System

Abstract

A system is provided.SOLUTION: The system includes a means for a user to input an emotion and text, a means for transmitting the input data of the user, a means for analyzing the received data, a means for generating an optimum message based on the analysis result, a means for transmitting the generated message to another user terminal, and a means for receiving a reaction of the other user and displaying it to the original 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] People experience a variety of emotions and thoughts in their daily lives, but often find it difficult to communicate them appropriately to others. This can easily lead to misunderstandings and conflicts, hindering smooth communication. In particular, in text-based communication, where emotional expression is poor, it is difficult to convey users' emotions appropriately. To solve this problem, a system is needed that allows users to easily and appropriately share their emotions and thoughts with others. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. A system is configured including means for a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user's terminal, and means for receiving the other user's reaction and displaying it to the original user. Furthermore, security is ensured by encrypting the data before transmission, and the received emotions are analyzed using natural language processing, allowing the user's emotional state to be accurately grasped and shared. As a result, a system is realized that makes it easy for users to share their thoughts and emotions, deepening mutual understanding and empathy.

[0006] "User" refers to an individual person who utilizes the system to input feelings and thoughts.

[0007] "Emotions" refer to various psychological states that humans experience, such as joy, sadness, and anger.

[0008] "Text" refers to a string of characters that a user enters to express their thoughts and feelings.

[0009] "Input means" refers to an interface that allows a user to input emotions and text into the system.

[0010] "Transmission means" refers to a process or module for transmitting input data to a server.

[0011] "Receiving means" refers to a process or module that allows the server to receive transmitted data.

[0012] "Analysis means" refers to a process or module that analyzes received data using natural language processing technology to understand the user's emotions and thoughts.

[0013] "Generation means" refers to the process or module that creates an appropriate message based on the analysis results.

[0014] "Transmission means (for another user terminal)" refers to a process or module for transmitting the generated message to the selected terminal of another user.

[0015] "Receiving means (receiving response)" refers to a process or module for receiving a response message from another user and displaying it to the original user.

[0016] "Encryption" refers to a security technology that converts transmitted data so that it cannot be deciphered by third parties.

[0017] "Natural Language Processing (NLP)" refers to the field and techniques of computer science for understanding and analyzing human language.

[0018] "Database" refers to a digital repository that stores analysis results and user interactions for future reference. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

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

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] 1. Overview

[0041] This invention is a system for sharing thoughts and feelings between users to deepen mutual understanding and empathy. The aim is to reduce misunderstandings and conflicts by allowing users to input their feelings and text, and then appropriately convey the analyzed data to other users. The system is provided as a cloud-based platform and can be accessed through software.

[0042] 2. System Configuration

[0043] The system is mainly composed of three main components: a user terminal, a server, and a database. The user terminal has input and receiving means, the server is responsible for analysis and message generation, and the database is responsible for storing analysis results and past interactions.

[0044] 3. Program Processing

[0045] The user enters emotions and text on the device

[0046] Users have a dedicated interface for inputting their own emotions and thoughts. Emotion options include "joy," "sadness," and "anger," and they can enter any sentence they like in the text input field. For example, they can enter, "Something very sad happened today."

[0047] Example: User (entered on the terminal)

[0048] Emotion selection: "Sadness"

[0049] Text: "Something very sad happened today."

[0050] The device sends the input data to the server

[0051] The emotion and text data entered by the user is encrypted and sent to the server using security protocols such as SSL / TLS.

[0052] Example: Terminal (data transmission)

[0053] encrypted_data = SSL / TLS(user_input)

[0054] Server (data reception)

[0055] decrypt(encrypted_data)

[0056] The server analyzes the received data

[0057] The server passes the received data to a natural language processing (NLP) engine for sentiment and text analysis. For example, it can detect a strong emotion of "sadness" from the user's text. The analysis results are stored in a database and compared with past data.

[0058] Example: Server (analysis)

[0059] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0060] Server (storing analysis results)

[0061] Database.save(user_id, emotion_analysis)

[0062] The server generates the appropriate message

[0063] Based on the analysis results, appropriate feedback messages and notification messages are generated for the user, such as "Your friend is very sad. Please say something kind to him / her."

[0064] Example: Server (message generation)

[0065] message = "My friend is very sad. Please say something kind to him."

[0066] The server sends a message to another user's device.

[0067] The generated message will be sent to the selected user's device via push notification, email, or other method of their choice.

[0068] Example: Server (data transmission)

[0069] send_notification(recipient_id, message)

[0070] Terminal (data reception)

[0071] display_notification(message)

[0072] The shared user receives the message and responds.

[0073] The receiving user can read the notification and send an appropriate response, which is then sent back to the server and displayed to the original user.

[0074] Example: Another user (entered in the terminal)

[0075] response_message = "What happened today? Let's talk and feel better."

[0076] Terminal (data transmission)

[0077] encrypted_response = SSL / TLS(response_message)

[0078] Server (data reception & analysis)

[0079] decrypt(encrypted_response)

[0080] The original user receives feedback

[0081] The original user can read the response and provide further feedback, which is then passed back to the server and communicated to other users as needed.

[0082] Example: Original user (displayed on terminal)

[0083] display_response(response_message)

[0084] Original user (entered on the terminal)

[0085] additional_feedback = "Thanks, I feel a little better now."

[0086] Terminal (data transmission)

[0087] send_feedback(additional_feedback)

[0088] 4. Specific examples of implementation

[0089] For example, user A enters, "Something very sad happened today." This data is encrypted and sent to the server, where the emotion "sadness" is analyzed using natural language processing. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then sent back through the server and displayed to user A. This process allows users A and B to share their emotions at a deep level.

[0090] As described above, this system provides a means for users to effectively share their feelings and thoughts, promoting mutual understanding and empathy.

[0091] The processing flow will be explained below.

[0092] Step 1:

[0093] User enters emotion and text

[0094] The user inputs emotions and text into the interface that opens using the device. Emotions can be selected from options such as "joy," "sadness," and "anger," and thoughts and feelings can be freely entered into the text input field. For example, the user can input "Something very sad happened today."

[0095] User (typed on device): Emotion selection: "Sadness" Text: "Something very sad happened today."

[0096] Step 2:

[0097] The device sends the input data to the server

[0098] The entered emotion and text data are encrypted on the device and sent to the server using a network protocol (e.g., SSL / TLS).

[0099] Terminal (data transmission): encrypted_data = SSL / TLS(user_input)

[0100] Server (receiving data): decrypt(encrypted_data)

[0101] Step 3:

[0102] The server analyzes the received data

[0103] The server passes the received data to a natural language processing (NLP) engine for sentiment and text analysis. The analysis engine extracts the level and type of emotion from the text and summarizes the results. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database.

[0104] Server(analysis): emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0105] Server (saving analysis results): Database.save(user_id, emotion_analysis)

[0106] Step 4:

[0107] The server generates the appropriate message

[0108] Based on the analysis results, the server generates a default or customized feedback message, along with a notification message to share with other users. For example, a message like "My friend is very sad. Please say something kind to him / her."

[0109] Server (Message generation): message = generateMessage(emotion_analysis)

[0110] Step 5:

[0111] The server sends a message to another user's device.

[0112] The generated messages and notifications are sent to other selected users via push notifications, email, or other methods depending on the user's settings.

[0113] Server (data sending): send_notification(recipient_id, message)

[0114] Device (receiving data): display_notification(message)

[0115] Step 6:

[0116] The person you shared with will receive the message

[0117] The receiving user reads the notification and, if necessary, prepares a reply message, which is sent again to the server and delivered to the original user.

[0118] Another user (typed on device): response_message = "What happened today? Let's talk and clear things up."

[0119] Terminal (data transmission): encrypted_response = SSL / TLS(response_message)

[0120] Server (receiving and analyzing data): decrypt(encrypted_response)

[0121] Step 7:

[0122] The original user receives feedback

[0123] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users if necessary.

[0124] Original user (displayed on terminal): display_response(response_message)

[0125] Original user (typed on device): additional_feedback = "Thanks, I feel a little better now."

[0126] Terminal (data transmission): send_feedback(additional_feedback)

[0127] summary

[0128] Through these steps, the system allows users to share their thoughts and feelings in real time, fostering deep levels of mutual understanding and empathy. At each step, data encryption, analysis, and feedback loops function properly to achieve high-quality communication.

[0129] Example 1

[0130] 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."

[0131] Conventional emotion sharing systems have difficulty effectively analyzing users' emotions and thoughts and generating and notifying appropriate feedback. Furthermore, data security and privacy protection may not be adequately ensured, potentially hindering the building of trust between users. Furthermore, there is a need to promote real-time interaction between users while reducing misunderstandings and conflicts.

[0132] 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.

[0133] In this invention, the server includes a means for encrypting and transmitting user input data, a means for decrypting and analyzing received data, and a means for analyzing received emotions using natural language processing. This makes it possible to securely share the user's emotions and thoughts, and to generate and notify appropriate feedback messages based on the analysis results.

