System

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving an input message from a user; means for generating a positive empathetic response to the input message; and means for providing the response to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Please state the "problem that the invention aims to solve" and the "means for solving the problem."

[0005] In modern society, many people suffer from loneliness and mental stress. It is extremely important to provide appropriate communication and psychological support to people who feel this way, but there is a lack of effective means to achieve this. A new system is needed to solve this problem. [Means for solving the problem]

[0006] This invention provides a system that receives a message input by a user, generates a positive and empathetic response to the input message, and provides the response to the user. Specifically, the system includes a means for transmitting a message input by the user about loneliness or worries to a server via the Internet, and for the server to generate a positive response using a natural language processing model and provide the response to the user, thereby providing the user with a sense of psychological security.

[0007] A "user" is an individual who utilizes the system to enter messages and receive responses.

[0008] An "input message" is information in text format that a user sends to the system.

[0009] The "receiving means" is an element having a function of acquiring a message input by a user.

[0010] A "means for generating" is an element that has the function of generating a response based on an input message.

[0011] A "positive and empathetic response" is text that is sympathetic to the user's emotions and situation and provides a positive message.

[0012] The "means for providing" is an element that has the function of transmitting the generated response to the user.

[0013] A "system" is a set of components that work in combination with these means.

[0014] A "natural language processing model" is an artificial intelligence algorithm for understanding and generating text data.

[0015] The "Internet" is a communications network that interconnects multiple computer networks.

[0016] A "server" is a computer system that performs central data processing and provides services to other computers. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This invention aims to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, the system operates in a series of steps: it receives the user's input message, generates a response using a natural language processing model, and provides that response to the user.

[0039] First, the user enters their feelings or concerns into the device as a text message. For example, they might type, "I've been feeling really lonely lately." The device then sends this message to a server. The server then analyzes the message and generates a positive, empathetic response using a natural language processing model. This model is often implemented using OpenAI's APIs.

[0040] Based on the user's input message, the server generates a response such as: "The loneliness you feel is really painful, but you are not alone. We are here and you can talk anytime." The generated response is then returned to the terminal in JSON format.

[0041] The device receives the response sent from the server and displays the message to the user, which affirms the user's feelings and gives the user a sense of psychological security.

[0042] For example, if a user types, "I failed at work and I don't have anyone to talk to," the system will generate a similarly empathetic response, such as, "That must have been a really painful experience. But failure is also a step toward growth. I'm rooting for you." This can help the user regain a positive attitude.

[0043] The system aims to support the user's mental health by empathizing with the loneliness and stress they are feeling and providing positive communication.

[0044] The above is an embodiment of the present invention.

[0045] The processing flow will be explained below.

[0046] Step 1:

[0047] The user inputs a message about their feelings of loneliness or worries into the device. For example, they might input, "I've been feeling very lonely lately."

[0048] Step 2:

[0049] The terminal receives the message.

[0050] Step 3:

[0051] The device sends the acquired message to the server via the Internet as a POST request. The body of the HTTP request contains the user's message.

[0052] Step 4:

[0053] The server receives a POST request from the terminal.

[0054] Step 5:

[0055] The server extracts the user's message from the request body received. For example, use request.json.get('message') to get the message "I've been feeling very lonely lately."

[0056] Step 6:

[0057] The server calls the "generate_positive_response" function, passing the user's message as an argument.

[0058] Step 7:

[0059] The server generates a positive and empathetic response to the user's message using OpenAI's API in the "generate_positive_response" function. For example, it sends an API request like this: "User said: I've been feeling really lonely lately\nRespond with empathy and positivity:"

[0060] Step 8:

[0061] The server receives the response from the OpenAI API and extracts the generated response message from it, for example, "The loneliness you feel is really painful. But you're not alone. We're here, so we're always available to talk."

[0062] Step 9:

[0063] The server extracts the response message and formats it into JSON. Example: {"response": "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."}

[0064] Step 10:

[0065] The server sends the formatted JSON response to the device as an HTTP response.

[0066] Step 11:

[0067] The terminal receives the response from the server.

[0068] Step 12:

[0069] The device displays the received response message to the user. For example, the user's screen may display a message such as, "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime."

[0070] The above are the specific processing steps of the program.

[0071] Example 1

[0072] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0073] In modern society, the number of people feeling lonely and stressed is increasing. However, there are limited means to respond appropriately to these feelings and provide positive and empathetic support. In particular, there is a need for a system that can respond quickly and appropriately to user messages, but current systems have issues with the quality and timing of responses.

[0074] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0075] In this invention, the server includes means for receiving a message input by a user, means for analyzing the input message and generating a prompt sentence, means for generating a positive and empathetic response by a generative AI model using the generated prompt sentence, and means for providing the response to the user, thereby enabling the provision of a prompt and high-quality response to support the user's mental health.

[0076] "User" refers to a person who utilizes the system to enter messages and receive responses.

[0077] "Message" refers to textual information entered by a user.

[0078] A "prompt sentence" refers to a text sentence created by the server to prompt the generative AI model to generate a response.

[0079] "Generative AI model" refers to an artificial intelligence model that uses natural language processing technology to generate a response to an input message.

[0080] "Response" refers to a positive, empathetic text message generated by a generative AI model and provided to a user.

[0081] A "server" refers to a computer system that is responsible for analyzing messages input by users, generating responses, and providing them.

[0082] "Internet" refers to a global computer network that connects devices and servers and allows data to be sent and received.

[0083] This invention aims to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, the system operates in a series of steps: it receives the user's input message, generates a response using a natural language processing model, and provides that response to the user.

[0084] First, we will explain the hardware and software configuration. This system mainly uses the following hardware and software.

[0085] Hardware

[0086] Device: A device used by a user, such as a smartphone or PC

[0087] Server: A computer system in a cloud server or data center

[0088] software

[0089] User interface: A text input interface implemented on a terminal.

[0090] API: Natural Language Processing model (e.g., OpenAI's API)

[0091] Network Protocol: HTTP / HTTPS communication over the Internet

[0092] Next, the operation of this system will be specifically described.

[0093] User Input

[0094] Users input their feelings and worries into the device as text messages. This input is done using a keyboard or touch screen, and the message is sent by clicking or tapping the send button. For example, a user might type, "I've been feeling very lonely lately."

[0095] Sending a message

[0096] The device converts the user's input message into JSON format and sends it to the server as an HTTP POST request. Data privacy and security are ensured by secure communication (HTTPS) over an internet connection.

[0097] Message Parsing

[0098] After receiving the message sent from the device, the server analyzes it. During the analysis process, a prompt sentence is generated and passed to the generative AI model. As a specific example, the generated prompt sentence is in the following text format:

[0099] "A user types in a message like, 'I've been feeling really lonely lately.' Please respond with empathy and affirmation."

[0100] Generating a response

[0101] The server sends the prompt to a generative AI model (e.g., OpenAI's API) to generate a response. The generated response is received as a message like this:

[0102] "The loneliness you feel is really tough, but you're not alone. We're here, and you can always talk."

[0103] Sending a Response

[0104] The server returns the generated response in JSON format to the terminal, again using a secure communication method (HTTPS).

[0105] Viewing the response

[0106] The device analyzes the response received from the server and displays it to the user in text format. For example, if the user types, "I've been feeling very lonely lately," the following response will be displayed:

[0107] "The loneliness you feel is really tough, but you're not alone. We're here, and you can always talk."

[0108] This system allows users to affirm their own emotions and gain a sense of psychological security. Furthermore, the responses provided by the system are of high quality and are delivered quickly, which contributes greatly to supporting the user's mental health.

[0109] The above is a specific embodiment for carrying out the present invention.

[0110] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0111] Step 1:

[0112] The user inputs their feelings and worries into the device as a text message. For example, the user inputs, "I've been feeling very lonely lately." The input text message is stored in the device as input information.

[0113] Step 2:

[0114] The device converts the message entered by the user into JSON format and sends it to the server via the Internet as an HTTP POST request. At this time, the specific data sent is the JSON format message shown below.

[0115] json

[0116] {

[0117] "message": "I've been feeling really lonely lately"

[0118] }

[0119] As output, this JSON formatted message is sent to the server.

[0120] Step 3:

[0121] The server receives a JSON-formatted message sent from the device, which is first decoded and the text message is extracted as input data for analysis.

[0122] Type: "I've been feeling really lonely lately."

[0123] The server analyzes the text messages and processes the data to understand the user's emotions and situation.

[0124] Step 4:

[0125] The server generates a prompt sentence to be input to the generative AI model based on the parsed text message. For example, the following prompt sentence is generated:

[0126] "A user types in a message like, 'I've been feeling really lonely lately.' Please respond with empathy and affirmation."

[0127] After the prompt sentence is generated, it becomes the input data for the generative AI model.

[0128] Step 5:

[0129] The server sends the generated prompt to a generative AI model (e.g., OpenAI's API) to generate an empathetic and positive response. The generative AI model generates an appropriate text response to the prompt.

[0130] Input: Generated prompt text

[0131] Output: An empathetic, affirmative response, such as, "I know the loneliness you feel is really tough, but you're not alone. We're here, and we're always available to talk."

[0132] Step 6:

[0133] The server converts the generated response into JSON format and sends it to the terminal as an HTTP response. Specific output data includes the following JSON format message:

[0134] json

[0135] {

[0136] "response": "The loneliness you feel is really tough. But you're not alone. We're here, and we're always available to talk."

[0137] }

[0138] Step 7:

[0139] The terminal parses the JSON formatted response message received from the server, and the parsed response message is displayed to the user as text.

[0140] Input: JSON format response message from the server

[0141] Output: Response message in text format

[0142] The above is the flow of processing of the program of this system.

[0143] (Application example 1)

[0144] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0145] In modern society, many people suffer from feelings of loneliness and stress. These mental health issues not only reduce the quality of life for individuals, but also have a negative impact on society as a whole. However, conventional systems face the challenge of being unable to provide empathetic responses in real time in physical stores. In particular, there is a need for a quick and accurate response to the loneliness and worries that users feel on the spot, but there are limited means to efficiently resolve this.

[0146] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0147] In this invention, the server

[0148] means for receiving a message input by a user;

[0149] a means for generating a positive and empathetic response to an input message;

[0150] means for providing said response to a user;

[0151] means for receiving a message input by a user using the smart glasses;

[0152] means for displaying the response in conjunction with the smart glasses;

[0153] This allows users to receive empathetic responses in real time, even in physical stores, when they feel lonely or distressed.

[0154] The "means for receiving a message input by a user" is a function that allows the terminal to receive a message input by a user about feelings of loneliness or worries.

[0155] The "means for generating a positive and empathetic response to an input message" is a function that analyzes the received message and generates a positive and empathetic response to the content that is in tune with the user's emotions.

[0156] The "means for providing the response to the user" is a function for presenting the generated response to the user in an appropriate manner.

[0157] The "means for receiving a message input by a user using smart glasses" is a function for receiving a message input by a user through smart glasses.

[0158] The "means for displaying a response in cooperation with the smart glasses" is a function for displaying the generated response on the display of the smart glasses.

[0159] A "natural language processing model" is a model that uses technology to understand, analyze, and generate human language.

[0160] A "server" is a computer system that analyzes received messages and generates and sends responses.

[0161] The "means for sending messages via the Internet" is a function for sending received user messages to a server via the Internet.

[0162] The purpose of this invention is to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, this is a series of systems that receive the user's input message, generate a response using a natural language processing model, and provide that response to the user.

[0163] System Configuration

[0164] The following hardware and software are used to implement the present invention.

[0165] Hardware

[0166] Smart glasses (e.g. Google Glass)

[0167] Robots (e.g., SoftBank Robotics' Pepper)

[0168] Server (Central Processing Unit for Response Generation)

[0169] software

[0170] Natural language processing models (e.g., OpenAI's GPT-3)

[0171] Response generation script (using Python language)

[0172] System Operation Overview

[0173] 1. Receiving user input

[0174] The user uses the smart glasses to input their feelings of loneliness and worries. For example, they can input something like, "I've been feeling a lot of stress at work lately" through the microphone in the smart glasses.

[0175] 2. Sending a Message

[0176] The smart glasses send the received message to a server over the Internet.

[0177] 3. Generating a Response

[0178] The server analyzes the received message and uses OpenAI's GPT-3 model to generate an empathetic response, such as a prompt like this: "User: I've been feeling a lot of stress at work lately. Please generate an empathetic response."

[0179] 4. Viewing the Response

[0180] The generated response is then presented to the user again through the smart glasses, for example, "That's really hard. It's important not to push yourself too hard and to work at your own pace."

[0181] Specific examples

[0182] Example of user input and response

[0183] 1. User input: through voice input on smart glasses

[0184] "I recently made a mistake at work and I can't tell anyone about it."

[0185] 2. Server Response: A response generated using a natural language processing model

[0186] "That must have been a really tough experience. But failure is also a step towards growth. I'm rooting for you."

[0187] Examples of prompt statements

[0188] "User: I've been feeling a lot of stress at work lately. Please generate an empathetic response."

[0189] In this way, when users feel lonely or distressed, they can use this system to receive empathetic responses in real time, which is expected to support users' mental health and improve their quality of life.

[0190] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0191] Step 1:

[0192] The user uses the smart glasses to input voice. The user inputs a message about feelings of loneliness or worries through the microphone of the smart glasses. This voice data is converted into text data inside the smart glasses. For example, if the user inputs "I've been feeling a lot of stress at work lately," the voice is obtained as text data "I've been feeling a lot of stress at work lately."

[0193] Step 2:

[0194] The device (smart glasses) sends text data to a server via the Internet. The smart glasses then use a Wi-Fi connection to send the converted text data to the server. This may include authentication information and a session ID. This process allows the server to receive the text message from the user.

[0195] Step 3:

[0196] The server analyzes the received text message and generates an appropriate prompt. The server receives text data (e.g., "I've been feeling a lot of stress at work lately") and creates a prompt based on it to generate an empathetic response. The prompt is in the format: "User: I've been feeling a lot of stress at work lately.\nPlease generate an empathetic response."

[0197] Step 4:

[0198] The server uses a generative AI model (e.g., OpenAI's GPT-3) to generate an appropriate response based on the prompt. The server inputs the generated prompt into the AI ​​model and obtains the generated response. Based on this prompt, the AI ​​model generates an empathetic response such as, "That's really hard. Don't push yourself too hard, and it's important to work at your own pace."

