system

Abstract

We provide the system. [Solution] A means for receiving messages sent by a user via a communication terminal, A means for analyzing keywords contained in the received message, A generative artificial intelligence system that generates appropriate empathetic and encouraging messages based on analysis results, A means for sending the generated message back to the communication terminal, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, the number of people suffering mentally is increasing, and as a result, not a few people choose suicide. In particular, even when one wants to talk to someone, it is often difficult to find appropriate support or a counseling partner immediately. Therefore, it is important to provide mental support quickly and accurately. However, in currently widely used messaging services, experts often cannot respond immediately, and users may feel a sense of isolation and despair. To solve this problem, there is a need for a system that can quickly respond to user messages and provide appropriate empathy and encouragement.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides a system having the following configuration: a system comprising means for receiving a message sent by a user via a communication terminal, means for analyzing keywords contained in the received message, a generative artificial intelligence means for generating an appropriate empathetic and encouraging message based on the analysis results, and means for sending the generated message back to the communication terminal. The system may further include means for pre-processing and logging messages from the user. This system can quickly analyze the content of messages sent by a user and provide an appropriate response according to their psychological state. As a result, the user can receive emotional support without feeling isolated.

[0006] A "user" refers to an individual who sends a message via a communication device.

[0007] A "communication terminal" refers to an electronic device used by a user to send and receive messages.

[0008] A "message" refers to text or written information that a user sends through a communication device.

[0009] A "server" refers to a computer system that receives messages from users, requests processing from generative artificial intelligence, and returns the results.

[0010] "Means of receiving" refers to the technical means by which a server receives a message sent from a communication terminal.

[0011] "Preprocessing" refers to the process of removing unnecessary information from a received message and converting it into a format that is easy to analyze.

[0012] "Keywords" refer to important words or phrases included in a message.

[0013] "Means of analysis" refers to technical means for extracting keywords from received messages and understanding their content.

[0014] "Generating means" refers to technical means for creating appropriate empathetic and encouraging messages based on the analysis results.

[0015] "Generative artificial intelligence" refers to an advanced computer program that has the function of analyzing received messages and generating response messages based on those analyses.

[0016] "Means of replying" refers to the technical means of sending the generated response message to the user's communication terminal.

[0017] A "log" refers to a record of events and messages that occur within a system. [Brief explanation of the drawing]

[0018] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the 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.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0032] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] This invention relates to a system that provides empathetic and encouraging messages to users with suicidal thoughts via LINE's official account. This system is realized by receiving messages sent by users in real time, generating appropriate replies using generative artificial intelligence, and sending them back to the user.

[0040] System Configuration

[0041] 1. User terminal

[0042] A user's device is a communication terminal such as a smartphone or tablet on which the LINE app is installed. Users send and receive messages through this device.

[0043] 2. Server

[0044] The server receives messages and requests generative artificial intelligence to analyze them and generate replies. The server also sends the generated messages to the user's terminal.

[0045] 3. Generative Artificial Intelligence

[0046] Includes a program that analyzes input messages and generates appropriate messages of empathy and encouragement.

[0047] Program Processing Overview

[0048] Message reception and preprocessing

[0049] The user's device types "I've been having a really hard time lately. I'm tired of living" and sends the message to the LINE official account.

[0050] The server receives user messages from the LINE platform and preprocesses the content appropriately. Preprocessing includes removing whitespace and escaping special characters.

[0051] Message parsing and reply generation

[0052] The server sends the pre-processed message to the generative artificial intelligence.

[0053] A generative artificial intelligence analyzes the received message and extracts keywords (e.g., spicy, tired).

[0054] Based on keywords extracted by the generative artificial intelligence, it generates a message of empathy and encouragement such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0055] Send a reply

[0056] The server receives the generated response message and sends it back to the user's terminal.

[0057] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0058] Specific example

[0059] Let's consider a scenario where a user sends a message to the official LINE account saying, "I've been having a really hard time lately. I'm tired of living." This message is received by the server and pre-processed. Then, a generative artificial intelligence extracts the keywords "hard" and "tired." Based on these keywords, the generative AI creates a message of empathy and encouragement and returns it to the server. The server sends this message to the user's device, and the user receives support in real time.

[0060] In this way, the system of the present invention can provide rapid and accurate support to users who have suicidal thoughts.

[0061] The following describes the processing flow.

[0062] Step 1:

[0063] A user uses the LINE app to type and send the message "I've been having a really hard time lately. I'm tired of living" to the official account.

[0064] Step 2:

[0065] The server receives the user's sent message from the LINE platform.

[0066] Step 3:

[0067] Messages received by the server are saved to a database for logging purposes.

[0068] Step 4:

[0069] The server begins message preprocessing. Preprocessing includes the following actions:

[0070] Removal of unnecessary whitespace

[0071] Special character escaping

[0072] Message content normalization

[0073] Step 5:

[0074] The server extracts important keywords from the pre-processed messages. For example, keywords such as "painful" and "tired" might be extracted.

[0075] Step 6:

[0076] The server sends a request to the generative artificial intelligence API. The request includes the message content after preprocessing and keyword extraction.

[0077] Step 7:

[0078] The generative artificial intelligence receives the request and analyzes the message content and extracted keywords.

[0079] Step 8:

[0080] The generative artificial intelligence generates appropriate empathetic and encouraging messages based on the analysis results. For example, it might generate a message like, "I understand how you're going through. You're not alone. I'm here to listen."

[0081] Step 9:

[0082] The generative artificial intelligence returns the generated message to the server.

[0083] Step 10:

[0084] The server logs the generated messages and saves them to the database.

[0085] Step 11:

[0086] The server generates a message and sends it to the user via the LINE platform.

[0087] Step 12:

[0088] The user receives a message via the LINE app that says, "I understand how you're going through. You're not alone. I'm here to listen."

[0089] The above outlines the specific processing steps of this system.

[0090] (Example 1)

[0091] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0092] There is a need for a means to quickly and accurately provide empathetic and encouraging messages to users who have suicidal thoughts. However, conventional systems may be slow to analyze user messages and generate appropriate replies, or may generate inappropriate messages. Therefore, an effective means is needed to alleviate the emotional burden on users and provide support quickly.

[0093] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0094] In this invention, the server includes means for receiving a message sent by a user via a communication terminal, means for pre-processing the received message, means for analyzing keywords contained in the pre-processed message, means for generating an appropriate message of empathy and encouragement based on the analysis results using generative artificial intelligence, and means for sending the generated message back to the communication terminal. This makes it possible to quickly analyze messages sent by users and provide appropriate messages of empathy and encouragement in real time.

[0095] A "communication terminal" is an electronic device used by a user to send and receive messages, and includes smartphones, tablets, personal computers, and other similar devices.

[0096] A "server" is a central computer system used for receiving, pre-processing, parsing, and generating replies to messages.

[0097] A "message" refers to text information sent by a user via a communication device, and includes content that expresses the user's emotions or state of mind.

[0098] "Preprocessing" refers to data organization operations performed before analysis, such as removing whitespace from received messages and escaping special characters.

[0099] "Keywords" are important words or phrases extracted from a message, and they serve as criteria for generative artificial intelligence to generate empathetic and encouraging messages.

[0100] "Generative artificial intelligence" refers to an artificial intelligence program that analyzes an input message and automatically generates an appropriate response based on the analysis results.

[0101] A "prompt" is a text containing instructions or questions for generating a specific response from a generative artificial intelligence system.

[0102] A "log" is a data file used to record messages that have been sent and messages that have been generated.

[0103] A "message of empathy and encouragement" is a message created by a generative artificial intelligence system that appropriately empathizes with the user's emotions and state of mind and has the intention of offering encouragement.

[0104] This invention relates to a system that receives messages sent by users in real time and returns appropriate reply messages using generative artificial intelligence. In particular, it aims to provide empathetic and encouraging messages quickly and accurately to users who have suicidal thoughts.

[0105] System Configuration

[0106] Hardware and software

[0107] This system uses the following hardware and software.

[0108] 1. Communication terminal: An electronic device used by users to send and receive messages, including smartphones, tablets, and personal computers.

[0109] 2. Server: A central computer system for receiving, pre-processing, parsing, and generating replies to messages.

[0110] 3. Generative Artificial Intelligence: This is an artificial intelligence program that analyzes input messages and generates appropriate empathetic and encouraging messages.

[0111] Message reception and preprocessing

[0112] The user's device sends a message via the LINE app in response to the user's input: "I've been having a really hard time lately. I'm tired of living."

[0113] The server receives this message from the LINE platform and performs preprocessing such as removing whitespace and escaping special characters.

[0114] Message parsing and reply generation

[0115] The server sends the pre-processed message to the generative artificial intelligence. The following prompt is used: "Receive the user's message, 'I've been having a really hard time lately. I'm tired of living,' extract keywords, and generate a message of empathy and encouragement."

[0116] A generative artificial intelligence analyzes the received message and extracts keywords such as "painful" and "tired."

[0117] The generative artificial intelligence generates a message of empathy and encouragement based on the extracted keywords, such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0118] Send a reply

[0119] The server receives a response message generated by a generative artificial intelligence and sends it to the user's terminal via the LINE platform.

[0120] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0121] As a concrete example, consider a case where a user sends the message "I've been having a really hard time lately. I'm tired of living" to the official LINE account. This message is received by the server, where whitespace is removed and special characters are escaped. Then, a generative artificial intelligence extracts the keywords "hard" and "tired," and generates a message of empathy and encouragement such as: "I understand how you're feeling. You're not alone. I'm here to listen."

[0122] This invention makes it possible to quickly analyze messages sent by users and provide appropriate messages of empathy and encouragement in real time.

[0123] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0124] Step 1:

[0125] The user's device sends the message "I've been having a really hard time lately. I'm tired of living" through the LINE app in response to the user's input. Specifically, the user types the message in the chat window within the LINE app and presses the send button. The input is the user's text message, and the output is a message that reaches the server via the LINE platform.

[0126] Step 2:

[0127] The server receives user messages from the LINE platform. The received messages undergo preprocessing, such as whitespace removal and special character escaping. Specifically, a message like "It's spicy." is converted to "It's spicy." The input is the raw message sent from the user's terminal, and the output is the preprocessed message.

[0128] Step 3:

[0129] The server sends a pre-processed message to a generative artificial intelligence. The following prompt is used: "Receive the message 'I've been having a really hard time lately. I'm tired of living' sent by the user, extract keywords, and generate a message of empathy and encouragement." The input is the pre-processed message and the prompt, and the output is the data sent to the generative artificial intelligence.

[0130] Step 4:

[0131] A generative artificial intelligence analyzes pre-processed messages received from a server. During the analysis, it extracts keywords such as "painful" and "tired." The input consists of the pre-processed message and prompt text, while the output is the keywords resulting from the analysis. Specifically, natural language processing techniques are used to analyze the message content, performing sentiment analysis and keyword extraction.

[0132] Step 5:

[0133] The generative artificial intelligence generates empathetic and encouraging messages based on the extracted keywords. Specifically, it generates a message such as, "I understand how you're going through. You're not alone. I'm here to listen." The input is the keywords extracted in step 4, and the output is the generated empathetic and encouraging message.

[0134] Step 6:

[0135] The server receives messages generated by a generative artificial intelligence and sends them to the user's terminal via the LINE platform. Specifically, the server receives the generated message and forwards it to the user's terminal via the LINE platform. The input is the generated message, and the output is the message sent to the user's terminal.

[0136] Step 7:

[0137] The user's device receives empathy and encouragement messages sent from the server via the LINE app. The user then views the messages displayed in the chat window within the LINE app. Specifically, when the user taps a notification in the LINE app, the chat window automatically opens and displays the reply message. The input is the message sent from the server, and the output is the message displayed within the LINE app.

[0138] This allows for the rapid analysis of messages sent by users, providing appropriate messages of empathy and encouragement in real time.

[0139] (Application Example 1)

[0140] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0141] While systems exist to quickly provide empathetic and encouraging messages to users with suicidal thoughts, only a limited number of systems can respond to urgent situations. Furthermore, current systems often fail to recognize emergencies, making it difficult to provide appropriate support immediately. This means that users in dangerous situations may not receive adequate and timely support.

[0142] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0143] In this invention, the server includes means for receiving messages sent by a user via a communication terminal, means for analyzing keywords contained in the received messages, generative artificial intelligence means for generating appropriate empathetic and encouraging messages based on the analysis results, means for examining messages to determine their urgency, means for sending notifications to registered contacts if the means for determining urgency determines that the message is urgent, and means for sending the generated message back to the communication terminal. This makes it possible to respond quickly to emergencies and provide users with immediate and appropriate support.

[0144] A "communication terminal" is a device used by users to send and receive messages, and includes smartphones, tablets, and personal computers.

[0145] A "keyword" is a specific word or phrase contained within a received message, and it is an important element for analyzing the content of the message.

[0146] "Generative artificial intelligence" is a general term for programs and systems that analyze input messages and generate appropriate responses.

[0147] "Means for determining urgency" refers to a function or algorithm that analyzes the content of a received message and determines whether or not that message is an emergency.

[0148] "Means of sending notifications" refers to a function that sends alerts and notifications to pre-configured contacts when an emergency is determined.

[0149] "Preprocessing" is the process of cleaning and filtering text to make it easier to analyze the content of received messages.

[0150] A "log" is a record used to store and manage sent messages and generated responses.

[0151] This invention relates to a system that processes messages sent by users via a communication terminal quickly and appropriately, and provides immediate notification in emergencies. Based on the claims, embodiments for carrying out this invention are described below.

[0152] System Configuration

[0153] 1. User terminal

[0154] Users send messages using communication devices (smartphones, tablets, PCs, etc.). Messages are sent via communication platforms such as the LINE app.

[0155] 2. Server

[0156] The server receives messages sent from user terminals, analyzes them using generative artificial intelligence (AI models), and generates appropriate replies. The server also plays a role in determining urgency and sending notifications.

[0157] 3. Generative Artificial Intelligence

[0158] The generative artificial intelligence analyzes messages received from users and extracts keywords. It includes a program that generates empathetic and encouraging messages based on the extracted keywords. Furthermore, in emergency situations, it generates appropriate response messages and sends them back to the server.

[0159] Program Processing Overview

[0160] Processing received messages

[0161] A user sends a message via a communication device saying, "I've been having a really hard time lately. I'm tired of living." The server receives this message and performs preprocessing. Preprocessing includes removing whitespace and handling special characters.

[0162] Message parsing and reply generation

[0163] The server sends the pre-processed message to the generative artificial intelligence. The generative AI analyzes the message and extracts keywords (e.g., "painful," "tired"). Based on the extracted keywords, it generates an empathetic and encouraging message such as, "I understand how you're feeling. You're not alone. I'm here to listen."

[0164] Assessment and notification of urgency

[0165] Furthermore, the generative artificial intelligence examines the message for urgent keywords (e.g., "help," "now") to determine its urgency. If it determines it is urgent, the server sends a notification to pre-configured emergency contacts.

[0166] Send message

[0167] The server sends the generated reply message to the user's terminal. The user's terminal receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0168] Hardware and software to be used

[0169] Communication devices: Smartphones, tablets, personal computers

[0170] Communication platform: LINE app, etc.

[0171] Server: Cloud server (AWS®, Google® Cloud, etc.)

[0172] Generative artificial intelligence: AI models such as GPT-3(registered trademark)

[0173] Log management system: Database (MySQL®, PostgreSQL, etc.)

[0174] Specific example

[0175] A user sends a message from their communication device saying, "I've been having a really hard time lately. I'm tired of living." This message is received by the server and pre-processed. Then, an AI model extracts keywords such as "hard" and "tired." Based on these keywords, the AI ​​model generates an empathetic and encouraging message, such as "I understand how you're feeling. You're not alone. I'm here to listen," and sends it back to the server. The server sends this message to the user's device, and the user receives support in real time. In addition, if urgent keywords such as "help" or "right now" are detected, a notification is sent to the registered emergency contact.

[0176] Example of a prompt

[0177] "I've been having a really hard time lately. I'm tired of living."

[0178] "Help me, I need someone to listen to me right now."

[0179] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0180] Step 1:

[0181] The user sends a message via a communication device. The user uses a communication platform such as the LINE app to type a message like, "I've been having a really hard time lately. I'm tired of living," and presses the send button. The input data is a text message.

[0182] Step 2:

[0183] The server receives messages sent from the user's terminal. The input data is a text message sent by the user. The server retrieves the message through the communication platform's API. Specifically, this is achieved by using the LINE platform's API and listening for message events. The output data is a text message that requires preprocessing.

[0184] Step 3:

[0185] The server preprocesses the received message. Preprocessing includes removing whitespace, escaping special characters, and standardizing the message text. The input data is the received text message, and the output data is the preprocessed text message.

[0186] Step 4:

[0187] The server sends a pre-processed message to a generative artificial intelligence (AI). The input data is a pre-processed text message. The server calls the AI's API and sends a request for message analysis and reply generation. The output data is the analysis result and the generated response message returned by the AI.

[0188] Step 5:

[0189] Generative artificial intelligence analyzes received messages and extracts keywords. The input data is a pre-processed text message sent from a server. As part of the data processing, natural language processing techniques are used to tokenize the message and extract keywords. The output data consists of the extracted keywords and a response message generated based on those keywords.

[0190] Step 6:

[0191] Generative artificial intelligence generates appropriate empathetic and encouraging messages based on extracted keywords. The input data consists of extracted keywords. A generative AI model (e.g., GPT-3) is used to generate response messages based on prompts. The output data consists of the generated empathetic and encouraging messages.

