. Specifically, it identifies keywords such as "It was fun" and "Let's play."

[0723] Step 4:

[0724] The server uses a sentiment analysis engine to analyze the sentiment of the entire text message. For example, it recognizes the positive sentiment of "fun" from the message "Today was so much fun. Let's hang out again!" The input is the text message, and the output is the recognized sentiment (e.g., positive). This process identifies the sentiment of the message.

[0725] Step 5:

[0726] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, "I had fun" corresponds to the emoji "😊" and "Let's play" corresponds to the emoji "🎮". Next, a new message is generated by inserting the identified emojis into a text message. The input is the analyzed keywords and emotions, and the output is the identified emojis and a new text message (e.g., "I had a lot of fun today 😊. Let's play again 🎮!").

[0727] Step 6:

[0728] The server repackages the generated new message into JSON format and sends it as an HTTP response to the user's device. The input is the new text message and the output is JSON formatted data. This process sends the new message to the device.

[0729] Step 7:

[0730] The device receives the HTTP response and parses the JSON-formatted data. The resulting new message is displayed in the user's chat window. The input is JSON-formatted data, and the output is a new message (e.g., "Today was so much fun 😊. Let's play again 🎮!") that is displayed in the user's chat window. This allows the user to visually confirm the new message.

[0731] The above are the specific processing steps and flow of the system. This system allows users to easily send text messages that reflect their emotions, thereby improving the quality of communication.

[0732] (Application example 2)

[0733] 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."

[0734] With conventional messaging systems, it is difficult to convey emotions in text-based communication, making it difficult to accurately grasp the other person's intentions and emotions. Furthermore, in brick-and-mortar stores, communication with customers tends to be emotionless and monotonous, which can lead to a decrease in customer satisfaction. To solve these problems, there is a need for a way to reflect emotions in text messages and convey them in a visually easy-to-understand format.

[0735] 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 receiving a text message entered by a user, means for analyzing keywords and set phrases in the text message, means for recognizing emotions in the text message using an emotion engine, means for identifying emojis corresponding to the analyzed keywords and set phrases and the recognized emotions, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to a user's terminal, means for displaying the generated message on the user's device, and means corresponding to an application installed on a smartphone, smart glasses, a head-mounted display, or a robot. This makes it possible to easily reflect emotions in a text message and convey them in a visually easy-to-understand manner.

[0736] "User" means a person who uses a system or device to input and send text messages.

[0737] "Text message" refers to a message in the form of a string of characters that is entered and sent by a user.

[0738] "Keywords" refer to important words that appear in a text message and have a particular meaning or sentiment.

[0739] A "fixed phrase" is a commonly used expression or phrase.

[0740] "Emotion engine" refers to a software component for analyzing and recognizing emotions from input text messages.

[0741] "Emoji" refers to small icons inserted into text messages to visually express emotions or concepts.

[0742] A "natural language processing library" refers to a software tool used to analyze text data and identify keywords and phrases.

[0743] A "smartphone" refers to a mobile information terminal that has multiple functions, including voice communication capabilities, Internet access, and application execution.

[0744] "Smart glasses" are a wearable device in the shape of glasses that has the ability to display information and connect to the Internet.

[0745] A "head-mounted display" refers to a display device worn on the head to display visual information and digital content.

[0746] "Robot" refers to a mechanical device that performs automated operation or interaction and is programmed to perform specific tasks or interactions.

[0747] This invention is a system that analyzes text messages entered by a user, recognizes emotions, and inserts appropriate emoticons. This system uses the following hardware and software configuration.

[0748] First, a user types and sends a text message from a device such as a smartphone, smart glasses, head-mounted display, or robot. When the user sends a message such as "Do you have any recommendations for me today?", the text message is packaged in JSON format and sent to the server.

[0749] The server then processes the received text message using the following software:

[0750] 1. Use a natural language processing library (e.g., SpaCy, NLTK) to analyze text messages and identify keywords and boilerplate phrases.

[0751] 2. Recognize the sentiment of the message using an emotion engine (e.g., Google Cloud Natural Language API).

[0752] Based on the analysis results, emojis corresponding to keywords, phrases, and recognized emotions are retrieved from a database or mapping list. For example, "🛍" is identified for "recommended items." Then, the identified emojis are inserted into a text message to generate a new message: "Do you have any recommendations for me today? 🛍?"

[0753] The generated message is then packaged in JSON format and sent to the user's device for display, allowing users to visually express emotions in their text messages, making communication smoother and richer.

[0754] Specific examples of hardware and software used

[0755] Hardware:

[0756] Smartphones (iOS and Android devices)

[0757] Smart Glasses

[0758] head-mounted display

[0759] Robots (e.g. Pepper)

[0760] software:

[0761] Natural language processing libraries: SpaCy, NLTK

[0762] Sentiment analysis engine: Google Cloud Natural Language API

[0763] Database: MySQL, Firebase Realtime Database

[0764] Application Framework: Flutter, React Native

[0765] Examples of concrete examples and prompts

[0766] A concrete example is when a user sends a message to a friend saying, "What do you have for me today?" This message is parsed to detect emotion and generate a new message with the appropriate emoji inserted: "What do you have for me today? 🛍?"

[0767] Example prompt sentence:

[0768] Based on the message entered by the customer, analyze the sentiment and create a reply with appropriate emojis.

[0769] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0770] Step 1:

[0771] A user types a text message into a device (e.g., smartphone, smart glasses, head-mounted display, robot) and clicks the "Send" button. The input is "Do you have any recommendations for me today?". This causes the text message typed by the user to be captured within the device.

[0772] Step 2:

[0773] The device packages the captured text message into JSON format and sends it to the server as an HTTP POST request. The input data is the text message and the user's ID, and the output data is the HTTP request sent to the server.

[0774] Step 3:

[0775] The server receives an HTTP request and extracts the text message. The input data is message data in JSON format, and the output data is the extracted text message. Specifically, the server analyzes the received data and extracts the string portion of the text message.

[0776] Step 4:

[0777] The server uses natural language processing libraries (SpaCy or NLTK) to analyze text messages and identify keywords and phrases. The input data is the extracted text message, and the output data is the identified keywords and phrases. Specific operations include tokenizing the text, tagging parts of speech, and dependency analysis.

[0778] Step 5:

[0779] The server uses an emotion engine (such as the Google Cloud Natural Language API) to recognize the emotion of a text message. The input data is a text message containing identified keywords and phrases, and the output data is the emotion type (e.g., positive, negative, neutral). Specific operations include calculating an emotion score for the entire message and classifying it.

[0780] Step 6:

[0781] The server retrieves the analysis results and emojis corresponding to the emotions from a database or mapping list. The input data are the identified keywords and emotion types, and the output data are the corresponding emojis. Specifically, the server searches for and retrieves the corresponding emojis from the database.

[0782] Step 7:

[0783] The server inserts the identified emoji into the text message to generate a new message. The input data is the original text message and the corresponding emoji, and the output data is the new message with the inserted emoji. The specific operation is to insert the emoji into a specific position in the text.

[0784] Step 8:

[0785] The server then packages the new message into JSON format and sends it to the user's device as an HTTP response. The input data is the new text message, and the output data is the JSON response. Specifically, the server converts the message into a JSON object and sends it.

[0786] Step 9:

[0787] The terminal receives the HTTP response and parses the JSON format. The input data is the received JSON response, and the output data is the parsed new text message. Specifically, the terminal parses the response data and extracts the text portion.

[0788] Step 10:

[0789] The terminal displays the parsed new message on the user's device. The input data is the parsed new message, and the output data is the message displayed in the user's chat window. A specific operation is to render the message in a user interface.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] [Third embodiment]

[0794] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0795] 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.

[0796] 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).

[0797] 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.

[0798] 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.

[0799] 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).

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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."

[0806] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, and identifies and inserts corresponding emoticons. This system improves the visibility and emotional conveyance of text message communications, thereby realizing smoother communication.

[0807] System configuration and operation

[0808] 1. User input:

[0809] The user types a text message into the chat tool's input field, for example, "Today was so much fun! Let's hang out again!"

[0810] The user sends the message by clicking the send button.

[0811] 2. Sending a message:

[0812] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint.

[0813] 3. Message received and parsed by the server:

[0814] The server receives the HTTP request and extracts the text message.

[0815] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "that was fun" or "let's play."

[0816] 4. Identify and insert emojis:

[0817] The server retrieves emojis corresponding to the identified keywords or phrases from a database or mapping list. For example, "It was fun" corresponds to the emoji "😊" and "Let's play" corresponds to the emoji "🎮."

[0818] The server then inserts the identified emoji into a text message and generates a new message, such as "Today was so much fun 😊. Let's hang out again 🎮!"

[0819] 5. Send a new message:

[0820] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[0821] 6. Displaying messages:

[0822] The terminal receives the HTTP response and parses the JSON format.

[0823] A new message appears in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0824] Specific examples

[0825] Situation

[0826] A user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!"

[0827] How it works

[0828] 1. User input and submission:

[0829] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[0830] 2. Sending a message from the device to the server:

[0831] The device sends a message in JSON format to the server.

[0832] 3. Receiving and parsing messages on the server:

[0833] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[0834] 4. Identify and insert emojis:

[0835] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play" and inserts them into the message.

[0836] Generate a new message: "Today was so much fun 😊. Let's play again 🎮!"

[0837] 5. Send a new message:

[0838] The server sends a new message to the device.

[0839] 6. Displaying messages on the terminal:

[0840] Your device will receive a new message and display it in the chat window.

[0841] This system allows users to effectively insert appropriate emojis into text messages, improving the quality of communication.

[0842] The processing flow will be explained below.

[0843] Step 1:

[0844] The user types a message, for example, "Today was so much fun! Let's hang out again!" into the chat tool's input field.

[0845] Step 2:

[0846] The user clicks the send button to send the entered text message.