[0199] Step 5:

[0200] The server converts the generated response into JSON format and sends it to the smart glasses via the Internet. The server converts the received response text data into JSON format and sends it to the user's smart glasses. This process returns the response message to the user's device.

[0201] Step 6:

[0202] The smart glasses parse the received JSON response and display it appropriately to the user. The smart glasses parse the received JSON data and display an empathetic response text on the display. The user can see the response message on the smart glasses display, saying, "That's really hard. It's important not to push yourself too hard and to work at your own pace."

[0203] Through these processing steps, users can easily input their feelings of loneliness and worries using smart glasses and receive empathetic responses in real time. This system is an effective means of supporting users' mental health.

[0204] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0205] This invention aims to realize a system that allows users to input messages about their feelings of loneliness or worries and provides positive and empathetic responses to those messages. Furthermore, by combining this system with an emotion engine, it can recognize the user's emotions and provide more appropriate responses.

[0206] First, the user enters their feelings and worries into the device as a text message. For example, they might type, "I've been feeling very lonely lately." The device then sends this message to the server. The server analyzes the message received from the device and uses an emotion engine to recognize the user's emotions. This emotion engine uses a machine learning algorithm to analyze emotions, and can recognize, for example, that the user is feeling emotions such as "sad" or "anxious."

[0207] The server uses a natural language processing model to generate a positive and empathetic response based on the recognized emotional information. This model is often implemented using OpenAI's API. For example, if the emotion engine recognizes that the user is "sad," the system generates the following response: "I know the loneliness you feel is really painful. But you're not alone. We're here, and we're always available to talk." The generated response is then returned to the device in JSON format.

[0208] The device receives the response sent from the server and displays the message to the user, which gives the user a sense of psychological relief that their feelings have been recognized and dealt with appropriately.

[0209] For example, if a user inputs "I failed at work and I can't talk to anyone about it," the emotion engine will recognize the user's emotion as "depressed." Similarly, the system will generate an empathetic response, such as, "That must have been a really painful experience. But failure is also a step toward growth. I'm rooting for you." This will help the user regain a positive attitude.

[0210] The system aims to support the user's mental health by empathizing with the loneliness and stress they feel and providing appropriate communication.

[0211] The above is an embodiment of the present invention.

[0212] The processing flow will be explained below.

[0213] Step 1:

[0214] The user inputs a message about their feelings of loneliness or worries into the device. For example, they might input, "I've been feeling very lonely lately."

[0215] Step 2:

[0216] The terminal receives the message.

[0217] Step 3:

[0218] The device sends the acquired message to the server via the Internet as a POST request. The body of the HTTP request contains the user's message.

[0219] Step 4:

[0220] The server receives a POST request from the terminal.

[0221] Step 5:

[0222] The server extracts the user's message from the request body received. For example, use request.json.get('message') to get the message "I've been feeling very lonely lately."

[0223] Step 6:

[0224] The server then passes the extracted messages to an emotion engine that analyzes the user's emotions. This emotion engine uses machine learning algorithms to recognize emotions such as "feeling lonely" or "sad."

[0225] Step 7:

[0226] Based on the emotional information obtained from the emotion engine, the server calls the "generate_positive_response" function, passing the user's message and the recognized emotional information as arguments.

[0227] Step 8:

[0228] In the “generate_positive_response” function, the server uses a natural language processing model (e.g., OpenAI’s API) to generate a positive and empathetic response to the user’s message and emotions, such as “I know the loneliness you feel is really painful, but you’re not alone. We’re here, and we’re always available to talk.”

[0229] Step 9:

[0230] The server formats the generated response message into JSON format, e.g. {"response": "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."}

[0231] Step 10:

[0232] The server sends the formatted JSON response to the device as an HTTP response.

[0233] Step 11:

[0234] The terminal receives the response from the server.

[0235] Step 12:

[0236] The device displays the received response message to the user. For example, the user's screen may display a message such as, "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime."

[0237] The above are the specific processing steps of the program.

[0238] Example 2

[0239] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0240] In modern society, the number of people suffering from loneliness and anxiety is increasing, and appropriate psychological support is needed. However, conventional systems have difficulty accurately recognizing users' emotions and responding individually, which makes it difficult to effectively support users' mental health.

[0241] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving a message input by a user, a means for analyzing the received message and recognizing the user's emotion, a means for generating a positive and empathetic response using a natural language processing model based on the recognized emotion information, and a means for providing the generated response to the user. As a result, by accurately recognizing the user's emotion and providing an appropriate response corresponding to the emotion, it becomes possible to increase the user's sense of psychological security and effectively support their mental health.

[0242] "User" refers to a person who uses the system to enter messages and receive responses.

[0243] A "message" refers to text data in which a user expresses their feelings or concerns.

[0244] The "means for receiving" refers to a method or device for incorporating a message input by a user into the system.

[0245] "Means for analyzing" refers to a method or device for analyzing a received message to extract information.

[0246] "Means for recognizing emotions" refers to a method or device for identifying a user's emotions from an analyzed message.

[0247] A "natural language processing model" refers to a computational model that generates responses in natural language based on input text data.

[0248] A "positive and empathetic response" refers to a response that is in tune with the user's emotions and contains positive content.

[0249] "Means for providing" refers to a method or device for presenting the generated response to the user.

[0250] "Generative AI model" refers to a computational model for generating responses using artificial intelligence.

[0251] "Network" refers to the communications infrastructure that connects servers and terminals.

[0252] "Server" refers to a computer system used for the purpose of processing data received from a user and generating a response.

[0253] The above are definitions of the important terms included in the rewritten claims.

[0254] This invention realizes a system that allows users to input messages about their feelings of loneliness or worries and provides positive and empathetic responses to those messages. The system recognizes the user's emotions by combining an emotion engine and provides more appropriate responses.

[0255] First, the user enters their feelings and worries as a text message into the device. For example, the user might enter, "I've been feeling very lonely lately." This message is sent to the server via the device. The device sends the message as an HTTP POST request, and the server receives the data.

[0256] The server uses a text analysis API to analyze the received messages. The analyzed text data is then used by an emotion engine to recognize the user's emotions. The emotion engine uses a machine learning algorithm and natural language processing technology to detect emotions such as "sadness" or "anxiety" felt by the user.

[0257] Next, the server uses a generative AI model to generate a positive and empathetic response based on the recognized emotional information. A natural language processing model is used as this generative AI model. For example, OpenAI's API can be used. The server passes the analysis results to the generative AI model as a prompt to generate a response. An example of a specific prompt sentence is "User's emotion: sad. Please generate a response."

[0258] The generated response is sent from the server to the device in JSON format. The device receives this response and displays it to the user. For example, if the generated response is "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime," the device will display this message on the user's screen.

[0259] As a concrete example, consider the case where a user types, "I failed at work and I can't tell anyone." The device sends this message to the server, which uses an emotion engine to analyze the user's emotions. The server uses a generative AI model to generate an empathetic response, such as, "That must have been a really painful experience. But failure is also a step towards growth. I'm rooting for you." The device displays this response message, providing the user with a positive feeling.

[0260] The above is a description of the mode for carrying out the invention, and the purpose of this system is to support the mental health of the user.

[0261] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0262] Step 1:

[0263] The user inputs their feelings and worries into the terminal as a text message.

[0264] Input: A user types "I've been feeling really lonely lately" into a text field.

[0265] Action: Text is entered into the device's input form.

[0266] Output: The text message is saved to a terminal variable.

[0267] Step 2:

[0268] The terminal transmits the entered text message to the server.

[0269] Input: A text message stored in a terminal variable.

[0270] How it works: The device makes an HTTP POST request and sends data containing a message to the server.

[0271] Output: Request sent to server as POST / messages {"text": "I've been feeling really lonely lately"}.

[0272] Step 3:

[0273] The server analyzes the received message and recognizes the user's emotions.

[0274] Input: The message data received by the server.

[0275] How it works: The server calls the text analysis API to analyze the message, and uses the emotion engine to recognize the user's emotion based on the analysis results.

[0276] Output: emotion_engine.analyze("I've been feeling very lonely lately") is executed and the emotion "sad" is recognized.

[0277] Step 4:

[0278] The server generates a positive and empathetic response based on the recognized emotional information using a natural language processing model.

[0279] Input: Emotion information recognized by the emotion engine (e.g., "sad").

[0280] Behavior: The server calls the generative AI model and passes the prompt to the model to generate a response. For example, openai.Completion.create(prompt="User emotion: sad. Please generate a response") is executed.

[0281] Output: Generates the response "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."

[0282] Step 5:

[0283] The server generates a response and sends it to the device in JSON format.

[0284] Input: The generated response data.

[0285] How it works: The server creates an HTTP response and sends the response data to the device. For example, response = {"text": "The loneliness you feel is really painful. But you're not alone. We're here, and we're always available to talk."}

[0286] Output: The response data is sent to the terminal in JSON format.

[0287] Step 6:

[0288] The terminal displays the response received from the server to the user.

[0289] Input: The response data received from the server.

[0290] Operation: The device analyzes the received response and displays it on the screen. In the case of a web application, it uses JavaScript to display it as follows: document.getElementById("response").innerText = response.text;

[0291] Output: The response message is displayed on the user's screen.

[0292] The above are the specific processing steps of the program of this system.

[0293] (Application example 2)

[0294] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0295] To provide a system capable of properly analyzing emotions such as loneliness, anxiety, and fear when a user feels such emotions, and automatically providing a sympathetic and reassuring response.

[0296] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a message input by a user, means for analyzing the input message and recognizing emotions, and means for generating a positive and empathetic response based on the recognized emotions. This makes it possible to appropriately recognize the anxiety and loneliness felt by the user and automatically generate an empathetic response that provides a sense of security.

[0297] "User" means any person or entity that utilizes the System to enter messages and receive responses.

[0298] "Message" refers to textual information that a user inputs to the system.

[0299] "Sentiment analysis" refers to the process of using machine learning and data analysis techniques to recognize the emotions contained in a message based on the content of the message entered by the user.

[0300] A "natural language processing model" refers to a collection of machine learning algorithms and techniques used to understand and generate human language.

[0301] "Response" refers to a positive and empathetic message provided to the user based on the analyzed emotions.

[0302] "Server" refers to a computing device or system for receiving messages, analyzing sentiment, and generating responses.

[0303] "Internet" refers to a general term for communication technologies that connect computer networks around the world and enable the sending and receiving of information.

[0304] "System" refers to a set of processes, including receiving messages from users, analyzing emotions, and generating responses, as well as the combination of hardware and software for executing those processes.

[0305] This invention realizes a system in which a user inputs feelings such as loneliness, anxiety, and fear as a text message, and receives a sympathetic and positive response.

[0306] Program Generation

[0307] The program processing of this system will be explained in natural language below.

[0308] System processing explanation

[0309] Hardware and Software

[0310] 1. User device: A device where the user types messages, such as a smartphone or robot.

[0311] 2. Server: A server is used to receive messages, analyze sentiment, and generate responses.

[0312] 3. Sentiment Analysis Engine: An engine is used to analyze messages entered by users and recognize their emotions.

[0313] 4. Natural Language Processing Model: Uses natural language processing techniques to generate responses based on the recognized sentiment.

[0314] 5. API: We may also use external services such as OpenAI's API.

[0315] Data processing and calculation

[0316] 1. Message received:

[0317] Users input messages containing feelings such as loneliness and anxiety via their smartphone or robot.

[0318] The terminal sends this message to a server over the Internet.

[0319] 2. Emotion analysis:

[0320] The server sends the received message to the emotion analysis engine for analysis.

[0321] The emotion analysis engine returns emotion labels such as "sad," "anxiety," and "fear" as the analysis results.

[0322] 3. Response generation:

[0323] The server generates prompts (inputs) for the natural language processing model based on the sentiment analysis results and creates an appropriate response.

[0324] The responses generated will be positive and empathetic.

[0325] 4. Response provision:

[0326] The server returns the generated response in JSON format to the user's device.

[0327] The terminal displays the response to the user.

[0328] The specific hardware and software used

[0329] Hardware: smartphones, robots, servers

[0330] Software: Sentiment analysis engine, natural language processing model, OpenAI API

[0331] Specific examples

[0332] If a user types, "When I'm alone at night, I suddenly get anxious. I can't stop thinking about what I might do if something were to happen," the emotion analysis engine recognizes this as "anxiety." The system then generates an empathetic response like, "It's very natural to feel anxious at night. I understand how you feel. It would be a little reassuring to have your contact details close at hand so you can call for help if something were to happen."

[0333] Prompt Sentence Examples

[0334] User Emotion: Anxiety

[0335] User message: When I'm alone at night, I suddenly get anxious. I can't stop thinking about what might happen.

[0336] Response message:

[0337] The above is an embodiment of the present invention.

[0338] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0339] Step 1:

[0340] The user inputs a message containing feelings such as loneliness or anxiety into a device such as a smartphone or robot. The input message is sent to a server via the Internet.

[0341] Input: A message typed by the user (e.g., "When I'm alone at night, I suddenly get anxious. I can't stop thinking about what might happen if something happens.")

[0342] Output: A message is sent from the terminal to the server.

[0343] Step 2:

[0344] The server sends the received message to the sentiment analysis engine, which uses machine learning algorithms to identify the sentiment of the message.

[0345] Input: User's message sent to the server\

[0346] Data processing: Messages are fed into a sentiment analysis engine, where an algorithmic analysis is performed.

[0347] Output: Parsed emotion (e.g. "anxiety")

[0348] Step 3:

[0349] The server generates a prompt based on the sentiment analysis results and sends it to a natural language processing model, which generates a positive and empathetic response based on the user's message and the analyzed sentiment.

[0350] Input: Sentiment analysis result and original message\

[0351] Data Calculation: Generate prompts and generate responses using natural language processing models.

[0352] Output: Generated response message (e.g., "It's very natural to feel anxious in the middle of the night. I understand how you feel. It can be a little reassuring to have your contact details handy so you can call for help if something happens.")

[0353] Step 4:

[0354] The server converts the generated response message into JSON format and sends it to the user's terminal.

[0355] Input: Generated response message\

[0356] Data processing: Convert the response into JSON format and send it to the terminal.

[0357] Output: The response message sent to the user's terminal

[0358] Step 5:

[0359] The terminal receives the response message sent by the server and displays it to the user.

[0360] Input: Response message sent from the server\

[0361] Output: A response message that is displayed on the user's terminal.