[0192] Step 7:

[0193] Generative artificial intelligence examines messages for urgent keywords and determines their urgency. The input data is the entire message. As a data calculation, it scans the message to check if it contains urgent keywords (e.g., "help", "now"). The output data is an urgency flag (whether it is urgent or not).

[0194] Step 8:

[0195] The server receives the response message and the urgency assessment result from the generative artificial intelligence. The input data consists of the generated response message and the urgency assessment result. Based on this information, the server continues the necessary processing. Specifically, it prepares to send the response message to the user terminal and, if it is an emergency, prepares to send a notification to the emergency contact. The output data consists of the message to be sent and the emergency notification.

[0196] Step 9:

[0197] The server sends the generated response message to the user's terminal. The input data is the response message received from the generative artificial intelligence. The server uses the communication platform's API to send the message to the user. The output data is the response message sent to the user's terminal.

[0198] Step 10:

[0199] If the server determines that an emergency is occurring, it will send a notification to the registered emergency contact. The input data includes an urgency flag and emergency contact information. Specifically, notifications will be sent to the registered email address or phone number. The output data is the contact information to which the emergency notification was sent.

[0200] Processing at each step enables quick and appropriate responses to user messages and, when necessary, emergency notifications.

[0201] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0202] This invention relates to a system that uses an emotion engine to recognize the emotions of users with suicidal thoughts via LINE's official account and quickly provides them with empathetic and encouraging messages. This system is realized by receiving messages sent by users in real time, analyzing the user's emotions using the emotion engine, generating an appropriate reply using generative artificial intelligence, and sending it back to the user.

[0203] System Configuration

[0204] 1. User terminal

[0205] A user's device is a communication terminal such as a smartphone or tablet on which the LINE app is installed. Users send and receive messages through this device.

[0206] 2. Server

[0207] The server receives messages and requests the emotion engine and generative artificial intelligence to analyze the messages and generate replies. The server also has the function of sending the generated messages to the user's terminal.

[0208] 3. Emotional Engine

[0209] Includes a program that analyzes input messages and recognizes the user's emotional state (e.g., sadness, loneliness, anxiety).

[0210] 4. Generative Artificial Intelligence

[0211] This includes a program that generates empathetic and encouraging messages tailored to the user's psychological state, based on emotional information provided by an emotion engine.

[0212] Program Processing Overview

[0213] Message reception and preprocessing

[0214] The user's device types "I've been having a really hard time lately. I'm tired of living" and sends the message to the LINE official account.

[0215] The server receives user messages from the LINE platform and preprocesses the content appropriately. Preprocessing includes removing whitespace and escaping special characters.

[0216] Emotional analysis

[0217] The server sends the pre-processed message to the emotion engine.

[0218] The emotion engine analyzes the received message to recognize the user's emotional state. For example, keywords such as "sad" or "tired" are extracted from the words and context in the message, and based on these, emotions such as "sadness" or "isolation" are recognized.

[0219] Reply generation and sending

[0220] The server transmits the emotional information obtained by the emotion engine to the generative artificial intelligence.

[0221] Generative artificial intelligence uses the user's emotional information to generate empathetic and encouraging messages such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0222] The server sends the generated response message back to the user's terminal.

[0223] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0224] Specific example

[0225] Let's consider a scenario where a user sends a message to the official LINE account saying, "I've been feeling really down lately. I'm tired of living." This message is received by the server and pre-processed. Then, the emotion engine analyzes the keywords "down" and "tired" and recognizes emotions such as "sadness" and "isolation." Based on the emotional information recognized by the emotion engine, a generative artificial intelligence generates a message saying, "I understand how you're feeling. You're not alone. I'm here to listen." The server sends this message to the user's device, and the user receives support in real time.

[0226] In this way, the system of the present invention can more accurately recognize the user's emotional state by combining it with an emotion engine, and provide appropriate support based on that recognition.

[0227] The following describes the processing flow.

[0228] Step 1:

[0229] A user uses the LINE app to type and send the message "I've been having a really hard time lately. I'm tired of living" to the official account.

[0230] Step 2:

[0231] The server receives the user's sent message from the LINE platform.

[0232] Step 3:

[0233] Messages received by the server are saved to a database for logging purposes.

[0234] Step 4:

[0235] The server begins message preprocessing. Preprocessing includes the following actions:

[0236] Removal of unnecessary whitespace

[0237] Special character escaping

[0238] Message content normalization

[0239] Step 5:

[0240] The server sends the pre-processed message to the emotion engine.

[0241] Step 6:

[0242] The emotion engine analyzes the received message and recognizes the user's emotional state. For example, it extracts keywords such as "sad" and "tired" from the words and context in the message, and uses that to recognize emotions such as "sadness" and "isolation."

[0243] Step 7:

[0244] The emotion engine returns the recognized emotion information to the server as an analysis result.

[0245] Step 8:

[0246] The server transmits emotional information obtained from the emotion engine to the generative artificial intelligence.

[0247] Step 9:

[0248] Generative artificial intelligence uses the user's emotional information to generate empathetic and encouraging messages such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0249] Step 10:

[0250] The generative artificial intelligence returns the generated message to the server.

[0251] Step 11:

[0252] The server logs the generated messages and saves them to the database.

[0253] Step 12:

[0254] The server generates a message and sends it to the user via the LINE platform.

[0255] Step 13:

[0256] The user receives a message via the LINE app that says, "I understand how you're going through. You're not alone. I'm here to listen."

[0257] (Example 2)

[0258] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0259] There is a need to provide prompt and appropriate empathy and encouragement to users who are in an emotionally unstable state. In particular, accurately recognizing the emotions in messages sent by users and generating appropriate responses based on that is difficult. Furthermore, some systems suffer from problems with the accuracy of emotion analysis due to insufficient preprocessing. Therefore, a system is needed that can accurately recognize the emotions of users and provide appropriate response messages.

[0260] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0261] In this invention, the server includes means for receiving a message sent by a user via an information processing device, means for pre-processing the received message, means for analyzing keywords contained in the pre-processed message and recognizing emotions, means for generating an appropriate empathy and encouragement message based on the analyzed emotion information, and means for sending the generated message back to the information processing device. This makes it possible to accurately recognize the user's emotions and quickly provide an appropriate response message.

[0262] An "information processing device" is a communication device, such as a smartphone or tablet, used by users to send and receive messages.

[0263] "Means of receiving" refers to the function that allows the server to retrieve messages sent by the user.

[0264] "Pre-processing means" refers to functions that remove whitespace and escape special characters from received messages.

[0265] "A means of analyzing keywords and recognizing emotions" refers to a function that analyzes the words and context of pre-processed messages and extracts the user's emotional state.

[0266] A "generative artificial intelligence means" is a program that generates empathetic and encouraging messages that match the user's psychological state based on emotional information.

[0267] The "means of replying" refer to the function of sending the generated response message back to the user's information processing device.

[0268] A "natural language processing algorithm" is an algorithm used to analyze text data and is a technology used to understand emotions and meaning.

[0269] A "recording medium" is a data storage system for saving transmitted and generated messages.

[0270] This invention is a system that integrates an information processing device, a server, an emotion engine, and a generative artificial intelligence to perform emotion analysis in response to messages sent by users, generate appropriate empathetic and encouraging messages, and send them back. A specific example of this system is described in detail below.

[0271] First, the user uses an information processing device such as a smartphone or tablet to type a message and send it through the LINE app. For example, a message like "I've been having a really hard time lately. I'm tired of living" might be entered.

[0272] Next, this message is received by the server. The server retrieves the message from the LINE platform and preprocesses the received message. Preprocessing includes removing whitespace and escaping special characters.

[0273] The pre-processed message is then sent from the server to the emotion engine. The emotion engine analyzes the keywords and context contained in the message to recognize the user's emotional state. For example, keywords such as "painful" and "tired" may be interpreted as emotions such as "sadness" or "isolation."

[0274] Next, the recognized emotion information is sent to a generative artificial intelligence (AI) via a server. The AI ​​generates an appropriate reply message based on the provided emotion information. For example, a message such as, "I understand how you're feeling. You're not alone. I'm here to listen," might be generated.

[0275] Finally, the generated message is sent again by the server to the user's information processing device. The information processing device displays the received message on the LINE app's chat screen, allowing the user to receive messages of empathy and encouragement in real time.

[0276] Specific example

[0277] Consider the case where a user sends a message "I've been really struggling lately. It's so tiring to live." to the official LINE account. This message is received by the server and undergoes preprocessing. The sentiment engine analyzes keywords such as "struggling" and "tiring", and recognizes emotions such as "sadness" and "isolation". Based on the sentiment information, the generative AI generates a message of empathy and encouragement: "I really understand how you feel. You're not alone. I'm here to listen." The server sends this message to the user terminal, and the user receives it.

[0278] Thus, the system of the present invention can accurately recognize the user's emotional state and quickly provide an appropriate response.

[0279] The flow of the specific process in Example 2 will be described using FIG. 13.

[0280] Step 1:

[0281] Message transmission from the user terminal

[0282] The user uses the LINE app to enter the message "I've been really struggling lately. It's so tiring to live." and presses the send button.

[0283] Input: The text message entered by the user

[0284] Output: Transmission of the message to the LINE server

[0285] Specific operation: The user opens the chat screen of the LINE app, enters a message using the keyboard, and taps the send button.

[0286] Step 2:

[0287] Message reception and preprocessing by the server

[0288] The server receives user messages from the LINE platform. The received messages are pre-processed. Pre-processing includes removing whitespace and escaping special characters.

[0289] Input: Raw message data received from the LINE server

[0290] Output: Pre-processed, clean message data

[0291] Specific operation: The server retrieves messages using the LINE API and removes unnecessary whitespace and special characters using string manipulation functions.

[0292] Step 3:

[0293] Sending messages from the server to the emotion engine

[0294] The server sends the pre-processed message to the emotion engine.

[0295] Input: Pre-processed, clean message data

[0296] Output: Sending a message to the emotion engine

[0297] Specific operation: The server sends an HTTP request to the emotion engine's API endpoint, passing the pre-processed message.

[0298] Step 4:

[0299] Emotional analysis using an emotion engine

[0300] The emotion engine analyzes received messages and recognizes the user's emotional state. For example, it can recognize emotions such as "sadness" or "isolation" from keywords like "painful" or "tired."

[0301] Input: Clean message data

[0302] Output: Emotional information such as "sadness" and "sense of isolation"

[0303] Specific operation: The emotion engine uses a natural language processing algorithm to extract keywords and assign emotion labels.

[0304] Step 5:

[0305] Transmission of emotional information from the server to the generative artificial intelligence

[0306] The server transmits the emotional information obtained by the emotion engine to the generative artificial intelligence.

[0307] Input: Emotional information obtained from the emotion engine

[0308] Output: Transmission of emotional information to the generative artificial intelligence

[0309] Specific operation: The server sends an HTTP request to the API endpoint of the generative artificial intelligence and passes the emotional information.

[0310] Step 6:

[0311] Generation of a reply message by the generative artificial intelligence

[0312] The generative artificial intelligence generates an appropriate reply message based on the provided emotional information. For example, a message such as "I fully understand your difficult feelings. You are not alone. I am here to listen to you." is generated.

[0313] Input: Emotional information

[0314] Output: Generated reply message[[ID=*]]

[0315] Specific operation: The generative artificial intelligence executes an algorithm that generates text containing emotional information based on a prompt.

[0316] Step 7:

[0317] Server sends reply message to user terminal

[0318] The server then resends the generated response message to the user's LINE account.

[0319] Input: Generated reply message

[0320] Output: Sending a message to the user's LINE account

[0321] Specific operation: The server uses the LINE API to send the generated message to the user's LINE account.

[0322] Step 8:

[0323] Receiving reply messages from the user's terminal

[0324] The user's information processing device receives the reply message and displays it on the LINE app's chat screen. The user receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0325] Input: Reply message sent from the server

[0326] Output: Message displayed on the LINE app chat screen

[0327] Specific operation: The user's device uses the LINE API to retrieve messages and displays them on the chat screen.

[0328] (Application Example 2)

[0329] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0330] In modern society, systems that provide responses tailored to a user's emotional state are crucial. In particular, there is a need for psychological support, such as providing appropriate empathy and encouragement to emotionally unstable users. However, current systems struggle to accurately analyze user emotions and generate appropriate messages, resulting in insufficient individual adaptation. Furthermore, the lack of content recommendation features (such as movies and music) based on emotional states makes it difficult to improve user satisfaction.

[0331] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0332] In this invention, the server includes means for receiving a message sent by a user via a communication terminal, means for analyzing keywords contained in the received message, means for generating appropriate empathetic and encouraging messages based on the analysis results, means for sending the generated message back to the communication terminal, means for analyzing a message about emotions entered by the user and recommending content (such as movies or music) that is appropriate for that emotion, and means for sending the recommended content to the communication terminal. This enables personalized messages and content recommendations that correspond to the user's emotional state.

[0333] "Means for receiving messages sent by users via communication terminals" refers to a function that allows a server to receive text messages sent by users through devices such as smartphones and tablets.

[0334] "Means for analyzing keywords contained in the received message" refers to a function that examines the content of the received message, extracts important words and phrases, and understands their meaning and sentiment.

[0335] "Generative artificial intelligence means for generating appropriate empathetic and encouraging messages based on analysis results" refers to an artificial intelligence system that automatically creates empathetic and encouraging messages tailored to the user's psychological state based on analyzed keywords and context.

[0336] "Means for sending the generated message back to the communication terminal" refers to a function for sending and displaying a message created by a generative artificial intelligence system on a device used by the user.

[0337] "A means of analyzing emotional messages entered by users and recommending content (such as movies or music) that is appropriate for those emotions" refers to a function that analyzes the emotional expressions contained in the user's message and suggests entertainment content such as movies and music based on that analysis.

[0338] "Means for transmitting the recommended content to a communication terminal" refers to a function that transmits suggested content information, such as movies and music, to the user's device so that it can be displayed and played.

[0339] The system based on this invention aims to generate empathetic and encouraging messages according to the user's emotional state, and further recommend content (such as movies and music) that is appropriate to the user's emotions. This system consists of the following main hardware and software components.

[0340] 1. Hardware Configuration

[0341] User terminal: A communication device such as a smartphone or tablet. Users send and receive messages through this device.

[0342] Server: A central processing unit that receives, parses, generates, and sends messages.

[0343] 2. Software Configuration

[0344] LINE app: A messaging application used by users.

[0345] Emotion Engine: Uses libraries such as TextBlob to analyze the sentiment of messages sent by users.

[0346] Generative artificial intelligence: Uses APIs such as OpenAI (registered trademark) to generate empathetic and encouraging messages based on analysis results.

[0347] Content recommendation system: Recommends content such as movies and music based on generated messages and sentiment information.

[0348] 3. Program Processing Overview

[0349] When a user sends a message using the LINE app, the server receives the message and performs preprocessing. This preprocessing includes removing whitespace and escaping special characters. The emotion engine then analyzes the message and recognizes the user's emotional state. For example, keywords such as "sad" and "tired" are extracted from the words and context in the message, and the emotion engine recognizes emotions such as "sadness" and "isolation."

[0350] Based on the analysis results, a generative artificial intelligence generates empathetic and encouraging messages that are appropriate to the user's emotions. For example, it might generate a message like, "I understand how you're feeling. You're not alone. I'm here to listen." At the same time, a content recommendation system suggests movies, music, and other content that are appropriate to the user's emotions.

[0351] 4. Specific Examples

[0352] Let's consider a scenario where a user sends the message "I'm feeling kind of down today" to the official LINE account. This message is received by the server and preprocessed. Then, the emotion engine analyzes the keyword "down" and recognizes "sadness" as an emotion. Based on the analysis, the generative artificial intelligence generates the message "I understand how you're feeling. You're not alone. I'm here to listen," and simultaneously recommends the movie "The Blind Side" and the song "Let It Be" by The Beatles.

[0353] Example of a prompt

[0354] "A user is feeling sad. Recommend a movie or music that can help them feel better."

[0355] By sending this prompt to the OpenAI API, appropriate content will be recommended and provided to the user.

[0356] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0357] Step 1:

[0358] The user sends a message via the LINE app. This message is sent to the server by the user's device. Specifically, the user types the message "I feel kind of depressed today" into the LINE official account and sends it. The input is text data, which is sent to the server.

[0359] Step 2:

[0360] The server receives the message and performs preprocessing. This preprocessing includes removing whitespace and escaping special characters. Specifically, it removes unnecessary spaces and special characters from the received text data to prepare it for analysis. The input is text data, and the output is preprocessed text data.

[0361] Step 3:

[0362] The server sends pre-processed messages to the sentiment engine for sentiment analysis. Using sentiment analysis libraries such as TextBlob, the engine analyzes keywords and context within the messages to determine the user's emotional state. The input is pre-processed text data, and the output is emotional information (such as "sadness" or "isolation"). For example, the word "melancholy" might be interpreted as the emotion "sadness."

[0363] Step 4:

[0364] The server sends emotional information obtained from the emotion engine to a generative artificial intelligence system, which then generates empathetic and encouraging messages. Using the OpenAI API and other tools, it automatically generates appropriate messages based on the analysis results. The input is emotional information, and the output is the generated empathetic and encouraging message. Example prompt: "A user is feeling sadness. Provide an empathetic and encouraging message."

[0365] Step 5:

[0366] The server sends a generated message to the user's device for display. Specifically, the generated message, "I understand how you're going through. You're not alone. I'm here to listen," is sent to the user's device and displayed in the LINE app. The input is the generated message, and the output is the display on the user's device.