[0134] "User" refers to an individual who uses the system to input emotions and text and share and receive that data.

[0135] "Emotion" refers to the expression of specific feelings or sensations that the user inputs into the system, and includes options such as "joy," "sadness," and "anger."

[0136] "Text" refers to any sentence that a user can freely input into the system.

[0137] "Means for input" refers to an interface or tool that allows a user to input emotions and text on a terminal.

[0138] "Means for sending" refers to the process and technology for sending the data entered by the user to the server.

[0139] "Encryption" refers to the technical process used to secure user-entered data, typically using the SSL / TLS protocol.

[0140] "Decryption" refers to the process of restoring encrypted data to a readable state on the server side.

[0141] "Means of analysis" refers to the technology used by the server to process and analyze the data received and understand its meaning and sentiment.

[0142] "Natural language processing" refers to the AI ​​technology used by servers to understand the meaning and sentiment of text, typically an NLP engine.

[0143] "Feedback message" refers to a response or notification to the user that the server generates based on the analysis results.

[0144] "User terminal" refers to the device through which a user accesses the system and inputs emotions and text, typically a smartphone or computer.

[0145] "Notification" refers to the communication method used to notify the user of server-generated feedback messages, including push notifications and email.

[0146] "Secure" refers to a state in which data is kept private and secure and cannot be accessed without permission.

[0147] MODE FOR CARRYING OUT THE INVENTION

[0148] 1. Overview

[0149] This invention is a system for sharing thoughts and feelings between users to deepen mutual understanding and empathy. The aim is to reduce misunderstandings and conflicts by allowing users to input their feelings and text, and then appropriately convey the analyzed data to other users. The system is provided as a cloud-based platform and can be accessed through software.

[0150] 2. System Configuration

[0151] The system is mainly composed of three main components: a user terminal, a server, and a database. The user terminal has input and receiving means, the server is responsible for analysis and message generation, and the database is responsible for storing analysis results and past interactions.

[0152] 3. Hardware and Software Used

[0153] User device: A device such as a smartphone or PC that allows the user to access the system and input emotions and text.

[0154] Server: A cloud-based server with high-performance computing power that analyzes input data and generates messages.

[0155] Database: Cloud-based data storage for analysis results and past messages.

[0156] Software: Natural language processing (NLP) engines, data encryption software via SSL / TLS protocols, push notification services, etc.

[0157] 4. Program Processing

[0158] Input method: The user inputs emotions and text through a dedicated interface. Emotion options include "joy," "sadness," and "anger," and the user can enter any text in the text input field.

[0159] Data transmission: The data entered by the user is encrypted using the SSL / TLS protocol and sent to the server.

[0160] Data analysis: The server passes the received data to a natural language processing (NLP) engine for sentiment analysis and text analysis. The analysis results are stored in a database.

[0161] Message Generation: Based on the analysis results, the server generates an appropriate feedback message, for example, "My friend is very sad. Please say some kind words to him."

[0162] Message sending: The generated message is sent to the selected user's device via push notification, email, or other method of their choice.

[0163] Feedback reception: The shared user receives the message and can send an appropriate response. The response message is sent back to the server and displayed to the original user.

[0164] Show Feedback: The original user can read the response and provide further feedback.

[0165] 5. Specific Examples

[0166] For example, user A enters, "Something very sad happened today." This data is encrypted and sent to the server, where the emotion "sadness" is analyzed using natural language processing. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then sent back through the server and displayed to user A. This process allows users A and B to share their emotions at a deep level.

[0167] 6. Examples of prompts

[0168] 1. "Generate a message to communicate to User B that User A is sad."

[0169] 2. "Please explain the steps to perform sentiment analysis and generate an appropriate response message."

[0170] This will create a system that allows users to securely share their feelings and thoughts, promoting mutual understanding and empathy.

[0171] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0172] The flow of this system's program processing

[0173] Step 1:

[0174] The user enters emotions and text on the device

[0175] explanation:

[0176] Users use a dedicated interface on their device to input their own emotions and thoughts. Emotion options include "joy," "sadness," and "anger," and they can enter any text they like in the text input field.

[0177] Input and Output:

[0178] Input: Emotion (e.g., "Sad") and text (e.g., "Something very sad happened to me today.")

[0179] Output: User input data

[0180] Specific behavior:

[0181] The user selects "sadness" from the emotion selection list, enters "Something very sad happened today" in the text box, and clicks the send button.

[0182] Step 2:

[0183] The device sends the input data to the server

[0184] explanation:

[0185] The device encrypts the emotions and text data entered by the user using the SSL / TLS protocol and securely transmits them to the server.

[0186] Input and Output:

[0187] Input: User-entered data

[0188] Output: Encrypted data

[0189] Specific behavior:

[0190] The device encrypts the data "something very sad happened today" and "sadness," and makes a request to the server to send the data.

[0191] Step 3:

[0192] The server analyzes the received data

[0193] explanation:

[0194] The server decrypts the received data using the SSL / TLS protocol, then passes it to a natural language processing (NLP) engine for sentiment and text analysis, and stores the results in a database.

[0195] Input and Output:

[0196] Input: Encrypted data

[0197] Output: Analysis result data

[0198] Specific behavior:

[0199] The server passes the decoded data to the NLP engine, which analyzes the text "Something very sad happened today" and the emotion "sadness." The analysis results are stored in a database along with the user ID.

[0200] Step 4:

[0201] The server generates the appropriate message

[0202] explanation:

[0203] Based on the analysis, the server generates a feedback message, such as "Your friend is very sad. Please say something kind to him / her."

[0204] Input and Output:

[0205] Input: Analysis result data

[0206] Output: Feedback message

[0207] Specific behavior:

[0208] The server compares the analysis results with past data and generates a notification message saying, "Your friend is very sad. Please say some kind words to him."

[0209] Step 5:

[0210] The server sends a message to another user's device.

[0211] explanation:

[0212] The generated message will be sent to the selected user's device via push notification, email, or other method of their choice.

[0213] Input and Output:

[0214] Input: Feedback message

[0215] Output: Notification message sent

[0216] Specific behavior:

[0217] The server sends a notification message to User B. On User B's device, a message saying "Your friend is very sad. Please say something kind to him / her." is displayed in the notification bar.

[0218] Step 6:

[0219] The shared user receives the message and responds.

[0220] explanation:

[0221] The receiving user can read the notification and send an appropriate response, which is then sent back to the server and displayed to the original user.

[0222] Input and Output:

[0223] Input: Notification message

[0224] Output: Response message

[0225] Specific behavior:

[0226] User B types in "What happened today? Let's talk and feel better." and clicks the send button. The device encrypts this and sends it to the server.

[0227] Step 7:

[0228] The original user receives feedback

[0229] explanation:

[0230] The original user reads the reply message and can then send further messages as feedback, which are again routed through the server and notified to other users as needed.

[0231] Input and Output:

[0232] Input: Response message

[0233] Output: Feedback message

[0234] Specific behavior:

[0235] User A reads the response, "What happened today? Let's talk and feel better," on the device, and enters and sends feedback such as, "Thank you, I feel a little better now." The device then encrypts the feedback and sends it to the server.

[0236] The above steps provide a detailed explanation of the processing flow of a system that allows users to share emotions and text and promote mutual understanding and empathy.

[0237] (Application example 1)

[0238] 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."

[0239] Current security systems face the challenge of being unable to immediately detect and respond to abnormal emotions and behaviors. In particular, when strengthening security at work or home, there are limited means of monitoring changes in the emotions and abnormalities of employees and residents in real time, making it difficult to prevent serious incidents.

[0240] 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.

[0241] In this invention, the server includes means for a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user terminal, means for receiving a response from another user and displaying it to the original user, means for acquiring video and audio data, means for analyzing the acquired data in real time, and means for detecting abnormal emotions from the analysis results and generating a notification, thereby enabling abnormal emotions and behaviors to be detected quickly and appropriate measures to be taken.

[0242] "Means for users to input emotions and text" refers to an interface that allows users to freely input their own emotions and thoughts.

[0243] "Means for transmitting user input data" refers to a communication means for transmitting data input by a user to a server.

[0244] "Means for analyzing received data" refers to software or algorithms used by the server to analyze user input data received by the server.

[0245] "Means for generating optimal messages based on analysis results" refers to a system or process for generating appropriate messages for users based on analyzed data.

[0246] The "means for transmitting the generated message to another user terminal" refers to a communication means for transmitting the generated message to another user terminal.

[0247] "Means for receiving a response from another user and displaying it to the original user" refers to a system or process for receiving a response from another user and displaying the content to the original user.

[0248] "Means for acquiring video and audio data" refers to a device or system for collecting video and audio data using a camera or microphone.

[0249] "Means for analyzing acquired data in real time" refers to software or algorithms for analyzing collected video and audio data in real time.