[0362] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0363] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0364] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0365] [Second embodiment]

[0366] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0367] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0368] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0369] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0370] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0371] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0372] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0373] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0374] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0375] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0376] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0377] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0378] This invention aims to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, the system operates in a series of steps: it receives the user's input message, generates a response using a natural language processing model, and provides that response to the user.

[0379] First, the user enters their feelings or concerns into the device as a text message. For example, they might type, "I've been feeling really lonely lately." The device then sends this message to a server. The server then analyzes the message and generates a positive, empathetic response using a natural language processing model. This model is often implemented using OpenAI's APIs.

[0380] Based on the user's input message, the server generates a response such as: "The loneliness you feel is really painful, but you are not alone. We are here and you can talk anytime." The generated response is then returned to the terminal in JSON format.

[0381] The device receives the response sent from the server and displays the message to the user, which affirms the user's feelings and gives the user a sense of psychological security.

[0382] For example, if a user types, "I failed at work and I don't have anyone to talk to," the system will generate a similarly empathetic response, such as, "That must have been a really painful experience. But failure is also a step toward growth. I'm rooting for you." This can help the user regain a positive attitude.

[0383] The system aims to support the user's mental health by empathizing with the loneliness and stress they are feeling and providing positive communication.

[0384] The above is an embodiment of the present invention.

[0385] The processing flow will be explained below.

[0386] Step 1:

[0387] The user inputs a message about their feelings of loneliness or worries into the device. For example, they might input, "I've been feeling very lonely lately."

[0388] Step 2:

[0389] The terminal receives the message.

[0390] Step 3:

[0391] The device sends the acquired message to the server via the Internet as a POST request. The body of the HTTP request contains the user's message.

[0392] Step 4:

[0393] The server receives a POST request from the terminal.

[0394] Step 5:

[0395] The server extracts the user's message from the request body received. For example, use request.json.get('message') to get the message "I've been feeling very lonely lately."

[0396] Step 6:

[0397] The server calls the "generate_positive_response" function, passing the user's message as an argument.

[0398] Step 7:

[0399] The server generates a positive and empathetic response to the user's message using OpenAI's API in the "generate_positive_response" function. For example, it sends an API request like this: "User said: I've been feeling really lonely lately\nRespond with empathy and positivity:"

[0400] Step 8:

[0401] The server receives the response from the OpenAI API and extracts the generated response message from it, for example, "The loneliness you feel is really painful. But you're not alone. We're here, so we're always available to talk."

[0402] Step 9:

[0403] The server extracts the response message and formats it into JSON. Example: {"response": "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."}

[0404] Step 10:

[0405] The server sends the formatted JSON response to the device as an HTTP response.

[0406] Step 11:

[0407] The terminal receives the response from the server.

[0408] Step 12:

[0409] The device displays the received response message to the user. For example, the user's screen may display a message such as, "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime."

[0410] The above are the specific processing steps of the program.

[0411] Example 1

[0412] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0413] In modern society, the number of people feeling lonely and stressed is increasing. However, there are limited means to respond appropriately to these feelings and provide positive and empathetic support. In particular, there is a need for a system that can respond quickly and appropriately to user messages, but current systems have issues with the quality and timing of responses.

[0414] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0415] In this invention, the server includes means for receiving a message input by a user, means for analyzing the input message and generating a prompt sentence, means for generating a positive and empathetic response by a generative AI model using the generated prompt sentence, and means for providing the response to the user, thereby enabling the provision of a prompt and high-quality response to support the user's mental health.

[0416] "User" refers to a person who utilizes the system to enter messages and receive responses.

[0417] "Message" refers to textual information entered by a user.

[0418] A "prompt sentence" refers to a text sentence created by the server to prompt the generative AI model to generate a response.

[0419] "Generative AI model" refers to an artificial intelligence model that uses natural language processing technology to generate a response to an input message.

[0420] "Response" refers to a positive, empathetic text message generated by a generative AI model and provided to a user.

[0421] A "server" refers to a computer system that is responsible for analyzing messages input by users, generating responses, and providing them.

[0422] "Internet" refers to a global computer network that connects devices and servers and allows data to be sent and received.

[0423] This invention aims to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, the system operates in a series of steps: it receives the user's input message, generates a response using a natural language processing model, and provides that response to the user.

[0424] First, we will explain the hardware and software configuration. This system mainly uses the following hardware and software.

[0425] Hardware

[0426] Device: A device used by a user, such as a smartphone or PC

[0427] Server: A computer system in a cloud server or data center

[0428] software

[0429] User interface: A text input interface implemented on a terminal.

[0430] API: Natural Language Processing model (e.g., OpenAI's API)

[0431] Network Protocol: HTTP / HTTPS communication over the Internet

[0432] Next, the operation of this system will be specifically described.

[0433] User Input

[0434] Users input their feelings and worries into the device as text messages. This input is done using a keyboard or touch screen, and the message is sent by clicking or tapping the send button. For example, a user might type, "I've been feeling very lonely lately."

[0435] Sending a message

[0436] The device converts the user's input message into JSON format and sends it to the server as an HTTP POST request. Data privacy and security are ensured by secure communication (HTTPS) over an internet connection.

[0437] Message Parsing

[0438] After receiving the message sent from the device, the server analyzes it. During the analysis process, a prompt sentence is generated and passed to the generative AI model. As a specific example, the generated prompt sentence is in the following text format:

[0439] "A user types in a message like, 'I've been feeling really lonely lately.' Please respond with empathy and affirmation."

[0440] Generating a response

[0441] The server sends the prompt to a generative AI model (e.g., OpenAI's API) to generate a response. The generated response is received as a message like this:

[0442] "The loneliness you feel is really tough, but you're not alone. We're here, and you can always talk."

[0443] Sending a Response

[0444] The server returns the generated response in JSON format to the terminal, again using a secure communication method (HTTPS).

[0445] Viewing the response

[0446] The device analyzes the response received from the server and displays it to the user in text format. For example, if the user types, "I've been feeling very lonely lately," the following response will be displayed:

[0447] "The loneliness you feel is really tough, but you're not alone. We're here, and you can always talk."

[0448] This system allows users to affirm their own emotions and gain a sense of psychological security. Furthermore, the responses provided by the system are of high quality and are delivered quickly, which contributes greatly to supporting the user's mental health.

[0449] The above is a specific embodiment for carrying out the present invention.

[0450] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0451] Step 1:

[0452] The user inputs their feelings and worries into the device as a text message. For example, the user inputs, "I've been feeling very lonely lately." The input text message is stored in the device as input information.

[0453] Step 2:

[0454] The device converts the message entered by the user into JSON format and sends it to the server via the Internet as an HTTP POST request. At this time, the specific data sent is the JSON format message shown below.

[0455] json

[0456] {

[0457] "message": "I've been feeling really lonely lately"

[0458] }

[0459] As output, this JSON formatted message is sent to the server.

[0460] Step 3:

[0461] The server receives a JSON-formatted message sent from the device, which is first decoded and the text message is extracted as input data for analysis.

[0462] Type: "I've been feeling really lonely lately."

[0463] The server analyzes the text messages and processes the data to understand the user's emotions and situation.

[0464] Step 4:

[0465] The server generates a prompt sentence to be input to the generative AI model based on the parsed text message. For example, the following prompt sentence is generated:

[0466] "A user types in a message like, 'I've been feeling really lonely lately.' Please respond with empathy and affirmation."

[0467] After the prompt sentence is generated, it becomes the input data for the generative AI model.

[0468] Step 5:

[0469] The server sends the generated prompt to a generative AI model (e.g., OpenAI's API) to generate an empathetic and positive response. The generative AI model generates an appropriate text response to the prompt.

[0470] Input: Generated prompt text

[0471] Output: An empathetic, affirmative response, such as, "I know the loneliness you feel is really tough, but you're not alone. We're here, and we're always available to talk."

[0472] Step 6:

[0473] The server converts the generated response into JSON format and sends it to the terminal as an HTTP response. Specific output data includes the following JSON format message:

[0474] json

[0475] {

[0476] "response": "The loneliness you feel is really tough. But you're not alone. We're here, and we're always available to talk."

[0477] }

[0478] Step 7:

[0479] The terminal parses the JSON formatted response message received from the server, and the parsed response message is displayed to the user as text.

[0480] Input: JSON format response message from the server

[0481] Output: Response message in text format

[0482] The above is the flow of processing of the program of this system.

[0483] (Application example 1)

[0484] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0485] In modern society, many people suffer from feelings of loneliness and stress. These mental health issues not only reduce the quality of life for individuals, but also have a negative impact on society as a whole. However, conventional systems face the challenge of being unable to provide empathetic responses in real time in physical stores. In particular, there is a need for a quick and accurate response to the loneliness and worries that users feel on the spot, but there are limited means to efficiently resolve this.

[0486] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0487] In this invention, the server

[0488] means for receiving a message input by a user;

[0489] a means for generating a positive and empathetic response to an input message;

[0490] means for providing said response to a user;

[0491] means for receiving a message input by a user using the smart glasses;

[0492] means for displaying the response in conjunction with the smart glasses;

[0493] This allows users to receive empathetic responses in real time, even in physical stores, when they feel lonely or distressed.

[0494] The "means for receiving a message input by a user" is a function that allows the terminal to receive a message input by a user about feelings of loneliness or worries.

[0495] The "means for generating a positive and empathetic response to an input message" is a function that analyzes the received message and generates a positive and empathetic response to the content that is in tune with the user's emotions.

[0496] The "means for providing the response to the user" is a function for presenting the generated response to the user in an appropriate manner.

[0497] The "means for receiving a message input by a user using smart glasses" is a function for receiving a message input by a user through smart glasses.

[0498] The "means for displaying a response in cooperation with the smart glasses" is a function for displaying the generated response on the display of the smart glasses.

[0499] A "natural language processing model" is a model that uses technology to understand, analyze, and generate human language.

[0500] A "server" is a computer system that analyzes received messages and generates and sends responses.

[0501] The "means for sending messages via the Internet" is a function for sending received user messages to a server via the Internet.

[0502] The purpose of this invention is to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, this is a series of systems that receive the user's input message, generate a response using a natural language processing model, and provide that response to the user.

[0503] System Configuration

[0504] The following hardware and software are used to implement the present invention.

[0505] Hardware

[0506] Smart glasses (e.g. Google Glass)

[0507] Robots (e.g., SoftBank Robotics' Pepper)

[0508] Server (Central Processing Unit for Response Generation)

[0509] software

[0510] Natural language processing models (e.g., OpenAI's GPT-3)

[0511] Response generation script (using Python language)

[0512] System Operation Overview

[0513] 1. Receiving user input

[0514] The user uses the smart glasses to input their feelings of loneliness and worries. For example, they can input something like, "I've been feeling a lot of stress at work lately" through the microphone in the smart glasses.

[0515] 2. Sending a Message

[0516] The smart glasses send the received message to a server over the Internet.

[0517] 3. Generating a Response

[0518] The server analyzes the received message and uses OpenAI's GPT-3 model to generate an empathetic response, such as a prompt like this: "User: I've been feeling a lot of stress at work lately. Please generate an empathetic response."

[0519] 4. Viewing the Response

[0520] The generated response is then presented to the user again through the smart glasses, for example, "That's really hard. It's important not to push yourself too hard and to work at your own pace."

[0521] Specific examples

[0522] Example of user input and response

[0523] 1. User input: through voice input on smart glasses

[0524] "I recently made a mistake at work and I can't tell anyone about it."

[0525] 2. Server Response: A response generated using a natural language processing model

[0526] "That must have been a really tough experience. But failure is also a step towards growth. I'm rooting for you."

[0527] Examples of prompt statements

[0528] "User: I've been feeling a lot of stress at work lately. Please generate an empathetic response."

[0529] In this way, when users feel lonely or distressed, they can use this system to receive empathetic responses in real time, which is expected to support users' mental health and improve their quality of life.

[0530] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0531] Step 1:

[0532] The user uses the smart glasses to input voice. The user inputs a message about feelings of loneliness or worries through the microphone of the smart glasses. This voice data is converted into text data inside the smart glasses. For example, if the user inputs "I've been feeling a lot of stress at work lately," the voice is obtained as text data "I've been feeling a lot of stress at work lately."

[0533] Step 2:

[0534] The device (smart glasses) sends text data to a server via the Internet. The smart glasses then use a Wi-Fi connection to send the converted text data to the server. This may include authentication information and a session ID. This process allows the server to receive the text message from the user.

[0535] Step 3:

[0536] The server analyzes the received text message and generates an appropriate prompt. The server receives text data (e.g., "I've been feeling a lot of stress at work lately") and creates a prompt based on it to generate an empathetic response. The prompt is in the format: "User: I've been feeling a lot of stress at work lately.\nPlease generate an empathetic response."

[0537] Step 4:

[0538] The server uses a generative AI model (e.g., OpenAI's GPT-3) to generate an appropriate response based on the prompt. The server inputs the generated prompt into the AI ​​model and obtains the generated response. Based on this prompt, the AI ​​model generates an empathetic response such as, "That's really hard. Don't push yourself too hard, and it's important to work at your own pace."

[0539] Step 5:

[0540] The server converts the generated response into JSON format and sends it to the smart glasses via the Internet. The server converts the received response text data into JSON format and sends it to the user's smart glasses. This process returns the response message to the user's device.

[0541] Step 6:

[0542] The smart glasses parse the received JSON response and display it appropriately to the user. The smart glasses parse the received JSON data and display an empathetic response text on the display. The user can see the response message on the smart glasses display, saying, "That's really hard. It's important not to push yourself too hard and to work at your own pace."

[0543] Through these processing steps, users can easily input their feelings of loneliness and worries using smart glasses and receive empathetic responses in real time. This system is an effective means of supporting users' mental health.

[0544] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0545] This invention aims to realize a system that allows users to input messages about their feelings of loneliness or worries and provides positive and empathetic responses to those messages. Furthermore, by combining this system with an emotion engine, it can recognize the user's emotions and provide more appropriate responses.

[0546] First, the user enters their feelings and worries into the device as a text message. For example, they might type, "I've been feeling very lonely lately." The device then sends this message to the server. The server analyzes the message received from the device and uses an emotion engine to recognize the user's emotions. This emotion engine uses a machine learning algorithm to analyze emotions, and can recognize, for example, that the user is feeling emotions such as "sad" or "anxious."

[0547] The server uses a natural language processing model to generate a positive and empathetic response based on the recognized emotional information. This model is often implemented using OpenAI's API. For example, if the emotion engine recognizes that the user is "sad," the system generates the following response: "I know the loneliness you feel is really painful. But you're not alone. We're here, and we're always available to talk." The generated response is then returned to the device in JSON format.