[0847] Step 3:

[0848] The device packages the user-entered text message into JSON format.

[0849] Step 4:

[0850] The device sends a message as an HTTP POST request to the server endpoint.

[0851] Step 5:

[0852] The server receives the HTTP request and extracts the text message.

[0853] Step 6:

[0854] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[0855] Step 7:

[0856] Based on the analysis results, the server refers to a database or mapping list to identify emojis that correspond to keywords or phrases.

[0857] Step 8:

[0858] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play."

[0859] Step 9:

[0860] The server then inserts the identified emoji into the appropriate position in the text message, for example, "Today was so much fun 😊. Let's hang out again 🎮!"

[0861] Step 10:

[0862] The server generates a new text message with the emoji inserted and repackages it into JSON format.

[0863] Step 11:

[0864] The server sends the generated new message to the user's device as an HTTP response.

[0865] Step 12:

[0866] The device receives the HTTP response and parses the JSON format.

[0867] Step 13:

[0868] The device displays a new message in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0869] Example 1

[0870] 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."

[0871] In recent years, communication using text messages has become very common, but there are issues with text alone, such as a lack of visibility and ability to convey emotions. This can lead to misunderstandings and impair smooth communication. To solve this problem and achieve richer and more effective communication, a system that can easily and automatically insert appropriate emojis into text messages is needed.

[0872] 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.

[0873] In this invention, the server includes means for receiving a text message entered by a user, means for analyzing keywords and set phrases in the text message, means for identifying emojis corresponding to the analyzed keywords and set phrases, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to the user's terminal, and means for displaying the generated message on the user's terminal. This allows the user to easily insert appropriate emojis into the text message, improving the visibility of communication and the ability to convey emotions, thereby enabling smoother communication.

[0874] "User" means a person who utilizes the System to enter, send, and receive text messages.

[0875] "Text message" refers to character string information that a user inputs and sends using a terminal.

[0876] "Keywords" refer to important words in a text message that convey a particular meaning or emotion.

[0877] "Phrases" refer to specific expressions or phrases that are frequently used in text messages.

[0878] "Analyzing" refers to analyzing text messages using natural language processing libraries and identifying keywords and phrases.

[0879] "Emoji" refers to small images or icons inserted into text messages that visually convey emotions or states.

[0880] "Inserting" refers to placing the identified emoji in the position of the corresponding keyword or phrase.

[0881] "Generating" refers to creating a new text message with the emoji inserted.

[0882] "Sending" refers to transferring the generated text message from the server to the user's terminal.

[0883] "Display" refers to displaying the generated text message on the screen of the user's terminal.

[0884] A "natural language processing library" refers to a software library that helps analyze and understand text data.

[0885] "JSON format" is an abbreviation for JavaScript Object Notation and refers to a lightweight data exchange format for representing structured data.

[0886] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a user uses to enter and receive text messages.

[0887] "Server" refers to the computer system that parses messages, identifies and inserts emojis, and creates and sends new messages.

[0888] MODE FOR CARRYING OUT THE INVENTION

[0889] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, and identifies and inserts corresponding emoticons. This system improves the visibility and emotional conveyance of text message communications, thereby realizing smoother communication.

[0890] Configuration and Operation

[0891] User Input

[0892] A user types a text message into the chat tool's input field and clicks the send button. For example, the user can type "I had a great time today. Let's hang out again!"

[0893] Sending a message

[0894] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint. Specifically, it converts the message into the format { "message": "Today was so much fun. Let's play again!"} and sends a POST request to https: / / example.com / api / messages.

[0895] Server receives and analyzes messages

[0896] The server receives an HTTP request and extracts the text message. For example, the extracted message might be {"message": "Today was so much fun. Let's hang out again!"}. The server then uses a natural language processing library to analyze the message and identify keywords and boilerplate phrases. Examples of natural language processing libraries that can be used include SpaCy and NLTK. The analysis results in the identification of "I had fun" and "Let's hang out."

[0897] Identifying and inserting emojis

[0898] The server retrieves emojis from a database or mapping list that correspond to the identified keywords or phrases. For example, it retrieves the emoji "😊" that corresponds to "I had fun" and the emoji "🎮" that corresponds to "Let's play." The server then inserts these emojis into the appropriate places and generates a new message. As a result, the text message is transformed into "Today was so much fun 😊. Let's play again 🎮!"

[0899] Sending a new message

[0900] The server then packages the new message into JSON format and sends it to the user's device as an HTTP response. Specifically, the server converts the new message into the format { "message": "Today was so much fun 😊. Let's play again 🎮!"} and returns it as a response.

[0901] Displaying messages

[0902] The device receives the HTTP response and parses the JSON format. The parsed message is displayed in the chat window. For example, a message like "Today was so much fun 😊. Let's play again 🎮!" is displayed.

[0903] Specific examples

[0904] For example, if a user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!", the system will analyze the message and insert appropriate emojis. Ultimately, the friend will see the message, "Today was so much fun! 😊 Let's hang out again! 🎮!" This improves the visibility of text messages and their ability to convey emotions, making communication more effective.

[0905] Prompt Sentence Examples

[0906] "If a user types 'I had so much fun today. Let's hang out again!', explain how you would insert an emoji."

[0907] This system allows users to easily insert appropriate emojis into text messages, improving the quality of communication.

[0908] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0909] Step 1: User Input and Submission

[0910] The user enters a text message in the input field of the chat tool and clicks the send button. An example of input content is "Today was so much fun. Let's hang out again!". The text "Today was so much fun. Let's hang out again!" is given as input. Here, the user presses the enter key or clicks the send icon. This triggers the sending of the text message to the terminal as output.

[0911] Step 2: Sending a message

[0912] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint. The input is the text message entered by the user. Data processing converts the message to { "message": "Today was so much fun. Let's play again!"}. The output is an HTTP POST request containing the packaged JSON message.

[0913] Step 3: Server receives and analyzes the message

[0914] The server receives an HTTP request and extracts the text message. The input is an HTTP request in JSON format. Data processing involves extracting {"message": "Today was so much fun. Let's play again!"} from the request body to obtain the message. The output is the extracted text message. Next, the server uses a natural language processing library (for example, SpaCy or NLTK) to parse the text message. The input is the extracted text message. Data processing involves analyzing the message and identifying keywords such as "I had fun" or "Let's play." The output is the identified keywords.

[0915] Step 4: Identify and insert emojis

[0916] The server retrieves emojis from a database or mapping list that correspond to the identified keywords or phrases. The input is the identified keywords. The data processing involves retrieving the corresponding emojis from the database. For example, "😊" corresponds to "fun" and "🎮" corresponds to "let's play." The output is the corresponding emojis. The server then inserts these emojis into the appropriate places to generate a new message. The input is the original text message and the identified emojis. The data operation involves inserting the emojis to generate a new message, for example, "Today was so much fun 😊. Let's play again 🎮!" The output is the new message that is generated.

[0917] Step 5: Send a new message

[0918] The server packages the generated new message into JSON format again and sends it to the user's device as an HTTP response. The input is the generated new text message. For data processing, the new message is packaged into { "message": "Today was so much fun 😊. Let's play again 🎮!"}. The output is sent to the user's device as a JSON format HTTP response.

[0919] Step 6: Displaying messages

[0920] The terminal receives the HTTP response and parses the JSON format. The input is the HTTP response. As data processing, it extracts {"message": "Today was so much fun 😊. Let's hang out again 🎮!"} from the response body. The output is the extracted new message. Next, the terminal displays the new message in the user's chat window. The input is the extracted new message. As data processing, it converts it into a displayable format and displays it in the chat window. For example, the message "Today was so much fun 😊. Let's hang out again 🎮!" is displayed. This is the final output.

[0921] (Application example 1)

[0922] 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."

[0923] Traditional text message communication lacks visibility and the ability to convey emotions, and especially in virtual stores, the interaction between store staff and customers can feel robotic and unfriendly, which can lead to a poor user experience and negatively impact customer satisfaction and repeat business.

[0924] 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.

[0925] In this invention, the server includes means for receiving a text message input by a user, means for analyzing keywords and fixed phrases in the text message, means for identifying emojis corresponding to the analyzed keywords and fixed phrases, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to the user's terminal, and means installed in the smart glasses for realizing emotional dialogue in real time, thereby enabling the effective insertion of appropriate emojis into the text message and improving the quality of communication.

[0926] "User" means a person who uses the System to enter and send text messages.

[0927] A "text message" refers to a message consisting of characters and symbols entered by a user.

[0928] "Keywords" refer to important words contained within a text message that the system analyzes.

[0929] "Phrases" refer to specific patterns or phrases contained within text messages.

[0930] "Analysis" refers to the process of analyzing text messages to identify keywords and phrases.

[0931] "Emoji" refers to symbols or images inserted into text messages to visually express emotions.

[0932] A "server" refers to a computer system that receives, analyzes, and processes text messages sent from user terminals.

[0933] "Smart glasses" are wearable devices worn by users that have communication and display functions and can send and receive messages in real time.

[0934] "Real-time" refers to the property of providing a nearly instantaneous response.

[0935] The present invention relates to a message processing system that receives text messages entered by a user, analyzes keywords and phrases in the messages, and identifies and inserts corresponding emojis. This system is specialized for realizing emotionally rich interactions in real time using smart glasses. The following describes in detail the embodiments of the present invention.

[0936] System configuration and operation

[0937] 1. User input:

[0938] The user inputs a text message using the input interface of the smart glasses, for example, "Here are the latest sales! Check them out!" The input is temporarily stored in the smart glasses.

[0939] 2. Sending a message:

[0940] The smart glasses convert the text message entered by the user into JSON format and send it to the server as an HTTP POST request. The communication protocol used here is HTTP, and the data format is JSON.

[0941] 3. Message analysis:

[0942] The server parses the incoming HTTP request and extracts the text message, which is then analyzed using a natural language processing library (e.g., SpaCy) to identify keywords and phrases, such as "sale items" or "check it out."