[0367] Step 6:

[0368] Simultaneously, the server activates a content recommendation system based on emotional information to recommend appropriate movies and music. It uses the OpenAI API to generate emotionally-based content. The input is emotional information, and the output is information about recommended content (e.g., "The Blind Side" movie or "Let It Be" music). Example prompt: "A user is feeling sadness. Recommend a movie or music that can help them feel better."

[0369] Step 7:

[0370] The server sends recommended content information to the user's terminal and displays it to the user. This allows the user to browse and listen to the recommended movies and music. The input is information about the recommended content, and the output is the display on the user's terminal and the provision of links.

[0371] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0372] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0373] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0374] [Second Embodiment]

[0375] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0376] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0377] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0378] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0379] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0380] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0381] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0382] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0383] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0384] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0385] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0386] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0387] This invention relates to a system that provides empathetic and encouraging messages to users with suicidal thoughts via LINE's official account. This system is realized by receiving messages sent by users in real time, generating appropriate replies using generative artificial intelligence, and sending them back to the user.

[0388] System Configuration

[0389] 1. User terminal

[0390] A user's device is a communication terminal such as a smartphone or tablet on which the LINE app is installed. Users send and receive messages through this device.

[0391] 2. Server

[0392] The server receives messages and requests generative artificial intelligence to analyze them and generate replies. The server also sends the generated messages to the user's terminal.

[0393] 3. Generative Artificial Intelligence

[0394] Includes a program that analyzes input messages and generates appropriate messages of empathy and encouragement.

[0395] Program Processing Overview

[0396] Message reception and preprocessing

[0397] The user's device types "I've been having a really hard time lately. I'm tired of living" and sends the message to the LINE official account.

[0398] The server receives user messages from the LINE platform and preprocesses the content appropriately. Preprocessing includes removing whitespace and escaping special characters.

[0399] Message parsing and reply generation

[0400] The server sends the pre-processed message to the generative artificial intelligence.

[0401] A generative artificial intelligence analyzes the received message and extracts keywords (e.g., spicy, tired).

[0402] Based on keywords extracted by the generative artificial intelligence, it generates a message of empathy and encouragement such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0403] Send a reply

[0404] The server receives the generated response message and sends it back to the user's terminal.

[0405] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0406] Specific example

[0407] Let's consider a scenario where a user sends a message to the official LINE account saying, "I've been having a really hard time lately. I'm tired of living." This message is received by the server and pre-processed. Then, a generative artificial intelligence extracts the keywords "hard" and "tired." Based on these keywords, the generative AI creates a message of empathy and encouragement and returns it to the server. The server sends this message to the user's device, and the user receives support in real time.

[0408] In this way, the system of the present invention can provide rapid and accurate support to users who have suicidal thoughts.

[0409] The following describes the processing flow.

[0410] Step 1:

[0411] A user uses the LINE app to type and send the message "I've been having a really hard time lately. I'm tired of living" to the official account.

[0412] Step 2:

[0413] The server receives the user's sent message from the LINE platform.

[0414] Step 3:

[0415] Messages received by the server are saved to a database for logging purposes.

[0416] Step 4:

[0417] The server begins message preprocessing. Preprocessing includes the following actions:

[0418] Removal of unnecessary whitespace

[0419] Special character escaping

[0420] Message content normalization

[0421] Step 5:

[0422] The server extracts important keywords from the pre-processed messages. For example, keywords such as "painful" and "tired" might be extracted.

[0423] Step 6:

[0424] The server sends a request to the generative artificial intelligence API. The request includes the message content after preprocessing and keyword extraction.

[0425] Step 7:

[0426] The generative artificial intelligence receives the request and analyzes the message content and extracted keywords.

[0427] Step 8:

[0428] The generative artificial intelligence generates appropriate empathetic and encouraging messages based on the analysis results. For example, it might generate a message like, "I understand how you're going through. You're not alone. I'm here to listen."

[0429] Step 9:

[0430] The generative artificial intelligence returns the generated message to the server.

[0431] Step 10:

[0432] The server logs the generated messages and saves them to the database.

[0433] Step 11:

[0434] The server generates a message and sends it to the user via the LINE platform.

[0435] Step 12:

[0436] The user receives a message via the LINE app that says, "I understand how you're going through. You're not alone. I'm here to listen."

[0437] The above outlines the specific processing steps of this system.

[0438] (Example 1)

[0439] Next, we will describe Example 1. 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."

[0440] There is a need for a means to quickly and accurately provide empathetic and encouraging messages to users who have suicidal thoughts. However, conventional systems may be slow to analyze user messages and generate appropriate replies, or may generate inappropriate messages. Therefore, an effective means is needed to alleviate the emotional burden on users and provide support quickly.

[0441] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0442] In this invention, the server includes means for receiving a message sent by a user via a communication terminal, means for pre-processing the received message, means for analyzing keywords contained in the pre-processed message, means for generating an appropriate message of empathy and encouragement based on the analysis results using generative artificial intelligence, and means for sending the generated message back to the communication terminal. This makes it possible to quickly analyze messages sent by users and provide appropriate messages of empathy and encouragement in real time.

[0443] A "communication terminal" is an electronic device used by a user to send and receive messages, and includes smartphones, tablets, personal computers, and other similar devices.

[0444] A "server" is a central computer system used for receiving, pre-processing, parsing, and generating replies to messages.

[0445] A "message" refers to text information sent by a user via a communication device, and includes content that expresses the user's emotions or state of mind.

[0446] "Preprocessing" refers to data organization operations performed before analysis, such as removing whitespace from received messages and escaping special characters.

[0447] "Keywords" are important words or phrases extracted from a message, and they serve as criteria for generative artificial intelligence to generate empathetic and encouraging messages.

[0448] "Generative artificial intelligence" refers to an artificial intelligence program that analyzes an input message and automatically generates an appropriate response based on the analysis results.

[0449] A "prompt" is a text containing instructions or questions for generating a specific response from a generative artificial intelligence system.

[0450] A "log" is a data file used to record messages that have been sent and messages that have been generated.

[0451] A "message of empathy and encouragement" is a message created by a generative artificial intelligence system that appropriately empathizes with the user's emotions and state of mind and has the intention of offering encouragement.

[0452] This invention relates to a system that receives messages sent by users in real time and returns appropriate reply messages using generative artificial intelligence. In particular, it aims to provide empathetic and encouraging messages quickly and accurately to users who have suicidal thoughts.

[0453] System Configuration

[0454] Hardware and software

[0455] This system uses the following hardware and software.

[0456] 1. Communication terminal: An electronic device used by users to send and receive messages, including smartphones, tablets, and personal computers.

[0457] 2. Server: A central computer system for receiving, pre-processing, parsing, and generating replies to messages.

[0458] 3. Generative Artificial Intelligence: This is an artificial intelligence program that analyzes input messages and generates appropriate empathetic and encouraging messages.

[0459] Message reception and preprocessing

[0460] The user's device sends a message via the LINE app in response to the user's input: "I've been having a really hard time lately. I'm tired of living."

[0461] The server receives this message from the LINE platform and performs preprocessing such as removing whitespace and escaping special characters.

[0462] Message parsing and reply generation

[0463] The server sends the pre-processed message to the generative artificial intelligence. The following prompt is used: "Receive the user's message, 'I've been having a really hard time lately. I'm tired of living,' extract keywords, and generate a message of empathy and encouragement."

[0464] A generative artificial intelligence analyzes the received message and extracts keywords such as "painful" and "tired."

[0465] The generative artificial intelligence generates a message of empathy and encouragement based on the extracted keywords, such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0466] Send a reply

[0467] The server receives a response message generated by a generative artificial intelligence and sends it to the user's terminal via the LINE platform.

[0468] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0469] As a concrete example, consider a case where a user sends the message "I've been having a really hard time lately. I'm tired of living" to the official LINE account. This message is received by the server, where whitespace is removed and special characters are escaped. Then, a generative artificial intelligence extracts the keywords "hard" and "tired," and generates a message of empathy and encouragement such as: "I understand how you're feeling. You're not alone. I'm here to listen."

[0470] This invention makes it possible to quickly analyze messages sent by users and provide appropriate messages of empathy and encouragement in real time.

[0471] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0472] Step 1:

[0473] The user's device sends the message "I've been having a really hard time lately. I'm tired of living" through the LINE app in response to the user's input. Specifically, the user types the message in the chat window within the LINE app and presses the send button. The input is the user's text message, and the output is a message that reaches the server via the LINE platform.

[0474] Step 2:

[0475] The server receives user messages from the LINE platform. The received messages undergo preprocessing, such as whitespace removal and special character escaping. Specifically, a message like "It's spicy." is converted to "It's spicy." The input is the raw message sent from the user's terminal, and the output is the preprocessed message.

[0476] Step 3:

[0477] The server sends a pre-processed message to a generative artificial intelligence. The following prompt is used: "Receive the message 'I've been having a really hard time lately. I'm tired of living' sent by the user, extract keywords, and generate a message of empathy and encouragement." The input is the pre-processed message and the prompt, and the output is the data sent to the generative artificial intelligence.

[0478] Step 4:

[0479] A generative artificial intelligence analyzes pre-processed messages received from a server. During the analysis, it extracts keywords such as "painful" and "tired." The input consists of the pre-processed message and prompt text, while the output is the keywords resulting from the analysis. Specifically, natural language processing techniques are used to analyze the message content, performing sentiment analysis and keyword extraction.

[0480] Step 5:

[0481] The generative artificial intelligence generates empathetic and encouraging messages based on the extracted keywords. Specifically, it generates a message such as, "I understand how you're going through. You're not alone. I'm here to listen." The input is the keywords extracted in step 4, and the output is the generated empathetic and encouraging message.

[0482] Step 6:

[0483] The server receives messages generated by a generative artificial intelligence and sends them to the user's terminal via the LINE platform. Specifically, the server receives the generated message and forwards it to the user's terminal via the LINE platform. The input is the generated message, and the output is the message sent to the user's terminal.

[0484] Step 7:

[0485] The user's device receives empathy and encouragement messages sent from the server via the LINE app. The user then views the messages displayed in the chat window within the LINE app. Specifically, when the user taps a notification in the LINE app, the chat window automatically opens and displays the reply message. The input is the message sent from the server, and the output is the message displayed within the LINE app.

[0486] This allows for the rapid analysis of messages sent by users, providing appropriate messages of empathy and encouragement in real time.

[0487] (Application Example 1)

[0488] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0489] While systems exist to quickly provide empathetic and encouraging messages to users with suicidal thoughts, only a limited number of systems can respond to urgent situations. Furthermore, current systems often fail to recognize emergencies, making it difficult to provide appropriate support immediately. This means that users in dangerous situations may not receive adequate and timely support.

[0490] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0491] In this invention, the server includes means for receiving messages sent by a user via a communication terminal, means for analyzing keywords contained in the received messages, generative artificial intelligence means for generating appropriate empathetic and encouraging messages based on the analysis results, means for examining messages to determine their urgency, means for sending notifications to registered contacts if the means for determining urgency determines that the message is urgent, and means for sending the generated message back to the communication terminal. This makes it possible to respond quickly to emergencies and provide users with immediate and appropriate support.

[0492] A "communication terminal" is a device used by users to send and receive messages, and includes smartphones, tablets, and personal computers.

[0493] A "keyword" is a specific word or phrase contained within a received message, and it is an important element for analyzing the content of the message.

[0494] "Generative artificial intelligence" is a general term for programs and systems that analyze input messages and generate appropriate responses.

[0495] "Means for determining urgency" refers to a function or algorithm that analyzes the content of a received message and determines whether or not that message is an emergency.

[0496] "Means of sending notifications" refers to a function that sends alerts and notifications to pre-configured contacts when an emergency is determined.

[0497] "Preprocessing" is the process of cleaning and filtering text to make it easier to analyze the content of received messages.

[0498] A "log" is a record used to store and manage sent messages and generated responses.

[0499] This invention relates to a system that processes messages sent by users via a communication terminal quickly and appropriately, and provides immediate notification in emergencies. Based on the claims, embodiments for carrying out this invention are described below.

[0500] System Configuration

[0501] 1. User terminal

[0502] Users send messages using communication devices (smartphones, tablets, PCs, etc.). Messages are sent via communication platforms such as the LINE app.

[0503] 2. Server

[0504] The server receives messages sent from user terminals, analyzes them using generative artificial intelligence (AI models), and generates appropriate replies. The server also plays a role in determining urgency and sending notifications.

[0505] 3. Generative Artificial Intelligence

[0506] The generative artificial intelligence analyzes messages received from users and extracts keywords. It includes a program that generates empathetic and encouraging messages based on the extracted keywords. Furthermore, in emergency situations, it generates appropriate response messages and sends them back to the server.

[0507] Program Processing Overview

[0508] Processing received messages

[0509] A user sends a message via a communication device saying, "I've been having a really hard time lately. I'm tired of living." The server receives this message and performs preprocessing. Preprocessing includes removing whitespace and handling special characters.

[0510] Message parsing and reply generation

[0511] The server sends the pre-processed message to the generative artificial intelligence. The generative AI analyzes the message and extracts keywords (e.g., "painful," "tired"). Based on the extracted keywords, it generates an empathetic and encouraging message such as, "I understand how you're feeling. You're not alone. I'm here to listen."

[0512] Assessment and notification of urgency

[0513] Furthermore, the generative artificial intelligence examines the message for urgent keywords (e.g., "help," "now") to determine its urgency. If it determines it is urgent, the server sends a notification to pre-configured emergency contacts.

[0514] Send message

[0515] The server sends the generated reply message to the user's terminal. The user's terminal receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0516] Hardware and software to be used

[0517] Communication devices: Smartphones, tablets, personal computers

[0518] Communication platform: LINE app, etc.

[0519] Server: Cloud server (AWS, Google Cloud, etc.)

[0520] Generative artificial intelligence: AI models such as GPT-3

[0521] Log management system: Database (MySQL, PostgreSQL, etc.)

[0522] Specific example

[0523] A user sends a message from their communication device saying, "I've been having a really hard time lately. I'm tired of living." This message is received by the server and pre-processed. Then, an AI model extracts keywords such as "hard" and "tired." Based on these keywords, the AI ​​model generates an empathetic and encouraging message, such as "I understand how you're feeling. You're not alone. I'm here to listen," and sends it back to the server. The server sends this message to the user's device, and the user receives support in real time. In addition, if urgent keywords such as "help" or "right now" are detected, a notification is sent to the registered emergency contact.

[0524] Example of a prompt

[0525] "I've been having a really hard time lately. I'm tired of living."

[0526] "Help me, I need someone to listen to me right now."

[0527] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0528] Step 1:

[0529] The user sends a message via a communication device. The user uses a communication platform such as the LINE app to type a message like, "I've been having a really hard time lately. I'm tired of living," and presses the send button. The input data is a text message.

[0530] Step 2:

[0531] The server receives messages sent from the user's terminal. The input data is a text message sent by the user. The server retrieves the message through the communication platform's API. Specifically, this is achieved by using the LINE platform's API and listening for message events. The output data is a text message that requires preprocessing.

[0532] Step 3:

[0533] The server preprocesses the received message. Preprocessing includes removing whitespace, escaping special characters, and standardizing the message text. The input data is the received text message, and the output data is the preprocessed text message.

[0534] Step 4:

[0535] The server sends a pre-processed message to a generative artificial intelligence (AI). The input data is a pre-processed text message. The server calls the AI's API and sends a request for message analysis and reply generation. The output data is the analysis result and the generated response message returned by the AI.

[0536] Step 5:

[0537] Generative artificial intelligence analyzes received messages and extracts keywords. The input data is a pre-processed text message sent from a server. As part of the data processing, natural language processing techniques are used to tokenize the message and extract keywords. The output data consists of the extracted keywords and a response message generated based on those keywords.

[0538] Step 6:

[0539] Generative artificial intelligence generates appropriate empathetic and encouraging messages based on extracted keywords. The input data consists of extracted keywords. A generative AI model (e.g., GPT-3) is used to generate response messages based on prompts. The output data consists of the generated empathetic and encouraging messages.

[0540] Step 7:

[0541] Generative artificial intelligence examines messages for urgent keywords and determines their urgency. The input data is the entire message. As a data calculation, it scans the message to check if it contains urgent keywords (e.g., "help", "now"). The output data is an urgency flag (whether it is urgent or not).

[0542] Step 8:

[0543] The server receives the response message and the urgency assessment result from the generative artificial intelligence. The input data consists of the generated response message and the urgency assessment result. Based on this information, the server continues the necessary processing. Specifically, it prepares to send the response message to the user terminal and, if it is an emergency, prepares to send a notification to the emergency contact. The output data consists of the message to be sent and the emergency notification.

[0544] Step 9:

[0545] The server sends the generated response message to the user's terminal. The input data is the response message received from the generative artificial intelligence. The server uses the communication platform's API to send the message to the user. The output data is the response message sent to the user's terminal.

[0546] Step 10:

[0547] If the server determines that an emergency is occurring, it will send a notification to the registered emergency contact. The input data includes an urgency flag and emergency contact information. Specifically, notifications will be sent to the registered email address or phone number. The output data is the contact information to which the emergency notification was sent.

[0548] Processing at each step enables quick and appropriate responses to user messages and, when necessary, emergency notifications.

[0549] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0550] This invention relates to a system that uses an emotion engine to recognize the emotions of users with suicidal thoughts via LINE's official account and quickly provides them with empathetic and encouraging messages. This system is realized by receiving messages sent by users in real time, analyzing the user's emotions using the emotion engine, generating an appropriate reply using generative artificial intelligence, and sending it back to the user.

[0551] System Configuration

[0552] 1. User terminal

[0553] A user's device is a communication terminal such as a smartphone or tablet on which the LINE app is installed. Users send and receive messages through this device.