[0548] The device receives the response sent from the server and displays the message to the user, which gives the user a sense of psychological relief that their feelings have been recognized and dealt with appropriately.

[0549] For example, if a user inputs "I failed at work and I can't talk to anyone about it," the emotion engine will recognize the user's emotion as "depressed." Similarly, the system will generate an empathetic response, such as, "That must have been a really painful experience. But failure is also a step toward growth. I'm rooting for you." This will help the user regain a positive attitude.

[0550] The system aims to support the user's mental health by empathizing with the loneliness and stress they feel and providing appropriate communication.

[0551] The above is an embodiment of the present invention.

[0552] The processing flow will be explained below.

[0553] Step 1:

[0554] The user inputs a message about their feelings of loneliness or worries into the device. For example, they might input, "I've been feeling very lonely lately."

[0555] Step 2:

[0556] The terminal receives the message.

[0557] Step 3:

[0558] The device sends the acquired message to the server via the Internet as a POST request. The body of the HTTP request contains the user's message.

[0559] Step 4:

[0560] The server receives a POST request from the terminal.

[0561] Step 5:

[0562] The server extracts the user's message from the request body received. For example, use request.json.get('message') to get the message "I've been feeling very lonely lately."

[0563] Step 6:

[0564] The server then passes the extracted messages to an emotion engine that analyzes the user's emotions. This emotion engine uses machine learning algorithms to recognize emotions such as "feeling lonely" or "sad."

[0565] Step 7:

[0566] Based on the emotional information obtained from the emotion engine, the server calls the "generate_positive_response" function, passing the user's message and the recognized emotional information as arguments.

[0567] Step 8:

[0568] In the “generate_positive_response” function, the server uses a natural language processing model (e.g., OpenAI’s API) to generate a positive and empathetic response to the user’s message and emotions, such as “I know the loneliness you feel is really painful, but you’re not alone. We’re here, and we’re always available to talk.”

[0569] Step 9:

[0570] The server formats the generated response message into JSON format, e.g. {"response": "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."}

[0571] Step 10:

[0572] The server sends the formatted JSON response to the device as an HTTP response.

[0573] Step 11:

[0574] The terminal receives the response from the server.

[0575] Step 12:

[0576] The device displays the received response message to the user. For example, the user's screen may display a message such as, "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime."

[0577] The above are the specific processing steps of the program.

[0578] Example 2

[0579] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0580] In modern society, the number of people suffering from loneliness and anxiety is increasing, and appropriate psychological support is needed. However, conventional systems have difficulty accurately recognizing users' emotions and responding individually, which makes it difficult to effectively support users' mental health.

[0581] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving a message input by a user, a means for analyzing the received message and recognizing the user's emotion, a means for generating a positive and empathetic response using a natural language processing model based on the recognized emotion information, and a means for providing the generated response to the user. As a result, by accurately recognizing the user's emotion and providing an appropriate response corresponding to the emotion, it becomes possible to increase the user's sense of psychological security and effectively support their mental health.

[0582] "User" refers to a person who uses the system to enter messages and receive responses.

[0583] A "message" refers to text data in which a user expresses their feelings or concerns.

[0584] The "means for receiving" refers to a method or device for incorporating a message input by a user into the system.

[0585] "Means for analyzing" refers to a method or device for analyzing a received message to extract information.

[0586] "Means for recognizing emotions" refers to a method or device for identifying a user's emotions from an analyzed message.

[0587] A "natural language processing model" refers to a computational model that generates responses in natural language based on input text data.

[0588] A "positive and empathetic response" refers to a response that is in tune with the user's emotions and contains positive content.

[0589] "Means for providing" refers to a method or device for presenting the generated response to the user.

[0590] "Generative AI model" refers to a computational model for generating responses using artificial intelligence.

[0591] "Network" refers to the communications infrastructure that connects servers and terminals.

[0592] "Server" refers to a computer system used for the purpose of processing data received from a user and generating a response.

[0593] The above are definitions of the important terms included in the rewritten claims.

[0594] This invention realizes a system that allows users to input messages about their feelings of loneliness or worries and provides positive and empathetic responses to those messages. The system recognizes the user's emotions by combining an emotion engine and provides more appropriate responses.

[0595] First, the user enters their feelings and worries as a text message into the device. For example, the user might enter, "I've been feeling very lonely lately." This message is sent to the server via the device. The device sends the message as an HTTP POST request, and the server receives the data.

[0596] The server uses a text analysis API to analyze the received messages. The analyzed text data is then used by an emotion engine to recognize the user's emotions. The emotion engine uses a machine learning algorithm and natural language processing technology to detect emotions such as "sadness" or "anxiety" felt by the user.

[0597] Next, the server uses a generative AI model to generate a positive and empathetic response based on the recognized emotional information. A natural language processing model is used as this generative AI model. For example, OpenAI's API can be used. The server passes the analysis results to the generative AI model as a prompt to generate a response. An example of a specific prompt sentence is "User's emotion: sad. Please generate a response."

[0598] The generated response is sent from the server to the device in JSON format. The device receives this response and displays it to the user. For example, if the generated response is "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime," the device will display this message on the user's screen.

[0599] As a concrete example, consider the case where a user types, "I failed at work and I can't tell anyone." The device sends this message to the server, which uses an emotion engine to analyze the user's emotions. The server uses a generative AI model to generate an empathetic response, such as, "That must have been a really painful experience. But failure is also a step towards growth. I'm rooting for you." The device displays this response message, providing the user with a positive feeling.

[0600] The above is a description of the mode for carrying out the invention, and the purpose of this system is to support the mental health of the user.

[0601] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0602] Step 1:

[0603] The user inputs their feelings and worries into the terminal as a text message.

[0604] Input: A user types "I've been feeling really lonely lately" into a text field.

[0605] Action: Text is entered into the device's input form.

[0606] Output: The text message is saved to a terminal variable.

[0607] Step 2:

[0608] The terminal transmits the entered text message to the server.

[0609] Input: A text message stored in a terminal variable.

[0610] How it works: The device makes an HTTP POST request and sends data containing a message to the server.

[0611] Output: Request sent to server as POST / messages {"text": "I've been feeling really lonely lately"}.

[0612] Step 3:

[0613] The server analyzes the received message and recognizes the user's emotions.

[0614] Input: The message data received by the server.

[0615] How it works: The server calls the text analysis API to analyze the message, and uses the emotion engine to recognize the user's emotion based on the analysis results.

[0616] Output: emotion_engine.analyze("I've been feeling very lonely lately") is executed and the emotion "sad" is recognized.

[0617] Step 4:

[0618] The server generates a positive and empathetic response based on the recognized emotional information using a natural language processing model.

[0619] Input: Emotion information recognized by the emotion engine (e.g., "sad").

[0620] Behavior: The server calls the generative AI model and passes the prompt to the model to generate a response. For example, openai.Completion.create(prompt="User emotion: sad. Please generate a response") is executed.

[0621] Output: Generates the response "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."

[0622] Step 5:

[0623] The server generates a response and sends it to the device in JSON format.

[0624] Input: The generated response data.

[0625] How it works: The server creates an HTTP response and sends the response data to the device. For example, response = {"text": "The loneliness you feel is really painful. But you're not alone. We're here, and we're always available to talk."}

[0626] Output: The response data is sent to the terminal in JSON format.

[0627] Step 6:

[0628] The terminal displays the response received from the server to the user.

[0629] Input: The response data received from the server.

[0630] Operation: The device analyzes the received response and displays it on the screen. In the case of a web application, it uses JavaScript to display it as follows: document.getElementById("response").innerText = response.text;

[0631] Output: The response message is displayed on the user's screen.

[0632] The above are the specific processing steps of the program of this system.

[0633] (Application example 2)

[0634] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0635] To provide a system capable of properly analyzing emotions such as loneliness, anxiety, and fear when a user feels such emotions, and automatically providing a sympathetic and reassuring response.

[0636] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a message input by a user, means for analyzing the input message and recognizing emotions, and means for generating a positive and empathetic response based on the recognized emotions. This makes it possible to appropriately recognize the anxiety and loneliness felt by the user and automatically generate an empathetic response that provides a sense of security.

[0637] "User" means any person or entity that utilizes the System to enter messages and receive responses.

[0638] "Message" refers to textual information that a user inputs to the system.

[0639] "Sentiment analysis" refers to the process of using machine learning and data analysis techniques to recognize the emotions contained in a message based on the content of the message entered by the user.

[0640] A "natural language processing model" refers to a collection of machine learning algorithms and techniques used to understand and generate human language.

[0641] "Response" refers to a positive and empathetic message provided to the user based on the analyzed emotions.

[0642] "Server" refers to a computing device or system for receiving messages, analyzing sentiment, and generating responses.

[0643] "Internet" refers to a general term for communication technologies that connect computer networks around the world and enable the sending and receiving of information.

[0644] "System" refers to a set of processes, including receiving messages from users, analyzing emotions, and generating responses, as well as the combination of hardware and software for executing those processes.

[0645] This invention realizes a system in which a user inputs feelings such as loneliness, anxiety, and fear as a text message, and receives a sympathetic and positive response.

[0646] Program Generation

[0647] The program processing of this system will be explained in natural language below.

[0648] System processing explanation

[0649] Hardware and Software

[0650] 1. User device: A device where the user types messages, such as a smartphone or robot.

[0651] 2. Server: A server is used to receive messages, analyze sentiment, and generate responses.

[0652] 3. Sentiment Analysis Engine: An engine is used to analyze messages entered by users and recognize their emotions.

[0653] 4. Natural Language Processing Model: Uses natural language processing techniques to generate responses based on the recognized sentiment.

[0654] 5. API: We may also use external services such as OpenAI's API.

[0655] Data processing and calculation

[0656] 1. Message received:

[0657] Users input messages containing feelings such as loneliness and anxiety via their smartphone or robot.

[0658] The terminal sends this message to a server over the Internet.

[0659] 2. Emotion analysis:

[0660] The server sends the received message to the emotion analysis engine for analysis.

[0661] The emotion analysis engine returns emotion labels such as "sad," "anxiety," and "fear" as the analysis results.

[0662] 3. Response generation:

[0663] The server generates prompts (inputs) for the natural language processing model based on the sentiment analysis results and creates an appropriate response.

[0664] The responses generated will be positive and empathetic.

[0665] 4. Response provision:

[0666] The server returns the generated response in JSON format to the user's device.

[0667] The terminal displays the response to the user.

[0668] The specific hardware and software used

[0669] Hardware: smartphones, robots, servers

[0670] Software: Sentiment analysis engine, natural language processing model, OpenAI API

[0671] Specific examples

[0672] If a user types, "When I'm alone at night, I suddenly get anxious. I can't stop thinking about what I might do if something were to happen," the emotion analysis engine recognizes this as "anxiety." The system then generates an empathetic response like, "It's very natural to feel anxious at night. I understand how you feel. It would be a little reassuring to have your contact details close at hand so you can call for help if something were to happen."

[0673] Prompt Sentence Examples

[0674] User Emotion: Anxiety

[0675] User message: When I'm alone at night, I suddenly get anxious. I can't stop thinking about what might happen.

[0676] Response message:

[0677] The above is an embodiment of the present invention.

[0678] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0679] Step 1:

[0680] The user inputs a message containing feelings such as loneliness or anxiety into a device such as a smartphone or robot. The input message is sent to a server via the Internet.

[0681] Input: A message typed by the user (e.g., "When I'm alone at night, I suddenly get anxious. I can't stop thinking about what might happen if something happens.")

[0682] Output: A message is sent from the terminal to the server.

[0683] Step 2:

[0684] The server sends the received message to the sentiment analysis engine, which uses machine learning algorithms to identify the sentiment of the message.

[0685] Input: User's message sent to the server\

[0686] Data processing: Messages are fed into a sentiment analysis engine, where an algorithmic analysis is performed.

[0687] Output: Parsed emotion (e.g. "anxiety")

[0688] Step 3:

[0689] The server generates a prompt based on the sentiment analysis results and sends it to a natural language processing model, which generates a positive and empathetic response based on the user's message and the analyzed sentiment.

[0690] Input: Sentiment analysis result and original message\

[0691] Data Calculation: Generate prompts and generate responses using natural language processing models.

[0692] Output: Generated response message (e.g., "It's very natural to feel anxious in the middle of the night. I understand how you feel. It can be a little reassuring to have your contact details handy so you can call for help if something happens.")

[0693] Step 4:

[0694] The server converts the generated response message into JSON format and sends it to the user's terminal.

[0695] Input: Generated response message\

[0696] Data processing: Convert the response into JSON format and send it to the terminal.

[0697] Output: The response message sent to the user's terminal

[0698] Step 5:

[0699] The terminal receives the response message sent by the server and displays it to the user.

[0700] Input: Response message sent from the server\

[0701] Output: A response message that is displayed on the user's terminal.

[0702] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0703] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0704] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0705] [Third embodiment]

[0706] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0707] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0708] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0709] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0710] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0711] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0712] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0713] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0714] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0715] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0716] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0717] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0718] This invention aims to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, the system operates in a series of steps: it receives the user's input message, generates a response using a natural language processing model, and provides that response to the user.

[0719] First, the user enters their feelings or concerns into the device as a text message. For example, they might type, "I've been feeling really lonely lately." The device then sends this message to a server. The server then analyzes the message and generates a positive, empathetic response using a natural language processing model. This model is often implemented using OpenAI's APIs.

[0720] Based on the user's input message, the server generates a response such as: "The loneliness you feel is really painful, but you are not alone. We are here and you can talk anytime." The generated response is then returned to the terminal in JSON format.

[0721] The device receives the response sent from the server and displays the message to the user, which affirms the user's feelings and gives the user a sense of psychological security.

[0722] For example, if a user types, "I failed at work and I don't have anyone to talk to," the system will generate a similarly empathetic response, such as, "That must have been a really painful experience. But failure is also a step toward growth. I'm rooting for you." This can help the user regain a positive attitude.

[0723] The system aims to support the user's mental health by empathizing with the loneliness and stress they are feeling and providing positive communication.

[0724] The above is an embodiment of the present invention.

[0725] The processing flow will be explained below.

[0726] Step 1:

[0727] The user inputs a message about their feelings of loneliness or worries into the device. For example, they might input, "I've been feeling very lonely lately."