[0250] "Means for detecting anomalous emotions from the analysis results and generating notifications" refers to a system or process for detecting anomalous emotions from data analyzed in real time and generating corresponding notifications.

[0251] Overall system configuration

[0252] This invention is a system designed to allow users to share their thoughts and feelings and deepen mutual understanding and empathy. The system is mainly composed of three main components: a user terminal, a server, and a database.

[0253] Hardware and Software Configuration

[0254] User terminal

[0255] The user terminal is equipped with an interface for inputting emotions and text, a camera and a microphone for collecting video and audio data, and a dedicated application installed on it, which transmits the data input by the user to a server.

[0256] server

[0257] The server uses an advanced natural language processing (NLP) engine and machine learning algorithms to analyze user input data in real time. The server has the following functions:

[0258] Parses the received data and generates the appropriate message.

[0259] Video and audio data is analyzed in real time to detect abnormal emotions.

[0260] The analysis results, generated messages, and notification contents are saved in a database.

[0261] Database

[0262] The database stores users' emotional data, past interactions, and analysis results, allowing it to compare with past data to more accurately detect abnormal emotions and generate appropriate feedback.

[0263] Specific examples of hardware and software used

[0264] Camera: A device for acquiring video data

[0265] Microphone: A device for collecting audio data

[0266] PC: A computer for analyzing video and audio data

[0267] NLP engine: Natural language processing (e.g. NLPEngine)

[0268] Communication protocol: Data encryption via SSL / TLS

[0269] How to operate the system

[0270] Users can input their feelings and thoughts using an interface for inputting emotions and text, and the system captures the user's video and audio data through a camera and microphone. This data is then encrypted and sent to a server.

[0271] The server analyzes the received data and generates an appropriate message or notification if it detects an abnormal emotion. The generated message is immediately sent to another user device. The user who receives this message can check the content of the notification and take appropriate action.

[0272] Specific examples

[0273] For example, if this system is implemented in a workplace security system, an employee can input "Something very sad happened today." This data is sent to the server along with video and audio data collected through cameras and microphones. The server analyzes this data in real time and generates a notification based on the analysis results saying, "An abnormal emotion has been detected. Please check immediately." This notification is then immediately sent to the security staff's device.

[0274] Prompt Sentence Examples

[0275] For example, you could use a prompt like, "We want to use emotion analysis to improve security in the workplace. Please propose an application that can quickly detect people's anger or fear and immediately notify security staff. Please also tell us the specific implementation method and technology used."

[0276] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0277] Step 1:

[0278] The user inputs emotions and text. The user inputs "Something very sad happened today" into a dedicated interface on the terminal. This input data includes the user's emotion options and text. Input: Emotion (sadness) and text (Something very sad happened today). Output: Input data.

[0279] Step 2:

[0280] The device sends the input data to the server. The device encrypts the input emotion and text data using the SSL / TLS protocol and then sends it to the server. Input: Emotion and text data. Output: Encrypted data.

[0281] Step 3:

[0282] The server decrypts and analyzes the received data. The server decrypts the received encrypted data and passes it to a natural language processing (NLP) engine for sentiment and text analysis. Input: Encrypted data. Output: Analysis results (e.g., "very sad").

[0283] Step 4:

[0284] The server generates the optimal message based on the analysis results. Based on the analysis results, the server automatically generates a recommended message such as "Your friend is very sad. Please say something kind to them." Input: Analysis results. Output: Generated message.

[0285] Step 5:

[0286] The server sends the generated message to another user's device. The server sends the generated message to another user's device. The sending method depends on the user's settings, such as push notification or email. Input: Generated message. Output: Notification to another user's device.

[0287] Step 6:

[0288] Another user receives the message and responds. Another user receives the message, types a response such as "What happened today? Let's talk and feel better," and sends it from their device. This response is encrypted and sent to the server. Input: Generated message. Output: Response message.

[0289] Step 7:

[0290] The server sends a response message to the original user. The server decrypts the received response message and sends it to the original user's terminal. Input: Response message. Output: Feedback message to the original user.

[0291] Step 8:

[0292] The original user receives the feedback. The original user receives the feedback message and can enter their own emotions and situation again if necessary to make a further response. Input: Feedback message. Output: New emotions and text data.

[0293] In this way, users can share their thoughts and feelings in real time, deepening mutual understanding and empathy.

[0294] 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.

[0295] 1. Overview

[0296] This invention is a system for sharing thoughts and emotions between users to deepen mutual understanding and empathy. The purpose is to reduce misunderstandings and conflicts by having users input their emotions and thoughts and then appropriately convey the analyzed data to other users. Furthermore, this invention combines an emotion engine to enhance the recognition of users' emotions.

[0297] 2. System Configuration

[0298] This system consists of a user terminal, a server, a database, and an emotion engine. The user terminal is equipped with input and receiving means, and the server is responsible for analyzing data and generating messages. The database stores the analysis results and past interactions, and the emotion engine recognizes the user's emotions.

[0299] 3. Program Processing

[0300] The user enters emotions and text on the device

[0301] The user inputs emotions and text through the interface. The emotions are analyzed in real time by the emotion engine. The emotion engine integrates the selected emotion, text input, voice input, and facial expression analysis using facial recognition to determine a comprehensive emotion. For example, if a user inputs "Something very sad happened today," the emotion engine will recognize that the emotion "sadness" is strong.

[0302] Example: User (entered on the terminal)

[0303] Emotion selection: "Sadness"

[0304] Text: "Something very sad happened today."

[0305] The device sends the input data to the server

[0306] The entered emotion and text data is encrypted on the device and then sent to the server using the SSL / TLS protocol.

[0307] Example: Terminal (data transmission)

[0308] encrypted_data = SSL / TLS(user_input)

[0309] Server (data reception)

[0310] decrypt(encrypted_data)

[0311] The server analyzes the received data

[0312] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for emotion and text analysis. The analysis engine extracts emotions from the text in real time, and the emotion engine performs a comprehensive emotion determination by combining facial recognition and voice analysis. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database and compared with past data.

[0313] Example: Server (analysis)

[0314] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0315] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[0316] Server (storing analysis results)

[0317] Database.save(user_id, comprehensive_emotion)

[0318] The server generates the appropriate message

[0319] Based on the analysis results, the server generates appropriate feedback and notification messages for the user, such as "My friend is very sad. Please say some kind words to him."

[0320] Example: Server (message generation)

[0321] message = generateMessage(comprehensive_emotion)

[0322] The server sends a message to another user's device.

[0323] The generated messages and notifications will be sent to the selected other users' devices via push notifications, emails, or other methods set by the user.

[0324] Example: Server (data transmission)

[0325] send_notification(recipient_id, message)

[0326] Terminal (data reception)

[0327] display_notification(message)

[0328] The person you shared with will receive the message

[0329] The receiving user reads the notification, prepares a response message if necessary, and sends it to the server via the terminal, which then sends the message back to the server and delivers it to the original user.

[0330] Example: Another user (entered in the terminal)

[0331] response_message = "What happened today? Let's talk and feel better."

[0332] Terminal (data transmission)

[0333] encrypted_response = SSL / TLS(response_message)

[0334] Server (data reception & analysis)

[0335] decrypt(encrypted_response)

[0336] The original user receives feedback

[0337] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users as needed.

[0338] Example: Original user (displayed on terminal)

[0339] display_response(response_message)

[0340] Original user (entered on the terminal)

[0341] additional_feedback = "Thanks, I feel a little better now."

[0342] Terminal (data transmission)

[0343] send_feedback(additional_feedback)

[0344] 4. Specific examples of implementation

[0345] For example, if user A enters "Something very sad happened today," the emotion engine will determine this as "sadness." This data is encrypted and sent to the server, where it is analyzed by natural language processing and the emotion engine. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then displayed to user A via the server again. Through this process, users A and B share their emotions at a deep level, promoting mutual understanding and empathy.

[0346] As described above, the system of the present invention provides an embodiment that effectively shares users' emotions and thoughts and combines advanced emotion recognition technology, improving the quality of communication between users and facilitating the sharing of emotions.

[0347] The processing flow will be explained below.

[0348] Step 1:

[0349] User enters emotion and text

[0350] The user inputs emotions and text through the device's interface. Emotions can be selected from options such as "joy," "sadness," and "anger," and thoughts and feelings can be freely entered in the text entry field. Furthermore, facial expressions can be captured using voice input or a camera, if necessary. For example, a user can select the emotion of sadness along with the text "Something very sad happened today."

[0351] User (typed on device): Emotion selection: "Sadness" Text: "Something very sad happened today."

[0352] Step 2:

[0353] The device sends the input data to the server

[0354] The input emotion and text data, as well as audio and image data, are encrypted on the device and sent to the server using the SSL / TLS protocol.