[0554] 2. Server

[0555] The server receives messages and requests the emotion engine and generative artificial intelligence to analyze the messages and generate replies. The server also has the function of sending the generated messages to the user's terminal.

[0556] 3. Emotional Engine

[0557] Includes a program that analyzes input messages and recognizes the user's emotional state (e.g., sadness, loneliness, anxiety).

[0558] 4. Generative Artificial Intelligence

[0559] This includes a program that generates empathetic and encouraging messages tailored to the user's psychological state, based on emotional information provided by an emotion engine.

[0560] Program Processing Overview

[0561] Message reception and preprocessing

[0562] The user's device types "I've been having a really hard time lately. I'm tired of living" and sends the message to the LINE official account.

[0563] The server receives user messages from the LINE platform and preprocesses the content appropriately. Preprocessing includes removing whitespace and escaping special characters.

[0564] Emotional analysis

[0565] The server sends the pre-processed message to the emotion engine.

[0566] The emotion engine analyzes the received message to recognize the user's emotional state. For example, keywords such as "sad" or "tired" are extracted from the words and context in the message, and based on these, emotions such as "sadness" or "isolation" are recognized.

[0567] Reply generation and sending

[0568] The server transmits the emotional information obtained by the emotion engine to the generative artificial intelligence.

[0569] Generative artificial intelligence uses the user's emotional information to generate empathetic and encouraging messages such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0570] The server sends the generated response message back to the user's terminal.

[0571] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0572] Specific example

[0573] Let's consider a scenario where a user sends a message to the official LINE account saying, "I've been feeling really down lately. I'm tired of living." This message is received by the server and pre-processed. Then, the emotion engine analyzes the keywords "down" and "tired" and recognizes emotions such as "sadness" and "isolation." Based on the emotional information recognized by the emotion engine, a generative artificial intelligence generates a message saying, "I understand how you're feeling. You're not alone. I'm here to listen." The server sends this message to the user's device, and the user receives support in real time.

[0574] In this way, the system of the present invention can more accurately recognize the user's emotional state by combining it with an emotion engine, and provide appropriate support based on that recognition.

[0575] The following describes the processing flow.

[0576] Step 1:

[0577] A user uses the LINE app to type and send the message "I've been having a really hard time lately. I'm tired of living" to the official account.

[0578] Step 2:

[0579] The server receives the user's sent message from the LINE platform.

[0580] Step 3:

[0581] Messages received by the server are saved to a database for logging purposes.

[0582] Step 4:

[0583] The server begins message preprocessing. Preprocessing includes the following actions:

[0584] Removal of unnecessary whitespace

[0585] Special character escaping

[0586] Message content normalization

[0587] Step 5:

[0588] The server sends the pre-processed message to the emotion engine.

[0589] Step 6:

[0590] The emotion engine analyzes the received message and recognizes the user's emotional state. For example, it extracts keywords such as "sad" and "tired" from the words and context in the message, and uses that to recognize emotions such as "sadness" and "isolation."

[0591] Step 7:

[0592] The emotion engine returns the recognized emotion information to the server as an analysis result.

[0593] Step 8:

[0594] The server transmits emotional information obtained from the emotion engine to the generative artificial intelligence.

[0595] Step 9:

[0596] Generative artificial intelligence uses the user's emotional information to generate empathetic and encouraging messages such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0597] Step 10:

[0598] The generative artificial intelligence returns the generated message to the server.

[0599] Step 11:

[0600] The server logs the generated messages and saves them to the database.

[0601] Step 12:

[0602] The server generates a message and sends it to the user via the LINE platform.

[0603] Step 13:

[0604] The user receives a message via the LINE app that says, "I understand how you're going through. You're not alone. I'm here to listen."

[0605] (Example 2)

[0606] Next, we will describe Example 2. 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".

[0607] There is a need to provide prompt and appropriate empathy and encouragement to users who are in an emotionally unstable state. In particular, accurately recognizing the emotions in messages sent by users and generating appropriate responses based on that is difficult. Furthermore, some systems suffer from problems with the accuracy of emotion analysis due to insufficient preprocessing. Therefore, a system is needed that can accurately recognize the emotions of users and provide appropriate response messages.

[0608] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0609] In this invention, the server includes means for receiving a message sent by a user via an information processing device, means for preprocessing the received message, means for analyzing keywords contained in the preprocessed message and recognizing emotions, generative artificial intelligence means for generating appropriate empathy and encouragement messages based on the analyzed emotion information, and means for sending the generated message back to the information processing device. This makes it possible to accurately recognize the user's emotions and quickly provide an appropriate response message.

[0610] An "information processing device" is a communication device, such as a smartphone or tablet, used by users to send and receive messages.

[0611] "Means of receiving" refers to the function that allows the server to retrieve messages sent by the user.

[0612] "Pre-processing means" refers to functions that remove whitespace and escape special characters from received messages.

[0613] "A means of analyzing keywords and recognizing emotions" refers to a function that analyzes the words and context of pre-processed messages and extracts the user's emotional state.

[0614] A "generative artificial intelligence means" is a program that generates empathetic and encouraging messages that match the user's psychological state based on emotional information.

[0615] The "means of replying" refer to the function of sending the generated response message back to the user's information processing device.

[0616] A "natural language processing algorithm" is an algorithm used to analyze text data and is a technology used to understand emotions and meaning.

[0617] A "recording medium" is a data storage system for saving transmitted and generated messages.

[0618] This invention is a system that integrates an information processing device, a server, an emotion engine, and a generative artificial intelligence to perform emotion analysis in response to messages sent by users, generate appropriate empathetic and encouraging messages, and send them back. A specific example of this system is described in detail below.

[0619] First, the user uses an information processing device such as a smartphone or tablet to type a message and send it through the LINE app. For example, a message like "I've been having a really hard time lately. I'm tired of living" might be entered.

[0620] Next, this message is received by the server. The server retrieves the message from the LINE platform and preprocesses the received message. Preprocessing includes removing whitespace and escaping special characters.

[0621] The pre-processed message is then sent from the server to the emotion engine. The emotion engine analyzes the keywords and context contained in the message to recognize the user's emotional state. For example, keywords such as "painful" and "tired" may be interpreted as emotions such as "sadness" or "isolation."

[0622] Next, the recognized emotion information is sent to a generative artificial intelligence (AI) via a server. The AI ​​generates an appropriate reply message based on the provided emotion information. For example, a message such as, "I understand how you're feeling. You're not alone. I'm here to listen," might be generated.

[0623] Finally, the generated message is sent again by the server to the user's information processing device. The information processing device displays the received message on the LINE app's chat screen, allowing the user to receive messages of empathy and encouragement in real time.

[0624] Specific example

[0625] Consider a scenario where a user sends a message to a LINE official account saying, "I've been feeling really down lately. I'm tired of living." This message is received by the server and preprocessed. An emotion engine analyzes the keywords "down" and "tired," recognizing emotions such as "sadness" and "isolation." Based on this emotional information, a generative artificial intelligence generates an empathetic and encouraging message: "I understand how you're feeling. You're not alone. I'm here to listen." The server then sends this message to the user's device, which the user receives.

[0626] As a result, the system of the present invention can accurately recognize the user's emotional state and provide a quick and appropriate response.

[0627] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0628] Step 1:

[0629] Message sending from user terminal

[0630] The user uses the LINE app to type the message, "I've been having a really hard time lately. I'm tired of living," and presses the send button.

[0631] Input: Text message entered by the user

[0632] Output: Sending a message to the LINE server

[0633] Specific actions: The user opens the LINE app's chat screen, types a message using the keyboard, and taps the send button.

[0634] Step 2:

[0635] Message reception and preprocessing by the server

[0636] The server receives user messages from the LINE platform. The received messages are pre-processed. Pre-processing includes removing whitespace and escaping special characters.

[0637] Input: Raw message data received from the LINE server

[0638] Output: Pre-processed, clean message data

[0639] Specific operation: The server retrieves messages using the LINE API and removes unnecessary whitespace and special characters using string manipulation functions.

[0640] Step 3:

[0641] Sending messages from the server to the emotion engine

[0642] The server sends the pre-processed message to the emotion engine.

[0643] Input: Pre-processed, clean message data

[0644] Output: Sending a message to the emotion engine

[0645] Specific operation: The server sends an HTTP request to the emotion engine's API endpoint, passing the pre-processed message.

[0646] Step 4:

[0647] Emotional analysis using an emotion engine

[0648] The emotion engine analyzes received messages and recognizes the user's emotional state. For example, it can recognize emotions such as "sadness" or "isolation" from keywords like "painful" or "tired."

[0649] Input: Clean message data

[0650] Output: Emotional information such as "sadness" and "isolation."

[0651] Specific operation: The emotion engine uses a natural language processing algorithm to extract keywords and assign emotion labels.

[0652] Step 5:

[0653] Emotional information transmission from the server to the generative artificial intelligence.

[0654] The server transmits the emotional information obtained by the emotion engine to the generative artificial intelligence.

[0655] Input: Emotional information obtained from the emotion engine.

[0656] Output: Sending emotional information to a generative artificial intelligence system.

[0657] Specific operation: The server sends an HTTP request to the generative artificial intelligence API endpoint, passing emotion information.

[0658] Step 6:

[0659] Generative AI-powered reply message generation

[0660] Generative artificial intelligence generates appropriate reply messages based on the emotional information provided. For example, it might generate a message like, "I understand how you're going through. You're not alone. I'm here to listen."

[0661] Input: Emotional information

[0662] Output: Generated reply message

[0663] Specific operation: The generative artificial intelligence executes an algorithm that generates text containing emotional information based on the prompt.

[0664] Step 7:

[0665] Server sends reply message to user terminal

[0666] The server then resends the generated response message to the user's LINE account.

[0667] Input: Generated reply message

[0668] Output: Sending a message to the user's LINE account

[0669] Specific operation: The server uses the LINE API to send the generated message to the user's LINE account.

[0670] Step 8:

[0671] Receiving reply messages from the user's terminal

[0672] The user's information processing device receives the reply message and displays it on the LINE app's chat screen. The user receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0673] Input: Reply message sent from the server

[0674] Output: Message displayed on the LINE app chat screen

[0675] Specific operation: The user's device uses the LINE API to retrieve messages and displays them on the chat screen.

[0676] (Application Example 2)

[0677] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0678] In modern society, systems that provide responses tailored to a user's emotional state are crucial. In particular, there is a need for psychological support, such as providing appropriate empathy and encouragement to emotionally unstable users. However, current systems struggle to accurately analyze user emotions and generate appropriate messages, resulting in insufficient individual adaptation. Furthermore, the lack of content recommendation features (such as movies and music) based on emotional states makes it difficult to improve user satisfaction.

[0679] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0680] In this invention, the server includes means for receiving a message sent by a user via a communication terminal, means for analyzing keywords contained in the received message, means for generating appropriate empathetic and encouraging messages based on the analysis results, means for sending the generated message back to the communication terminal, means for analyzing a message about emotions entered by the user and recommending content (such as movies or music) that is appropriate for that emotion, and means for sending the recommended content to the communication terminal. This enables personalized messages and content recommendations that correspond to the user's emotional state.

[0681] "Means for receiving messages sent by users via communication terminals" refers to a function that allows a server to receive text messages sent by users through devices such as smartphones and tablets.

[0682] "Means for analyzing keywords contained in the received message" refers to a function that examines the content of the received message, extracts important words and phrases, and understands their meaning and sentiment.

[0683] "Generative artificial intelligence means for generating appropriate empathetic and encouraging messages based on analysis results" refers to an artificial intelligence system that automatically creates empathetic and encouraging messages tailored to the user's psychological state based on analyzed keywords and context.

[0684] "Means for sending the generated message back to the communication terminal" refers to a function for sending and displaying a message created by a generative artificial intelligence system on a device used by the user.

[0685] "A means of analyzing emotional messages entered by users and recommending content (such as movies or music) that is appropriate for those emotions" refers to a function that analyzes the emotional expressions contained in the user's message and suggests entertainment content such as movies and music based on that analysis.

[0686] "Means for transmitting the recommended content to a communication terminal" refers to a function that transmits suggested content information, such as movies and music, to the user's device so that it can be displayed and played.

[0687] The system based on this invention aims to generate empathetic and encouraging messages according to the user's emotional state, and further recommend content (such as movies and music) that is appropriate to the user's emotions. This system consists of the following main hardware and software components.

[0688] 1. Hardware Configuration

[0689] User terminal: A communication device such as a smartphone or tablet. Users send and receive messages through this device.

[0690] Server: A central processing unit that receives, parses, generates, and sends messages.

[0691] 2. Software Configuration

[0692] LINE app: A messaging application used by users.

[0693] Emotion Engine: Uses libraries such as TextBlob to analyze the sentiment of messages sent by users.

[0694] Generative artificial intelligence: Uses the OpenAI API and other tools to generate empathetic and encouraging messages based on analysis results.

[0695] Content recommendation system: Recommends content such as movies and music based on generated messages and sentiment information.

[0696] 3. Program Processing Overview

[0697] When a user sends a message using the LINE app, the server receives the message and performs preprocessing. This preprocessing includes removing whitespace and escaping special characters. The emotion engine then analyzes the message and recognizes the user's emotional state. For example, keywords such as "sad" and "tired" are extracted from the words and context in the message, and the emotion engine recognizes emotions such as "sadness" and "isolation."

[0698] Based on the analysis results, a generative artificial intelligence generates empathetic and encouraging messages that are appropriate to the user's emotions. For example, it might generate a message like, "I understand how you're feeling. You're not alone. I'm here to listen." At the same time, a content recommendation system suggests movies, music, and other content that are appropriate to the user's emotions.

[0699] 4. Specific Examples

[0700] Let's consider a scenario where a user sends the message "I'm feeling kind of down today" to the official LINE account. This message is received by the server and preprocessed. Then, the emotion engine analyzes the keyword "down" and recognizes "sadness" as an emotion. Based on the analysis, the generative artificial intelligence generates the message "I understand how you're feeling. You're not alone. I'm here to listen," and simultaneously recommends the movie "The Blind Side" and the song "Let It Be" by The Beatles.

[0701] Example of a prompt

[0702] "A user is feeling sad. Recommend a movie or music that can help them feel better."

[0703] By sending this prompt to the OpenAI API, appropriate content will be recommended and provided to the user.

[0704] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0705] Step 1:

[0706] A user sends a message via the LINE app. This message is sent to the server by the user's device. Specifically, the user types the message "I feel kind of depressed today" into the LINE official account and sends it. The input is text data, which is then sent to the server.

[0707] Step 2:

[0708] The server receives the message and performs preprocessing. This preprocessing includes removing whitespace and escaping special characters. Specifically, it removes unnecessary spaces and special characters from the received text data to prepare it for analysis. The input is text data, and the output is preprocessed text data.

[0709] Step 3:

[0710] The server sends pre-processed messages to the sentiment engine for sentiment analysis. Using sentiment analysis libraries such as TextBlob, the engine analyzes keywords and context within the messages to determine the user's emotional state. The input is pre-processed text data, and the output is emotional information (such as "sadness" or "isolation"). For example, the word "melancholy" might be interpreted as the emotion "sadness."

[0711] Step 4:

[0712] The server sends emotional information obtained from the emotion engine to a generative artificial intelligence system, which then generates empathetic and encouraging messages. Using the OpenAI API and other tools, it automatically generates appropriate messages based on the analysis results. The input is emotional information, and the output is the generated empathetic and encouraging message. Example prompt: "A user is feeling sadness. Provide an empathetic and encouraging message."

[0713] Step 5:

[0714] The server sends a generated message to the user's device for display. Specifically, the generated message, "I understand how you're going through. You're not alone. I'm here to listen," is sent to the user's device and displayed in the LINE app. The input is the generated message, and the output is the display on the user's device.

[0715] Step 6:

[0716] Simultaneously, the server activates a content recommendation system based on emotional information to recommend appropriate movies and music. It uses the OpenAI API to generate emotionally-based content. The input is emotional information, and the output is information about recommended content (e.g., "The Blind Side" movie or "Let It Be" music). Example prompt: "A user is feeling sadness. Recommend a movie or music that can help them feel better."

[0717] Step 7:

[0718] The server sends recommended content information to the user's terminal and displays it to the user. This allows the user to browse and listen to the recommended movies and music. The input is information about the recommended content, and the output is the display on the user's terminal and the provision of links.

[0719] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0720] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0721] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0722] [Third Embodiment]

[0723] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0724] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0725] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0726] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0727] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0728] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0729] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0730] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0731] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0732] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0733] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0734] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0735] This invention relates to a system that provides empathetic and encouraging messages to users with suicidal thoughts via LINE's official account. This system is realized by receiving messages sent by users in real time, generating appropriate replies using generative artificial intelligence, and sending them back to the user.

[0736] System Configuration

[0737] 1. User terminal

[0738] A user's device is a communication terminal such as a smartphone or tablet on which the LINE app is installed. Users send and receive messages through this device.

[0739] 2. Server

[0740] The server receives messages and requests generative artificial intelligence to analyze them and generate replies. The server also sends the generated messages to the user's terminal.

[0741] 3. Generative Artificial Intelligence

[0742] Includes a program that analyzes input messages and generates appropriate messages of empathy and encouragement.

[0743] Program Processing Overview

[0744] Message reception and preprocessing

[0745] The user's device types "I've been having a really hard time lately. I'm tired of living" and sends the message to the LINE official account.

[0746] The server receives user messages from the LINE platform and preprocesses the content appropriately. Preprocessing includes removing whitespace and escaping special characters.