[0728] Step 2:

[0729] The terminal receives the message.

[0730] Step 3:

[0731] The device sends the acquired message to the server via the Internet as a POST request. The body of the HTTP request contains the user's message.

[0732] Step 4:

[0733] The server receives a POST request from the terminal.

[0734] Step 5:

[0735] The server extracts the user's message from the request body received. For example, use request.json.get('message') to get the message "I've been feeling very lonely lately."

[0736] Step 6:

[0737] The server calls the "generate_positive_response" function, passing the user's message as an argument.

[0738] Step 7:

[0739] The server generates a positive and empathetic response to the user's message using OpenAI's API in the "generate_positive_response" function. For example, it sends an API request like this: "User said: I've been feeling really lonely lately\nRespond with empathy and positivity:"

[0740] Step 8:

[0741] The server receives the response from the OpenAI API and extracts the generated response message from it, for example, "The loneliness you feel is really painful. But you're not alone. We're here, so we're always available to talk."

[0742] Step 9:

[0743] The server extracts the response message and formats it into JSON. Example: {"response": "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."}

[0744] Step 10:

[0745] The server sends the formatted JSON response to the device as an HTTP response.

[0746] Step 11:

[0747] The terminal receives the response from the server.

[0748] Step 12:

[0749] The device displays the received response message to the user. For example, the user's screen may display a message such as, "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime."

[0750] The above are the specific processing steps of the program.

[0751] Example 1

[0752] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0753] In modern society, the number of people feeling lonely and stressed is increasing. However, there are limited means to respond appropriately to these feelings and provide positive and empathetic support. In particular, there is a need for a system that can respond quickly and appropriately to user messages, but current systems have issues with the quality and timing of responses.

[0754] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0755] In this invention, the server includes means for receiving a message input by a user, means for analyzing the input message and generating a prompt sentence, means for generating a positive and empathetic response by a generative AI model using the generated prompt sentence, and means for providing the response to the user, thereby enabling the provision of a prompt and high-quality response to support the user's mental health.

[0756] "User" refers to a person who utilizes the system to enter messages and receive responses.

[0757] "Message" refers to textual information entered by a user.

[0758] A "prompt sentence" refers to a text sentence created by the server to prompt the generative AI model to generate a response.

[0759] "Generative AI model" refers to an artificial intelligence model that uses natural language processing technology to generate a response to an input message.

[0760] "Response" refers to a positive, empathetic text message generated by a generative AI model and provided to a user.

[0761] A "server" refers to a computer system that is responsible for analyzing messages input by users, generating responses, and providing them.

[0762] "Internet" refers to a global computer network that connects devices and servers and allows data to be sent and received.

[0763] This invention aims to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, the system operates in a series of steps: it receives the user's input message, generates a response using a natural language processing model, and provides that response to the user.

[0764] First, we will explain the hardware and software configuration. This system mainly uses the following hardware and software.

[0765] Hardware

[0766] Device: A device such as a smartphone or PC used by a user

[0767] Server: A computer system in a cloud server or data center

[0768] software

[0769] User interface: A text input interface implemented on a terminal.

[0770] API: Natural Language Processing model (e.g., OpenAI's API)

[0771] Network Protocol: HTTP / HTTPS communication over the Internet

[0772] Next, the operation of this system will be specifically described.

[0773] User Input

[0774] Users input their feelings and worries into the device as text messages. This input is done using a keyboard or touch screen, and the message is sent by clicking or tapping the send button. For example, a user might type, "I've been feeling very lonely lately."

[0775] Sending a message

[0776] The device converts the user's input message into JSON format and sends it to the server as an HTTP POST request. Data privacy and security are ensured by secure communication (HTTPS) over an internet connection.

[0777] Message Parsing

[0778] After receiving the message sent from the device, the server analyzes it. During the analysis process, a prompt sentence is generated and passed to the generative AI model. As a specific example, the generated prompt sentence is in the following text format:

[0779] "A user types in a message like, 'I've been feeling really lonely lately.' Please respond with empathy and affirmation."

[0780] Generating a response

[0781] The server sends the prompt to a generative AI model (e.g., OpenAI's API) to generate a response. The generated response is received as a message like this:

[0782] "The loneliness you feel is really tough, but you're not alone. We're here, and you can always talk."

[0783] Sending a Response

[0784] The server returns the generated response in JSON format to the terminal, again using a secure communication method (HTTPS).

[0785] Viewing the response

[0786] The device analyzes the response received from the server and displays it to the user in text format. For example, if the user types, "I've been feeling very lonely lately," the following response will be displayed:

[0787] "The loneliness you feel is really tough, but you're not alone. We're here, and you can always talk."

[0788] This system allows users to affirm their own emotions and gain a sense of psychological security. Furthermore, the responses provided by the system are of high quality and are delivered quickly, which contributes greatly to supporting the user's mental health.

[0789] The above is a specific embodiment for carrying out the present invention.

[0790] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0791] Step 1:

[0792] The user inputs their feelings and worries into the device as a text message. For example, the user inputs, "I've been feeling very lonely lately." The input text message is stored in the device as input information.

[0793] Step 2:

[0794] The device converts the message entered by the user into JSON format and sends it to the server via the Internet as an HTTP POST request. At this time, the specific data sent is the JSON format message shown below.

[0795] json

[0796] {

[0797] "message": "I've been feeling really lonely lately"

[0798] }

[0799] As output, this JSON formatted message is sent to the server.

[0800] Step 3:

[0801] The server receives a JSON-formatted message sent from the device, which is first decoded and the text message is extracted as input data for analysis.

[0802] Type: "I've been feeling really lonely lately."

[0803] The server analyzes the text messages and processes the data to understand the user's emotions and situation.

[0804] Step 4:

[0805] The server generates a prompt sentence to be input to the generative AI model based on the parsed text message. For example, the following prompt sentence is generated:

[0806] "A user types in a message like, 'I've been feeling really lonely lately.' Please respond with empathy and affirmation."

[0807] After the prompt sentence is generated, it becomes the input data for the generative AI model.

[0808] Step 5:

[0809] The server sends the generated prompt to a generative AI model (e.g., OpenAI's API) to generate an empathetic and positive response. The generative AI model generates an appropriate text response to the prompt.

[0810] Input: Generated prompt text

[0811] Output: An empathetic, affirmative response, such as, "I know the loneliness you're feeling is really tough, but you're not alone. We're here, and we're always available to talk."

[0812] Step 6:

[0813] The server converts the generated response into JSON format and sends it to the terminal as an HTTP response. Specific output data includes the following JSON format message:

[0814] json

[0815] {

[0816] "response": "The loneliness you feel is really tough. But you're not alone. We're here, and we're always available to talk."

[0817] }

[0818] Step 7:

[0819] The terminal parses the JSON formatted response message received from the server, and the parsed response message is displayed to the user as text.

[0820] Input: JSON format response message from the server

[0821] Output: Response message in text format

[0822] The above is the flow of processing of the program of this system.

[0823] (Application example 1)

[0824] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0825] In modern society, many people suffer from feelings of loneliness and stress. These mental health issues not only reduce the quality of life for individuals, but also have a negative impact on society as a whole. However, conventional systems face the challenge of being unable to provide empathetic responses in real time in physical stores. In particular, there is a need for a quick and accurate response to the loneliness and worries that users feel on the spot, but there are limited means to efficiently resolve this.

[0826] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0827] In this invention, the server

[0828] means for receiving a message input by a user;

[0829] a means for generating a positive and empathetic response to an input message;

[0830] means for providing said response to a user;

[0831] means for receiving a message input by a user using the smart glasses;

[0832] means for displaying the response in conjunction with the smart glasses;

[0833] This allows users to receive empathetic responses in real time, even in physical stores, when they feel lonely or distressed.

[0834] The "means for receiving a message input by a user" is a function that allows the terminal to receive a message input by a user about feelings of loneliness or worries.

[0835] The "means for generating a positive and empathetic response to an input message" is a function that analyzes the received message and generates a positive and empathetic response to the content that is in tune with the user's emotions.

[0836] The "means for providing the response to the user" is a function for presenting the generated response to the user in an appropriate manner.

[0837] The "means for receiving a message input by a user using smart glasses" is a function for receiving a message input by a user through smart glasses.

[0838] The "means for displaying a response in cooperation with the smart glasses" is a function for displaying the generated response on the display of the smart glasses.

[0839] A "natural language processing model" is a model that uses technology to understand, analyze, and generate human language.

[0840] A "server" is a computer system that analyzes received messages and generates and sends responses.

[0841] The "means for sending messages via the Internet" is a function for sending received user messages to a server via the Internet.

[0842] The purpose of this invention is to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, this is a series of systems that receive the user's input message, generate a response using a natural language processing model, and provide that response to the user.

[0843] System Configuration

[0844] The following hardware and software are used to implement the present invention.

[0845] Hardware

[0846] Smart glasses (e.g. Google Glass)

[0847] Robots (e.g., SoftBank Robotics' Pepper)

[0848] Server (Central Processing Unit for Response Generation)

[0849] software

[0850] Natural language processing models (e.g., OpenAI's GPT-3)

[0851] Response generation script (using Python language)

[0852] System Operation Overview

[0853] 1. Receiving user input

[0854] The user uses the smart glasses to input their feelings of loneliness and worries. For example, they can input something like, "I've been feeling a lot of stress at work lately" through the microphone in the smart glasses.

[0855] 2. Sending a Message

[0856] The smart glasses send the received message to a server over the Internet.

[0857] 3. Generating a Response

[0858] The server analyzes the received message and uses OpenAI's GPT-3 model to generate an empathetic response, such as a prompt like this: "User: I've been feeling a lot of stress at work lately. Please generate an empathetic response."

[0859] 4. Viewing the Response

[0860] The generated response is then presented to the user again through the smart glasses, for example, "That's really hard. It's important not to push yourself too hard and to work at your own pace."

[0861] Specific examples

[0862] Example of user input and response

[0863] 1. User input: through voice input on smart glasses

[0864] "I recently made a mistake at work and I can't tell anyone about it."

[0865] 2. Server Response: A response generated using a natural language processing model

[0866] "That must have been a really tough experience. But failure is also a step towards growth. I'm rooting for you."

[0867] Examples of prompt statements

[0868] "User: I've been feeling a lot of stress at work lately. Please generate an empathetic response."

[0869] In this way, when users feel lonely or distressed, they can use this system to receive empathetic responses in real time, which is expected to support users' mental health and improve their quality of life.

[0870] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0871] Step 1:

[0872] The user uses the smart glasses to input voice. The user inputs a message about feelings of loneliness or worries through the microphone of the smart glasses. This voice data is converted into text data inside the smart glasses. For example, if the user inputs "I've been feeling a lot of stress at work lately," the voice is obtained as text data "I've been feeling a lot of stress at work lately."

[0873] Step 2:

[0874] The device (smart glasses) sends text data to a server via the Internet. The smart glasses then use a Wi-Fi connection to send the converted text data to the server. This may include authentication information and a session ID. This process allows the server to receive the text message from the user.

[0875] Step 3:

[0876] The server analyzes the received text message and generates an appropriate prompt. The server receives text data (e.g., "I've been feeling a lot of stress at work lately") and creates a prompt based on it to generate an empathetic response. The prompt is in the format: "User: I've been feeling a lot of stress at work lately.\nPlease generate an empathetic response."

[0877] Step 4:

[0878] The server uses a generative AI model (e.g., OpenAI's GPT-3) to generate an appropriate response based on the prompt. The server inputs the generated prompt into the AI ​​model and obtains the generated response. Based on this prompt, the AI ​​model generates an empathetic response such as, "That's really hard. Don't push yourself too hard, and it's important to work at your own pace."

[0879] Step 5:

[0880] The server converts the generated response into JSON format and sends it to the smart glasses via the Internet. The server converts the received response text data into JSON format and sends it to the user's smart glasses. This process returns the response message to the user's device.

[0881] Step 6:

[0882] The smart glasses parse the received JSON response and display it appropriately to the user. The smart glasses parse the received JSON data and display an empathetic response text on the display. The user can see the response message on the smart glasses display, saying, "That's really hard. It's important not to push yourself too hard and to work at your own pace."

[0883] Through these processing steps, users can easily input their feelings of loneliness and worries using smart glasses and receive empathetic responses in real time. This system is an effective means of supporting users' mental health.

[0884] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0885] This invention aims to realize a system that allows users to input messages about their feelings of loneliness or worries and provides positive and empathetic responses to those messages. Furthermore, by combining this system with an emotion engine, it can recognize the user's emotions and provide more appropriate responses.

[0886] First, the user enters their feelings and worries into the device as a text message. For example, they might type, "I've been feeling very lonely lately." The device then sends this message to the server. The server analyzes the message received from the device and uses an emotion engine to recognize the user's emotions. This emotion engine uses a machine learning algorithm to analyze emotions, and can recognize, for example, that the user is feeling emotions such as "sad" or "anxious."

[0887] The server uses a natural language processing model to generate a positive and empathetic response based on the recognized emotional information. This model is often implemented using OpenAI's API. For example, if the emotion engine recognizes that the user is "sad," the system generates the following response: "I know the loneliness you feel is really painful. But you're not alone. We're here, and we're always available to talk." The generated response is then returned to the device in JSON format.

[0888] The device receives the response sent from the server and displays the message to the user, which gives the user a sense of psychological relief that their feelings have been recognized and dealt with appropriately.

[0889] For example, if a user inputs "I failed at work and I can't talk to anyone about it," the emotion engine will recognize the user's emotion as "depressed." Similarly, the system will generate an empathetic response, such as, "That must have been a really painful experience. But failure is also a step toward growth. I'm rooting for you." This will help the user regain a positive attitude.

[0890] The system aims to support the user's mental health by empathizing with the loneliness and stress they feel and providing appropriate communication.

[0891] The above is an embodiment of the present invention.

[0892] The processing flow will be explained below.

[0893] Step 1:

[0894] The user inputs a message about their feelings of loneliness or worries into the device. For example, they might input, "I've been feeling very lonely lately."

[0895] Step 2:

[0896] The terminal receives the message.

[0897] Step 3:

[0898] The device sends the acquired message to the server via the Internet as a POST request. The body of the HTTP request contains the user's message.

[0899] Step 4:

[0900] The server receives a POST request from the terminal.

[0901] Step 5:

[0902] The server extracts the user's message from the request body received. For example, use request.json.get('message') to get the message "I've been feeling very lonely lately."