[0943] 4. Identify and insert emojis:

[0944] The server retrieves emojis corresponding to the identified keywords or phrases from a database (e.g., SQLite) or mapping list. For example, "sale items" corresponds to the emoji "🛍️" and "check it out" corresponds to the emoji "👀". The server then inserts the identified emojis into a text message to generate a new message. For example, "Here are our latest sale items 🛍️! Check them out 👀!"

[0945] 5. Create and send a new message:

[0946] The server then packages the new generated message back into JSON format and sends it to the smart glasses as an HTTP response.

[0947] 6. Displaying messages:

[0948] The smart glasses parse the received HTTP response and extract the new message from the JSON formatted data, which is then displayed on the smart glasses' display, allowing users to continue communicating with appropriate emojis inserted into their text messages.

[0949] Specific examples

[0950] For example, if a customer in a virtual store sends a text message through their smart glasses saying, "Tell me what products are on sale," the server will identify the keyword "products on sale" and insert the corresponding emoji "🛒" into the message, which will generate a new message "Tell me what products are on sale 🛒" and display it on the customer's smart glasses.

[0951] Prompt Sentence Examples

[0952] Generate a program that reads "Here are our latest sale items! Check them out" and displays "Here are our latest sale items 🛍️! Check them out 👀" with an emoji inserted.

[0953] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0954] Step 1:

[0955] A user inputs a text message using the input interface of the smart glasses. The input message is temporarily stored in the smart glasses. The input of this step is the text message input by the user, and the output is the text data temporarily stored in the smart glasses.

[0956] Step 2:

[0957] The smart glasses convert the stored text message into JSON format and send it as an HTTP POST request to the server. The input of this step is the stored text data, and the output is the data converted into JSON format. The smart glasses send this to the server using the HTTP protocol.

[0958] Step 3:

[0959] The server analyzes the received HTTP request and extracts the text message. It parses the received data to get the text message part. The input of this step is the JSON data sent from the smart glasses, and the output is the extracted text message.

[0960] Step 4:

[0961] The server analyzes the extracted text messages using a natural language processing library (e.g., SpaCy) to identify keywords and standard phrases. The data processing performed in this step is to identify keywords and standard phrases. The input of this step is the extracted text messages, and the output is the identified keywords and standard phrases.

[0962] Step 5:

[0963] The server retrieves emojis corresponding to the identified keywords or phrases from a database (e.g., SQLite) or mapping list. The input of this step is the identified keywords or phrases, and the output is the corresponding emojis. The server queries the database to retrieve the corresponding emojis.

[0964] Step 6:

[0965] The server inserts the identified emoji into the text message and generates a new message. The input of this step is the identified emoji and the original text message, and the output is the newly generated message. Specifically, string manipulation is used to insert the emoji at the appropriate position.

[0966] Step 7:

[0967] The server packages the generated new message into JSON format again and sends it to the smart glasses as an HTTP response. The input of this step is the generated message and the output is JSON format data, which the server sends to the smart glasses using the HTTP protocol.

[0968] Step 8:

[0969] The smart glasses parse the received HTTP response and extract the new message from the JSON formatted data. The input of this step is the JSON data sent from the server, and the output is the extracted new message, which the smart glasses then convert into a format for display.

[0970] Step 9:

[0971] The smart glasses display the extracted new message on the display. The input of this step is the extracted new message, and the output is the message displayed on the display, allowing the user to view the message with the emoji inserted.

[0972] 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.

[0973] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, recognizes emotions using an emotion engine, and identifies and inserts corresponding emojis. This system significantly improves the readability and emotional conveyance of text messages, enabling smoother and richer communication.

[0974] System configuration and operation

[0975] 1. User input:

[0976] The user types a text message into the chat tool's input field, for example, "Today was so much fun! Let's hang out again!"

[0977] The user sends the message by clicking the send button.

[0978] 2. Sending a message:

[0979] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint.

[0980] 3. Message received and parsed by the server:

[0981] The server receives the HTTP request and extracts the text message.

[0982] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "that was fun" or "let's play."

[0983] 4. Use of Emotion Engine:

[0984] The server uses an emotion engine to analyze the emotion of the entire text message, for example recognizing that the message expresses a positive emotion such as "fun."

[0985] 5. Identify and insert emojis:

[0986] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, the emoji "😊" corresponds to "It was fun," and the emoji "🎮" corresponds to "Let's play."

[0987] The server then inserts the identified emoji into a text message and generates a new message, such as "Today was so much fun 😊. Let's hang out again 🎮!"

[0988] 6. Send a new message:

[0989] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[0990] 7. Displaying messages:

[0991] The terminal receives the HTTP response and parses the JSON format.

[0992] A new message appears in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[0993] Specific examples

[0994] Situation

[0995] A user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!"

[0996] How it works

[0997] 1. User input and submission:

[0998] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[0999] 2. Sending a message from the device to the server:

[1000] The device sends a message in JSON format to the server.

[1001] 3. Receiving and parsing messages on the server:

[1002] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[1003] 4. Use of Emotion Engine:

[1004] The server uses an emotion engine to recognize that the message expresses a positive emotion.

[1005] 5. Identify and insert emojis:

[1006] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play," and then selects appropriate emojis that express positive emotions.

[1007] Generate a new message: "Today was so much fun 😊. Let's play again 🎮!"

[1008] 6. Send a new message:

[1009] The server sends a new message to the device.

[1010] 7. Displaying messages in the terminal:

[1011] Your device will receive a new message and display it in the chat window.

[1012] This system allows users to effectively insert appropriate emojis that reflect their emotions into text messages, significantly improving the quality of communication.

[1013] The processing flow will be explained below.

[1014] Step 1:

[1015] The user types a message, for example, "Today was so much fun! Let's hang out again!" into the chat tool's input field.

[1016] Step 2:

[1017] The user clicks the send button to send the entered text message.

[1018] Step 3:

[1019] The device packages the user-entered text message into JSON format.

[1020] Step 4:

[1021] The device sends a message as an HTTP POST request to the server endpoint.

[1022] Step 5:

[1023] The server receives the HTTP request and extracts the text message.

[1024] Step 6:

[1025] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[1026] Step 7:

[1027] The server uses an emotion engine to analyze the emotion of the entire text message, for example, recognizing that the message expresses a positive emotion such as "fun."

[1028] Step 8:

[1029] Based on the analysis results, the server retrieves emojis corresponding to keywords, phrases, and the emotion engine's recognition results from a database or mapping list.

[1030] Step 9:

[1031] The server identifies the emoji "😊" that corresponds to "It was fun," the emoji "😁" that corresponds to the positive emotion identified by the emotion engine, and the emoji "🎮" that corresponds to "Let's play."

[1032] Step 10:

[1033] The server then inserts the identified emoji into the appropriate position in the text message, for example, "Today was so much fun 😊😁. Let's hang out again 🎮!"

[1034] Step 11:

[1035] The server generates a new text message with the emoji inserted and repackages it into JSON format.

[1036] Step 12:

[1037] The server sends the generated new message to the user's device as an HTTP response.

[1038] Step 13:

[1039] The device receives the HTTP response and parses the JSON format.

[1040] Step 14:

[1041] The device displays a new message in the user's chat window: "Today was so much fun 😊😁. Let's hang out again 🎮!"

[1042] Example 2

[1043] 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."

[1044] In recent years, communication primarily based on text messages has rapidly spread, but there is a problem in that it is difficult to accurately convey emotions. This is because simple text alone cannot adequately convey the emotional nuances of a message, which can easily lead to misunderstandings and lack of communication between users. In addition, manually inserting emojis is time-consuming, which can detract from the user experience. There is a need for a system that can solve these issues and enable smoother and richer communication.

[1045] 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.

[1046] In this invention, the server includes means for receiving a text message entered by a user, means for analyzing keywords and fixed phrases in the text message, means for recognizing emotions in the analyzed text message, means for identifying emojis corresponding to the recognized emotions based on the identified emotions, means for inserting the identified emojis into the text message, and means for transmitting the generated message to the user's terminal. This allows the user to automatically insert emojis that reflect emotions into messages, thereby reducing misunderstandings about emotions and enabling richer communication.

[1047] "User" means a person who uses the System to enter and send text messages.

[1048] "Text Message" means textual information entered by a User and sent and received through the System.

[1049] "Keywords" are important words or phrases within a text message that are identified and analyzed by the system.

[1050] A "fixed phrase" is a phrase or expression that has a certain pattern and is included in a text message and is the subject of analysis.

[1051] "Emotion" refers to the psychological nuances or states expressed in text messages, and can be classified as positive, negative, neutral, etc.

[1052] "Emoji" refers to small images or icons used to visually represent emotions or concepts.

[1053] "Natural language processing libraries" refers to software tools and frameworks used to analyze text messages.

[1054] "JSON format" is an abbreviation for JavaScript Object Notation and refers to a lightweight data format used for data exchange.

[1055] An "HTTP POST request" is a type of HTTP method for sending data to a web server, and is primarily used for data submission.

[1056] MODE FOR CARRYING OUT THE INVENTION

[1057] The present invention is a message processing system that receives a text message entered by a user, analyzes keywords and fixed phrases in the message, recognizes emotions using an emotion engine, and identifies and inserts corresponding emojis to improve the readability and emotional communication of the text message. This system is configured by combining hardware and software.

[1058] Hardware and software used

[1059] Hardware:

[1060] User device (e.g. smartphone, PC)

[1061] Server (e.g. cloud server, dedicated server)

[1062] software:

[1063] Natural language processing libraries (e.g., SpaCy, NLTK)

[1064] Sentiment Analysis Engine

[1065] Database or Mapping List

[1066] Communication protocol (e.g. HTTP, JSON)

[1067] How the system is implemented

[1068] 1. User Input

[1069] The user enters a text message into the chat tool's input field and clicks the send button. For example, the user can enter "I had a great time today. Let's hang out again!"