[0747] Message parsing and reply generation

[0748] The server sends the pre-processed message to the generative artificial intelligence.

[0749] A generative artificial intelligence analyzes the received message and extracts keywords (e.g., spicy, tired).

[0750] Based on keywords extracted by the generative artificial intelligence, it generates a message of empathy and encouragement such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0751] Send a reply

[0752] The server receives the generated response message and sends it back to the user's terminal.

[0753] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0754] Specific example

[0755] Let's consider a scenario where a user sends a message to the official LINE account saying, "I've been having a really hard time lately. I'm tired of living." This message is received by the server and pre-processed. Then, a generative artificial intelligence extracts the keywords "hard" and "tired." Based on these keywords, the generative AI creates a message of empathy and encouragement and returns it to the server. The server sends this message to the user's device, and the user receives support in real time.

[0756] In this way, the system of the present invention can provide rapid and accurate support to users who have suicidal thoughts.

[0757] The following describes the processing flow.

[0758] Step 1:

[0759] A user uses the LINE app to type and send the message "I've been having a really hard time lately. I'm tired of living" to the official account.

[0760] Step 2:

[0761] The server receives the user's sent message from the LINE platform.

[0762] Step 3:

[0763] Messages received by the server are saved to a database for logging purposes.

[0764] Step 4:

[0765] The server begins message preprocessing. Preprocessing includes the following actions:

[0766] Removal of unnecessary whitespace

[0767] Special character escaping

[0768] Message content normalization

[0769] Step 5:

[0770] The server extracts important keywords from the pre-processed messages. For example, keywords such as "painful" and "tired" might be extracted.

[0771] Step 6:

[0772] The server sends a request to the generative artificial intelligence API. The request includes the message content after preprocessing and keyword extraction.

[0773] Step 7:

[0774] The generative artificial intelligence receives the request and analyzes the message content and extracted keywords.

[0775] Step 8:

[0776] The generative artificial intelligence generates appropriate empathetic and encouraging messages based on the analysis results. For example, it might generate a message like, "I understand how you're going through. You're not alone. I'm here to listen."

[0777] Step 9:

[0778] The generative artificial intelligence returns the generated message to the server.

[0779] Step 10:

[0780] The server logs the generated messages and saves them to the database.

[0781] Step 11:

[0782] The server generates a message and sends it to the user via the LINE platform.

[0783] Step 12:

[0784] The user receives a message via the LINE app that says, "I understand how you're going through. You're not alone. I'm here to listen."

[0785] The above outlines the specific processing steps of this system.

[0786] (Example 1)

[0787] Next, we will describe Example 1. 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."

[0788] There is a need for a means to quickly and accurately provide empathetic and encouraging messages to users who have suicidal thoughts. However, conventional systems may be slow to analyze user messages and generate appropriate replies, or may generate inappropriate messages. Therefore, an effective means is needed to alleviate the emotional burden on users and provide support quickly.

[0789] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0790] In this invention, the server includes means for receiving a message sent by a user via a communication terminal, means for pre-processing the received message, means for analyzing keywords contained in the pre-processed message, means for generating an appropriate message of empathy and encouragement based on the analysis results using generative artificial intelligence, and means for sending the generated message back to the communication terminal. This makes it possible to quickly analyze messages sent by users and provide appropriate messages of empathy and encouragement in real time.

[0791] A "communication terminal" is an electronic device used by a user to send and receive messages, and includes smartphones, tablets, personal computers, and other similar devices.

[0792] A "server" is a central computer system used for receiving, pre-processing, parsing, and generating replies to messages.

[0793] A "message" refers to text information sent by a user via a communication device, and includes content that expresses the user's emotions or state of mind.

[0794] "Preprocessing" refers to data organization operations performed before analysis, such as removing whitespace from received messages and escaping special characters.

[0795] "Keywords" are important words or phrases extracted from a message, and they serve as criteria for generative artificial intelligence to generate empathetic and encouraging messages.

[0796] "Generative artificial intelligence" refers to an artificial intelligence program that analyzes an input message and automatically generates an appropriate response based on the analysis results.

[0797] A "prompt" is a text containing instructions or questions for generating a specific response from a generative artificial intelligence system.

[0798] A "log" is a data file used to record messages that have been sent and messages that have been generated.

[0799] A "message of empathy and encouragement" is a message created by a generative artificial intelligence system that appropriately empathizes with the user's emotions and state of mind and has the intention of offering encouragement.

[0800] This invention relates to a system that receives messages sent by users in real time and returns appropriate reply messages using generative artificial intelligence. In particular, it aims to provide empathetic and encouraging messages quickly and accurately to users who have suicidal thoughts.

[0801] System Configuration

[0802] Hardware and software

[0803] This system uses the following hardware and software.

[0804] 1. Communication terminal: An electronic device used by users to send and receive messages, including smartphones, tablets, and personal computers.

[0805] 2. Server: A central computer system for receiving, pre-processing, parsing, and generating replies to messages.

[0806] 3. Generative Artificial Intelligence: This is an artificial intelligence program that analyzes input messages and generates appropriate empathetic and encouraging messages.

[0807] Message reception and preprocessing

[0808] The user's device sends a message via the LINE app in response to the user's input: "I've been having a really hard time lately. I'm tired of living."

[0809] The server receives this message from the LINE platform and performs preprocessing such as removing whitespace and escaping special characters.

[0810] Message parsing and reply generation

[0811] The server sends the pre-processed message to the generative artificial intelligence. The following prompt is used: "Receive the user's message, 'I've been having a really hard time lately. I'm tired of living,' extract keywords, and generate a message of empathy and encouragement."

[0812] A generative artificial intelligence analyzes the received message and extracts keywords such as "painful" and "tired."

[0813] The generative artificial intelligence generates a message of empathy and encouragement based on the extracted keywords, such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0814] Send a reply

[0815] The server receives a response message generated by a generative artificial intelligence and sends it to the user's terminal via the LINE platform.

[0816] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0817] As a concrete example, consider a case where a user sends the message "I've been having a really hard time lately. I'm tired of living" to the official LINE account. This message is received by the server, where whitespace is removed and special characters are escaped. Then, a generative artificial intelligence extracts the keywords "hard" and "tired," and generates a message of empathy and encouragement such as: "I understand how you're feeling. You're not alone. I'm here to listen."

[0818] This invention makes it possible to quickly analyze messages sent by users and provide appropriate messages of empathy and encouragement in real time.

[0819] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0820] Step 1:

[0821] The user's device sends the message "I've been having a really hard time lately. I'm tired of living" through the LINE app in response to the user's input. Specifically, the user types the message in the chat window within the LINE app and presses the send button. The input is the user's text message, and the output is a message that reaches the server via the LINE platform.

[0822] Step 2:

[0823] The server receives user messages from the LINE platform. The received messages undergo preprocessing, such as whitespace removal and special character escaping. Specifically, a message like "It's spicy." is converted to "It's spicy." The input is the raw message sent from the user's terminal, and the output is the preprocessed message.

[0824] Step 3:

[0825] The server sends a pre-processed message to a generative artificial intelligence. The following prompt is used: "Receive the message 'I've been having a really hard time lately. I'm tired of living' sent by the user, extract keywords, and generate a message of empathy and encouragement." The input is the pre-processed message and the prompt, and the output is the data sent to the generative artificial intelligence.

[0826] Step 4:

[0827] A generative artificial intelligence analyzes pre-processed messages received from a server. During the analysis, it extracts keywords such as "painful" and "tired." The input consists of the pre-processed message and prompt text, while the output is the keywords resulting from the analysis. Specifically, natural language processing techniques are used to analyze the message content, performing sentiment analysis and keyword extraction.

[0828] Step 5:

[0829] The generative artificial intelligence generates empathetic and encouraging messages based on the extracted keywords. Specifically, it generates a message such as, "I understand how you're going through. You're not alone. I'm here to listen." The input is the keywords extracted in step 4, and the output is the generated empathetic and encouraging message.

[0830] Step 6:

[0831] The server receives messages generated by a generative artificial intelligence and sends them to the user's terminal via the LINE platform. Specifically, the server receives the generated message and forwards it to the user's terminal via the LINE platform. The input is the generated message, and the output is the message sent to the user's terminal.

[0832] Step 7:

[0833] The user's device receives empathy and encouragement messages sent from the server via the LINE app. The user then views the messages displayed in the chat window within the LINE app. Specifically, when the user taps a notification in the LINE app, the chat window automatically opens and displays the reply message. The input is the message sent from the server, and the output is the message displayed within the LINE app.

[0834] This allows for the rapid analysis of messages sent by users, providing appropriate messages of empathy and encouragement in real time.

[0835] (Application Example 1)

[0836] Next, we will explain Application Example 1. In the following explanation, 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."

[0837] While systems exist to quickly provide empathetic and encouraging messages to users with suicidal thoughts, only a limited number of systems can respond to urgent situations. Furthermore, current systems often fail to recognize emergencies, making it difficult to provide appropriate support immediately. This means that users in dangerous situations may not receive adequate and timely support.

[0838] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0839] In this invention, the server includes means for receiving messages sent by a user via a communication terminal, means for analyzing keywords contained in the received messages, generative artificial intelligence means for generating appropriate empathetic and encouraging messages based on the analysis results, means for examining messages to determine their urgency, means for sending notifications to registered contacts if the means for determining urgency determines that the message is urgent, and means for sending the generated message back to the communication terminal. This makes it possible to respond quickly to emergencies and provide users with immediate and appropriate support.

[0840] A "communication terminal" is a device used by users to send and receive messages, and includes smartphones, tablets, and personal computers.

[0841] A "keyword" is a specific word or phrase contained within a received message, and it is an important element for analyzing the content of the message.

[0842] "Generative artificial intelligence" is a general term for programs and systems that analyze input messages and generate appropriate responses.

[0843] "Means for determining urgency" refers to a function or algorithm that analyzes the content of a received message and determines whether or not that message is an emergency.

[0844] "Means of sending notifications" refers to a function that sends alerts and notifications to pre-configured contacts when an emergency is determined.

[0845] "Preprocessing" is the process of cleaning and filtering text to make it easier to analyze the content of received messages.

[0846] A "log" is a record used to store and manage sent messages and generated responses.

[0847] This invention relates to a system that processes messages sent by users via a communication terminal quickly and appropriately, and provides immediate notification in emergencies. Based on the claims, embodiments for carrying out this invention are described below.

[0848] System Configuration

[0849] 1. User terminal

[0850] Users send messages using communication devices (smartphones, tablets, PCs, etc.). Messages are sent via communication platforms such as the LINE app.

[0851] 2. Server

[0852] The server receives messages sent from user terminals, analyzes them using generative artificial intelligence (AI models), and generates appropriate replies. The server also plays a role in determining urgency and sending notifications.

[0853] 3. Generative Artificial Intelligence

[0854] The generative artificial intelligence analyzes messages received from users and extracts keywords. It includes a program that generates empathetic and encouraging messages based on the extracted keywords. Furthermore, in emergency situations, it generates appropriate response messages and sends them back to the server.

[0855] Program Processing Overview

[0856] Processing received messages

[0857] A user sends a message via a communication device saying, "I've been having a really hard time lately. I'm tired of living." The server receives this message and performs preprocessing. Preprocessing includes removing whitespace and handling special characters.

[0858] Message parsing and reply generation

[0859] The server sends the pre-processed message to the generative artificial intelligence. The generative AI analyzes the message and extracts keywords (e.g., "painful," "tired"). Based on the extracted keywords, it generates an empathetic and encouraging message such as, "I understand how you're feeling. You're not alone. I'm here to listen."

[0860] Assessment and notification of urgency

[0861] Furthermore, the generative artificial intelligence examines the message for urgent keywords (e.g., "help," "now") to determine its urgency. If it determines it is urgent, the server sends a notification to pre-configured emergency contacts.

[0862] Send message

[0863] The server sends the generated reply message to the user's terminal. The user's terminal receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0864] Hardware and software to be used

[0865] Communication devices: Smartphones, tablets, personal computers

[0866] Communication platform: LINE app, etc.

[0867] Server: Cloud server (AWS, Google Cloud, etc.)

[0868] Generative artificial intelligence: AI models such as GPT-3

[0869] Log management system: Database (MySQL, PostgreSQL, etc.)

[0870] Specific example

[0871] A user sends a message from their communication device saying, "I've been having a really hard time lately. I'm tired of living." This message is received by the server and pre-processed. Then, an AI model extracts keywords such as "hard" and "tired." Based on these keywords, the AI ​​model generates an empathetic and encouraging message, such as "I understand how you're feeling. You're not alone. I'm here to listen," and sends it back to the server. The server sends this message to the user's device, and the user receives support in real time. In addition, if urgent keywords such as "help" or "right now" are detected, a notification is sent to the registered emergency contact.

[0872] Example of a prompt

[0873] "I've been having a really hard time lately. I'm tired of living."

[0874] "Help me, I need someone to listen to me right now."

[0875] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0876] Step 1:

[0877] The user sends a message via a communication device. The user uses a communication platform such as the LINE app to type a message like, "I've been having a really hard time lately. I'm tired of living," and presses the send button. The input data is a text message.

[0878] Step 2:

[0879] The server receives messages sent from the user's terminal. The input data is a text message sent by the user. The server retrieves the message through the communication platform's API. Specifically, this is achieved by using the LINE platform's API and listening for message events. The output data is a text message that requires preprocessing.

[0880] Step 3:

[0881] The server preprocesses the received message. Preprocessing includes removing whitespace, escaping special characters, and standardizing the message text. The input data is the received text message, and the output data is the preprocessed text message.

[0882] Step 4:

[0883] The server sends a pre-processed message to a generative artificial intelligence (AI). The input data is a pre-processed text message. The server calls the AI's API and sends a request for message analysis and reply generation. The output data is the analysis result and the generated response message returned by the AI.

[0884] Step 5:

[0885] Generative artificial intelligence analyzes received messages and extracts keywords. The input data is a pre-processed text message sent from a server. As part of the data processing, natural language processing techniques are used to tokenize the message and extract keywords. The output data consists of the extracted keywords and a response message generated based on those keywords.

[0886] Step 6:

[0887] Generative artificial intelligence generates appropriate empathetic and encouraging messages based on extracted keywords. The input data consists of extracted keywords. A generative AI model (e.g., GPT-3) is used to generate response messages based on prompts. The output data consists of the generated empathetic and encouraging messages.

[0888] Step 7:

[0889] Generative artificial intelligence examines messages for urgent keywords and determines their urgency. The input data is the entire message. As a data calculation, it scans the message to check if it contains urgent keywords (e.g., "help", "now"). The output data is an urgency flag (whether it is urgent or not).

[0890] Step 8:

[0891] The server receives the response message and the urgency assessment result from the generative artificial intelligence. The input data consists of the generated response message and the urgency assessment result. Based on this information, the server continues the necessary processing. Specifically, it prepares to send the response message to the user terminal and, if it is an emergency, prepares to send a notification to the emergency contact. The output data consists of the message to be sent and the emergency notification.

[0892] Step 9:

[0893] The server sends the generated response message to the user's terminal. The input data is the response message received from the generative artificial intelligence. The server uses the communication platform's API to send the message to the user. The output data is the response message sent to the user's terminal.

[0894] Step 10:

[0895] If the server determines that an emergency is occurring, it will send a notification to the registered emergency contact. The input data includes an urgency flag and emergency contact information. Specifically, notifications will be sent to the registered email address or phone number. The output data is the contact information to which the emergency notification was sent.

[0896] Processing at each step enables quick and appropriate responses to user messages and, when necessary, emergency notifications.

[0897] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0898] This invention relates to a system that uses an emotion engine to recognize the emotions of users with suicidal thoughts via LINE's official account and quickly provides them with empathetic and encouraging messages. This system is realized by receiving messages sent by users in real time, analyzing the user's emotions using the emotion engine, generating an appropriate reply using generative artificial intelligence, and sending it back to the user.

[0899] System Configuration

[0900] 1. User terminal

[0901] A user's device is a communication terminal such as a smartphone or tablet on which the LINE app is installed. Users send and receive messages through this device.

[0902] 2. Server

[0903] The server receives messages and requests the emotion engine and generative artificial intelligence to analyze the messages and generate replies. The server also has the function of sending the generated messages to the user's terminal.

[0904] 3. Emotional Engine

[0905] Includes a program that analyzes input messages and recognizes the user's emotional state (e.g., sadness, loneliness, anxiety).

[0906] 4. Generative Artificial Intelligence

[0907] This includes a program that generates empathetic and encouraging messages tailored to the user's psychological state, based on emotional information provided by an emotion engine.

[0908] Program Processing Overview

[0909] Message reception and preprocessing

[0910] The user's device types "I've been having a really hard time lately. I'm tired of living" and sends the message to the LINE official account.

[0911] The server receives user messages from the LINE platform and preprocesses the content appropriately. Preprocessing includes removing whitespace and escaping special characters.

[0912] Emotional analysis

[0913] The server sends the pre-processed message to the emotion engine.

[0914] The emotion engine analyzes the received message to recognize the user's emotional state. For example, keywords such as "sad" or "tired" are extracted from the words and context in the message, and based on these, emotions such as "sadness" or "isolation" are recognized.

[0915] Reply generation and sending

[0916] The server transmits the emotional information obtained by the emotion engine to the generative artificial intelligence.

[0917] Generative artificial intelligence uses the user's emotional information to generate empathetic and encouraging messages such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0918] The server sends the generated response message back to the user's terminal.