[0903] Step 6:

[0904] The server then passes the extracted messages to an emotion engine that analyzes the user's emotions. This emotion engine uses machine learning algorithms to recognize emotions such as "feeling lonely" or "sad."

[0905] Step 7:

[0906] Based on the emotional information obtained from the emotion engine, the server calls the "generate_positive_response" function, passing the user's message and the recognized emotional information as arguments.

[0907] Step 8:

[0908] In the “generate_positive_response” function, the server uses a natural language processing model (e.g., OpenAI’s API) to generate a positive and empathetic response to the user’s message and emotions, such as “I know the loneliness you feel is really painful, but you’re not alone. We’re here, and we’re always available to talk.”

[0909] Step 9:

[0910] The server formats the generated response message into JSON format, e.g. {"response": "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."}

[0911] Step 10:

[0912] The server sends the formatted JSON response to the device as an HTTP response.

[0913] Step 11:

[0914] The terminal receives the response from the server.

[0915] Step 12:

[0916] The device displays the received response message to the user. For example, the user's screen may display a message such as, "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime."

[0917] The above are the specific processing steps of the program.

[0918] Example 2

[0919] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0920] In modern society, the number of people suffering from loneliness and anxiety is increasing, and appropriate psychological support is needed. However, conventional systems have difficulty accurately recognizing users' emotions and responding individually, which makes it difficult to effectively support users' mental health.

[0921] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving a message input by a user, a means for analyzing the received message and recognizing the user's emotion, a means for generating a positive and empathetic response using a natural language processing model based on the recognized emotion information, and a means for providing the generated response to the user. As a result, by accurately recognizing the user's emotion and providing an appropriate response corresponding to the emotion, it becomes possible to increase the user's sense of psychological security and effectively support their mental health.

[0922] "User" refers to a person who uses the system to enter messages and receive responses.

[0923] A "message" refers to text data in which a user expresses their feelings or concerns.

[0924] The "means for receiving" refers to a method or device for incorporating a message input by a user into the system.

[0925] "Means for analyzing" refers to a method or device for analyzing a received message to extract information.

[0926] "Means for recognizing emotions" refers to a method or device for identifying a user's emotions from an analyzed message.

[0927] A "natural language processing model" refers to a computational model that generates responses in natural language based on input text data.

[0928] A "positive and empathetic response" refers to a response that is in tune with the user's emotions and contains positive content.

[0929] "Means for providing" refers to a method or device for presenting the generated response to the user.

[0930] "Generative AI model" refers to a computational model for generating responses using artificial intelligence.

[0931] "Network" refers to the communications infrastructure that connects servers and terminals.

[0932] "Server" refers to a computer system used for the purpose of processing data received from a user and generating a response.

[0933] The above are definitions of the important terms included in the rewritten claims.

[0934] This invention realizes a system that allows users to input messages about their feelings of loneliness or worries and provides positive and empathetic responses to those messages. The system recognizes the user's emotions by combining an emotion engine and provides more appropriate responses.

[0935] First, the user enters their feelings and worries as a text message into the device. For example, the user might enter, "I've been feeling very lonely lately." This message is sent to the server via the device. The device sends the message as an HTTP POST request, and the server receives the data.

[0936] The server uses a text analysis API to analyze the received messages. The analyzed text data is then used by an emotion engine to recognize the user's emotions. The emotion engine uses a machine learning algorithm and natural language processing technology to detect emotions such as "sadness" or "anxiety" felt by the user.

[0937] Next, the server uses a generative AI model to generate a positive and empathetic response based on the recognized emotional information. A natural language processing model is used as this generative AI model. For example, OpenAI's API can be used. The server passes the analysis results to the generative AI model as a prompt to generate a response. An example of a specific prompt sentence is "User's emotion: sad. Please generate a response."

[0938] The generated response is sent from the server to the device in JSON format. The device receives this response and displays it to the user. For example, if the generated response is "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime," the device will display this message on the user's screen.

[0939] As a concrete example, consider the case where a user types, "I failed at work and I can't tell anyone." The device sends this message to the server, which uses an emotion engine to analyze the user's emotions. The server uses a generative AI model to generate an empathetic response, such as, "That must have been a really painful experience. But failure is also a step towards growth. I'm rooting for you." The device displays this response message, providing the user with a positive feeling.

[0940] The above is a description of the mode for carrying out the invention, and the purpose of this system is to support the mental health of the user.

[0941] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0942] Step 1:

[0943] The user inputs their feelings and worries into the terminal as a text message.

[0944] Input: A user types "I've been feeling really lonely lately" into a text field.

[0945] Action: Text is entered into the device's input form.

[0946] Output: The text message is saved to a terminal variable.

[0947] Step 2:

[0948] The terminal transmits the entered text message to the server.

[0949] Input: A text message stored in a terminal variable.

[0950] How it works: The device makes an HTTP POST request and sends data containing a message to the server.

[0951] Output: Request sent to server as POST / messages {"text": "I've been feeling really lonely lately"}.

[0952] Step 3:

[0953] The server analyzes the received message and recognizes the user's emotions.

[0954] Input: The message data received by the server.

[0955] How it works: The server calls the text analysis API to analyze the message, and uses the emotion engine to recognize the user's emotion based on the analysis results.

[0956] Output: emotion_engine.analyze("I've been feeling very lonely lately") is executed and the emotion "sad" is recognized.

[0957] Step 4:

[0958] The server generates a positive and empathetic response based on the recognized emotional information using a natural language processing model.

[0959] Input: Emotion information recognized by the emotion engine (e.g., "sad").

[0960] Behavior: The server calls the generative AI model and passes the prompt to the model to generate a response. For example, openai.Completion.create(prompt="User emotion: sad. Please generate a response") is executed.

[0961] Output: Generates the response "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."

[0962] Step 5:

[0963] The server generates a response and sends it to the device in JSON format.

[0964] Input: The generated response data.

[0965] How it works: The server creates an HTTP response and sends the response data to the device. For example, response = {"text": "The loneliness you feel is really painful. But you're not alone. We're here, and we're always available to talk."}

[0966] Output: The response data is sent to the terminal in JSON format.

[0967] Step 6:

[0968] The terminal displays the response received from the server to the user.

[0969] Input: The response data received from the server.

[0970] Operation: The device analyzes the received response and displays it on the screen. In the case of a web application, it uses JavaScript to display it as follows: document.getElementById("response").innerText = response.text;

[0971] Output: The response message is displayed on the user's screen.

[0972] The above are the specific processing steps of the program of this system.

[0973] (Application example 2)

[0974] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0975] To provide a system capable of properly analyzing emotions such as loneliness, anxiety, and fear when a user feels such emotions, and automatically providing a sympathetic and reassuring response.

[0976] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a message input by a user, means for analyzing the input message and recognizing emotions, and means for generating a positive and empathetic response based on the recognized emotions. This makes it possible to appropriately recognize the anxiety and loneliness felt by the user and automatically generate an empathetic response that provides a sense of security.

[0977] "User" means any person or entity that utilizes the System to enter messages and receive responses.

[0978] "Message" refers to textual information that a user inputs to the system.

[0979] "Sentiment analysis" refers to the process of using machine learning and data analysis techniques to recognize the emotions contained in a message based on the content of the message entered by the user.

[0980] A "natural language processing model" refers to a collection of machine learning algorithms and techniques used to understand and generate human language.

[0981] "Response" refers to a positive and empathetic message provided to the user based on the analyzed emotions.

[0982] "Server" refers to a computing device or system for receiving messages, analyzing sentiment, and generating responses.

[0983] "Internet" refers to a general term for communication technologies that connect computer networks around the world and enable the sending and receiving of information.

[0984] "System" refers to a set of processes, including receiving messages from users, analyzing emotions, and generating responses, as well as the combination of hardware and software for executing those processes.

[0985] This invention realizes a system in which a user inputs feelings such as loneliness, anxiety, and fear as a text message, and receives a sympathetic and positive response.

[0986] Program Generation

[0987] The program processing of this system will be explained in natural language below.

[0988] System processing explanation

[0989] Hardware and Software

[0990] 1. User device: A device where the user types messages, such as a smartphone or robot.

[0991] 2. Server: A server is used to receive messages, analyze sentiment, and generate responses.

[0992] 3. Sentiment Analysis Engine: An engine is used to analyze messages entered by users and recognize their emotions.

[0993] 4. Natural Language Processing Model: Uses natural language processing techniques to generate responses based on the recognized sentiment.

[0994] 5. API: We may also use external services such as OpenAI's API.

[0995] Data processing and calculation

[0996] 1. Message received:

[0997] Users input messages containing feelings such as loneliness and anxiety via their smartphone or robot.

[0998] The terminal sends this message to a server over the Internet.

[0999] 2. Emotion analysis:

[1000] The server sends the received message to the emotion analysis engine for analysis.

[1001] The emotion analysis engine returns emotion labels such as "sad," "anxiety," and "fear" as the analysis results.

[1002] 3. Response generation:

[1003] The server generates prompts (inputs) for the natural language processing model based on the sentiment analysis results and creates an appropriate response.

[1004] The responses generated will be positive and empathetic.

[1005] 4. Response provision:

[1006] The server returns the generated response in JSON format to the user's device.

[1007] The terminal displays the response to the user.

[1008] The specific hardware and software used

[1009] Hardware: smartphones, robots, servers

[1010] Software: Sentiment analysis engine, natural language processing model, OpenAI API

[1011] Specific examples

[1012] If a user types, "When I'm alone at night, I suddenly get anxious. I can't stop thinking about what I might do if something were to happen," the emotion analysis engine recognizes this as "anxiety." The system then generates an empathetic response like, "It's very natural to feel anxious at night. I understand how you feel. It would be a little reassuring to have your contact details close at hand so you can call for help if something were to happen."

[1013] Prompt Sentence Examples

[1014] User Emotion: Anxiety

[1015] User message: When I'm alone at night, I suddenly get anxious. I can't stop thinking about what might happen.

[1016] Response message:

[1017] The above is an embodiment of the present invention.

[1018] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1019] Step 1:

[1020] The user inputs a message containing feelings such as loneliness or anxiety into a device such as a smartphone or robot. The input message is sent to a server via the Internet.

[1021] Input: A message typed by the user (e.g., "When I'm alone at night, I suddenly get anxious. I can't stop thinking about what might happen if something happens.")

[1022] Output: A message is sent from the terminal to the server.

[1023] Step 2:

[1024] The server sends the received message to the sentiment analysis engine, which uses machine learning algorithms to identify the sentiment of the message.

[1025] Input: User's message sent to the server\

[1026] Data processing: Messages are fed into a sentiment analysis engine, where an algorithmic analysis is performed.

[1027] Output: Parsed emotion (e.g. "anxiety")

[1028] Step 3:

[1029] The server generates a prompt based on the sentiment analysis results and sends it to a natural language processing model, which generates a positive and empathetic response based on the user's message and the analyzed sentiment.

[1030] Input: Sentiment analysis result and original message\

[1031] Data Calculation: Generate prompts and generate responses using natural language processing models.

[1032] Output: Generated response message (e.g., "It's very natural to feel anxious in the middle of the night. I understand how you feel. It can be a little reassuring to have your contact details handy so you can call for help if something happens.")

[1033] Step 4:

[1034] The server converts the generated response message into JSON format and sends it to the user's terminal.

[1035] Input: Generated response message\

[1036] Data processing: Convert the response into JSON format and send it to the terminal.

[1037] Output: The response message sent to the user's terminal

[1038] Step 5:

[1039] The terminal receives the response message sent by the server and displays it to the user.

[1040] Input: Response message sent from the server\

[1041] Output: A response message that is displayed on the user's terminal.

[1042] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1043] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1044] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1045] [Fourth embodiment]

[1046] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1047] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1048] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1049] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1050] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1051] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1052] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1053] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1054] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1055] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1056] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1057] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1058] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1059] This invention aims to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, the system operates in a series of steps: it receives the user's input message, generates a response using a natural language processing model, and provides that response to the user.

[1060] First, the user enters their feelings or concerns into the device as a text message. For example, they might type, "I've been feeling really lonely lately." The device then sends this message to a server. The server then analyzes the message and generates a positive, empathetic response using a natural language processing model. This model is often implemented using OpenAI's APIs.

[1061] Based on the user's input message, the server generates a response such as: "The loneliness you feel is really painful, but you are not alone. We are here and you can talk anytime." The generated response is then returned to the terminal in JSON format.

[1062] The device receives the response sent from the server and displays the message to the user, which affirms the user's feelings and gives the user a sense of psychological security.

[1063] For example, if a user types, "I failed at work and I don't have anyone to talk to," the system will generate a similarly empathetic response, such as, "That must have been a really painful experience. But failure is also a step toward growth. I'm rooting for you." This can help the user regain a positive attitude.

[1064] The system aims to support the user's mental health by empathizing with the loneliness and stress they are feeling and providing positive communication.

[1065] The above is an embodiment of the present invention.

[1066] The processing flow will be explained below.

[1067] Step 1:

[1068] The user inputs a message about their feelings of loneliness or worries into the device. For example, they might input, "I've been feeling very lonely lately."

[1069] Step 2:

[1070] The terminal receives the message.

[1071] Step 3:

[1072] The device sends the acquired message to the server via the Internet as a POST request. The body of the HTTP request contains the user's message.

[1073] Step 4:

[1074] The server receives a POST request from the terminal.

[1075] Step 5:

[1076] The server extracts the user's message from the request body received. For example, use request.json.get('message') to get the message "I've been feeling very lonely lately."

[1077] Step 6:

[1078] The server calls the "generate_positive_response" function, passing the user's message as an argument.

[1079] Step 7:

[1080] The server generates a positive and empathetic response to the user's message using OpenAI's API in the "generate_positive_response" function. For example, it sends an API request like this: "User said: I've been feeling really lonely lately\nRespond with empathy and positivity:"

[1081] Step 8:

[1082] The server receives the response from the OpenAI API and extracts the generated response message from it, for example, "The loneliness you feel is really painful. But you're not alone. We're here, so we're always available to talk."

[1083] Step 9:

[1084] The server extracts the response message and formats it into JSON. Example: {"response": "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."}

[1085] Step 10:

[1086] The server sends the formatted JSON response to the device as an HTTP response.

[1087] Step 11:

[1088] The terminal receives the response from the server.

[1089] Step 12:

[1090] The device displays the received response message to the user. For example, the user's screen may display a message such as, "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime."

[1091] The above are the specific processing steps of the program.