[1070] 2. Sending a Message

[1071] The device packages the text message entered by the user into JSON format and sends it to the server endpoint as an HTTP POST request, which transfers the message data to the server.

[1072] 3. Message Reception and Analysis by the Server

[1073] The server unpacks the received HTTP request and extracts the text message. It then uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases. For example, "It was fun" or "Let's play" might be identified.

[1074] 4. Use of Emotion Engine

[1075] The server uses an emotion engine to analyze the emotion of the entire text message, for example recognizing that the message expresses a positive emotion such as "fun."

[1076] 5. Identifying and Inserting Emojis

[1077] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, the emoji "😊" corresponds to "fun" and the emoji "🎮" corresponds to "let's play." The server then inserts the identified emojis into a text message to generate a new message. For example, "Today was so much fun 😊. Let's play again 🎮!"

[1078] 6. Send a new message

[1079] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[1080] 7. Displaying Messages

[1081] The device unpacks the received HTTP response and parses the message from the JSON format. The new message is then displayed in the user's chat window.

[1082] Specific examples

[1083] If a user wants to send a message to a friend saying, "I had a great time today. Let's hang out again!", the system works as follows:

[1084] 1. User input and submission

[1085] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[1086] 2. Sending a message from the device to the server

[1087] The device sends a message in JSON format to the server.

[1088] 3. Receiving and analyzing messages on the server

[1089] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[1090] 4. Use of Emotion Engine

[1091] The server uses an emotion engine to recognize that the message expresses a positive emotion.

[1092] 5. Identifying and Inserting Emojis

[1093] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play," and generates a new message: "Today was so much fun 😊. Let's play again 🎮!"

[1094] 6. Send a new message

[1095] The server sends a new message to the device.

[1096] 7. Displaying messages on the terminal

[1097] Your device will receive a new message and display it in the chat window.

[1098] This system allows users to effectively insert emojis that reflect their emotions into text messages, significantly improving the quality of communication.

[1099] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1100] Step 1:

[1101] A user enters a text message into the chat tool's input field and clicks the send button. For example, "I had a great time today. Let's hang out again!" The input in this case is the user's text message, and the output is the click event of the send button.

[1102] Step 2:

[1103] The device receives the text message entered by the user when the send button is clicked. The device then packages the text message in JSON format and sends it as an HTTP POST request to the specified endpoint on the server. The input is the user's text message, and the output is message data in JSON format. This process converts the text message into JSON format and sends it to the server.

[1104] Step 3:

[1105] The server receives the HTTP POST request and retrieves the message data in JSON format. After extracting the text message from the retrieved data, it uses a natural language processing library (e.g., SpaCy or NLTK) to analyze the text message and identify keywords and standard phrases. The input is the message data in JSON format, and the output is the analyzed keywords and standard phrases. Specifically, it identifies keywords such as "It was fun" and "Let's play."

[1106] Step 4:

[1107] The server uses a sentiment analysis engine to analyze the sentiment of the entire text message. For example, it recognizes the positive sentiment of "fun" from the message "Today was so much fun. Let's hang out again!" The input is the text message, and the output is the recognized sentiment (e.g., positive). This process identifies the sentiment of the message.

[1108] Step 5:

[1109] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, "I had fun" corresponds to the emoji "😊" and "Let's play" corresponds to the emoji "🎮". Next, a new message is generated by inserting the identified emojis into a text message. The input is the analyzed keywords and emotions, and the output is the identified emojis and a new text message (e.g., "I had a lot of fun today 😊. Let's play again 🎮!").

[1110] Step 6:

[1111] The server repackages the generated new message into JSON format and sends it as an HTTP response to the user's device. The input is the new text message and the output is JSON formatted data. This process sends the new message to the device.

[1112] Step 7:

[1113] The device receives the HTTP response and parses the JSON-formatted data. The resulting new message is displayed in the user's chat window. The input is JSON-formatted data, and the output is a new message (e.g., "Today was so much fun 😊. Let's play again 🎮!") that is displayed in the user's chat window. This allows the user to visually confirm the new message.

[1114] The above are the specific processing steps and flow of the system. This system allows users to easily send text messages that reflect their emotions, thereby improving the quality of communication.

[1115] (Application example 2)

[1116] 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."

[1117] With conventional messaging systems, it is difficult to convey emotions in text-based communication, making it difficult to accurately grasp the other person's intentions and emotions. Furthermore, in brick-and-mortar stores, communication with customers tends to be emotionless and monotonous, which can lead to a decrease in customer satisfaction. To solve these problems, there is a need for a way to reflect emotions in text messages and convey them in a visually easy-to-understand format.

[1118] 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 receiving a text message entered by a user, means for analyzing keywords and set phrases in the text message, means for recognizing emotions in the text message using an emotion engine, means for identifying emojis corresponding to the analyzed keywords and set phrases and the recognized emotions, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to a user's terminal, means for displaying the generated message on the user's device, and means corresponding to an application installed on a smartphone, smart glasses, a head-mounted display, or a robot. This makes it possible to easily reflect emotions in a text message and convey them in a visually easy-to-understand manner.

[1119] "User" means a person who uses a system or device to input and send text messages.

[1120] "Text message" refers to a message in the form of a string of characters that is entered and sent by a user.

[1121] "Keywords" refer to important words that appear in a text message and have a particular meaning or sentiment.

[1122] A "fixed phrase" is a commonly used expression or phrase.

[1123] "Emotion engine" refers to a software component for analyzing and recognizing emotions from input text messages.

[1124] "Emoji" refers to small icons inserted into text messages to visually express emotions or concepts.

[1125] A "natural language processing library" refers to a software tool used to analyze text data and identify keywords and phrases.

[1126] A "smartphone" refers to a mobile information terminal that has multiple functions, including voice communication capabilities, Internet access, and application execution.

[1127] "Smart glasses" are a wearable device in the shape of glasses that has the ability to display information and connect to the Internet.

[1128] A "head-mounted display" refers to a display device worn on the head to display visual information and digital content.

[1129] "Robot" refers to a mechanical device that performs automated operation or interaction and is programmed to perform specific tasks or interactions.

[1130] This invention is a system that analyzes text messages entered by a user, recognizes emotions, and inserts appropriate emoticons. This system uses the following hardware and software configuration.

[1131] First, a user types and sends a text message from a device such as a smartphone, smart glasses, head-mounted display, or robot. When the user sends a message such as "Do you have any recommendations for me today?", the text message is packaged in JSON format and sent to the server.

[1132] The server then processes the received text message using the following software:

[1133] 1. Use a natural language processing library (e.g., SpaCy, NLTK) to analyze text messages and identify keywords and boilerplate phrases.

[1134] 2. Recognize the sentiment of the message using an emotion engine (e.g., Google Cloud Natural Language API).

[1135] Based on the analysis results, emojis corresponding to keywords, phrases, and recognized emotions are retrieved from a database or mapping list. For example, "🛍" is identified for "recommended items." Then, the identified emojis are inserted into a text message to generate a new message: "Do you have any recommendations for me today? 🛍?"

[1136] The generated message is then packaged in JSON format and sent to the user's device for display, allowing users to visually express emotions in their text messages, making communication smoother and richer.

[1137] Specific examples of hardware and software used

[1138] Hardware:

[1139] Smartphones (iOS and Android devices)

[1140] Smart Glasses

[1141] head-mounted display

[1142] Robots (e.g. Pepper)

[1143] software:

[1144] Natural language processing libraries: SpaCy, NLTK

[1145] Sentiment analysis engine: Google Cloud Natural Language API

[1146] Database: MySQL, Firebase Realtime Database

[1147] Application Framework: Flutter, React Native

[1148] Examples of concrete examples and prompts

[1149] A concrete example is when a user sends a message to a friend saying, "What do you have for me today?" This message is parsed to detect emotion and generate a new message with the appropriate emoji inserted: "What do you have for me today? 🛍?"

[1150] Example prompt sentence:

[1151] Based on the message entered by the customer, analyze the sentiment and create a reply with appropriate emojis.

[1152] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1153] Step 1:

[1154] A user types a text message into a device (e.g., smartphone, smart glasses, head-mounted display, robot) and clicks the "Send" button. The input is "Do you have any recommendations for me today?". This causes the text message typed by the user to be captured within the device.

[1155] Step 2:

[1156] The device packages the captured text message into JSON format and sends it to the server as an HTTP POST request. The input data is the text message and the user's ID, and the output data is the HTTP request sent to the server.

[1157] Step 3:

[1158] The server receives an HTTP request and extracts the text message. The input data is message data in JSON format, and the output data is the extracted text message. Specifically, the server analyzes the received data and extracts the string portion of the text message.

[1159] Step 4:

[1160] The server uses natural language processing libraries (SpaCy or NLTK) to analyze text messages and identify keywords and phrases. The input data is the extracted text message, and the output data is the identified keywords and phrases. Specific operations include tokenizing the text, tagging parts of speech, and dependency analysis.

[1161] Step 5:

[1162] The server uses an emotion engine (such as the Google Cloud Natural Language API) to recognize the emotion of a text message. The input data is a text message containing identified keywords and phrases, and the output data is the emotion type (e.g., positive, negative, neutral). Specific operations include calculating an emotion score for the entire message and classifying it.

[1163] Step 6:

[1164] The server retrieves the analysis results and emojis corresponding to the emotions from a database or mapping list. The input data are the identified keywords and emotion types, and the output data are the corresponding emojis. Specifically, the server searches for and retrieves the corresponding emojis from the database.

[1165] Step 7:

[1166] The server inserts the identified emoji into the text message to generate a new message. The input data is the original text message and the corresponding emoji, and the output data is the new message with the inserted emoji. The specific operation is to insert the emoji into a specific position in the text.