[0919] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[0920] Specific example

[0921] Let's consider a scenario where a user sends a message to the official LINE account saying, "I've been feeling really down lately. I'm tired of living." This message is received by the server and pre-processed. Then, the emotion engine analyzes the keywords "down" and "tired" and recognizes emotions such as "sadness" and "isolation." Based on the emotional information recognized by the emotion engine, a generative artificial intelligence generates a message saying, "I understand how you're feeling. You're not alone. I'm here to listen." The server sends this message to the user's device, and the user receives support in real time.

[0922] In this way, the system of the present invention can more accurately recognize the user's emotional state by combining it with an emotion engine, and provide appropriate support based on that recognition.

[0923] The following describes the processing flow.

[0924] Step 1:

[0925] A user uses the LINE app to type and send the message "I've been having a really hard time lately. I'm tired of living" to the official account.

[0926] Step 2:

[0927] The server receives the user's sent message from the LINE platform.

[0928] Step 3:

[0929] Messages received by the server are saved to a database for logging purposes.

[0930] Step 4:

[0931] The server begins message preprocessing. Preprocessing includes the following actions:

[0932] Removal of unnecessary whitespace

[0933] Special character escaping

[0934] Message content normalization

[0935] Step 5:

[0936] The server sends the pre-processed message to the emotion engine.

[0937] Step 6:

[0938] The emotion engine analyzes the received message and recognizes the user's emotional state. For example, it extracts keywords such as "sad" and "tired" from the words and context in the message, and uses that to recognize emotions such as "sadness" and "isolation."

[0939] Step 7:

[0940] The emotion engine returns the recognized emotion information to the server as an analysis result.

[0941] Step 8:

[0942] The server transmits emotional information obtained from the emotion engine to the generative artificial intelligence.

[0943] Step 9:

[0944] Generative artificial intelligence uses the user's emotional information to generate empathetic and encouraging messages such as, "I understand how you're going through. You're not alone. I'm here to listen."

[0945] Step 10:

[0946] The generative artificial intelligence returns the generated message to the server.

[0947] Step 11:

[0948] The server logs the generated messages and saves them to the database.

[0949] Step 12:

[0950] The server generates a message and sends it to the user via the LINE platform.

[0951] Step 13:

[0952] The user receives a message via the LINE app that says, "I understand how you're going through. You're not alone. I'm here to listen."

[0953] (Example 2)

[0954] Next, we will describe Example 2. 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."

[0955] There is a need to provide prompt and appropriate empathy and encouragement to users who are in an emotionally unstable state. In particular, accurately recognizing the emotions in messages sent by users and generating appropriate responses based on that is difficult. Furthermore, some systems suffer from problems with the accuracy of emotion analysis due to insufficient preprocessing. Therefore, a system is needed that can accurately recognize the emotions of users and provide appropriate response messages.

[0956] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0957] In this invention, the server includes means for receiving a message sent by a user via an information processing device, means for preprocessing the received message, means for analyzing keywords contained in the preprocessed message and recognizing emotions, generative artificial intelligence means for generating appropriate empathy and encouragement messages based on the analyzed emotion information, and means for sending the generated message back to the information processing device. This makes it possible to accurately recognize the user's emotions and quickly provide an appropriate response message.

[0958] An "information processing device" is a communication device, such as a smartphone or tablet, used by users to send and receive messages.

[0959] "Means of receiving" refers to the function that allows the server to retrieve messages sent by the user.

[0960] "Pre-processing means" refers to functions that remove whitespace and escape special characters from received messages.

[0961] "A means of analyzing keywords and recognizing emotions" refers to a function that analyzes the words and context of pre-processed messages and extracts the user's emotional state.

[0962] A "generative artificial intelligence means" is a program that generates empathetic and encouraging messages that match the user's psychological state based on emotional information.

[0963] The "means of replying" refer to the function of sending the generated response message back to the user's information processing device.

[0964] A "natural language processing algorithm" is an algorithm used to analyze text data and is a technology used to understand emotions and meaning.

[0965] A "recording medium" is a data storage system for saving transmitted and generated messages.

[0966] This invention is a system that integrates an information processing device, a server, an emotion engine, and a generative artificial intelligence to perform emotion analysis in response to messages sent by users, generate appropriate empathetic and encouraging messages, and send them back. A specific example of this system is described in detail below.

[0967] First, the user uses an information processing device such as a smartphone or tablet to type a message and send it through the LINE app. For example, a message like "I've been having a really hard time lately. I'm tired of living" might be entered.

[0968] Next, this message is received by the server. The server retrieves the message from the LINE platform and preprocesses the received message. Preprocessing includes removing whitespace and escaping special characters.

[0969] The pre-processed message is then sent from the server to the emotion engine. The emotion engine analyzes the keywords and context contained in the message to recognize the user's emotional state. For example, keywords such as "painful" and "tired" may be interpreted as emotions such as "sadness" or "isolation."

[0970] Next, the recognized emotion information is sent to a generative artificial intelligence (AI) via a server. The AI ​​generates an appropriate reply message based on the provided emotion information. For example, a message such as, "I understand how you're feeling. You're not alone. I'm here to listen," might be generated.

[0971] Finally, the generated message is sent again by the server to the user's information processing device. The information processing device displays the received message on the LINE app's chat screen, allowing the user to receive messages of empathy and encouragement in real time.

[0972] Specific example

[0973] Consider a scenario where a user sends a message to a LINE official account saying, "I've been feeling really down lately. I'm tired of living." This message is received by the server and preprocessed. An emotion engine analyzes the keywords "down" and "tired," recognizing emotions such as "sadness" and "isolation." Based on this emotional information, a generative artificial intelligence generates an empathetic and encouraging message: "I understand how you're feeling. You're not alone. I'm here to listen." The server then sends this message to the user's device, which the user receives.

[0974] As a result, the system of the present invention can accurately recognize the user's emotional state and provide a quick and appropriate response.

[0975] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0976] Step 1:

[0977] Message sending from user terminal

[0978] The user uses the LINE app to type the message, "I've been having a really hard time lately. I'm tired of living," and presses the send button.

[0979] Input: Text message entered by the user

[0980] Output: Sending a message to the LINE server

[0981] Specific actions: The user opens the LINE app's chat screen, types a message using the keyboard, and taps the send button.

[0982] Step 2:

[0983] Message reception and preprocessing by the server

[0984] The server receives user messages from the LINE platform. The received messages are pre-processed. Pre-processing includes removing whitespace and escaping special characters.

[0985] Input: Raw message data received from the LINE server

[0986] Output: Pre-processed, clean message data

[0987] Specific operation: The server retrieves messages using the LINE API and removes unnecessary whitespace and special characters using string manipulation functions.

[0988] Step 3:

[0989] Sending messages from the server to the emotion engine

[0990] The server sends the pre-processed message to the emotion engine.

[0991] Input: Pre-processed, clean message data

[0992] Output: Sending a message to the emotion engine

[0993] Specific operation: The server sends an HTTP request to the emotion engine's API endpoint, passing the pre-processed message.

[0994] Step 4:

[0995] Emotional analysis using an emotion engine

[0996] The emotion engine analyzes received messages and recognizes the user's emotional state. For example, it can recognize emotions such as "sadness" or "isolation" from keywords like "painful" or "tired."

[0997] Input: Clean message data

[0998] Output: Emotional information such as "sadness" and "isolation."

[0999] Specific operation: The emotion engine uses a natural language processing algorithm to extract keywords and assign emotion labels.

[1000] Step 5:

[1001] Emotional information transmission from the server to the generative artificial intelligence.

[1002] The server transmits the emotional information obtained by the emotion engine to the generative artificial intelligence.

[1003] Input: Emotional information obtained from the emotion engine.

[1004] Output: Sending emotional information to a generative artificial intelligence system.

[1005] Specific operation: The server sends an HTTP request to the generative artificial intelligence API endpoint, passing emotion information.

[1006] Step 6:

[1007] Generative AI-powered reply message generation

[1008] Generative artificial intelligence generates appropriate reply messages based on the emotional information provided. For example, it might generate a message like, "I understand how you're going through. You're not alone. I'm here to listen."

[1009] Input: Emotional information

[1010] Output: Generated reply message

[1011] Specific operation: The generative artificial intelligence executes an algorithm that generates text containing emotional information based on the prompt.

[1012] Step 7:

[1013] Server sends reply message to user terminal

[1014] The server then resends the generated response message to the user's LINE account.

[1015] Input: Generated reply message

[1016] Output: Sending a message to the user's LINE account

[1017] Specific operation: The server uses the LINE API to send the generated message to the user's LINE account.

[1018] Step 8:

[1019] Receiving reply messages from the user's terminal

[1020] The user's information processing device receives the reply message and displays it on the LINE app's chat screen. The user receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[1021] Input: Reply message sent from the server

[1022] Output: Message displayed on the LINE app chat screen

[1023] Specific operation: The user's device uses the LINE API to retrieve messages and displays them on the chat screen.

[1024] (Application Example 2)

[1025] Next, we will explain application example 2. In the following explanation, 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."

[1026] In modern society, systems that provide responses tailored to a user's emotional state are crucial. In particular, there is a need for psychological support, such as providing appropriate empathy and encouragement to emotionally unstable users. However, current systems struggle to accurately analyze user emotions and generate appropriate messages, resulting in insufficient individual adaptation. Furthermore, the lack of content recommendation features (such as movies and music) based on emotional states makes it difficult to improve user satisfaction.

[1027] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1028] In this invention, the server includes means for receiving a message sent by a user via a communication terminal, means for analyzing keywords contained in the received message, means for generating appropriate empathetic and encouraging messages based on the analysis results, means for sending the generated message back to the communication terminal, means for analyzing a message about emotions entered by the user and recommending content (such as movies or music) that is appropriate for that emotion, and means for sending the recommended content to the communication terminal. This enables personalized messages and content recommendations that correspond to the user's emotional state.

[1029] "Means for receiving messages sent by users via communication terminals" refers to a function that allows a server to receive text messages sent by users through devices such as smartphones and tablets.

[1030] "Means for analyzing keywords contained in the received message" refers to a function that examines the content of the received message, extracts important words and phrases, and understands their meaning and sentiment.

[1031] "Generative artificial intelligence means for generating appropriate empathetic and encouraging messages based on analysis results" refers to an artificial intelligence system that automatically creates empathetic and encouraging messages tailored to the user's psychological state based on analyzed keywords and context.

[1032] "Means for sending the generated message back to the communication terminal" refers to a function for sending and displaying a message created by a generative artificial intelligence system on a device used by the user.

[1033] "A means of analyzing emotional messages entered by users and recommending content (such as movies or music) that is appropriate for those emotions" refers to a function that analyzes the emotional expressions contained in the user's message and suggests entertainment content such as movies and music based on that analysis.

[1034] "Means for transmitting the recommended content to a communication terminal" refers to a function that transmits suggested content information, such as movies and music, to the user's device so that it can be displayed and played.

[1035] The system based on this invention aims to generate empathetic and encouraging messages according to the user's emotional state, and further recommend content (such as movies and music) that is appropriate to the user's emotions. This system consists of the following main hardware and software components.

[1036] 1. Hardware Configuration

[1037] User terminal: A communication device such as a smartphone or tablet. Users send and receive messages through this device.

[1038] Server: A central processing unit that receives, parses, generates, and sends messages.

[1039] 2. Software Configuration

[1040] LINE app: A messaging application used by users.

[1041] Emotion Engine: Uses libraries such as TextBlob to analyze the sentiment of messages sent by users.

[1042] Generative artificial intelligence: Uses the OpenAI API and other tools to generate empathetic and encouraging messages based on analysis results.

[1043] Content recommendation system: Recommends content such as movies and music based on generated messages and sentiment information.

[1044] 3. Program Processing Overview

[1045] When a user sends a message using the LINE app, the server receives the message and performs preprocessing. This preprocessing includes removing whitespace and escaping special characters. The emotion engine then analyzes the message and recognizes the user's emotional state. For example, keywords such as "sad" and "tired" are extracted from the words and context in the message, and the emotion engine recognizes emotions such as "sadness" and "isolation."

[1046] Based on the analysis results, a generative artificial intelligence generates empathetic and encouraging messages that are appropriate to the user's emotions. For example, it might generate a message like, "I understand how you're feeling. You're not alone. I'm here to listen." At the same time, a content recommendation system suggests movies, music, and other content that are appropriate to the user's emotions.

[1047] 4. Specific Examples

[1048] Let's consider a scenario where a user sends the message "I'm feeling kind of down today" to the official LINE account. This message is received by the server and preprocessed. Then, the emotion engine analyzes the keyword "down" and recognizes "sadness" as an emotion. Based on the analysis, the generative artificial intelligence generates the message "I understand how you're feeling. You're not alone. I'm here to listen," and simultaneously recommends the movie "The Blind Side" and the song "Let It Be" by The Beatles.

[1049] Example of a prompt

[1050] "A user is feeling sad. Recommend a movie or music that can help them feel better."

[1051] By sending this prompt to the OpenAI API, appropriate content will be recommended and provided to the user.

[1052] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1053] Step 1:

[1054] A user sends a message via the LINE app. This message is sent to the server by the user's device. Specifically, the user types the message "I feel kind of depressed today" into the LINE official account and sends it. The input is text data, which is then sent to the server.

[1055] Step 2:

[1056] The server receives the message and performs preprocessing. This preprocessing includes removing whitespace and escaping special characters. Specifically, it removes unnecessary spaces and special characters from the received text data to prepare it for analysis. The input is text data, and the output is preprocessed text data.

[1057] Step 3:

[1058] The server sends pre-processed messages to the sentiment engine for sentiment analysis. Using sentiment analysis libraries such as TextBlob, the engine analyzes keywords and context within the messages to determine the user's emotional state. The input is pre-processed text data, and the output is emotional information (such as "sadness" or "isolation"). For example, the word "melancholy" might be interpreted as the emotion "sadness."

[1059] Step 4:

[1060] The server sends emotional information obtained from the emotion engine to a generative artificial intelligence system, which then generates empathetic and encouraging messages. Using the OpenAI API and other tools, it automatically generates appropriate messages based on the analysis results. The input is emotional information, and the output is the generated empathetic and encouraging message. Example prompt: "A user is feeling sadness. Provide an empathetic and encouraging message."

[1061] Step 5:

[1062] The server sends a generated message to the user's device for display. Specifically, the generated message, "I understand how you're going through. You're not alone. I'm here to listen," is sent to the user's device and displayed in the LINE app. The input is the generated message, and the output is the display on the user's device.

[1063] Step 6:

[1064] Simultaneously, the server activates a content recommendation system based on emotional information to recommend appropriate movies and music. It uses the OpenAI API to generate emotionally-based content. The input is emotional information, and the output is information about recommended content (e.g., "The Blind Side" movie or "Let It Be" music). Example prompt: "A user is feeling sadness. Recommend a movie or music that can help them feel better."

[1065] Step 7:

[1066] The server sends recommended content information to the user's terminal and displays it to the user. This allows the user to browse and listen to the recommended movies and music. The input is information about the recommended content, and the output is the display on the user's terminal and the provision of links.

[1067] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1068] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1069] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1070] [Fourth Embodiment]

[1071] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1072] As shown in Figure 7, the 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.

[1073] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1074] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1075] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1076] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1077] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1078] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1079] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1080] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1081] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1082] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1083] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1084] This invention relates to a system that provides empathetic and encouraging messages to users with suicidal thoughts via LINE's official account. This system is realized by receiving messages sent by users in real time, generating appropriate replies using generative artificial intelligence, and sending them back to the user.

[1085] System Configuration

[1086] 1. User terminal

[1087] A user's device is a communication terminal such as a smartphone or tablet on which the LINE app is installed. Users send and receive messages through this device.

[1088] 2. Server

[1089] The server receives messages and requests generative artificial intelligence to analyze them and generate replies. The server also sends the generated messages to the user's terminal.

[1090] 3. Generative Artificial Intelligence

[1091] Includes a program that analyzes input messages and generates appropriate messages of empathy and encouragement.

[1092] Program Processing Overview

[1093] Message reception and preprocessing

[1094] The user's device types "I've been having a really hard time lately. I'm tired of living" and sends the message to the LINE official account.

[1095] The server receives user messages from the LINE platform and preprocesses the content appropriately. Preprocessing includes removing whitespace and escaping special characters.

[1096] Message parsing and reply generation

[1097] The server sends the pre-processed message to the generative artificial intelligence.

[1098] A generative artificial intelligence analyzes the received message and extracts keywords (e.g., spicy, tired).

[1099] Based on keywords extracted by the generative artificial intelligence, it generates a message of empathy and encouragement such as, "I understand how you're going through. You're not alone. I'm here to listen."

[1100] Send a reply

[1101] The server receives the generated response message and sends it back to the user's terminal.

[1102] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[1103] Specific example

[1104] Let's consider a scenario where a user sends a message to the official LINE account saying, "I've been having a really hard time lately. I'm tired of living." This message is received by the server and pre-processed. Then, a generative artificial intelligence extracts the keywords "hard" and "tired." Based on these keywords, the generative AI creates a message of empathy and encouragement and returns it to the server. The server sends this message to the user's device, and the user receives support in real time.

[1105] In this way, the system of the present invention can provide rapid and accurate support to users who have suicidal thoughts.

[1106] The following describes the processing flow.

[1107] Step 1:

[1108] A user uses the LINE app to type and send the message "I've been having a really hard time lately. I'm tired of living" to the official account.

[1109] Step 2:

[1110] The server receives the user's sent message from the LINE platform.

[1111] Step 3:

[1112] Messages received by the server are saved to a database for logging purposes.

[1113] Step 4:

[1114] The server begins message preprocessing. Preprocessing includes the following actions:

[1115] Removal of unnecessary whitespace

[1116] Special character escaping

[1117] Message content normalization

[1118] Step 5:

[1119] The server extracts important keywords from the pre-processed messages. For example, keywords such as "painful" and "tired" might be extracted.