[0355] Terminal (data transmission): encrypted_data = SSL / TLS(user_input)

[0356] Server (receiving data): decrypt(encrypted_data)

[0357] Step 3:

[0358] The server analyzes the received data

[0359] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for analysis. The natural language processing engine extracts emotions from the text, and the emotion engine performs voice analysis and facial recognition to comprehensively determine emotions. For example, text analysis may recognize strong "sadness," voice analysis may sense "sadness" from a low tone, and facial recognition may detect traces of tears.

[0360] Server(analysis): emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0361] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[0362] Server (saving analysis results): Database.save(user_id, comprehensive_emotion)

[0363] Step 4:

[0364] The server generates the appropriate message

[0365] Based on the analysis results, the server generates an appropriate feedback or notification message, such as "Your friend is very sad. Please say something kind to him / her."

[0366] Server (Message generation): message = generateMessage(comprehensive_emotion)

[0367] Step 5:

[0368] The server sends a message to another user's device.

[0369] The generated messages and notifications are sent to the selected users' devices via push notifications or emails, depending on the recipient's settings.

[0370] Server (data sending): send_notification(recipient_id, message)

[0371] Device (receiving data): display_notification(message)

[0372] Step 6:

[0373] The person you shared with will receive the message

[0374] The recipient user reads the notification, prepares a response message if necessary, and sends it from the terminal to the server, where it is again encrypted and sent to the server.

[0375] Another user (typed on device): response_message = "What happened today? Let's talk and clear things up."

[0376] Terminal (data transmission): encrypted_response = SSL / TLS(response_message)

[0377] Server (receiving and analyzing data): decrypt(encrypted_response)

[0378] Step 7:

[0379] The original user receives feedback

[0380] The original user can read the reply message from the other user and send additional feedback, which is then passed through the server again and may be notified to other users if necessary.

[0381] Original user (displayed on terminal): display_response(response_message)

[0382] Original user (typed on device): additional_feedback = "Thanks, I feel a little better now."

[0383] Terminal (data transmission): send_feedback(additional_feedback)

[0384] summary

[0385] Through these steps, the system allows users to share their thoughts and feelings in real time, fostering a deep level of mutual understanding and empathy. At each step, data encryption, analysis, and feedback loops function properly to achieve high-quality communication.

[0386] Example 2

[0387] 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."

[0388] In modern society, many people face misunderstandings and conflicts in communication. In particular, it is difficult to accurately convey emotions, resulting in a lack of mutual understanding and empathy. Therefore, a system that allows users to efficiently share their emotions and thoughts and deepen mutual understanding and empathy is needed.

[0389] 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 device for a user to input emotions and text, a device for encrypting and transmitting the input data, a device for analyzing the received data, a device for generating an appropriate message based on the analysis result, a device for transmitting the generated message to other terminals, and a device for receiving and displaying responses from other terminals. This enables users to effectively share emotions and thoughts, reducing misunderstandings and conflicts.

[0390] A "user" is an individual or group that uses the system and inputs emotions and text into a terminal.

[0391] A "device" is a combination of hardware and software that performs a specific function and is used to process data entered by a user.

[0392] "Encryption" is a technology that converts transmitted data so that it cannot be read by third parties, and is used to ensure secure data transmission.

[0393] The "SSL / TLS protocol" is an encryption protocol for securely transmitting data over the Internet, preventing data tampering and eavesdropping.

[0394] A "server" is a central processing unit that receives data sent by users and performs analysis and message generation.

[0395] A "natural language processing engine" is software that analyzes text data entered by a user and recognizes its meaning and emotion.

[0396] An "emotion engine" is software that evaluates and analyzes a user's emotions and generates appropriate messages based on the results.

[0397] A "database" is a data storage system for storing analysis results and past data, facilitating data management and retrieval.

[0398] "Message generation" is the process of creating appropriate notification or response messages based on the analysis results.

[0399] "Push notification" is a technology that sends messages directly from a server to a user's device, enabling instant information transmission.

[0400] "Feedback" is a response or additional information from a user, including a reaction or impression of another user.

[0401] 1. Overview

[0402] This invention is a system for sharing thoughts and emotions between users to deepen mutual understanding and empathy. The purpose is to reduce misunderstandings and conflicts by having users input their emotions and thoughts and then appropriately convey the analyzed data to other users. Furthermore, this invention combines an emotion engine to enhance the recognition of users' emotions.

[0403] 2. System Configuration

[0404] This system consists of a user terminal, a server, a database, and an emotion engine. The user terminal is equipped with input and receiving means, and the server is responsible for analyzing data and generating messages. The database stores the analysis results and past interactions, and the emotion engine recognizes the user's emotions.

[0405] 3. The user enters the emotion and text on the device.

[0406] The user inputs emotions and text through the interface. The emotions are analyzed in real time by the emotion engine. The emotion engine integrates the selected emotion, text input, voice input, and facial expression analysis using facial recognition to determine a comprehensive emotion. For example, if a user inputs "Something very sad happened today," the emotion engine will recognize that the emotion "sadness" is strong.

[0407] Example: User (entered on the terminal)

[0408] Emotion selection: "Sadness"

[0409] Text: "Something very sad happened today."

[0410] 4. The device sends the input data to the server

[0411] The entered emotion and text data is encrypted on the device and then sent to the server using the SSL / TLS protocol.

[0412] Example: Terminal (data transmission)

[0413] encrypted_data = SSL / TLS(user_input)

[0414] Server (data reception)

[0415] decrypt(encrypted_data)

[0416] 5. The server analyzes the received data

[0417] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for emotion and text analysis. The analysis engine extracts emotions from the text in real time, and the emotion engine performs a comprehensive emotion determination by combining facial recognition and voice analysis. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database and compared with past data.

[0418] Example: Server (analysis)

[0419] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0420] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[0421] Server (storing analysis results)

[0422] Database.save(user_id, comprehensive_emotion)

[0423] 6. The server generates the appropriate message

[0424] Based on the analysis results, the server generates appropriate feedback and notification messages for the user, such as "My friend is very sad. Please say some kind words to him."

[0425] Example: Server (message generation)

[0426] message = generateMessage(comprehensive_emotion)

[0427] 7. The server sends the message to another user device

[0428] The generated messages and notifications will be sent to the selected other users' devices via push notifications, emails, or other methods set by the user.

[0429] Example: Server (data transmission)

[0430] send_notification(recipient_id, message)

[0431] Terminal (data reception)

[0432] display_notification(message)

[0433] 8. The shared user receives the message

[0434] The receiving user reads the notification, prepares a response message if necessary, and sends it to the server via the terminal, which then sends the message back to the server and delivers it to the original user.

[0435] Example: Another user (entered in the terminal)

[0436] response_message = "What happened today? Let's talk and feel better."

[0437] Terminal (data transmission)

[0438] encrypted_response = SSL / TLS(response_message)

[0439] Server (data reception & analysis)

[0440] decrypt(encrypted_response)

[0441] 9. The original user receives feedback

[0442] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users as needed.

[0443] Example: Original user (displayed on terminal)

[0444] display_response(response_message)

[0445] Original user (entered on the terminal)

[0446] additional_feedback = "Thanks, I feel a little better now."

[0447] Terminal (data transmission)

[0448] send_feedback(additional_feedback)

[0449] 10. Specific examples of implementation

[0450] For example, if user A enters "Something very sad happened today," the emotion engine will determine this as "sadness." This data is encrypted and sent to the server, where it is analyzed by natural language processing and the emotion engine. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then displayed to user A via the server again. Through this process, users A and B share their emotions at a deep level, promoting mutual understanding and empathy.

[0451] As described above, the system of the present invention provides an embodiment that effectively shares users' emotions and thoughts and combines advanced emotion recognition technology, improving the quality of communication between users and facilitating the sharing of emotions.

[0452] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0453] Step 1: User enters emotion and text on device

[0454] The user inputs emotions and text through the device interface. By selecting an emotion and entering text, for example, "Something very sad happened today," the input data (emotion, text) is analyzed in real time by the emotion engine, and is integrated with facial recognition and voice analysis data to determine a comprehensive emotion.

[0455] Input: User emotion selection ("Sad") and text ("Something very sad happened today")

[0456] Output: Comprehensive emotion judgment data

[0457] Step 2: The device sends the input data to the server

[0458] The device encrypts the input emotion and text data using the SSL / TLS protocol and sends it to the server. Encryption ensures secure data transmission.

[0459] Input: User input data and emotion judgment data

[0460] Output: Encrypted data

[0461] Step 3: Parse the data received by the server

[0462] The server decrypts the received encrypted data using the SSL / TLS protocol and passes it to a natural language processing (NLP) engine and emotion engine for analysis. The NLP engine analyzes the text, and the emotion engine performs emotion analysis, including voice analysis and facial recognition data.