[1167] Step 8:

[1168] The server then packages the new message into JSON format and sends it to the user's device as an HTTP response. The input data is the new text message, and the output data is the JSON response. Specifically, the server converts the message into a JSON object and sends it.

[1169] Step 9:

[1170] The terminal receives the HTTP response and parses the JSON format. The input data is the received JSON response, and the output data is the parsed new text message. Specifically, the terminal parses the response data and extracts the text portion.

[1171] Step 10:

[1172] The terminal displays the parsed new message on the user's device. The input data is the parsed new message, and the output data is the message displayed in the user's chat window. A specific operation is to render the message in a user interface.

[1173] 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.

[1174] 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.

[1175] 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.

[1176] [Fourth embodiment]

[1177] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1178] 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.

[1179] 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).

[1180] 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.

[1181] 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.

[1182] 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).

[1183] 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.

[1184] 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.

[1185] 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.

[1186] 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.

[1187] 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.

[1188] 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.

[1189] 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."

[1190] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, and identifies and inserts corresponding emoticons. This system improves the visibility and emotional conveyance of text message communications, thereby realizing smoother communication.

[1191] System configuration and operation

[1192] 1. User input:

[1193] The user types a text message into the chat tool's input field, for example, "Today was so much fun! Let's hang out again!"

[1194] The user sends the message by clicking the send button.

[1195] 2. Sending a message:

[1196] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint.

[1197] 3. Message received and parsed by the server:

[1198] The server receives the HTTP request and extracts the text message.

[1199] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "that was fun" or "let's play."

[1200] 4. Identify and insert emojis:

[1201] The server retrieves emojis corresponding to the identified keywords or phrases from a database or mapping list. For example, "It was fun" corresponds to the emoji "😊" and "Let's play" corresponds to the emoji "🎮."

[1202] The server then inserts the identified emoji into a text message and generates a new message, such as "Today was so much fun 😊. Let's hang out again 🎮!"

[1203] 5. Send a new message:

[1204] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[1205] 6. Displaying messages:

[1206] The terminal receives the HTTP response and parses the JSON format.

[1207] A new message appears in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[1208] Specific examples

[1209] Situation

[1210] A user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!"

[1211] How it works

[1212] 1. User input and submission:

[1213] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[1214] 2. Sending a message from the device to the server:

[1215] The device sends a message in JSON format to the server.

[1216] 3. Receiving and parsing messages on the server:

[1217] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[1218] 4. Identify and insert emojis:

[1219] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play" and inserts them into the message.

[1220] Generate a new message: "Today was so much fun 😊. Let's play again 🎮!"

[1221] 5. Send a new message:

[1222] The server sends a new message to the device.

[1223] 6. Displaying messages on the terminal:

[1224] Your device will receive a new message and display it in the chat window.

[1225] This system allows users to effectively insert appropriate emojis into text messages, improving the quality of communication.

[1226] The processing flow will be explained below.

[1227] Step 1:

[1228] The user types a message, for example, "Today was so much fun! Let's hang out again!" into the chat tool's input field.

[1229] Step 2:

[1230] The user clicks the send button to send the entered text message.

[1231] Step 3:

[1232] The device packages the user-entered text message into JSON format.

[1233] Step 4:

[1234] The device sends a message as an HTTP POST request to the server endpoint.

[1235] Step 5:

[1236] The server receives the HTTP request and extracts the text message.

[1237] Step 6:

[1238] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[1239] Step 7:

[1240] Based on the analysis results, the server refers to a database or mapping list to identify emojis that correspond to keywords or phrases.

[1241] Step 8:

[1242] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play."

[1243] Step 9:

[1244] The server then inserts the identified emoji into the appropriate position in the text message, for example, "Today was so much fun 😊. Let's hang out again 🎮!"

[1245] Step 10:

[1246] The server generates a new text message with the emoji inserted and repackages it into JSON format.

[1247] Step 11:

[1248] The server sends the generated new message to the user's device as an HTTP response.

[1249] Step 12:

[1250] The device receives the HTTP response and parses the JSON format.

[1251] Step 13:

[1252] The device displays a new message in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[1253] Example 1

[1254] 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."

[1255] In recent years, communication using text messages has become very common, but there are issues with text alone, such as a lack of visibility and ability to convey emotions. This can lead to misunderstandings and impair smooth communication. To solve this problem and achieve richer and more effective communication, a system that can easily and automatically insert appropriate emojis into text messages is needed.

[1256] 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.

[1257] In this invention, the server includes means for receiving a text message entered by a user, means for analyzing keywords and set phrases in the text message, means for identifying emojis corresponding to the analyzed keywords and set phrases, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to the user's terminal, and means for displaying the generated message on the user's terminal. This allows the user to easily insert appropriate emojis into the text message, improving the visibility of communication and the ability to convey emotions, thereby enabling smoother communication.

[1258] "User" means a person who utilizes the System to enter, send, and receive text messages.

[1259] "Text message" refers to character string information that a user inputs and sends using a terminal.

[1260] "Keywords" refer to important words in a text message that convey a particular meaning or emotion.

[1261] "Phrases" refer to specific expressions or phrases that are frequently used in text messages.

[1262] "Analyzing" refers to analyzing text messages using natural language processing libraries and identifying keywords and phrases.

[1263] "Emoji" refers to small images or icons inserted into text messages that visually convey emotions or states.

[1264] "Inserting" refers to placing the identified emoji in the position of the corresponding keyword or phrase.

[1265] "Generating" refers to creating a new text message with the emoji inserted.

[1266] "Sending" refers to transferring the generated text message from the server to the user's terminal.

[1267] "Display" refers to displaying the generated text message on the screen of the user's terminal.

[1268] A "natural language processing library" refers to a software library that helps analyze and understand text data.

[1269] "JSON format" is an abbreviation for JavaScript Object Notation and refers to a lightweight data exchange format for representing structured data.

[1270] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a user uses to enter and receive text messages.

[1271] "Server" refers to the computer system that parses messages, identifies and inserts emojis, and creates and sends new messages.

[1272] MODE FOR CARRYING OUT THE INVENTION

[1273] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, and identifies and inserts corresponding emoticons. This system improves the visibility and emotional conveyance of text message communications, thereby realizing smoother communication.

[1274] Configuration and Operation

[1275] User Input

[1276] A user types a text message into the chat tool's input field and clicks the send button. For example, the user can type "I had a great time today. Let's hang out again!"

[1277] Sending a message

[1278] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint. Specifically, it converts the message into the format { "message": "Today was so much fun. Let's play again!"} and sends a POST request to https: / / example.com / api / messages.

[1279] Server receives and analyzes messages

[1280] The server receives an HTTP request and extracts the text message. For example, the extracted message might be {"message": "Today was so much fun. Let's hang out again!"}. The server then uses a natural language processing library to analyze the message and identify keywords and boilerplate phrases. Examples of natural language processing libraries that can be used include SpaCy and NLTK. The analysis results in the identification of "I had fun" and "Let's hang out."

[1281] Identifying and inserting emojis

[1282] The server retrieves emojis from a database or mapping list that correspond to the identified keywords or phrases. For example, it retrieves the emoji "😊" that corresponds to "I had fun" and the emoji "🎮" that corresponds to "Let's play." The server then inserts these emojis into the appropriate places and generates a new message. As a result, the text message is transformed into "Today was so much fun 😊. Let's play again 🎮!"

[1283] Sending a new message

[1284] The server then packages the new message into JSON format and sends it to the user's device as an HTTP response. Specifically, the server converts the new message into the format { "message": "Today was so much fun 😊. Let's play again 🎮!"} and returns it as a response.

[1285] Displaying messages

[1286] The device receives the HTTP response and parses the JSON format. The parsed message is displayed in the chat window. For example, a message like "Today was so much fun 😊. Let's play again 🎮!" is displayed.

[1287] Specific examples

[1288] For example, if a user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!", the system will analyze the message and insert appropriate emojis. Ultimately, the friend will see the message, "Today was so much fun! 😊 Let's hang out again! 🎮!" This improves the visibility of text messages and their ability to convey emotions, making communication more effective.

[1289] Prompt Sentence Examples

[1290] "If a user types 'I had so much fun today. Let's hang out again!', explain how you would insert an emoji."

[1291] This system allows users to easily insert appropriate emojis into text messages, improving the quality of communication.

[1292] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1293] Step 1: User Input and Submission

[1294] The user enters a text message in the input field of the chat tool and clicks the send button. An example of input content is "Today was so much fun. Let's hang out again!". The text "Today was so much fun. Let's hang out again!" is given as input. Here, the user presses the enter key or clicks the send icon. This triggers the sending of the text message to the terminal as output.

[1295] Step 2: Sending a message

[1296] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint. The input is the text message entered by the user. Data processing converts the message to { "message": "Today was so much fun. Let's play again!"}. The output is an HTTP POST request containing the packaged JSON message.

[1297] Step 3: Server receives and analyzes the message

[1298] The server receives an HTTP request and extracts the text message. The input is an HTTP request in JSON format. Data processing involves extracting {"message": "Today was so much fun. Let's play again!"} from the request body to obtain the message. The output is the extracted text message. Next, the server uses a natural language processing library (for example, SpaCy or NLTK) to parse the text message. The input is the extracted text message. Data processing involves analyzing the message and identifying keywords such as "I had fun" or "Let's play." The output is the identified keywords.

[1299] Step 4: Identify and insert emojis

[1300] The server retrieves emojis from a database or mapping list that correspond to the identified keywords or phrases. The input is the identified keywords. The data processing involves retrieving the corresponding emojis from the database. For example, "😊" corresponds to "fun" and "🎮" corresponds to "let's play." The output is the corresponding emojis. The server then inserts these emojis into the appropriate places to generate a new message. The input is the original text message and the identified emojis. The data operation involves inserting the emojis to generate a new message, for example, "Today was so much fun 😊. Let's play again 🎮!" The output is the new message that is generated.