[1120] Step 6:

[1121] The server sends a request to the generative artificial intelligence API. The request includes the message content after preprocessing and keyword extraction.

[1122] Step 7:

[1123] The generative artificial intelligence receives the request and analyzes the message content and extracted keywords.

[1124] Step 8:

[1125] The generative artificial intelligence generates appropriate empathetic and encouraging messages based on the analysis results. For example, it might generate a message like, "I understand how you're going through. You're not alone. I'm here to listen."

[1126] Step 9:

[1127] The generative artificial intelligence returns the generated message to the server.

[1128] Step 10:

[1129] The server logs the generated messages and saves them to the database.

[1130] Step 11:

[1131] The server generates a message and sends it to the user via the LINE platform.

[1132] Step 12:

[1133] The user receives a message via the LINE app that says, "I understand how you're going through. You're not alone. I'm here to listen."

[1134] The above outlines the specific processing steps of this system.

[1135] (Example 1)

[1136] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1137] There is a need for a means to quickly and accurately provide empathetic and encouraging messages to users who have suicidal thoughts. However, conventional systems may be slow to analyze user messages and generate appropriate replies, or may generate inappropriate messages. Therefore, an effective means is needed to alleviate the emotional burden on users and provide support quickly.

[1138] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1139] In this invention, the server includes means for receiving a message sent by a user via a communication terminal, means for pre-processing the received message, means for analyzing keywords contained in the pre-processed message, means for generating an appropriate message of empathy and encouragement based on the analysis results using generative artificial intelligence, and means for sending the generated message back to the communication terminal. This makes it possible to quickly analyze messages sent by users and provide appropriate messages of empathy and encouragement in real time.

[1140] A "communication terminal" is an electronic device used by a user to send and receive messages, and includes smartphones, tablets, personal computers, and other similar devices.

[1141] A "server" is a central computer system used for receiving, pre-processing, parsing, and generating replies to messages.

[1142] A "message" refers to text information sent by a user via a communication device, and includes content that expresses the user's emotions or state of mind.

[1143] "Preprocessing" refers to data organization operations performed before analysis, such as removing whitespace from received messages and escaping special characters.

[1144] "Keywords" are important words or phrases extracted from a message, and they serve as criteria for generative artificial intelligence to generate empathetic and encouraging messages.

[1145] "Generative artificial intelligence" refers to an artificial intelligence program that analyzes an input message and automatically generates an appropriate response based on the analysis results.

[1146] A "prompt" is a text containing instructions or questions for generating a specific response from a generative artificial intelligence system.

[1147] A "log" is a data file used to record messages that have been sent and messages that have been generated.

[1148] A "message of empathy and encouragement" is a message created by a generative artificial intelligence system that appropriately empathizes with the user's emotions and state of mind and has the intention of offering encouragement.

[1149] This invention relates to a system that receives messages sent by users in real time and returns appropriate reply messages using generative artificial intelligence. In particular, it aims to provide empathetic and encouraging messages quickly and accurately to users who have suicidal thoughts.

[1150] System Configuration

[1151] Hardware and software

[1152] This system uses the following hardware and software.

[1153] 1. Communication terminal: An electronic device used by users to send and receive messages, including smartphones, tablets, and personal computers.

[1154] 2. Server: A central computer system for receiving, pre-processing, parsing, and generating replies to messages.

[1155] 3. Generative Artificial Intelligence: This is an artificial intelligence program that analyzes input messages and generates appropriate empathetic and encouraging messages.

[1156] Message reception and preprocessing

[1157] The user's device sends a message via the LINE app in response to the user's input: "I've been having a really hard time lately. I'm tired of living."

[1158] The server receives this message from the LINE platform and performs preprocessing such as removing whitespace and escaping special characters.

[1159] Message parsing and reply generation

[1160] The server sends the pre-processed message to the generative artificial intelligence. The following prompt is used: "Receive the user's message, 'I've been having a really hard time lately. I'm tired of living,' extract keywords, and generate a message of empathy and encouragement."

[1161] A generative artificial intelligence analyzes the received message and extracts keywords such as "painful" and "tired."

[1162] The generative artificial intelligence generates a message of empathy and encouragement based on the extracted keywords, such as, "I understand how you're going through. You're not alone. I'm here to listen."

[1163] Send a reply

[1164] The server receives a response message generated by a generative artificial intelligence and sends it to the user's terminal via the LINE platform.

[1165] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[1166] As a concrete example, consider a case where a user sends the message "I've been having a really hard time lately. I'm tired of living" to the official LINE account. This message is received by the server, where whitespace is removed and special characters are escaped. Then, a generative artificial intelligence extracts the keywords "hard" and "tired," and generates a message of empathy and encouragement such as: "I understand how you're feeling. You're not alone. I'm here to listen."

[1167] This invention makes it possible to quickly analyze messages sent by users and provide appropriate messages of empathy and encouragement in real time.

[1168] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1169] Step 1:

[1170] The user's device sends the message "I've been having a really hard time lately. I'm tired of living" through the LINE app in response to the user's input. Specifically, the user types the message in the chat window within the LINE app and presses the send button. The input is the user's text message, and the output is a message that reaches the server via the LINE platform.

[1171] Step 2:

[1172] The server receives user messages from the LINE platform. The received messages undergo preprocessing, such as whitespace removal and special character escaping. Specifically, a message like "It's spicy." is converted to "It's spicy." The input is the raw message sent from the user's terminal, and the output is the preprocessed message.

[1173] Step 3:

[1174] The server sends a pre-processed message to a generative artificial intelligence. The following prompt is used: "Receive the message 'I've been having a really hard time lately. I'm tired of living' sent by the user, extract keywords, and generate a message of empathy and encouragement." The input is the pre-processed message and the prompt, and the output is the data sent to the generative artificial intelligence.

[1175] Step 4:

[1176] A generative artificial intelligence analyzes pre-processed messages received from a server. During the analysis, it extracts keywords such as "painful" and "tired." The input consists of the pre-processed message and prompt text, while the output is the keywords resulting from the analysis. Specifically, natural language processing techniques are used to analyze the message content, performing sentiment analysis and keyword extraction.

[1177] Step 5:

[1178] The generative artificial intelligence generates empathetic and encouraging messages based on the extracted keywords. Specifically, it generates a message such as, "I understand how you're going through. You're not alone. I'm here to listen." The input is the keywords extracted in step 4, and the output is the generated empathetic and encouraging message.

[1179] Step 6:

[1180] The server receives messages generated by a generative artificial intelligence and sends them to the user's terminal via the LINE platform. Specifically, the server receives the generated message and forwards it to the user's terminal via the LINE platform. The input is the generated message, and the output is the message sent to the user's terminal.

[1181] Step 7:

[1182] The user's device receives empathy and encouragement messages sent from the server via the LINE app. The user then views the messages displayed in the chat window within the LINE app. Specifically, when the user taps a notification in the LINE app, the chat window automatically opens and displays the reply message. The input is the message sent from the server, and the output is the message displayed within the LINE app.

[1183] This allows for the rapid analysis of messages sent by users, providing appropriate messages of empathy and encouragement in real time.

[1184] (Application Example 1)

[1185] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1186] While systems exist to quickly provide empathetic and encouraging messages to users with suicidal thoughts, only a limited number of systems can respond to urgent situations. Furthermore, current systems often fail to recognize emergencies, making it difficult to provide appropriate support immediately. This means that users in dangerous situations may not receive adequate and timely support.

[1187] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1188] In this invention, the server includes means for receiving messages sent by a user via a communication terminal, means for analyzing keywords contained in the received messages, generative artificial intelligence means for generating appropriate empathetic and encouraging messages based on the analysis results, means for examining messages to determine their urgency, means for sending notifications to registered contacts if the means for determining urgency determines that the message is urgent, and means for sending the generated message back to the communication terminal. This makes it possible to respond quickly to emergencies and provide users with immediate and appropriate support.

[1189] A "communication terminal" is a device used by users to send and receive messages, and includes smartphones, tablets, and personal computers.

[1190] A "keyword" is a specific word or phrase contained within a received message, and it is an important element for analyzing the content of the message.

[1191] "Generative artificial intelligence" is a general term for programs and systems that analyze input messages and generate appropriate responses.

[1192] "Means for determining urgency" refers to a function or algorithm that analyzes the content of a received message and determines whether or not that message is an emergency.

[1193] "Means of sending notifications" refers to a function that sends alerts and notifications to pre-configured contacts when an emergency is determined.

[1194] "Preprocessing" is the process of cleaning and filtering text to make it easier to analyze the content of received messages.

[1195] A "log" is a record used to store and manage sent messages and generated responses.

[1196] This invention relates to a system that processes messages sent by users via a communication terminal quickly and appropriately, and provides immediate notification in emergencies. Based on the claims, embodiments for carrying out this invention are described below.

[1197] System Configuration

[1198] 1. User terminal

[1199] Users send messages using communication devices (smartphones, tablets, PCs, etc.). Messages are sent via communication platforms such as the LINE app.

[1200] 2. Server

[1201] The server receives messages sent from user terminals, analyzes them using generative artificial intelligence (AI models), and generates appropriate replies. The server also plays a role in determining urgency and sending notifications.

[1202] 3. Generative Artificial Intelligence

[1203] The generative artificial intelligence analyzes messages received from users and extracts keywords. It includes a program that generates empathetic and encouraging messages based on the extracted keywords. Furthermore, in emergency situations, it generates appropriate response messages and sends them back to the server.

[1204] Program Processing Overview

[1205] Processing received messages

[1206] A user sends a message via a communication device saying, "I've been having a really hard time lately. I'm tired of living." The server receives this message and performs preprocessing. Preprocessing includes removing whitespace and handling special characters.

[1207] Message parsing and reply generation

[1208] The server sends the pre-processed message to the generative artificial intelligence. The generative AI analyzes the message and extracts keywords (e.g., "painful," "tired"). Based on the extracted keywords, it generates an empathetic and encouraging message such as, "I understand how you're feeling. You're not alone. I'm here to listen."

[1209] Assessment and notification of urgency

[1210] Furthermore, the generative artificial intelligence examines the message for urgent keywords (e.g., "help," "now") to determine its urgency. If it determines it is urgent, the server sends a notification to pre-configured emergency contacts.

[1211] Send message

[1212] The server sends the generated reply message to the user's terminal. The user's terminal receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[1213] Hardware and software to be used

[1214] Communication devices: Smartphones, tablets, personal computers

[1215] Communication platform: LINE app, etc.

[1216] Server: Cloud server (AWS, Google Cloud, etc.)

[1217] Generative artificial intelligence: AI models such as GPT-3

[1218] Log management system: Database (MySQL, PostgreSQL, etc.)

[1219] Specific example

[1220] A user sends a message from their communication device saying, "I've been having a really hard time lately. I'm tired of living." This message is received by the server and pre-processed. Then, an AI model extracts keywords such as "hard" and "tired." Based on these keywords, the AI ​​model generates an empathetic and encouraging message, such as "I understand how you're feeling. You're not alone. I'm here to listen," and sends it back to the server. The server sends this message to the user's device, and the user receives support in real time. In addition, if urgent keywords such as "help" or "right now" are detected, a notification is sent to the registered emergency contact.

[1221] Example of a prompt

[1222] "I've been having a really hard time lately. I'm tired of living."

[1223] "Help me, I need someone to listen to me right now."

[1224] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1225] Step 1:

[1226] The user sends a message via a communication device. The user uses a communication platform such as the LINE app to type a message like, "I've been having a really hard time lately. I'm tired of living," and presses the send button. The input data is a text message.

[1227] Step 2:

[1228] The server receives messages sent from the user's terminal. The input data is a text message sent by the user. The server retrieves the message through the communication platform's API. Specifically, this is achieved by using the LINE platform's API and listening for message events. The output data is a text message that requires preprocessing.

[1229] Step 3:

[1230] The server preprocesses the received message. Preprocessing includes removing whitespace, escaping special characters, and standardizing the message text. The input data is the received text message, and the output data is the preprocessed text message.

[1231] Step 4:

[1232] The server sends a pre-processed message to a generative artificial intelligence (AI). The input data is a pre-processed text message. The server calls the AI's API and sends a request for message analysis and reply generation. The output data is the analysis result and the generated response message returned by the AI.

[1233] Step 5:

[1234] Generative artificial intelligence analyzes received messages and extracts keywords. The input data is a pre-processed text message sent from a server. As part of the data processing, natural language processing techniques are used to tokenize the message and extract keywords. The output data consists of the extracted keywords and a response message generated based on those keywords.

[1235] Step 6:

[1236] Generative artificial intelligence generates appropriate empathetic and encouraging messages based on extracted keywords. The input data consists of extracted keywords. A generative AI model (e.g., GPT-3) is used to generate response messages based on prompts. The output data consists of the generated empathetic and encouraging messages.

[1237] Step 7:

[1238] Generative artificial intelligence examines messages for urgent keywords and determines their urgency. The input data is the entire message. As a data calculation, it scans the message to check if it contains urgent keywords (e.g., "help", "now"). The output data is an urgency flag (whether it is urgent or not).

[1239] Step 8:

[1240] The server receives the response message and the urgency assessment result from the generative artificial intelligence. The input data consists of the generated response message and the urgency assessment result. Based on this information, the server continues the necessary processing. Specifically, it prepares to send the response message to the user terminal and, if it is an emergency, prepares to send a notification to the emergency contact. The output data consists of the message to be sent and the emergency notification.

[1241] Step 9:

[1242] The server sends the generated response message to the user's terminal. The input data is the response message received from the generative artificial intelligence. The server uses the communication platform's API to send the message to the user. The output data is the response message sent to the user's terminal.

[1243] Step 10:

[1244] If the server determines that an emergency is occurring, it will send a notification to the registered emergency contact. The input data includes an urgency flag and emergency contact information. Specifically, notifications will be sent to the registered email address or phone number. The output data is the contact information to which the emergency notification was sent.

[1245] Processing at each step enables quick and appropriate responses to user messages and, when necessary, emergency notifications.

[1246] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1247] This invention relates to a system that uses an emotion engine to recognize the emotions of users with suicidal thoughts via LINE's official account and quickly provides them with empathetic and encouraging messages. This system is realized by receiving messages sent by users in real time, analyzing the user's emotions using the emotion engine, generating an appropriate reply using generative artificial intelligence, and sending it back to the user.

[1248] System Configuration

[1249] 1. User terminal

[1250] A user's device is a communication terminal such as a smartphone or tablet on which the LINE app is installed. Users send and receive messages through this device.

[1251] 2. Server

[1252] The server receives messages and requests the emotion engine and generative artificial intelligence to analyze the messages and generate replies. The server also has the function of sending the generated messages to the user's terminal.

[1253] 3. Emotional Engine

[1254] Includes a program that analyzes input messages and recognizes the user's emotional state (e.g., sadness, loneliness, anxiety).

[1255] 4. Generative Artificial Intelligence

[1256] This includes a program that generates empathetic and encouraging messages tailored to the user's psychological state, based on emotional information provided by an emotion engine.

[1257] Program Processing Overview

[1258] Message reception and preprocessing

[1259] The user's device types "I've been having a really hard time lately. I'm tired of living" and sends the message to the LINE official account.

[1260] The server receives user messages from the LINE platform and preprocesses the content appropriately. Preprocessing includes removing whitespace and escaping special characters.

[1261] Emotional analysis

[1262] The server sends the pre-processed message to the emotion engine.

[1263] The emotion engine analyzes the received message to recognize the user's emotional state. For example, keywords such as "sad" or "tired" are extracted from the words and context in the message, and based on these, emotions such as "sadness" or "isolation" are recognized.

[1264] Reply generation and sending

[1265] The server transmits the emotional information obtained by the emotion engine to the generative artificial intelligence.

[1266] Generative artificial intelligence uses the user's emotional information to generate empathetic and encouraging messages such as, "I understand how you're going through. You're not alone. I'm here to listen."

[1267] The server sends the generated response message back to the user's terminal.

[1268] The user's device receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[1269] Specific example

[1270] Let's consider a scenario where a user sends a message to the official LINE account saying, "I've been feeling really down lately. I'm tired of living." This message is received by the server and pre-processed. Then, the emotion engine analyzes the keywords "down" and "tired" and recognizes emotions such as "sadness" and "isolation." Based on the emotional information recognized by the emotion engine, a generative artificial intelligence generates a message saying, "I understand how you're feeling. You're not alone. I'm here to listen." The server sends this message to the user's device, and the user receives support in real time.

[1271] In this way, the system of the present invention can more accurately recognize the user's emotional state by combining it with an emotion engine, and provide appropriate support based on that recognition.

[1272] The following describes the processing flow.

[1273] Step 1:

[1274] A user uses the LINE app to type and send the message "I've been having a really hard time lately. I'm tired of living" to the official account.

[1275] Step 2:

[1276] The server receives the user's sent message from the LINE platform.

[1277] Step 3:

[1278] Messages received by the server are saved to a database for logging purposes.

[1279] Step 4:

[1280] The server begins message preprocessing. Preprocessing includes the following actions:

[1281] Removal of unnecessary whitespace

[1282] Special character escaping

[1283] Message content normalization

[1284] Step 5:

[1285] The server sends the pre-processed message to the emotion engine.

[1286] Step 6:

[1287] The emotion engine analyzes the received message and recognizes the user's emotional state. For example, it extracts keywords such as "sad" and "tired" from the words and context in the message, and uses that to recognize emotions such as "sadness" and "isolation."

[1288] Step 7:

[1289] The emotion engine returns the recognized emotion information to the server as an analysis result.