[0463] Input: Encrypted data, decrypted input data, and emotion judgment data

[0464] Output: Analyzed emotion data and text analysis results

[0465] Step 4: The server generates the appropriate message

[0466] The server generates appropriate feedback and notification messages for the user based on the analysis results, such as "My friend is very sad. Please say some kind words to him."

[0467] Input: Parsed sentiment data and text analysis results

[0468] Output: The generated feedback message

[0469] Step 5: The server sends the message to another user device

[0470] The server then sends the generated messages and notifications to the selected users' devices via push notification, email, or other methods set by the users.

[0471] Input: The generated feedback message

[0472] Output: Messages and notifications sent

[0473] Step 6: The person you shared with receives the message

[0474] Another user reads the notification and message sent, prepares an appropriate reply message based on the content, and sends the reply message to the server via the terminal.

[0475] Input: Messages and notifications sent

[0476] Output: Response message

[0477] Step 7: The original user receives feedback

[0478] The original user can read the reply message from the other user and send further feedback based on the content. This feedback is also sent via the server and notified to other users as needed.

[0479] Input: Response message

[0480] Output: More feedback messages

[0481] (Application example 2)

[0482] 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."

[0483] In factory work environments, it is difficult to grasp the health status and emotions of workers in real time, which is one of the factors that leads to a decrease in work efficiency and a worsening working environment. In particular, the lack of appropriate feedback and support for workers who are feeling fatigued or stressed is a problem.

[0484] 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 a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user terminal, means for receiving a response from another user and displaying it to the original user, means for analyzing the worker's facial expression, voice, and text and determining the worker's emotions, and means for generating appropriate feedback based on the determined emotions. This makes it possible to grasp the worker's emotions and state in real time and provide appropriate feedback and support.

[0485] A "means for user input of emotions and text" is a system or device that allows a user to input emotions and text through an interface.

[0486] The "means for transmitting user input data" refers to a communication means for transmitting data such as emotions and text input by the user to a server or other system.

[0487] "Means for analyzing received data" refers to analytical technology or software that processes the data received by the server from the user and determines their emotions or state.

[0488] The "means for generating optimal messages based on analysis results" refers to algorithms or programs for generating appropriate feedback or messages for users based on the results of data analysis.

[0489] The "means for transmitting the generated message to another user terminal" is a communication means for transmitting the generated message or feedback to the terminal of another designated user.

[0490] The "means for receiving a response from another user and displaying it to the original user" is a system or software for receiving a response or message from another user and displaying it to the original user.

[0491] "Means for analyzing the facial expressions, voice, and text of a worker and determining their emotions" refers to analytical technology and software for recognizing and determining the emotions of a worker using the worker's facial expressions, voice, and text data.

[0492] The "means for generating appropriate feedback based on the determined emotion" refers to an algorithm or program for generating appropriate feedback or support messages for the worker based on the determined emotion information.

[0493] The system for implementing this invention consists of a user terminal, a server, a database, and an emotion engine. The system analyzes the user's emotions and state in real time and provides appropriate feedback to improve the work environment and work efficiency.

[0494] System configuration

[0495] 1. User terminal: The user terminal provides an interface for the worker to input emotions and text. The emotion engine performs emotion analysis in real time, and the input data is sent to the server.

[0496] 2. Server: The server receives the data sent by the user and performs data analysis. Specifically, it performs sentiment analysis using a natural language processing (NLP) engine and an emotion engine, and generates appropriate messages and feedback based on the analysis results.

[0497] 3. Database: Includes a database for storing analysis results and past interactions, allowing historical data reference.

[0498] 4. Emotion engine: The emotion engine combines voice analysis, facial expression analysis, and text analysis to determine overall emotions.

[0499] Program processing

[0500] This system uses the following hardware and software:

[0501] Hardware:

[0502] Camera: for facial expression analysis

[0503] Microphone: For voice input

[0504] Computer: Data analysis and notification generation

[0505] software:

[0506] OpenCV: Camera image processing

[0507] EmotionEngine: Emotion recognition

[0508] NLPEngine: Text Analysis

[0509] Notification: Notification system

[0510] Processing flow and data calculation

[0511] 1. User input:

[0512] The user inputs emotions and text using the device, and the emotion engine analyzes the emotions in real time and sends the data to the server.

[0513] 2. Data transmission:

[0514] The data entered by the user is encrypted before being sent to the server. The SSL / TLS protocol is used.

[0515] 3. Data Analysis:

[0516] The server passes the received data to a natural language processing (NLP) engine and an emotion engine to perform emotion analysis and text analysis. The analysis results are stored in a database.

[0517] 4. Message Creation:

[0518] The server generates an appropriate feedback message for the user based on the analysis results. For example, if the emotion is determined to be "fatigue," an appropriate message (e.g., "You should take a break") is generated.

[0519] 5. Sending a message:

[0520] The server then sends the generated message to another user device via push notification, email, or other methods based on the user's settings.

[0521] 6. Receiving Response:

[0522] A response from another user is received and displayed to the original user.

[0523] Specific examples and prompts for the generative AI model

[0524] The system works as follows:

[0525] Examples:

[0526] The worker inputs "I'm tired," and the camera and microphone capture the situation. The results determine "fatigue" and "stress." The robot then notifies the worker, saying, "It's time to take a break."

[0527] Example prompt sentence:

[0528] "Worker has been detected as 'tired' based on facial expression, voice tone, and text input. Generate a notification to the worker suggesting a break."

[0529] This system makes it possible to grasp the emotions and state of workers in real time and provide appropriate feedback and support.

[0530] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0531] Step 1:

[0532] The user inputs emotions and text into the device. The input interface provides a text box and an emotion selection menu, and is also linked to a camera that detects facial expressions and a microphone that captures voice. The user's input includes the text data "Tired" and the emotion data "Tired," which are then analyzed in real time by the emotion engine.

[0533] Step 2:

[0534] The device encrypts the input emotion and text data and sends it to the server. The encryption uses the SSL / TLS protocol. If the input data is "tired" and "tired," the server receives it after encryption.

[0535] Step 3:

[0536] The server decrypts the received encrypted data and begins data analysis. The decrypted data is passed to a natural language processing (NLP) engine, which analyzes the text data "Tired." At the same time, the emotion engine analyzes the voice and facial expression data to determine a comprehensive emotion. For example, it may determine that "Tired" is very strong.

[0537] Step 4:

[0538] The server generates an appropriate message based on the analysis results. For example, if the result of emotion analysis is "fatigue," it generates a feedback message saying, "You should take a break." The analysis results and the generated message are stored in a database.

[0539] Step 5:

[0540] The server then sends the generated message to the worker using an appropriate notification method, such as push notification or email, and depending on the settings, a notification such as "It's best to take a break" is displayed on the worker's device.

[0541] Step 6:

[0542] The worker receives the notification and inputs a response, for example, "I'll continue working a little longer." This input data is then re-encrypted and sent to the server.

[0543] Step 7:

[0544] The server receives, decodes, and analyzes the worker's response, and determines how to address the original feedback using the results of the analysis, in this case generating a message to encourage further support.

[0545] Step 8:

[0546] The generated additional feedback message is then sent to the original worker. For example, a message saying, "Please take regular breaks and don't overexert yourself" is sent to the worker again. This process is repeated to manage the worker's health and work efficiency.

[0547] In this way, a system is realized that can grasp the emotions and state of the worker in real time and provide appropriate feedback.

[0548] 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.

[0549] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0550] 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.

[0551] [Second embodiment]

[0552] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0553] 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.

[0554] 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).

[0555] 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.

[0556] 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.

[0557] 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).

[0558] 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.

[0559] 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.

[0560] 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.

[0561] 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.

[0562] 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.

[0563] 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."

[0564] 1. Overview

[0565] This invention is a system for sharing thoughts and feelings between users to deepen mutual understanding and empathy. The aim is to reduce misunderstandings and conflicts by allowing users to input their feelings and text, and then appropriately convey the analyzed data to other users. The system is provided as a cloud-based platform and can be accessed through software.

[0566] 2. System Configuration

[0567] The system is mainly composed of three main components: a user terminal, a server, and a database. The user terminal has input and receiving means, the server is responsible for analysis and message generation, and the database is responsible for storing analysis results and past interactions.

[0568] 3. Program Processing

[0569] The user enters emotions and text on the device

[0570] Users have a dedicated interface for inputting their own emotions and thoughts. Emotion options include "joy," "sadness," and "anger," and they can enter any sentence they like in the text input field. For example, they can enter, "Something very sad happened today."

[0571] Example: User (entered on the terminal)

[0572] Emotion selection: "Sadness"

[0573] Text: "Something very sad happened today."

[0574] The device sends the input data to the server

[0575] The emotion and text data entered by the user is encrypted and sent to the server using security protocols such as SSL / TLS.