[1092] Example 1

[1093] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1094] In modern society, the number of people feeling lonely and stressed is increasing. However, there are limited means to respond appropriately to these feelings and provide positive and empathetic support. In particular, there is a need for a system that can respond quickly and appropriately to user messages, but current systems have issues with the quality and timing of responses.

[1095] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1096] In this invention, the server includes means for receiving a message input by a user, means for analyzing the input message and generating a prompt sentence, means for generating a positive and empathetic response by a generative AI model using the generated prompt sentence, and means for providing the response to the user, thereby enabling the provision of a prompt and high-quality response to support the user's mental health.

[1097] "User" refers to a person who utilizes the system to enter messages and receive responses.

[1098] "Message" refers to textual information entered by a user.

[1099] A "prompt sentence" refers to a text sentence created by the server to prompt the generative AI model to generate a response.

[1100] "Generative AI model" refers to an artificial intelligence model that uses natural language processing technology to generate a response to an input message.

[1101] "Response" refers to a positive, empathetic text message generated by a generative AI model and provided to a user.

[1102] A "server" refers to a computer system that is responsible for analyzing messages input by users, generating responses, and providing them.

[1103] "Internet" refers to a global computer network that connects devices and servers and allows data to be sent and received.

[1104] This invention aims to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, the system operates in a series of steps: it receives the user's input message, generates a response using a natural language processing model, and provides that response to the user.

[1105] First, we will explain the hardware and software configuration. This system mainly uses the following hardware and software.

[1106] Hardware

[1107] Device: A device such as a smartphone or PC used by a user

[1108] Server: A computer system in a cloud server or data center

[1109] software

[1110] User interface: A text input interface implemented on a terminal.

[1111] API: Natural Language Processing model (e.g., OpenAI's API)

[1112] Network Protocol: HTTP / HTTPS communication over the Internet

[1113] Next, the operation of this system will be specifically described.

[1114] User Input

[1115] Users input their feelings and worries into the device as text messages. This input is done using a keyboard or touch screen, and the message is sent by clicking or tapping the send button. For example, a user might type, "I've been feeling very lonely lately."

[1116] Sending a message

[1117] The device converts the user's input message into JSON format and sends it to the server as an HTTP POST request. Data privacy and security are ensured by secure communication (HTTPS) over an internet connection.

[1118] Message Parsing

[1119] After receiving the message sent from the device, the server analyzes it. During the analysis process, a prompt sentence is generated and passed to the generative AI model. As a specific example, the generated prompt sentence is in the following text format:

[1120] "A user types in a message like, 'I've been feeling really lonely lately.' Please respond with empathy and affirmation."

[1121] Generating a response

[1122] The server sends the prompt to a generative AI model (e.g., OpenAI's API) to generate a response. The generated response is received as a message like this:

[1123] "The loneliness you feel is really tough, but you're not alone. We're here, and you can always talk."

[1124] Sending a Response

[1125] The server returns the generated response in JSON format to the terminal, again using a secure communication method (HTTPS).

[1126] Viewing the response

[1127] The device analyzes the response received from the server and displays it to the user in text format. For example, if the user types, "I've been feeling very lonely lately," the following response will be displayed:

[1128] "The loneliness you feel is really tough, but you're not alone. We're here, and you can always talk."

[1129] This system allows users to affirm their own emotions and gain a sense of psychological security. Furthermore, the responses provided by the system are of high quality and are delivered quickly, which contributes greatly to supporting the user's mental health.

[1130] The above is a specific embodiment for carrying out the present invention.

[1131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1132] Step 1:

[1133] The user inputs their feelings and worries into the device as a text message. For example, the user inputs, "I've been feeling very lonely lately." The input text message is stored in the device as input information.

[1134] Step 2:

[1135] The device converts the message entered by the user into JSON format and sends it to the server via the Internet as an HTTP POST request. At this time, the specific data sent is the JSON format message shown below.

[1136] json

[1137] {

[1138] "message": "I've been feeling really lonely lately"

[1139] }

[1140] As output, this JSON formatted message is sent to the server.

[1141] Step 3:

[1142] The server receives a JSON-formatted message sent from the device, which is first decoded and the text message is extracted as input data for analysis.

[1143] Type: "I've been feeling really lonely lately."

[1144] The server analyzes the text messages and processes the data to understand the user's emotions and situation.

[1145] Step 4:

[1146] The server generates a prompt sentence to be input to the generative AI model based on the parsed text message. For example, the following prompt sentence is generated:

[1147] "A user types in a message like, 'I've been feeling really lonely lately.' Please respond with empathy and affirmation."

[1148] After the prompt sentence is generated, it becomes the input data for the generative AI model.

[1149] Step 5:

[1150] The server sends the generated prompt to a generative AI model (e.g., OpenAI's API) to generate an empathetic and positive response. The generative AI model generates an appropriate text response to the prompt.

[1151] Input: Generated prompt text

[1152] Output: An empathetic, affirmative response, such as, "I know the loneliness you're feeling is really tough, but you're not alone. We're here, and we're always available to talk."

[1153] Step 6:

[1154] The server converts the generated response into JSON format and sends it to the terminal as an HTTP response. Specific output data includes the following JSON format message:

[1155] json

[1156] {

[1157] "response": "The loneliness you feel is really tough. But you're not alone. We're here, and we're always available to talk."

[1158] }

[1159] Step 7:

[1160] The terminal parses the JSON formatted response message received from the server, and the parsed response message is displayed to the user as text.

[1161] Input: JSON format response message from the server

[1162] Output: Response message in text format

[1163] The above is the flow of processing of the program of this system.

[1164] (Application example 1)

[1165] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1166] In modern society, many people suffer from feelings of loneliness and stress. These mental health issues not only reduce the quality of life for individuals, but also have a negative impact on society as a whole. However, conventional systems face the challenge of being unable to provide empathetic responses in real time in physical stores. In particular, there is a need for a quick and accurate response to the loneliness and worries that users feel on the spot, but there are limited means to efficiently resolve this.

[1167] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1168] In this invention, the server

[1169] means for receiving a message input by a user;

[1170] a means for generating a positive and empathetic response to an input message;

[1171] means for providing said response to a user;

[1172] means for receiving a message input by a user using the smart glasses;

[1173] means for displaying the response in conjunction with the smart glasses;

[1174] This allows users to receive empathetic responses in real time, even in physical stores, when they feel lonely or distressed.

[1175] The "means for receiving a message input by a user" is a function that allows the terminal to receive a message input by a user about feelings of loneliness or worries.

[1176] The "means for generating a positive and empathetic response to an input message" is a function that analyzes the received message and generates a positive and empathetic response to the content that is in tune with the user's emotions.

[1177] The "means for providing the response to the user" is a function for presenting the generated response to the user in an appropriate manner.

[1178] The "means for receiving a message input by a user using smart glasses" is a function for receiving a message input by a user through smart glasses.

[1179] The "means for displaying a response in cooperation with the smart glasses" is a function for displaying the generated response on the display of the smart glasses.

[1180] A "natural language processing model" is a model that uses technology to understand, analyze, and generate human language.

[1181] A "server" is a computer system that analyzes received messages and generates and sends responses.

[1182] The "means for sending messages via the Internet" is a function for sending received user messages to a server via the Internet.

[1183] The purpose of this invention is to realize a system that allows a user to input a message about loneliness or distress and provides a positive and empathetic response to that message. Specifically, this is a series of systems that receive the user's input message, generate a response using a natural language processing model, and provide that response to the user.

[1184] System Configuration

[1185] The following hardware and software are used to implement the present invention.

[1186] Hardware

[1187] Smart glasses (e.g. Google Glass)

[1188] Robots (e.g., SoftBank Robotics' Pepper)

[1189] Server (Central Processing Unit for Response Generation)

[1190] software

[1191] Natural language processing models (e.g., OpenAI's GPT-3)

[1192] Response generation script (using Python language)

[1193] System Operation Overview

[1194] 1. Receiving user input

[1195] The user uses the smart glasses to input their feelings of loneliness and worries. For example, they can input something like, "I've been feeling a lot of stress at work lately" through the microphone in the smart glasses.

[1196] 2. Sending a Message

[1197] The smart glasses send the received message to a server over the Internet.

[1198] 3. Generating a Response

[1199] The server analyzes the received message and uses OpenAI's GPT-3 model to generate an empathetic response, such as a prompt like this: "User: I've been feeling a lot of stress at work lately. Please generate an empathetic response."

[1200] 4. Viewing the Response

[1201] The generated response is then presented to the user again through the smart glasses, for example, "That's really hard. It's important not to push yourself too hard and to work at your own pace."

[1202] Specific examples

[1203] Example of user input and response

[1204] 1. User input: through voice input on smart glasses

[1205] "I recently made a mistake at work and I can't tell anyone about it."

[1206] 2. Server Response: A response generated using a natural language processing model

[1207] "That must have been a really tough experience. But failure is also a step towards growth. I'm rooting for you."

[1208] Examples of prompt statements

[1209] "User: I've been feeling a lot of stress at work lately. Please generate an empathetic response."

[1210] In this way, when users feel lonely or distressed, they can use this system to receive empathetic responses in real time, which is expected to support users' mental health and improve their quality of life.

[1211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1212] Step 1:

[1213] The user uses the smart glasses to input voice. The user inputs a message about feelings of loneliness or worries through the microphone of the smart glasses. This voice data is converted into text data inside the smart glasses. For example, if the user inputs "I've been feeling a lot of stress at work lately," the voice is obtained as text data "I've been feeling a lot of stress at work lately."

[1214] Step 2:

[1215] The device (smart glasses) sends text data to a server via the Internet. The smart glasses then use a Wi-Fi connection to send the converted text data to the server. This may include authentication information and a session ID. This process allows the server to receive the text message from the user.

[1216] Step 3:

[1217] The server analyzes the received text message and generates an appropriate prompt. The server receives text data (e.g., "I've been feeling a lot of stress at work lately") and creates a prompt based on it to generate an empathetic response. The prompt is in the format: "User: I've been feeling a lot of stress at work lately.\nPlease generate an empathetic response."

[1218] Step 4:

[1219] The server uses a generative AI model (e.g., OpenAI's GPT-3) to generate an appropriate response based on the prompt. The server inputs the generated prompt into the AI ​​model and obtains the generated response. Based on this prompt, the AI ​​model generates an empathetic response such as, "That's really hard. Don't push yourself too hard, and it's important to work at your own pace."

[1220] Step 5:

[1221] The server converts the generated response into JSON format and sends it to the smart glasses via the Internet. The server converts the received response text data into JSON format and sends it to the user's smart glasses. This process returns the response message to the user's device.

[1222] Step 6:

[1223] The smart glasses parse the received JSON response and display it appropriately to the user. The smart glasses parse the received JSON data and display an empathetic response text on the display. The user can see the response message on the smart glasses display, saying, "That's really hard. It's important not to push yourself too hard and to work at your own pace."

[1224] Through these processing steps, users can easily input their feelings of loneliness and worries using smart glasses and receive empathetic responses in real time. This system is an effective means of supporting users' mental health.

[1225] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1226] This invention aims to realize a system that allows users to input messages about their feelings of loneliness or worries and provides positive and empathetic responses to those messages. Furthermore, by combining this system with an emotion engine, it can recognize the user's emotions and provide more appropriate responses.

[1227] First, the user enters their feelings and worries into the device as a text message. For example, they might type, "I've been feeling very lonely lately." The device then sends this message to the server. The server analyzes the message received from the device and uses an emotion engine to recognize the user's emotions. This emotion engine uses a machine learning algorithm to analyze emotions, and can recognize, for example, that the user is feeling emotions such as "sad" or "anxious."

[1228] The server uses a natural language processing model to generate a positive and empathetic response based on the recognized emotional information. This model is often implemented using OpenAI's API. For example, if the emotion engine recognizes that the user is "sad," the system generates the following response: "I know the loneliness you feel is really painful. But you're not alone. We're here, and we're always available to talk." The generated response is then returned to the device in JSON format.

[1229] The device receives the response sent from the server and displays the message to the user, which gives the user a sense of psychological relief that their feelings have been recognized and dealt with appropriately.

[1230] For example, if a user inputs "I failed at work and I can't talk to anyone about it," the emotion engine will recognize the user's emotion as "depressed." Similarly, the system will generate an empathetic response, such as, "That must have been a really painful experience. But failure is also a step toward growth. I'm rooting for you." This will help the user regain a positive attitude.

[1231] The system aims to support the user's mental health by empathizing with the loneliness and stress they feel and providing appropriate communication.

[1232] The above is an embodiment of the present invention.

[1233] The processing flow will be explained below.

[1234] Step 1:

[1235] The user inputs a message about their feelings of loneliness or worries into the device. For example, they might input, "I've been feeling very lonely lately."

[1236] Step 2:

[1237] The terminal receives the message.

[1238] Step 3:

[1239] The device sends the acquired message to the server via the Internet as a POST request. The body of the HTTP request contains the user's message.

[1240] Step 4:

[1241] The server receives a POST request from the terminal.

[1242] Step 5:

[1243] The server extracts the user's message from the request body received. For example, use request.json.get('message') to get the message "I've been feeling very lonely lately."

[1244] Step 6:

[1245] The server then passes the extracted messages to an emotion engine that analyzes the user's emotions. This emotion engine uses machine learning algorithms to recognize emotions such as "feeling lonely" or "sad."

[1246] Step 7:

[1247] Based on the emotional information obtained from the emotion engine, the server calls the "generate_positive_response" function, passing the user's message and the recognized emotional information as arguments.

[1248] Step 8:

[1249] In the “generate_positive_response” function, the server uses a natural language processing model (e.g., OpenAI’s API) to generate a positive and empathetic response to the user’s message and emotions, such as “I know the loneliness you feel is really painful, but you’re not alone. We’re here, and we’re always available to talk.”

[1250] Step 9:

[1251] The server formats the generated response message into JSON format, e.g. {"response": "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."}

[1252] Step 10:

[1253] The server sends the formatted JSON response to the device as an HTTP response.

[1254] Step 11:

[1255] The terminal receives the response from the server.

[1256] Step 12:

[1257] The device displays the received response message to the user. For example, the user's screen may display a message such as, "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime."

[1258] The above are the specific processing steps of the program.

[1259] Example 2

[1260] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1261] In modern society, the number of people suffering from loneliness and anxiety is increasing, and appropriate psychological support is needed. However, conventional systems have difficulty accurately recognizing users' emotions and responding individually, which makes it difficult to effectively support users' mental health.