[1290] Step 8:

[1291] The server transmits emotional information obtained from the emotion engine to the generative artificial intelligence.

[1292] Step 9:

[1293] Generative artificial intelligence uses the user's emotional information to generate empathetic and encouraging messages such as, "I understand how you're going through. You're not alone. I'm here to listen."

[1294] Step 10:

[1295] The generative artificial intelligence returns the generated message to the server.

[1296] Step 11:

[1297] The server logs the generated messages and saves them to the database.

[1298] Step 12:

[1299] The server generates a message and sends it to the user via the LINE platform.

[1300] Step 13:

[1301] The user receives a message via the LINE app that says, "I understand how you're going through. You're not alone. I'm here to listen."

[1302] (Example 2)

[1303] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1304] There is a need to provide prompt and appropriate empathy and encouragement to users who are in an emotionally unstable state. In particular, accurately recognizing the emotions in messages sent by users and generating appropriate responses based on that is difficult. Furthermore, some systems suffer from problems with the accuracy of emotion analysis due to insufficient preprocessing. Therefore, a system is needed that can accurately recognize the emotions of users and provide appropriate response messages.

[1305] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1306] In this invention, the server includes means for receiving a message sent by a user via an information processing device, means for preprocessing the received message, means for analyzing keywords contained in the preprocessed message and recognizing emotions, generative artificial intelligence means for generating appropriate empathy and encouragement messages based on the analyzed emotion information, and means for sending the generated message back to the information processing device. This makes it possible to accurately recognize the user's emotions and quickly provide an appropriate response message.

[1307] An "information processing device" is a communication device, such as a smartphone or tablet, used by users to send and receive messages.

[1308] "Means of receiving" refers to the function that allows the server to retrieve messages sent by the user.

[1309] "Pre-processing means" refers to functions that remove whitespace and escape special characters from received messages.

[1310] "A means of analyzing keywords and recognizing emotions" refers to a function that analyzes the words and context of pre-processed messages and extracts the user's emotional state.

[1311] A "generative artificial intelligence means" is a program that generates empathetic and encouraging messages that match the user's psychological state based on emotional information.

[1312] The "means of replying" refer to the function of sending the generated response message back to the user's information processing device.

[1313] A "natural language processing algorithm" is an algorithm used to analyze text data and is a technology used to understand emotions and meaning.

[1314] A "recording medium" is a data storage system for saving transmitted and generated messages.

[1315] This invention is a system that integrates an information processing device, a server, an emotion engine, and a generative artificial intelligence to perform emotion analysis in response to messages sent by users, generate appropriate empathetic and encouraging messages, and send them back. A specific example of this system is described in detail below.

[1316] First, the user uses an information processing device such as a smartphone or tablet to type a message and send it through the LINE app. For example, a message like "I've been having a really hard time lately. I'm tired of living" might be entered.

[1317] Next, this message is received by the server. The server retrieves the message from the LINE platform and preprocesses the received message. Preprocessing includes removing whitespace and escaping special characters.

[1318] The pre-processed message is then sent from the server to the emotion engine. The emotion engine analyzes the keywords and context contained in the message to recognize the user's emotional state. For example, keywords such as "painful" and "tired" may be interpreted as emotions such as "sadness" or "isolation."

[1319] Next, the recognized emotion information is sent to a generative artificial intelligence (AI) via a server. The AI ​​generates an appropriate reply message based on the provided emotion information. For example, a message such as, "I understand how you're feeling. You're not alone. I'm here to listen," might be generated.

[1320] Finally, the generated message is sent again by the server to the user's information processing device. The information processing device displays the received message on the LINE app's chat screen, allowing the user to receive messages of empathy and encouragement in real time.

[1321] Specific example

[1322] Consider a scenario where a user sends a message to a LINE official account saying, "I've been feeling really down lately. I'm tired of living." This message is received by the server and preprocessed. An emotion engine analyzes the keywords "down" and "tired," recognizing emotions such as "sadness" and "isolation." Based on this emotional information, a generative artificial intelligence generates an empathetic and encouraging message: "I understand how you're feeling. You're not alone. I'm here to listen." The server then sends this message to the user's device, which the user receives.

[1323] As a result, the system of the present invention can accurately recognize the user's emotional state and provide a quick and appropriate response.

[1324] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1325] Step 1:

[1326] Message sending from user terminal

[1327] The user uses the LINE app to type the message, "I've been having a really hard time lately. I'm tired of living," and presses the send button.

[1328] Input: Text message entered by the user

[1329] Output: Sending a message to the LINE server

[1330] Specific actions: The user opens the LINE app's chat screen, types a message using the keyboard, and taps the send button.

[1331] Step 2:

[1332] Message reception and preprocessing by the server

[1333] The server receives user messages from the LINE platform. The received messages are pre-processed. Pre-processing includes removing whitespace and escaping special characters.

[1334] Input: Raw message data received from the LINE server

[1335] Output: Pre-processed, clean message data

[1336] Specific operation: The server retrieves messages using the LINE API and removes unnecessary whitespace and special characters using string manipulation functions.

[1337] Step 3:

[1338] Sending messages from the server to the emotion engine

[1339] The server sends the pre-processed message to the emotion engine.

[1340] Input: Pre-processed, clean message data

[1341] Output: Sending a message to the emotion engine

[1342] Specific operation: The server sends an HTTP request to the emotion engine's API endpoint, passing the pre-processed message.

[1343] Step 4:

[1344] Emotional analysis using an emotion engine

[1345] The emotion engine analyzes received messages and recognizes the user's emotional state. For example, it can recognize emotions such as "sadness" or "isolation" from keywords like "painful" or "tired."

[1346] Input: Clean message data

[1347] Output: Emotional information such as "sadness" and "isolation."

[1348] Specific operation: The emotion engine uses a natural language processing algorithm to extract keywords and assign emotion labels.

[1349] Step 5:

[1350] Emotional information transmission from the server to the generative artificial intelligence.

[1351] The server transmits the emotional information obtained by the emotion engine to the generative artificial intelligence.

[1352] Input: Emotional information obtained from the emotion engine.

[1353] Output: Sending emotional information to a generative artificial intelligence system.

[1354] Specific operation: The server sends an HTTP request to the generative artificial intelligence API endpoint, passing emotion information.

[1355] Step 6:

[1356] Generative AI-powered reply message generation

[1357] Generative artificial intelligence generates appropriate reply messages based on the emotional information provided. For example, it might generate a message like, "I understand how you're going through. You're not alone. I'm here to listen."

[1358] Input: Emotional information

[1359] Output: Generated reply message

[1360] Specific operation: The generative artificial intelligence executes an algorithm that generates text containing emotional information based on the prompt.

[1361] Step 7:

[1362] Server sends reply message to user terminal

[1363] The server then resends the generated response message to the user's LINE account.

[1364] Input: Generated reply message

[1365] Output: Sending a message to the user's LINE account

[1366] Specific operation: The server uses the LINE API to send the generated message to the user's LINE account.

[1367] Step 8:

[1368] Receiving reply messages from the user's terminal

[1369] The user's information processing device receives the reply message and displays it on the LINE app's chat screen. The user receives the message, "I understand how you're going through. You're not alone. I'm here to listen."

[1370] Input: Reply message sent from the server

[1371] Output: Message displayed on the LINE app chat screen

[1372] Specific operation: The user's device uses the LINE API to retrieve messages and displays them on the chat screen.

[1373] (Application Example 2)

[1374] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1375] In modern society, systems that provide responses tailored to a user's emotional state are crucial. In particular, there is a need for psychological support, such as providing appropriate empathy and encouragement to emotionally unstable users. However, current systems struggle to accurately analyze user emotions and generate appropriate messages, resulting in insufficient individual adaptation. Furthermore, the lack of content recommendation features (such as movies and music) based on emotional states makes it difficult to improve user satisfaction.

[1376] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1377] In this invention, the server includes means for receiving a message sent by a user via a communication terminal, means for analyzing keywords contained in the received message, means for generating appropriate empathetic and encouraging messages based on the analysis results, means for sending the generated message back to the communication terminal, means for analyzing a message about emotions entered by the user and recommending content (such as movies or music) that is appropriate for that emotion, and means for sending the recommended content to the communication terminal. This enables personalized messages and content recommendations that correspond to the user's emotional state.

[1378] "Means for receiving messages sent by users via communication terminals" refers to a function that allows a server to receive text messages sent by users through devices such as smartphones and tablets.

[1379] "Means for analyzing keywords contained in the received message" refers to a function that examines the content of the received message, extracts important words and phrases, and understands their meaning and sentiment.

[1380] "Generative artificial intelligence means for generating appropriate empathetic and encouraging messages based on analysis results" refers to an artificial intelligence system that automatically creates empathetic and encouraging messages tailored to the user's psychological state based on analyzed keywords and context.

[1381] "Means for sending the generated message back to the communication terminal" refers to a function for sending and displaying a message created by a generative artificial intelligence system on a device used by the user.

[1382] "A means of analyzing emotional messages entered by users and recommending content (such as movies or music) that is appropriate for those emotions" refers to a function that analyzes the emotional expressions contained in the user's message and suggests entertainment content such as movies and music based on that analysis.

[1383] "Means for transmitting the recommended content to a communication terminal" refers to a function that transmits suggested content information, such as movies and music, to the user's device so that it can be displayed and played.

[1384] The system based on this invention aims to generate empathetic and encouraging messages according to the user's emotional state, and further recommend content (such as movies and music) that is appropriate to the user's emotions. This system consists of the following main hardware and software components.

[1385] 1. Hardware Configuration

[1386] User terminal: A communication device such as a smartphone or tablet. Users send and receive messages through this device.

[1387] Server: A central processing unit that receives, parses, generates, and sends messages.

[1388] 2. Software Configuration

[1389] LINE app: A messaging application used by users.

[1390] Emotion Engine: Uses libraries such as TextBlob to analyze the sentiment of messages sent by users.

[1391] Generative artificial intelligence: Uses the OpenAI API and other tools to generate empathetic and encouraging messages based on analysis results.

[1392] Content recommendation system: Recommends content such as movies and music based on generated messages and sentiment information.

[1393] 3. Program Processing Overview

[1394] When a user sends a message using the LINE app, the server receives the message and performs preprocessing. This preprocessing includes removing whitespace and escaping special characters. The emotion engine then analyzes the message and recognizes the user's emotional state. For example, keywords such as "sad" and "tired" are extracted from the words and context in the message, and the emotion engine recognizes emotions such as "sadness" and "isolation."

[1395] Based on the analysis results, a generative artificial intelligence generates empathetic and encouraging messages that are appropriate to the user's emotions. For example, it might generate a message like, "I understand how you're feeling. You're not alone. I'm here to listen." At the same time, a content recommendation system suggests movies, music, and other content that are appropriate to the user's emotions.

[1396] 4. Specific Examples

[1397] Let's consider a scenario where a user sends the message "I'm feeling kind of down today" to the official LINE account. This message is received by the server and preprocessed. Then, the emotion engine analyzes the keyword "down" and recognizes "sadness" as an emotion. Based on the analysis, the generative artificial intelligence generates the message "I understand how you're feeling. You're not alone. I'm here to listen," and simultaneously recommends the movie "The Blind Side" and the song "Let It Be" by The Beatles.

[1398] Example of a prompt

[1399] "A user is feeling sad. Recommend a movie or music that can help them feel better."

[1400] By sending this prompt to the OpenAI API, appropriate content will be recommended and provided to the user.

[1401] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1402] Step 1:

[1403] A user sends a message via the LINE app. This message is sent to the server by the user's device. Specifically, the user types the message "I feel kind of depressed today" into the LINE official account and sends it. The input is text data, which is then sent to the server.

[1404] Step 2:

[1405] The server receives the message and performs preprocessing. This preprocessing includes removing whitespace and escaping special characters. Specifically, it removes unnecessary spaces and special characters from the received text data to prepare it for analysis. The input is text data, and the output is preprocessed text data.

[1406] Step 3:

[1407] The server sends pre-processed messages to the sentiment engine for sentiment analysis. Using sentiment analysis libraries such as TextBlob, the engine analyzes keywords and context within the messages to determine the user's emotional state. The input is pre-processed text data, and the output is emotional information (such as "sadness" or "isolation"). For example, the word "melancholy" might be interpreted as the emotion "sadness."

[1408] Step 4:

[1409] The server sends emotional information obtained from the emotion engine to a generative artificial intelligence system, which then generates empathetic and encouraging messages. Using the OpenAI API and other tools, it automatically generates appropriate messages based on the analysis results. The input is emotional information, and the output is the generated empathetic and encouraging message. Example prompt: "A user is feeling sadness. Provide an empathetic and encouraging message."

[1410] Step 5:

[1411] The server sends a generated message to the user's device for display. Specifically, the generated message, "I understand how you're going through. You're not alone. I'm here to listen," is sent to the user's device and displayed in the LINE app. The input is the generated message, and the output is the display on the user's device.

[1412] Step 6:

[1413] Simultaneously, the server activates a content recommendation system based on emotional information to recommend appropriate movies and music. It uses the OpenAI API to generate emotionally-based content. The input is emotional information, and the output is information about recommended content (e.g., "The Blind Side" movie or "Let It Be" music). Example prompt: "A user is feeling sadness. Recommend a movie or music that can help them feel better."

[1414] Step 7:

[1415] The server sends recommended content information to the user's terminal and displays it to the user. This allows the user to browse and listen to the recommended movies and music. The input is information about the recommended content, and the output is the display on the user's terminal and the provision of links.

[1416] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1417] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1418] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1419] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1420] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1421] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1422] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1423] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1424] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1425] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1426] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1427] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1428] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1429] 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.

[1430] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1431] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1432] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1433] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1434] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1435] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1436] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1437] The following is further disclosed regarding the embodiments described above.

[1438] (Claim 1)

[1439] A means of receiving a message sent by a user via a communication terminal,

[1440] A means for analyzing keywords contained in the received message,

[1441] A generative artificial intelligence system that generates appropriate empathetic and encouraging messages based on analysis results,

[1442] A means for sending the generated message back to the communication terminal,

[1443] A system that includes this.

[1444] (Claim 2)

[1445] The system according to claim 1, further comprising means for preprocessing the message.

[1446] (Claim 3)

[1447] The system according to claim 1, further comprising means for recording the transmitted message and the generated message as a log.

[1448] "Example 1"

[1449] (Claim 1)

[1450] A means of receiving a message sent by a user via a communication terminal,

[1451] means for preprocessing the received message,

[1452] means for analyzing keywords contained in the preprocessed message,

[1453] A means for generating appropriate empathetic and encouraging messages based on the analysis results using generative artificial intelligence,

[1454] A means for sending the generated message back to the communication terminal,

[1455] A system that includes this.

[1456] (Claim 2)

[1457] The system according to claim 1, further comprising means for sending a prompt sentence to the generative artificial intelligence.

[1458] (Claim 3)

[1459] The system according to claim 1, further comprising means for recording the transmitted message and the generated message as a log.

[1460] "Application Example 1"

[1461] (Claim 1)

[1462] A means of receiving a message sent by a user via a communication terminal,

[1463] A means for analyzing keywords contained in the received message,

[1464] A generative artificial intelligence system that generates appropriate empathetic and encouraging messages based on analysis results,

[1465] A means of inspecting messages to determine urgency,

[1466] If the means for determining urgency determines that the situation is urgent, a means for sending a notification to the registered contact person,

[1467] A means for sending the generated message back to the communication terminal,

[1468] A system that includes this.

[1469] (Claim 2)

[1470] The system according to claim 1, further comprising means for preprocessing the message.

[1471] (Claim 3)

[1472] The system according to claim 1, further comprising means for recording the transmitted message and the generated message as a log.

[1473] "Example 2 of combining an emotion engine"

[1474] (Claim 1)

[1475] A means for receiving a message sent by a user via an information processing device,

[1476] means for preprocessing the received message,

[1477] A means for analyzing keywords contained in the pre-processed message and recognizing emotions,

[1478] A generative artificial intelligence means that generates appropriate empathetic and encouraging messages based on analyzed emotional information,

[1479] Means for sending the generated message back to the information processing device,

[1480] A system that includes this.

[1481] (Claim 2)

[1482] The system according to claim 1, further comprising means for storing the transmitted message and the generated message on a recording medium.

[1483] (Claim 3)

[1484] The system according to claim 1, further comprising means for using a natural language processing algorithm in emotion recognition.

[1485] "Application example 2 when combining with an emotional engine"

[1486] (Claim 1)

[1487] A means of receiving a message sent by a user via a communication terminal,

[1488] A means for analyzing keywords contained in the received message,

[1489] A generative artificial intelligence system that generates appropriate empathetic and encouraging messages based on analysis results,

[1490] A means for sending the generated message back to the communication terminal,

[1491] A method for analyzing emotional messages entered by users and recommending content (such as movies or music) that is appropriate for those emotions,

[1492] A means for transmitting the recommended content to a communication terminal,

[1493] A system that includes this.

[1494] (Claim 2)

[1495] The system according to claim 1, further comprising means for preprocessing the message.

[1496] (Claim 3)

[1497] The system according to claim 1, further comprising means for recording the transmitted message and the generated message as a log. [Explanation of symbols]

[1498] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving a message sent by a user via a communication terminal, A means for analyzing keywords contained in the received message, A generative artificial intelligence system that generates appropriate empathetic and encouraging messages based on analysis results, A means for sending the generated message back to the communication terminal, A system that includes this.

2. The system according to claim 1, further comprising means for preprocessing the message.

3. The system according to claim 1, further comprising means for recording the transmitted message and the generated message as a log.

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