[0576] Example: Terminal (data transmission)

[0577] encrypted_data = SSL / TLS(user_input)

[0578] Server (data reception)

[0579] decrypt(encrypted_data)

[0580] The server analyzes the received data

[0581] The server passes the received data to a natural language processing (NLP) engine for sentiment and text analysis. For example, it can detect a strong emotion of "sadness" from the user's text. The analysis results are stored in a database and compared with past data.

[0582] Example: Server (analysis)

[0583] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0584] Server (storing analysis results)

[0585] Database.save(user_id, emotion_analysis)

[0586] The server generates the appropriate message

[0587] Based on the analysis results, appropriate feedback messages and notification messages are generated for the user, such as "Your friend is very sad. Please say something kind to him / her."

[0588] Example: Server (message generation)

[0589] message = "My friend is very sad. Please say something kind to him."

[0590] The server sends a message to another user's device.

[0591] The generated message will be sent to the selected user's device via push notification, email, or other method of their choice.

[0592] Example: Server (data transmission)

[0593] send_notification(recipient_id, message)

[0594] Terminal (data reception)

[0595] display_notification(message)

[0596] The shared user receives the message and responds.

[0597] The receiving user can read the notification and send an appropriate response, which is then sent back to the server and displayed to the original user.

[0598] Example: Another user (entered in the terminal)

[0599] response_message = "What happened today? Let's talk and feel better."

[0600] Terminal (data transmission)

[0601] encrypted_response = SSL / TLS(response_message)

[0602] Server (data reception & analysis)

[0603] decrypt(encrypted_response)

[0604] The original user receives feedback

[0605] The original user can read the response and provide further feedback, which is then passed back to the server and communicated to other users as needed.

[0606] Example: Original user (displayed on terminal)

[0607] display_response(response_message)

[0608] Original user (entered on the terminal)

[0609] additional_feedback = "Thanks, I feel a little better now."

[0610] Terminal (data transmission)

[0611] send_feedback(additional_feedback)

[0612] 4. Specific examples of implementation

[0613] For example, user A enters, "Something very sad happened today." This data is encrypted and sent to the server, where the emotion "sadness" is analyzed using natural language processing. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then sent back through the server and displayed to user A. This process allows users A and B to share their emotions at a deep level.

[0614] As described above, this system provides a means for users to effectively share their feelings and thoughts, promoting mutual understanding and empathy.

[0615] The processing flow will be explained below.

[0616] Step 1:

[0617] User enters emotion and text

[0618] The user inputs emotions and text into the interface that opens using the device. Emotions can be selected from options such as "joy," "sadness," and "anger," and thoughts and feelings can be freely entered into the text input field. For example, the user can input "Something very sad happened today."

[0619] User (typed on device): Emotion selection: "Sadness" Text: "Something very sad happened today."

[0620] Step 2:

[0621] The device sends the input data to the server

[0622] The entered emotion and text data are encrypted on the device and sent to the server using a network protocol (e.g., SSL / TLS).

[0623] Terminal (data transmission): encrypted_data = SSL / TLS(user_input)

[0624] Server (receiving data): decrypt(encrypted_data)

[0625] Step 3:

[0626] The server analyzes the received data

[0627] The server passes the received data to a natural language processing (NLP) engine for sentiment and text analysis. The analysis engine extracts the level and type of emotion from the text and summarizes the results. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database.

[0628] Server(analysis): emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0629] Server (saving analysis results): Database.save(user_id, emotion_analysis)

[0630] Step 4:

[0631] The server generates the appropriate message

[0632] Based on the analysis results, the server generates a default or customized feedback message, along with a notification message to share with other users. For example, a message like "My friend is very sad. Please say something kind to him / her."

[0633] Server (Message generation): message = generateMessage(emotion_analysis)

[0634] Step 5:

[0635] The server sends a message to another user's device.

[0636] The generated messages and notifications are sent to other selected users via push notifications, email, or other methods depending on the user's settings.

[0637] Server (data sending): send_notification(recipient_id, message)

[0638] Device (receiving data): display_notification(message)

[0639] Step 6:

[0640] The person you shared with will receive the message

[0641] The receiving user reads the notification and, if necessary, prepares a reply message, which is sent again to the server and delivered to the original user.

[0642] Another user (typed on device): response_message = "What happened today? Let's talk and clear things up."

[0643] Terminal (data transmission): encrypted_response = SSL / TLS(response_message)

[0644] Server (receiving and analyzing data): decrypt(encrypted_response)

[0645] Step 7:

[0646] The original user receives feedback

[0647] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users if necessary.

[0648] Original user (displayed on terminal): display_response(response_message)

[0649] Original user (typed on device): additional_feedback = "Thanks, I feel a little better now."

[0650] Terminal (data transmission): send_feedback(additional_feedback)

[0651] summary

[0652] Through these steps, the system allows users to share their thoughts and feelings in real time, fostering deep levels of mutual understanding and empathy. At each step, data encryption, analysis, and feedback loops function properly to achieve high-quality communication.

[0653] Example 1

[0654] 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."

[0655] Conventional emotion sharing systems have difficulty effectively analyzing users' emotions and thoughts and generating and notifying appropriate feedback. Furthermore, data security and privacy protection may not be adequately ensured, potentially hindering the building of trust between users. Furthermore, there is a need to promote real-time interaction between users while reducing misunderstandings and conflicts.

[0656] 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.

[0657] In this invention, the server includes a means for encrypting and transmitting user input data, a means for decrypting and analyzing received data, and a means for analyzing received emotions using natural language processing. This makes it possible to securely share the user's emotions and thoughts, and to generate and notify appropriate feedback messages based on the analysis results.

[0658] "User" refers to an individual who uses the system to input emotions and text and share and receive that data.

[0659] "Emotion" refers to the expression of specific feelings or sensations that the user inputs into the system, and includes options such as "joy," "sadness," and "anger."

[0660] "Text" refers to any sentence that a user can freely input into the system.

[0661] "Means for input" refers to an interface or tool that allows a user to input emotions and text on a terminal.

[0662] "Means for sending" refers to the process and technology for sending the data entered by the user to the server.

[0663] "Encryption" refers to the technical process used to secure user-entered data, typically using the SSL / TLS protocol.

[0664] "Decryption" refers to the process of restoring encrypted data to a readable state on the server side.

[0665] "Means of analysis" refers to the technology used by the server to process and analyze the data received and understand its meaning and sentiment.

[0666] "Natural language processing" refers to the AI ​​technology used by servers to understand the meaning and sentiment of text, typically an NLP engine.

[0667] "Feedback message" refers to a response or notification to the user that the server generates based on the analysis results.

[0668] "User terminal" refers to the device through which a user accesses the system and inputs emotions and text, typically a smartphone or computer.

[0669] "Notification" refers to the communication method used to notify the user of server-generated feedback messages, including push notifications and email.

[0670] "Secure" refers to a state in which data is kept private and secure and cannot be accessed without permission.

[0671] MODE FOR CARRYING OUT THE INVENTION

[0672] 1. Overview

[0673] This invention is a system for sharing thoughts and feelings between users to deepen mutual understanding and empathy. The aim is to reduce misunderstandings and conflicts by allowing users to input their feelings and text, and then appropriately convey the analyzed data to other users. The system is provided as a cloud-based platform and can be accessed through software.

[0674] 2. System Configuration

[0675] The system is mainly composed of three main components: a user terminal, a server, and a database. The user terminal has input and receiving means, the server is responsible for analysis and message generation, and the database is responsible for storing analysis results and past interactions.

[0676] 3. Hardware and Software Used

[0677] User device: A device such as a smartphone or PC that allows the user to access the system and input emotions and text.

[0678] Server: A cloud-based server with high-performance computing power that analyzes input data and generates messages.

[0679] Database: Cloud-based data storage for analysis results and past messages.

[0680] Software: Natural language processing (NLP) engines, data encryption software via SSL / TLS protocols, push notification services, etc.

[0681] 4. Program Processing

[0682] Input method: The user inputs emotions and text through a dedicated interface. Emotion options include "joy," "sadness," and "anger," and the user can enter any text in the text input field.

[0683] Data transmission: The data entered by the user is encrypted using the SSL / TLS protocol and sent to the server.

[0684] Data analysis: The server passes the received data to a natural language processing (NLP) engine for sentiment analysis and text analysis. The analysis results are stored in a database.

[0685] Message Generation: Based on the analysis results, the server generates an appropriate feedback message, for example, "My friend is very sad. Please say some kind words to him."

[0686] Message sending: The generated message is sent to the selected user's device via push notification, email, or other method of their choice.

[0687] Feedback reception: The shared user receives the message and can send an appropriate response. The response message is sent back to the server and displayed to the original user.

[0688] Show Feedback: The original user can read the response and provide further feedback.

[0689] 5. Specific Examples

[0690] For example, user A enters, "Something very sad happened today." This data is encrypted and sent to the server, where the emotion "sadness" is analyzed using natural language processing. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then sent back through the server and displayed to user A. This process allows users A and B to share their emotions at a deep level.