[1262] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving a message input by a user, a means for analyzing the received message and recognizing the user's emotion, a means for generating a positive and empathetic response using a natural language processing model based on the recognized emotion information, and a means for providing the generated response to the user. As a result, by accurately recognizing the user's emotion and providing an appropriate response corresponding to the emotion, it becomes possible to increase the user's sense of psychological security and effectively support their mental health.

[1263] "User" refers to a person who uses the system to enter messages and receive responses.

[1264] A "message" refers to text data in which a user expresses their feelings or concerns.

[1265] The "means for receiving" refers to a method or device for incorporating a message input by a user into the system.

[1266] "Means for analyzing" refers to a method or device for analyzing a received message to extract information.

[1267] "Means for recognizing emotions" refers to a method or device for identifying a user's emotions from an analyzed message.

[1268] A "natural language processing model" refers to a computational model that generates responses in natural language based on input text data.

[1269] A "positive and empathetic response" refers to a response that is in tune with the user's emotions and contains positive content.

[1270] "Means for providing" refers to a method or device for presenting the generated response to the user.

[1271] "Generative AI model" refers to a computational model for generating responses using artificial intelligence.

[1272] "Network" refers to the communications infrastructure that connects servers and terminals.

[1273] "Server" refers to a computer system used for the purpose of processing data received from a user and generating a response.

[1274] The above are definitions of the important terms included in the rewritten claims.

[1275] This invention realizes a system that allows users to input messages about their feelings of loneliness or worries and provides positive and empathetic responses to those messages. The system recognizes the user's emotions by combining an emotion engine and provides more appropriate responses.

[1276] First, the user enters their feelings and worries as a text message into the device. For example, the user might enter, "I've been feeling very lonely lately." This message is sent to the server via the device. The device sends the message as an HTTP POST request, and the server receives the data.

[1277] The server uses a text analysis API to analyze the received messages. The analyzed text data is then used by an emotion engine to recognize the user's emotions. The emotion engine uses a machine learning algorithm and natural language processing technology to detect emotions such as "sadness" or "anxiety" felt by the user.

[1278] Next, the server uses a generative AI model to generate a positive and empathetic response based on the recognized emotional information. A natural language processing model is used as this generative AI model. For example, OpenAI's API can be used. The server passes the analysis results to the generative AI model as a prompt to generate a response. An example of a specific prompt sentence is "User's emotion: sad. Please generate a response."

[1279] The generated response is sent from the server to the device in JSON format. The device receives this response and displays it to the user. For example, if the generated response is "The loneliness you feel is really painful. But you are not alone. We are here, so you can talk anytime," the device will display this message on the user's screen.

[1280] As a concrete example, consider the case where a user types, "I failed at work and I can't tell anyone." The device sends this message to the server, which uses an emotion engine to analyze the user's emotions. The server uses a generative AI model to generate an empathetic response, such as, "That must have been a really painful experience. But failure is also a step towards growth. I'm rooting for you." The device displays this response message, providing the user with a positive feeling.

[1281] The above is a description of the mode for carrying out the invention, and the purpose of this system is to support the mental health of the user.

[1282] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1283] Step 1:

[1284] The user inputs their feelings and worries into the terminal as a text message.

[1285] Input: A user types "I've been feeling really lonely lately" into a text field.

[1286] Action: Text is entered into the device's input form.

[1287] Output: The text message is saved to a terminal variable.

[1288] Step 2:

[1289] The terminal transmits the entered text message to the server.

[1290] Input: A text message stored in a terminal variable.

[1291] How it works: The device makes an HTTP POST request and sends data containing a message to the server.

[1292] Output: Request sent to server as POST / messages {"text": "I've been feeling really lonely lately"}.

[1293] Step 3:

[1294] The server analyzes the received message and recognizes the user's emotions.

[1295] Input: The message data received by the server.

[1296] How it works: The server calls the text analysis API to analyze the message, and uses the emotion engine to recognize the user's emotion based on the analysis results.

[1297] Output: emotion_engine.analyze("I've been feeling very lonely lately") is executed and the emotion "sad" is recognized.

[1298] Step 4:

[1299] The server generates a positive and empathetic response based on the recognized emotional information using a natural language processing model.

[1300] Input: Emotion information recognized by the emotion engine (e.g., "sad").

[1301] Behavior: The server calls the generative AI model and passes the prompt to the model to generate a response. For example, openai.Completion.create(prompt="User emotion: sad. Please generate a response") is executed.

[1302] Output: Generates the response "I know the loneliness you feel is really tough, but you're not alone. We're here and we're always available to talk."

[1303] Step 5:

[1304] The server generates a response and sends it to the device in JSON format.

[1305] Input: The generated response data.

[1306] How it works: The server creates an HTTP response and sends the response data to the device. For example, response = {"text": "The loneliness you feel is really painful. But you're not alone. We're here, and we're always available to talk."}

[1307] Output: The response data is sent to the terminal in JSON format.

[1308] Step 6:

[1309] The terminal displays the response received from the server to the user.

[1310] Input: The response data received from the server.

[1311] Operation: The device analyzes the received response and displays it on the screen. In the case of a web application, it uses JavaScript to display it as follows: document.getElementById("response").innerText = response.text;

[1312] Output: The response message is displayed on the user's screen.

[1313] The above are the specific processing steps of the program of this system.

[1314] (Application example 2)

[1315] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1316] To provide a system capable of properly analyzing emotions such as loneliness, anxiety, and fear when a user feels such emotions, and automatically providing a sympathetic and reassuring response.

[1317] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a message input by a user, means for analyzing the input message and recognizing emotions, and means for generating a positive and empathetic response based on the recognized emotions. This makes it possible to appropriately recognize the anxiety and loneliness felt by the user and automatically generate an empathetic response that provides a sense of security.

[1318] "User" means any person or entity that utilizes the System to enter messages and receive responses.

[1319] "Message" refers to textual information that a user inputs to the system.

[1320] "Sentiment analysis" refers to the process of using machine learning and data analysis techniques to recognize the emotions contained in a message based on the content of the message entered by the user.

[1321] A "natural language processing model" refers to a collection of machine learning algorithms and techniques used to understand and generate human language.

[1322] "Response" refers to a positive and empathetic message provided to the user based on the analyzed emotions.

[1323] "Server" refers to a computing device or system for receiving messages, analyzing sentiment, and generating responses.

[1324] "Internet" refers to a general term for communication technologies that connect computer networks around the world and enable the sending and receiving of information.

[1325] "System" refers to a set of processes, including receiving messages from users, analyzing emotions, and generating responses, as well as the combination of hardware and software for executing those processes.

[1326] This invention realizes a system in which a user inputs feelings such as loneliness, anxiety, and fear as a text message, and receives a sympathetic and positive response.

[1327] Program Generation

[1328] The program processing of this system will be explained in natural language below.

[1329] System processing explanation

[1330] Hardware and Software

[1331] 1. User device: A device where the user types messages, such as a smartphone or robot.

[1332] 2. Server: A server is used to receive messages, analyze sentiment, and generate responses.

[1333] 3. Sentiment Analysis Engine: An engine is used to analyze messages entered by users and recognize their emotions.

[1334] 4. Natural Language Processing Model: Uses natural language processing techniques to generate responses based on the recognized sentiment.

[1335] 5. API: We may also use external services such as OpenAI's API.

[1336] Data processing and calculation

[1337] 1. Message received:

[1338] Users input messages containing feelings such as loneliness and anxiety via their smartphones or robots.

[1339] The terminal sends this message to a server over the Internet.

[1340] 2. Emotion analysis:

[1341] The server sends the received message to the emotion analysis engine for analysis.

[1342] The emotion analysis engine returns emotion labels such as "sad," "anxiety," and "fear" as the analysis results.

[1343] 3. Response generation:

[1344] The server generates prompts (inputs) for the natural language processing model based on the sentiment analysis results and creates an appropriate response.

[1345] The responses generated will be positive and empathetic.

[1346] 4. Response provision:

[1347] The server returns the generated response in JSON format to the user's device.

[1348] The terminal displays the response to the user.

[1349] The specific hardware and software used

[1350] Hardware: smartphones, robots, servers

[1351] Software: Sentiment analysis engine, natural language processing model, OpenAI API

[1352] Specific examples

[1353] If a user types, "When I'm alone at night, I suddenly get anxious. I can't stop thinking about what I might do if something were to happen," the emotion analysis engine recognizes this as "anxiety." The system then generates an empathetic response like, "It's very natural to feel anxious at night. I understand how you feel. It would be a little reassuring to have your contact details close at hand so you can call for help if something were to happen."

[1354] Prompt Sentence Examples

[1355] User Emotion: Anxiety

[1356] User message: When I'm alone at night, I suddenly get anxious. I can't stop thinking about what might happen.

[1357] Response message:

[1358] The above is an embodiment of the present invention.

[1359] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1360] Step 1:

[1361] The user inputs a message containing feelings such as loneliness or anxiety into a device such as a smartphone or robot. The input message is sent to a server via the Internet.

[1362] Input: A message typed by the user (e.g., "When I'm alone at night, I suddenly get anxious. I can't stop thinking about what might happen if something happens.")

[1363] Output: A message is sent from the terminal to the server.

[1364] Step 2:

[1365] The server sends the received message to the sentiment analysis engine, which uses machine learning algorithms to identify the sentiment of the message.

[1366] Input: User's message sent to the server\

[1367] Data processing: Messages are fed into a sentiment analysis engine, where an algorithmic analysis is performed.

[1368] Output: Parsed emotion (e.g. "anxiety")

[1369] Step 3:

[1370] The server generates a prompt based on the sentiment analysis results and sends it to a natural language processing model, which generates a positive and empathetic response based on the user's message and the analyzed sentiment.

[1371] Input: Sentiment analysis result and original message\

[1372] Data Calculation: Generate prompts and generate responses using natural language processing models.

[1373] Output: Generated response message (e.g., "It's very natural to feel anxious in the middle of the night. I understand how you feel. It can be a little reassuring to have your contact details handy so you can call for help if something happens.")

[1374] Step 4:

[1375] The server converts the generated response message into JSON format and sends it to the user's terminal.

[1376] Input: Generated response message\

[1377] Data processing: Convert the response into JSON format and send it to the terminal.

[1378] Output: The response message sent to the user's terminal

[1379] Step 5:

[1380] The terminal receives the response message sent by the server and displays it to the user.

[1381] Input: Response message sent from the server\

[1382] Output: A response message that is displayed on the user's terminal.

[1383] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1384] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1385] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1386] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1387] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1388] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1389] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1390] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1391] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1392] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1393] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1394] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1395] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1396] 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.

[1397] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1398] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1399] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1400] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1401] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1402] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1403] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1404] The following is further disclosed regarding the above embodiment.

[1405] (Claim 1)

[1406] means for receiving a message input by a user;

[1407] a means for generating a positive and empathetic response to an input message;

[1408] means for providing said response to a user;

[1409] A system including:

[1410] (Claim 2)

[1411] 10. The system of claim 1, wherein the means for generating a response uses a natural language processing model to generate the response.

[1412] (Claim 3)

[1413] 2. The system according to claim 1, wherein the means for receiving the input message transmits the message to a server via the Internet and processes the message at the server.

[1414] "Example 1"

[1415] (Claim 1)

[1416] means for receiving a message input by a user;

[1417] means for analyzing an input message and generating a prompt sentence;

[1418] A means for generating a positive and empathetic response using a generative AI model utilizing the generated prompt sentence; and

[1419] means for providing said response to a user;

[1420] A system including:

[1421] (Claim 2)

[1422] 10. The system of claim 1, wherein the means for generating a response uses a natural language processing model to generate the response.

[1423] (Claim 3)

[1424] 2. The system according to claim 1, wherein the means for receiving the input message transmits the message to a server via the Internet and processes the message at the server.

[1425] "Application Example 1"

[1426] (Claim 1)

[1427] means for receiving a message input by a user;

[1428] a means for generating a positive and empathetic response to an input message;

[1429] means for providing said response to a user;

[1430] means for receiving a message input by a user using the smart glasses;

[1431] means for displaying the response in conjunction with the smart glasses;

[1432] A system including:

[1433] (Claim 2)

[1434] 10. The system of claim 1, wherein the means for generating a response uses a natural language processing model to generate the response.

[1435] (Claim 3)

[1436] 2. The system according to claim 1, wherein the means for receiving the input message transmits the message to a server via the Internet and processes the message at the server.

[1437] "Example 2: Combining Emotion Engines"

[1438] (Claim 1)

[1439] means for receiving a message input by a user;

[1440] means for analyzing received messages and recognizing user emotions;

[1441] a means for generating a positive and empathetic response using a natural language processing model based on the recognized emotional information;

[1442] means for providing the generated response to a user;

[1443] A system including:

[1444] (Claim 2)

[1445] 10. The system of claim 1, wherein the means for generating a response uses a generative AI model to generate the response.

[1446] (Claim 3)

[1447] 2. The system according to claim 1, wherein the means for receiving the input message transmits the message to a server via a network and processes the message at the server.

[1448] "Application example 2 when combining emotion engines"

[1449] Extracting new parts

[1450] New parts:

[1451] 1. Analyzing messages from users with a sentiment analysis engine

[1452] 2. A natural language processing model generates a response based on the analyzed sentiment.

[1453] 3. The response will be used in applications such as the Security Counselor app.

[1454] Inventing new inventions

[1455] The original patent claims are rewritten based on the new invention.

[1456] Rewritten claims

[1457] (Claim 1)

[1458] means for receiving a message input by a user;

[1459] A means for analyzing an input message and recognizing emotions;

[1460] a means for generating a positive empathetic response based on the perceived emotion;

[1461] means for providing said response to a user;

[1462] A system including:

[1463] (Claim 2)

[1464] 10. The system of claim 1, wherein the means for generating a response uses a natural language processing model to generate the response.

[1465] (Claim 3)

[1466] 2. The system according to claim 1, wherein the means for receiving the input message transmits the message to a server via the Internet, and the server analyzes the message to recognize emotions. [Explanation of symbols]

[1467] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a message input by a user; a means for generating a positive and empathetic response to an input message; means for providing said response to a user; A system including:

2. The system of claim 1 , wherein the means for generating a response uses a natural language processing model to generate the response.

3. 2. The system according to claim 1, wherein said means for receiving an input message transmits the message to a server via the Internet and processes the message at the server.

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