[1301] Step 5: Send a new message

[1302] The server packages the generated new message into JSON format again and sends it to the user's device as an HTTP response. The input is the generated new text message. For data processing, the new message is packaged into { "message": "Today was so much fun 😊. Let's play again 🎮!"}. The output is sent to the user's device as a JSON format HTTP response.

[1303] Step 6: Displaying messages

[1304] The terminal receives the HTTP response and parses the JSON format. The input is the HTTP response. As data processing, it extracts {"message": "Today was so much fun 😊. Let's hang out again 🎮!"} from the response body. The output is the extracted new message. Next, the terminal displays the new message in the user's chat window. The input is the extracted new message. As data processing, it converts it into a displayable format and displays it in the chat window. For example, the message "Today was so much fun 😊. Let's hang out again 🎮!" is displayed. This is the final output.

[1305] (Application example 1)

[1306] 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."

[1307] Traditional text message communication lacks visibility and the ability to convey emotions, and especially in virtual stores, the interaction between store staff and customers can feel robotic and unfriendly, which can lead to a poor user experience and negatively impact customer satisfaction and repeat business.

[1308] 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.

[1309] In this invention, the server includes means for receiving a text message input by a user, means for analyzing keywords and fixed phrases in the text message, means for identifying emojis corresponding to the analyzed keywords and fixed phrases, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to the user's terminal, and means installed in the smart glasses for realizing emotional dialogue in real time, thereby enabling the effective insertion of appropriate emojis into the text message and improving the quality of communication.

[1310] "User" means a person who uses the System to enter and send text messages.

[1311] A "text message" refers to a message consisting of characters and symbols entered by a user.

[1312] "Keywords" refer to important words contained within a text message that the system analyzes.

[1313] "Phrases" refer to specific patterns or phrases contained within text messages.

[1314] "Analysis" refers to the process of analyzing text messages to identify keywords and phrases.

[1315] "Emoji" refers to symbols or images inserted into text messages to visually express emotions.

[1316] A "server" refers to a computer system that receives, analyzes, and processes text messages sent from user terminals.

[1317] "Smart glasses" are wearable devices worn by users that have communication and display functions and can send and receive messages in real time.

[1318] "Real-time" refers to the property of providing a nearly instantaneous response.

[1319] The present invention relates to a message processing system that receives text messages entered by a user, analyzes keywords and phrases in the messages, and identifies and inserts corresponding emojis. This system is specialized for realizing emotionally rich interactions in real time using smart glasses. The following describes in detail the embodiments of the present invention.

[1320] System configuration and operation

[1321] 1. User input:

[1322] The user inputs a text message using the input interface of the smart glasses, for example, "Here are the latest sales! Check them out!" The input is temporarily stored in the smart glasses.

[1323] 2. Sending a message:

[1324] The smart glasses convert the text message entered by the user into JSON format and send it to the server as an HTTP POST request. The communication protocol used here is HTTP, and the data format is JSON.

[1325] 3. Message analysis:

[1326] The server parses the incoming HTTP request and extracts the text message, which is then analyzed using a natural language processing library (e.g., SpaCy) to identify keywords and phrases, such as "sale items" or "check it out."

[1327] 4. Identify and insert emojis:

[1328] The server retrieves emojis corresponding to the identified keywords or phrases from a database (e.g., SQLite) or mapping list. For example, "sale items" corresponds to the emoji "🛍️" and "check it out" corresponds to the emoji "👀". The server then inserts the identified emojis into a text message to generate a new message. For example, "Here are our latest sale items 🛍️! Check them out 👀!"

[1329] 5. Create and send a new message:

[1330] The server then packages the new generated message back into JSON format and sends it to the smart glasses as an HTTP response.

[1331] 6. Displaying messages:

[1332] The smart glasses parse the received HTTP response and extract the new message from the JSON formatted data, which is then displayed on the smart glasses' display, allowing users to continue communicating with appropriate emojis inserted into their text messages.

[1333] Specific examples

[1334] For example, if a customer in a virtual store sends a text message through their smart glasses saying, "Tell me what products are on sale," the server will identify the keyword "products on sale" and insert the corresponding emoji "🛒" into the message, which will generate a new message "Tell me what products are on sale 🛒" and display it on the customer's smart glasses.

[1335] Prompt Sentence Examples

[1336] Generate a program that reads "Here are our latest sale items! Check them out" and displays "Here are our latest sale items 🛍️! Check them out 👀" with an emoji inserted.

[1337] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1338] Step 1:

[1339] A user inputs a text message using the input interface of the smart glasses. The input message is temporarily stored in the smart glasses. The input of this step is the text message input by the user, and the output is the text data temporarily stored in the smart glasses.

[1340] Step 2:

[1341] The smart glasses convert the stored text message into JSON format and send it as an HTTP POST request to the server. The input of this step is the stored text data, and the output is the data converted into JSON format. The smart glasses send this to the server using the HTTP protocol.

[1342] Step 3:

[1343] The server analyzes the received HTTP request and extracts the text message. It parses the received data to get the text message part. The input of this step is the JSON data sent from the smart glasses, and the output is the extracted text message.

[1344] Step 4:

[1345] The server analyzes the extracted text messages using a natural language processing library (e.g., SpaCy) to identify keywords and standard phrases. The data processing performed in this step is to identify keywords and standard phrases. The input of this step is the extracted text messages, and the output is the identified keywords and standard phrases.

[1346] Step 5:

[1347] The server retrieves emojis corresponding to the identified keywords or phrases from a database (e.g., SQLite) or mapping list. The input of this step is the identified keywords or phrases, and the output is the corresponding emojis. The server queries the database to retrieve the corresponding emojis.

[1348] Step 6:

[1349] The server inserts the identified emoji into the text message and generates a new message. The input of this step is the identified emoji and the original text message, and the output is the newly generated message. Specifically, string manipulation is used to insert the emoji at the appropriate position.

[1350] Step 7:

[1351] The server packages the generated new message into JSON format again and sends it to the smart glasses as an HTTP response. The input of this step is the generated message and the output is JSON format data, which the server sends to the smart glasses using the HTTP protocol.

[1352] Step 8:

[1353] The smart glasses parse the received HTTP response and extract the new message from the JSON formatted data. The input of this step is the JSON data sent from the server, and the output is the extracted new message, which the smart glasses then convert into a format for display.

[1354] Step 9:

[1355] The smart glasses display the extracted new message on the display. The input of this step is the extracted new message, and the output is the message displayed on the display, allowing the user to view the message with the emoji inserted.

[1356] 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.

[1357] The present invention relates to a message processing system that receives text messages entered by users, analyzes keywords and fixed phrases in the messages, recognizes emotions using an emotion engine, and identifies and inserts corresponding emojis. This system significantly improves the readability and emotional conveyance of text messages, enabling smoother and richer communication.

[1358] System configuration and operation

[1359] 1. User input:

[1360] The user types a text message into the chat tool's input field, for example, "Today was so much fun! Let's hang out again!"

[1361] The user sends the message by clicking the send button.

[1362] 2. Sending a message:

[1363] The device packages the text message entered by the user into JSON format and sends it as an HTTP POST request to the server endpoint.

[1364] 3. Message received and parsed by the server:

[1365] The server receives the HTTP request and extracts the text message.

[1366] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "that was fun" or "let's play."

[1367] 4. Use of Emotion Engine:

[1368] The server uses an emotion engine to analyze the emotion of the entire text message, for example recognizing that the message expresses a positive emotion such as "fun."

[1369] 5. Identify and insert emojis:

[1370] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, the emoji "😊" corresponds to "It was fun," and the emoji "🎮" corresponds to "Let's play."

[1371] The server then inserts the identified emoji into a text message and generates a new message, such as "Today was so much fun 😊. Let's hang out again 🎮!"

[1372] 6. Send a new message:

[1373] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[1374] 7. Displaying messages:

[1375] The terminal receives the HTTP response and parses the JSON format.

[1376] A new message appears in the user's chat window: "Today was so much fun 😊. Let's hang out again 🎮!"

[1377] Specific examples

[1378] Situation

[1379] A user wants to send a message to a friend saying, "Today was so much fun! Let's hang out again!"

[1380] How it works

[1381] 1. User input and submission:

[1382] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[1383] 2. Sending a message from the device to the server:

[1384] The device sends a message in JSON format to the server.

[1385] 3. Receiving and parsing messages on the server:

[1386] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[1387] 4. Use of Emotion Engine:

[1388] The server uses an emotion engine to recognize that the message expresses a positive emotion.

[1389] 5. Identify and insert emojis:

[1390] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play," and then selects appropriate emojis that express positive emotions.

[1391] Generate a new message: "Today was so much fun 😊. Let's play again 🎮!"

[1392] 6. Send a new message:

[1393] The server sends a new message to the device.

[1394] 7. Displaying messages in the terminal:

[1395] Your device will receive a new message and display it in the chat window.

[1396] This system allows users to effectively insert appropriate emojis that reflect their emotions into text messages, significantly improving the quality of communication.

[1397] The processing flow will be explained below.

[1398] Step 1:

[1399] The user types a message, for example, "Today was so much fun! Let's hang out again!" into the chat tool's input field.

[1400] Step 2:

[1401] The user clicks the send button to send the entered text message.

[1402] Step 3:

[1403] The device packages the user-entered text message into JSON format.

[1404] Step 4:

[1405] The device sends a message as an HTTP POST request to the server endpoint.

[1406] Step 5:

[1407] The server receives the HTTP request and extracts the text message.

[1408] Step 6:

[1409] The server uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases, such as "It was fun" or "Let's play."

[1410] Step 7:

[1411] The server uses an emotion engine to analyze the emotion of the entire text message, for example, recognizing that the message expresses a positive emotion such as "fun."

[1412] Step 8:

[1413] Based on the analysis results, the server retrieves emojis corresponding to keywords, phrases, and the emotion engine's recognition results from a database or mapping list.