[0691] 6. Examples of prompts

[0692] 1. "Generate a message to communicate to User B that User A is sad."

[0693] 2. "Please explain the steps to perform sentiment analysis and generate an appropriate response message."

[0694] This will create a system that allows users to securely share their feelings and thoughts, promoting mutual understanding and empathy.

[0695] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0696] The flow of this system's program processing

[0697] Step 1:

[0698] The user enters emotions and text on the device

[0699] explanation:

[0700] Users use a dedicated interface on their device to input their own emotions and thoughts. Emotion options include "joy," "sadness," and "anger," and they can enter any text they like in the text input field.

[0701] Input and Output:

[0702] Input: Emotion (e.g., "Sad") and text (e.g., "Something very sad happened to me today.")

[0703] Output: User input data

[0704] Specific behavior:

[0705] The user selects "sadness" from the emotion selection list, enters "Something very sad happened today" in the text box, and clicks the send button.

[0706] Step 2:

[0707] The device sends the input data to the server

[0708] explanation:

[0709] The device encrypts the emotions and text data entered by the user using the SSL / TLS protocol and securely transmits them to the server.

[0710] Input and Output:

[0711] Input: User-entered data

[0712] Output: Encrypted data

[0713] Specific behavior:

[0714] The device encrypts the data "something very sad happened today" and "sadness," and makes a request to the server to send the data.

[0715] Step 3:

[0716] The server analyzes the received data

[0717] explanation:

[0718] The server decrypts the received data using the SSL / TLS protocol, then passes it to a natural language processing (NLP) engine for sentiment and text analysis, and stores the results in a database.

[0719] Input and Output:

[0720] Input: Encrypted data

[0721] Output: Analysis result data

[0722] Specific behavior:

[0723] The server passes the decoded data to the NLP engine, which analyzes the text "Something very sad happened today" and the emotion "sadness." The analysis results are stored in a database along with the user ID.

[0724] Step 4:

[0725] The server generates the appropriate message

[0726] explanation:

[0727] Based on the analysis, the server generates a feedback message, such as "Your friend is very sad. Please say something kind to him / her."

[0728] Input and Output:

[0729] Input: Analysis result data

[0730] Output: Feedback message

[0731] Specific behavior:

[0732] The server compares the analysis results with past data and generates a notification message saying, "Your friend is very sad. Please say some kind words to him."

[0733] Step 5:

[0734] The server sends a message to another user's device.

[0735] explanation:

[0736] The generated message will be sent to the selected user's device via push notification, email, or other method of their choice.

[0737] Input and Output:

[0738] Input: Feedback message

[0739] Output: Notification message sent

[0740] Specific behavior:

[0741] The server sends a notification message to User B. On User B's device, a message saying "Your friend is very sad. Please say something kind to him / her." is displayed in the notification bar.

[0742] Step 6:

[0743] The shared user receives the message and responds.

[0744] explanation:

[0745] The receiving user can read the notification and send an appropriate response, which is then sent back to the server and displayed to the original user.

[0746] Input and Output:

[0747] Input: Notification message

[0748] Output: Response message

[0749] Specific behavior:

[0750] User B types in "What happened today? Let's talk and feel better." and clicks the send button. The device encrypts this and sends it to the server.

[0751] Step 7:

[0752] The original user receives feedback

[0753] explanation:

[0754] The original user reads the reply message and can then send further messages as feedback, which are again routed through the server and notified to other users as needed.

[0755] Input and Output:

[0756] Input: Response message

[0757] Output: Feedback message

[0758] Specific behavior:

[0759] User A reads the response, "What happened today? Let's talk and feel better," on the device, and enters and sends feedback such as, "Thank you, I feel a little better now." The device then encrypts the feedback and sends it to the server.

[0760] The above steps provide a detailed explanation of the processing flow of a system that allows users to share emotions and text and promote mutual understanding and empathy.

[0761] (Application example 1)

[0762] 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."

[0763] Current security systems face the challenge of being unable to immediately detect and respond to abnormal emotions and behaviors. In particular, when strengthening security at work or home, there are limited means of monitoring changes in the emotions and abnormalities of employees and residents in real time, making it difficult to prevent serious incidents.

[0764] 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.

[0765] In this invention, the server includes means for a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user terminal, means for receiving a response from another user and displaying it to the original user, means for acquiring video and audio data, means for analyzing the acquired data in real time, and means for detecting abnormal emotions from the analysis results and generating a notification, thereby enabling abnormal emotions and behaviors to be detected quickly and appropriate measures to be taken.

[0766] "Means for users to input emotions and text" refers to an interface that allows users to freely input their own emotions and thoughts.

[0767] "Means for transmitting user input data" refers to a communication means for transmitting data input by a user to a server.

[0768] "Means for analyzing received data" refers to software or algorithms used by the server to analyze user input data received by the server.

[0769] "Means for generating optimal messages based on analysis results" refers to a system or process for generating appropriate messages for users based on analyzed data.

[0770] The "means for transmitting the generated message to another user terminal" refers to a communication means for transmitting the generated message to another user terminal.

[0771] "Means for receiving a response from another user and displaying it to the original user" refers to a system or process for receiving a response from another user and displaying the content to the original user.

[0772] "Means for acquiring video and audio data" refers to a device or system for collecting video and audio data using a camera or microphone.

[0773] "Means for analyzing acquired data in real time" refers to software or algorithms for analyzing collected video and audio data in real time.

[0774] "Means for detecting anomalous emotions from the analysis results and generating notifications" refers to a system or process for detecting anomalous emotions from data analyzed in real time and generating corresponding notifications.

[0775] Overall system configuration

[0776] This invention is a system designed to allow users to share their thoughts and feelings and deepen mutual understanding and empathy. The system is mainly composed of three main components: a user terminal, a server, and a database.

[0777] Hardware and Software Configuration

[0778] User terminal

[0779] The user terminal is equipped with an interface for inputting emotions and text, a camera and a microphone for collecting video and audio data, and a dedicated application installed on it, which transmits the data input by the user to a server.

[0780] server

[0781] The server uses an advanced natural language processing (NLP) engine and machine learning algorithms to analyze user input data in real time. The server has the following functions:

[0782] Parses the received data and generates the appropriate message.

[0783] Video and audio data is analyzed in real time to detect abnormal emotions.

[0784] The analysis results, generated messages, and notification contents are saved in a database.

[0785] Database

[0786] The database stores users' emotional data, past interactions, and analysis results, allowing it to compare with past data to more accurately detect abnormal emotions and generate appropriate feedback.

[0787] Specific examples of hardware and software used

[0788] Camera: A device for acquiring video data

[0789] Microphone: A device for collecting audio data

[0790] PC: A computer for analyzing video and audio data

[0791] NLP engine: Natural language processing (e.g. NLPEngine)

[0792] Communication protocol: Data encryption via SSL / TLS

[0793] How to operate the system

[0794] Users can input their feelings and thoughts using an interface for inputting emotions and text, and the system captures the user's video and audio data through a camera and microphone. This data is then encrypted and sent to a server.

[0795] The server analyzes the received data and generates an appropriate message or notification if it detects an abnormal emotion. The generated message is immediately sent to another user device. The user who receives this message can check the content of the notification and take appropriate action.

[0796] Specific examples

[0797] For example, if this system is implemented in a workplace security system, an employee can input "Something very sad happened today." This data is sent to the server along with video and audio data collected through cameras and microphones. The server analyzes this data in real time and generates a notification based on the analysis results saying, "An abnormal emotion has been detected. Please check immediately." This notification is then immediately sent to the security staff's device.

[0798] Prompt Sentence Examples

[0799] For example, you could use a prompt like, "We want to use emotion analysis to improve security in the workplace. Please propose an application that can quickly detect people's anger or fear and immediately notify security staff. Please also tell us the specific implementation method and technology used."

[0800] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0801] Step 1:

[0802] The user inputs emotions and text. The user inputs "Something very sad happened today" into a dedicated interface on the terminal. This input data includes the user's emotion options and text. Input: Emotion (sadness) and text (Something very sad happened today). Output: Input data.

[0803] Step 2:

[0804] The device sends the input data to the server. The device encrypts the input emotion and text data using the SSL / TLS protocol and then sends it to the server. Input: Emotion and text data. Output: Encrypted data.

[0805] Step 3:

[0806] The server decrypts and analyzes the received data. The server decrypts the received encrypted data and passes it to a natural language processing (NLP) engine for sentiment and text analysis. Input: Encrypted data. Output: Analysis results (e.g., "very sad").

[0807] Step 4:

[0808] The server generates the optimal message based on the analysis results. Based on the analysis results, the server automatically generates a recommended message such as "Your friend is very sad. Please say something kind to them." Input: Analysis results. Output: Generated message.

[0809] Step 5:

[0810] The server sends the generated message to another user's device. The server sends the generated message to another user's device. The sending method depends on the user's settings, such as push notification or email. Input: Generated message. Output: Notification to another user's device.