[1414] Step 9:

[1415] The server identifies the emoji "😊" that corresponds to "It was fun," the emoji "😁" that corresponds to the positive emotion identified by the emotion engine, and the emoji "🎮" that corresponds to "Let's play."

[1416] Step 10:

[1417] The server then inserts the identified emoji into the appropriate position in the text message, for example, "Today was so much fun 😊😁. Let's hang out again 🎮!"

[1418] Step 11:

[1419] The server generates a new text message with the emoji inserted and repackages it into JSON format.

[1420] Step 12:

[1421] The server sends the generated new message to the user's device as an HTTP response.

[1422] Step 13:

[1423] The device receives the HTTP response and parses the JSON format.

[1424] Step 14:

[1425] The device displays a new message in the user's chat window: "Today was so much fun 😊😁. Let's hang out again 🎮!"

[1426] Example 2

[1427] 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."

[1428] In recent years, communication primarily based on text messages has rapidly spread, but there is a problem in that it is difficult to accurately convey emotions. This is because simple text alone cannot adequately convey the emotional nuances of a message, which can easily lead to misunderstandings and lack of communication between users. In addition, manually inserting emojis is time-consuming, which can detract from the user experience. There is a need for a system that can solve these issues and enable smoother and richer communication.

[1429] 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.

[1430] In this invention, the server includes means for receiving a text message entered by a user, means for analyzing keywords and fixed phrases in the text message, means for recognizing emotions in the analyzed text message, means for identifying emojis corresponding to the recognized emotions based on the identified emotions, means for inserting the identified emojis into the text message, and means for transmitting the generated message to the user's terminal. This allows the user to automatically insert emojis that reflect emotions into messages, thereby reducing misunderstandings about emotions and enabling richer communication.

[1431] "User" means a person who uses the System to enter and send text messages.

[1432] "Text Message" means textual information entered by a User and sent and received through the System.

[1433] "Keywords" are important words or phrases within a text message that are identified and analyzed by the system.

[1434] A "fixed phrase" is a phrase or expression that has a certain pattern and is included in a text message and is the subject of analysis.

[1435] "Emotion" refers to the psychological nuances or states expressed in text messages, and can be classified as positive, negative, neutral, etc.

[1436] "Emoji" refers to small images or icons used to visually represent emotions or concepts.

[1437] "Natural language processing libraries" refers to software tools and frameworks used to analyze text messages.

[1438] "JSON format" is an abbreviation for JavaScript Object Notation and refers to a lightweight data format used for data exchange.

[1439] An "HTTP POST request" is a type of HTTP method for sending data to a web server, and is primarily used for data submission.

[1440] MODE FOR CARRYING OUT THE INVENTION

[1441] The present invention is a message processing system that receives a text message entered by a user, analyzes keywords and fixed phrases in the message, recognizes emotions using an emotion engine, and identifies and inserts corresponding emojis to improve the readability and emotional communication of the text message. This system is configured by combining hardware and software.

[1442] Hardware and software used

[1443] Hardware:

[1444] User device (e.g. smartphone, PC)

[1445] Server (e.g. cloud server, dedicated server)

[1446] software:

[1447] Natural language processing libraries (e.g., SpaCy, NLTK)

[1448] Sentiment Analysis Engine

[1449] Database or Mapping List

[1450] Communication protocol (e.g. HTTP, JSON)

[1451] How the system is implemented

[1452] 1. User Input

[1453] The user enters a text message into the chat tool's input field and clicks the send button. For example, the user can enter "I had a great time today. Let's hang out again!"

[1454] 2. Sending a Message

[1455] The device packages the text message entered by the user into JSON format and sends it to the server endpoint as an HTTP POST request, which transfers the message data to the server.

[1456] 3. Message Reception and Analysis by the Server

[1457] The server unpacks the received HTTP request and extracts the text message. It then uses a natural language processing library (e.g., SpaCy or NLTK) to parse the text message and identify keywords and phrases. For example, "It was fun" or "Let's play" might be identified.

[1458] 4. Use of Emotion Engine

[1459] The server uses an emotion engine to analyze the emotion of the entire text message, for example recognizing that the message expresses a positive emotion such as "fun."

[1460] 5. Identifying and Inserting Emojis

[1461] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, the emoji "😊" corresponds to "fun" and the emoji "🎮" corresponds to "let's play." The server then inserts the identified emojis into a text message to generate a new message. For example, "Today was so much fun 😊. Let's play again 🎮!"

[1462] 6. Send a new message

[1463] The server then packages the new message into JSON format again and sends it to the user's device as an HTTP response.

[1464] 7. Displaying Messages

[1465] The device unpacks the received HTTP response and parses the message from the JSON format. The new message is then displayed in the user's chat window.

[1466] Specific examples

[1467] If a user wants to send a message to a friend saying, "I had a great time today. Let's hang out again!", the system works as follows:

[1468] 1. User input and submission

[1469] The user types, "Today was so much fun! Let's hang out again!" and clicks the send button.

[1470] 2. Sending a message from the device to the server

[1471] The device sends a message in JSON format to the server.

[1472] 3. Receiving and analyzing messages on the server

[1473] The server receives the message and uses a natural language processing library to identify "that was fun" and "let's play."

[1474] 4. Use of Emotion Engine

[1475] The server uses an emotion engine to recognize that the message expresses a positive emotion.

[1476] 5. Identifying and Inserting Emojis

[1477] The server identifies the emoji "😊" that corresponds to "It was fun" and the emoji "🎮" that corresponds to "Let's play," and generates a new message: "Today was so much fun 😊. Let's play again 🎮!"

[1478] 6. Send a new message

[1479] The server sends a new message to the device.

[1480] 7. Displaying messages on the terminal

[1481] Your device will receive a new message and display it in the chat window.

[1482] This system allows users to effectively insert emoticons that reflect their emotions into text messages, significantly improving the quality of communication.

[1483] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1484] Step 1:

[1485] A user enters a text message into the chat tool's input field and clicks the send button. For example, "I had a great time today. Let's hang out again!" The input in this case is the user's text message, and the output is the click event of the send button.

[1486] Step 2:

[1487] The device receives the text message entered by the user when the send button is clicked. The device then packages the text message in JSON format and sends it as an HTTP POST request to the specified endpoint on the server. The input is the user's text message, and the output is message data in JSON format. This process converts the text message into JSON format and sends it to the server.

[1488] Step 3:

[1489] The server receives the HTTP POST request and retrieves the message data in JSON format. After extracting the text message from the retrieved data, it uses a natural language processing library (e.g., SpaCy or NLTK) to analyze the text message and identify keywords and standard phrases. The input is the message data in JSON format, and the output is the analyzed keywords and standard phrases. Specifically, it identifies keywords such as "It was fun" and "Let's play."

[1490] Step 4:

[1491] The server uses a sentiment analysis engine to analyze the sentiment of the entire text message. For example, it recognizes the positive sentiment of "fun" from the message "Today was so much fun. Let's hang out again!" The input is the text message, and the output is the recognized sentiment (e.g., positive). This process identifies the sentiment of the message.

[1492] Step 5:

[1493] Based on the analysis results and the recognition results of the emotion engine, the server retrieves emojis corresponding to keywords, phrases, and emotions from a database or mapping list. For example, "I had fun" corresponds to the emoji "😊" and "Let's play" corresponds to the emoji "🎮". Next, a new message is generated by inserting the identified emojis into a text message. The input is the analyzed keywords and emotions, and the output is the identified emojis and a new text message (e.g., "I had a lot of fun today 😊. Let's play again 🎮!").

[1494] Step 6:

[1495] The server repackages the generated new message into JSON format and sends it to the user's device as an HTTP response. The input is the new text message and the output is JSON formatted data. This process sends the new message to the device.

[1496] Step 7:

[1497] The device receives the HTTP response and parses the JSON-formatted data. The resulting new message is displayed in the user's chat window. The input is JSON-formatted data, and the output is a new message (e.g., "Today was so much fun 😊. Let's play again 🎮!") that is displayed in the user's chat window. This allows the user to visually confirm the new message.

[1498] The above are the specific processing steps and flow of the system. This system allows users to easily send text messages that reflect their emotions, thereby improving the quality of communication.

[1499] (Application example 2)

[1500] 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."

[1501] With conventional messaging systems, it is difficult to convey emotions in text-based communication, making it difficult to accurately grasp the other person's intentions and emotions. Furthermore, in brick-and-mortar stores, communication with customers tends to be emotionless and monotonous, which can lead to a decrease in customer satisfaction. To solve these problems, there is a need for a way to reflect emotions in text messages and convey them in a visually easy-to-understand format.

[1502] 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 receiving a text message entered by a user, means for analyzing keywords and set phrases in the text message, means for recognizing emotions in the text message using an emotion engine, means for identifying emojis corresponding to the analyzed keywords and set phrases and the recognized emotions, means for inserting the identified emojis into the text message, means for generating a message with the emojis inserted, means for transmitting the generated message to a user's terminal, means for displaying the generated message on the user's device, and means corresponding to an application installed on a smartphone, smart glasses, a head-mounted display, or a robot. This makes it possible to easily reflect emotions in a text message and convey them in a visually easy-to-understand manner.

[1503] "User" means a person who uses a system or device to input and send text messages.

[1504] "Text message" refers to a message in the form of a string of characters that is entered and sent by a user.

[1505] "Keywords" refer to important words that appear in a text message and have a particular meaning or sentiment.

[1506] A "fixed phrase" is a commonly used expression or phrase.

[1507] "Emotion engine" refers to a software component for analyzing and recognizing emotions from input text messages.

[1508] "Emoji" refers to small icons inserted into text messages to visually express emotions or concepts.

[1509] A "natural language processing library" refers to a software tool used to analyze text data and identify keywords and phrases.

[1510] A "smartphone" refers to a mobile information terminal that has multiple functions, including voice communication capabilities, Internet access, and application execution.

[1511] "Smart glasses" are a wearable device in the shape of glasses that has the ability to display information and connect to the Internet.

[1512] A "head-mounted display" refers to a display device worn on the head to display visual information and digital content.

[1513] "Robot" refers to a mechanical device that performs automated operation or interaction and is programmed to perform specific tasks or interactions.

[1514] This invention is a system that analyzes text messages entered by a user, recognizes emotions, and inserts appropriate emoticons. This system uses the following hardware and software configuration.

[1515] First, a user types and sends a text message from a device such as a smartphone, smart glasses, head-mounted display, or robot. When the user sends a message such as "Do you have any recommendations for me today?", the text message is packaged in JSON format and sent to the server.

[1516] The server then processes the received text message using the following software:

[1517] 1. Use a natural language processing library (e.g., SpaCy, NLTK) to analyze text messages and identify keywords and boilerplate phrases.

[1518] 2. Recognize the sentiment of the message using an emotion engine (e.g., Google Cloud Natural Language API).

[1519] Based on the analysis results, emojis corresponding to keywords, phrases, and recognized emotions are retrieved from a database or mapping list. For example, "🛍" is identified for "recommended items." Then, the identified emojis are inserted into a text message to generate a new message: "Do you have any recommendations for me today? 🛍?"

[1520] The generated message is then packaged in JSON format and sent to the user's device for display, allowing users to visually express emotions in their text messages, making communication smoother and richer.

[1521] Specific examples of hardware and software used

[1522] Hardware:

[1523] Smartphones (iOS and Android devices)

[1524] Smart Glasses

[1525] head-mounted display

[1526] Robots (e.g. Pepper)

[1527] software:

[1528] Natural language processing libraries: SpaCy, NLTK

[1529] Sentiment analysis engine: Google Cloud Natural Language API

[1530] Database: MySQL, Firebase Realtime Database

[1531] Application Framework: Flutter, React Native

[1532] Examples of concrete examples and prompts

[1533] A concrete example is when a user sends a message to a friend saying, "What do you have for me today?" This message is parsed to detect emotion and generate a new message with the appropriate emoji inserted: "What do you have for me today? 🛍?"

[1534] Example prompt sentence:

[1535] Based on the message entered by the customer, analyze the sentiment and create a reply with appropriate emojis.

[1536] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1537] Step 1:

[1538] A user types a text message into a device (e.g., smartphone, smart glasses, head-mounted display, robot) and clicks the "Send" button. The input is "Do you have any recommendations for me today?". This causes the text message typed by the user to be captured within the device.

[1539] Step 2:

[1540] The device packages the captured text message into JSON format and sends it to the server as an HTTP POST request. The input data is the text message and the user's ID, and the output data is the HTTP request sent to the server.

[1541] Step 3:

[1542] The server receives an HTTP request and extracts the text message. The input data is message data in JSON format, and the output data is the extracted text message. Specifically, the server analyzes the received data and extracts the string portion of the text message.

[1543] Step 4:

[1544] The server uses natural language processing libraries (SpaCy or NLTK) to analyze text messages and identify keywords and phrases. The input data is the extracted text message, and the output data is the identified keywords and phrases. Specific operations include tokenizing the text, tagging parts of speech, and dependency analysis.

[1545] Step 5:

[1546] The server uses an emotion engine (such as the Google Cloud Natural Language API) to recognize the emotion of a text message. The input data is a text message containing identified keywords and phrases, and the output data is the emotion type (e.g., positive, negative, neutral). Specific operations include calculating an emotion score for the entire message and classifying it.

[1547] Step 6:

[1548] The server retrieves the analysis results and emojis corresponding to the emotions from a database or mapping list. The input data are the identified keywords and emotion types, and the output data are the corresponding emojis. Specifically, the server searches for and retrieves the corresponding emojis from the database.

[1549] Step 7:

[1550] The server inserts the identified emoji into the text message to generate a new message. The input data is the original text message and the corresponding emoji, and the output data is the new message with the inserted emoji. The specific operation is to insert the emoji into a specific position in the text.

[1551] Step 8:

[1552] The server then packages the new message into JSON format and sends it to the user's device as an HTTP response. The input data is the new text message, and the output data is the JSON response. Specifically, the server converts the message into a JSON object and sends it.

[1553] Step 9:

[1554] The terminal receives the HTTP response and parses the JSON format. The input data is the received JSON response, and the output data is the parsed new text message. Specifically, the terminal parses the response data and extracts the text portion.

[1555] Step 10:

[1556] The terminal displays the parsed new message on the user's device. The input data is the parsed new message, and the output data is the message displayed in the user's chat window. A specific operation is to render the message in a user interface.

[1557] 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.

[1558] 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.

[1559] 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.

[1560] 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.

[1561] 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.

[1562] 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.

[1563] 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).

[1564] 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.

[1565] 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."

[1566] 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.

[1567] 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).

[1568] 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.

[1569] 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.

[1570] 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.

[1571] 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.

[1572] 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.

[1573] 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.

[1574] 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.

[1575] 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.

[1576] 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.

[1577] 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.

[1578] The following is further disclosed regarding the above embodiment.

[1579] (Claim 1)

[1580] means for receiving a text message entered by a user;

[1581] means for analyzing keywords and phrases in the text message;

[1582] A means for identifying emojis corresponding to the analyzed keywords or phrases;

[1583] means for inserting the identified emoji into the text message;

[1584] means for generating a message having emojis inserted therein;

[1585] A means for sending the generated message to the user's terminal

[1586] A message processing system including:

[1587] (Claim 2)

[1588] 2. The message processing system according to claim 1, wherein the means for inserting emojis identified by the analyzed keywords or phrases utilizes a natural language processing library.

[1589] (Claim 3)

[1590] 2. The message processing system according to claim 1, further comprising means for transmitting a message generated based on the identified emoji in JSON format to the user's terminal.

[1591] "Example 1"

[1592] (Claim 1)

[1593] means for receiving a text message entered by a user;

[1594] means for analyzing keywords and phrases in the text message;

[1595] A means for identifying emojis corresponding to the analyzed keywords or phrases;

[1596] means for inserting the identified emoji into the text message;

[1597] means for generating a message having emojis inserted therein;

[1598] means for transmitting the generated message to a user's terminal;

[1599] A means of displaying the generated message on the user's terminal

[1600] A system including:

[1601] (Claim 2)

[1602] 2. The system of claim 1, wherein the means for identifying emojis corresponding to the analyzed keywords or phrases utilizes a natural language processing library.

[1603] (Claim 3)

[1604] 10. The system of claim 1, further comprising means for sending a message generated based on the identified emoji in JSON format to the user's terminal.

[1605] "Application Example 1"

[1606] (Claim 1)

[1607] means for receiving a text message entered by a user;

[1608] means for analyzing keywords and phrases in the text message;

[1609] A means for identifying emojis corresponding to the analyzed keywords or phrases;

[1610] means for inserting the identified emoji into the text message;

[1611] means for generating a message having emojis inserted therein;

[1612] means for transmitting the generated message to a user's terminal;

[1613] A means of real-time, emotional interaction installed on smart glasses

[1614] A system including:

[1615] (Claim 2)

[1616] 2. The system of claim 1, wherein the means for inserting emojis identified by the analyzed keywords or phrases utilizes a natural language processing library.

[1617] (Claim 3)

[1618] 10. The system of claim 1, further comprising means for sending a message generated based on the identified emoji in JSON format to the user's terminal.

[1619] "Example 2: Combining Emotion Engines"

[1620] (Claim 1)

[1621] means for receiving a text message entered by a user;

[1622] means for analyzing keywords and phrases in the text message;

[1623] means for recognizing sentiment in the analyzed text messages;

[1624] means for identifying a corresponding emoji based on the recognized emotion;

[1625] means for inserting the identified emoji into the text message;

[1626] means for generating a message having emojis inserted therein;

[1627] A means for sending the generated message to the user's terminal

[1628] A system including:

[1629] (Claim 2)

[1630] 2. The system of claim 1, wherein the means for inserting emojis identified by the analyzed keywords or phrases utilizes a natural language processing library.

[1631] (Claim 3)

[1632] 10. The system of claim 1, further comprising means for sending a message generated based on the identified emoji in JSON format to the user's terminal.

[1633] "Application example 2 when combining emotion engines"

[1634] (Claim 1)

[1635] means for receiving a text message entered by a user;

[1636] means for analyzing keywords and phrases in the text message;

[1637] means for recognizing sentiment in a text message using an emotion engine;

[1638] means for identifying emojis corresponding to the analyzed keywords, phrases, and recognized emotions;

[1639] means for inserting the identified emoji into the text message;

[1640] means for generating a message having emojis inserted therein;

[1641] means for transmitting the generated message to a user's terminal;

[1642] means for displaying the generated message on the user's device;

[1643] A means compatible with applications installed on smartphones, smart glasses, head-mounted displays, or robots

[1644] A system including:

[1645] (Claim 2)

[1646] 10. The system of claim 1, wherein the means for inserting emojis identified by the analyzed keywords, phrases, and recognized emotions utilizes a natural language processing library and an emotion analysis engine.

[1647] (Claim 3)

[1648] 10. The system of claim 1, further comprising means for sending a message generated based on the identified emoji in JSON format to the user's terminal. [Explanation of symbols]

[1649] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a text message entered by a user; means for analyzing keywords and phrases in the text message; A means for identifying emojis corresponding to the analyzed keywords or phrases; means for inserting the identified emoji into the text message; means for generating a message having emojis inserted therein; A means for sending the generated message to the user's terminal; A message processing system including:

2. 2. The message processing system according to claim 1, wherein the means for inserting emoticons specified by the analyzed keywords or set phrases utilizes a natural language processing library.

3. The message processing system according to claim 1, further comprising means for transmitting a message generated based on the identified emoji in JSON format to the user's terminal.

Images