[0811] Step 6:

[0812] Another user receives the message and responds. Another user receives the message, types a response such as "What happened today? Let's talk and feel better," and sends it from their device. This response is encrypted and sent to the server. Input: Generated message. Output: Response message.

[0813] Step 7:

[0814] The server sends a response message to the original user. The server decrypts the received response message and sends it to the original user's terminal. Input: Response message. Output: Feedback message to the original user.

[0815] Step 8:

[0816] The original user receives the feedback. The original user receives the feedback message and can enter their own emotions and situation again if necessary to make a further response. Input: Feedback message. Output: New emotions and text data.

[0817] In this way, users can share their thoughts and feelings in real time, deepening mutual understanding and empathy.

[0818] 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.

[0819] 1. Overview

[0820] This invention is a system for sharing thoughts and emotions between users to deepen mutual understanding and empathy. The purpose is to reduce misunderstandings and conflicts by having users input their emotions and thoughts and then appropriately convey the analyzed data to other users. Furthermore, this invention combines an emotion engine to enhance the recognition of users' emotions.

[0821] 2. System Configuration

[0822] This system consists of a user terminal, a server, a database, and an emotion engine. The user terminal is equipped with input and receiving means, and the server is responsible for analyzing data and generating messages. The database stores the analysis results and past interactions, and the emotion engine recognizes the user's emotions.

[0823] 3. Program Processing

[0824] The user enters emotions and text on the device

[0825] The user inputs emotions and text through the interface. The emotions are analyzed in real time by the emotion engine. The emotion engine integrates the selected emotion, text input, voice input, and facial expression analysis using facial recognition to determine a comprehensive emotion. For example, if a user inputs "Something very sad happened today," the emotion engine will recognize that the emotion "sadness" is strong.

[0826] Example: User (entered on the terminal)

[0827] Emotion selection: "Sadness"

[0828] Text: "Something very sad happened today."

[0829] The device sends the input data to the server

[0830] The entered emotion and text data is encrypted on the device and then sent to the server using the SSL / TLS protocol.

[0831] Example: Terminal (data transmission)

[0832] encrypted_data = SSL / TLS(user_input)

[0833] Server (data reception)

[0834] decrypt(encrypted_data)

[0835] The server analyzes the received data

[0836] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for emotion and text analysis. The analysis engine extracts emotions from the text in real time, and the emotion engine performs a comprehensive emotion determination by combining facial recognition and voice analysis. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database and compared with past data.

[0837] Example: Server (analysis)

[0838] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0839] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[0840] Server (storing analysis results)

[0841] Database.save(user_id, comprehensive_emotion)

[0842] The server generates the appropriate message

[0843] Based on the analysis results, the server generates appropriate feedback and notification messages for the user, such as "My friend is very sad. Please say some kind words to him."

[0844] Example: Server (message generation)

[0845] message = generateMessage(comprehensive_emotion)

[0846] The server sends a message to another user's device.

[0847] The generated messages and notifications will be sent to the selected other users' devices via push notifications, emails, or other methods set by the user.

[0848] Example: Server (data transmission)

[0849] send_notification(recipient_id, message)

[0850] Terminal (data reception)

[0851] display_notification(message)

[0852] The person you shared with will receive the message

[0853] The receiving user reads the notification, prepares a response message if necessary, and sends it to the server via the terminal, which then sends the message back to the server and delivers it to the original user.

[0854] Example: Another user (entered in the terminal)

[0855] response_message = "What happened today? Let's talk and feel better."

[0856] Terminal (data transmission)

[0857] encrypted_response = SSL / TLS(response_message)

[0858] Server (data reception & analysis)

[0859] decrypt(encrypted_response)

[0860] The original user receives feedback

[0861] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users as needed.

[0862] Example: Original user (displayed on terminal)

[0863] display_response(response_message)

[0864] Original user (entered on the terminal)

[0865] additional_feedback = "Thanks, I feel a little better now."

[0866] Terminal (data transmission)

[0867] send_feedback(additional_feedback)

[0868] 4. Specific examples of implementation

[0869] For example, if user A enters "Something very sad happened today," the emotion engine will determine this as "sadness." This data is encrypted and sent to the server, where it is analyzed by natural language processing and the emotion engine. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then displayed to user A via the server again. Through this process, users A and B share their emotions at a deep level, promoting mutual understanding and empathy.

[0870] As described above, the system of the present invention provides an embodiment that effectively shares users' emotions and thoughts and combines advanced emotion recognition technology, improving the quality of communication between users and facilitating the sharing of emotions.

[0871] The processing flow will be explained below.

[0872] Step 1:

[0873] User enters emotion and text

[0874] The user inputs emotions and text through the device's interface. Emotions can be selected from options such as "joy," "sadness," and "anger," and thoughts and feelings can be freely entered in the text entry field. Furthermore, facial expressions can be captured using voice input or a camera, if necessary. For example, a user can select the emotion of sadness along with the text "Something very sad happened today."

[0875] User (typed on device): Emotion selection: "Sadness" Text: "Something very sad happened today."

[0876] Step 2:

[0877] The device sends the input data to the server

[0878] The input emotion and text data, as well as audio and image data, are encrypted on the device and sent to the server using the SSL / TLS protocol.

[0879] Terminal (data transmission): encrypted_data = SSL / TLS(user_input)

[0880] Server (receiving data): decrypt(encrypted_data)

[0881] Step 3:

[0882] The server analyzes the received data

[0883] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for analysis. The natural language processing engine extracts emotions from the text, and the emotion engine performs voice analysis and facial recognition to comprehensively determine emotions. For example, text analysis may recognize strong "sadness," voice analysis may sense "sadness" from a low tone, and facial recognition may detect traces of tears.

[0884] Server(analysis): emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0885] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[0886] Server (saving analysis results): Database.save(user_id, comprehensive_emotion)

[0887] Step 4:

[0888] The server generates the appropriate message

[0889] Based on the analysis results, the server generates an appropriate feedback or notification message, such as "Your friend is very sad. Please say something kind to him / her."

[0890] Server (Message generation): message = generateMessage(comprehensive_emotion)

[0891] Step 5:

[0892] The server sends a message to another user's device.

[0893] The generated messages and notifications are sent to the selected users' devices via push notifications or emails, depending on the recipient's settings.

[0894] Server (data sending): send_notification(recipient_id, message)

[0895] Device (receiving data): display_notification(message)

[0896] Step 6:

[0897] The person you shared with will receive the message

[0898] The recipient user reads the notification, prepares a response message if necessary, and sends it from the terminal to the server, where it is again encrypted and sent to the server.

[0899] Another user (typed on device): response_message = "What happened today? Let's talk and clear things up."

[0900] Terminal (data transmission): encrypted_response = SSL / TLS(response_message)

[0901] Server (receiving and analyzing data): decrypt(encrypted_response)

[0902] Step 7:

[0903] The original user receives feedback

[0904] The original user can read the reply message from the other user and send additional feedback, which is then passed through the server again and may be notified to other users if necessary.

[0905] Original user (displayed on terminal): display_response(response_message)

[0906] Original user (typed on device): additional_feedback = "Thanks, I feel a little better now."

[0907] Terminal (data transmission): send_feedback(additional_feedback)

[0908] summary

[0909] Through these steps, the system allows users to share their thoughts and feelings in real time, fostering a deep level of mutual understanding and empathy. At each step, data encryption, analysis, and feedback loops function properly to achieve high-quality communication.

[0910] Example 2

[0911] 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."

[0912] In modern society, many people face misunderstandings and conflicts in communication. In particular, it is difficult to accurately convey emotions, resulting in a lack of mutual understanding and empathy. Therefore, a system that allows users to efficiently share their emotions and thoughts and deepen mutual understanding and empathy is needed.

[0913] 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 device for a user to input emotions and text, a device for encrypting and transmitting the input data, a device for analyzing the received data, a device for generating an appropriate message based on the analysis result, a device for transmitting the generated message to other terminals, and a device for receiving and displaying responses from other terminals. This enables users to effectively share emotions and thoughts, reducing misunderstandings and conflicts.

[0914] A "user" is an individual or group that uses the system and inputs emotions and text into a terminal.

[0915] A "device" is a combination of hardware and software that performs a specific function and is used to process data entered by a user.

[0916] "Encryption" is a technology that converts transmitted data so that it cannot be read by third parties, and is used to ensure secure data transmission.

[0917] The "SSL / TLS protocol" is an encryption protocol for securely transmitting data over the Internet, preventing data tampering and eavesdropping.

[0918] A "server" is a central processing unit that receives data sent by users and performs analysis and message generation.

[0919] A "natural language processing engine" is software that analyzes text data entered by a user and recognizes its meaning and emotion.

[0920] An "emotion engine" is software that evaluates and analyzes a user's emotions and generates appropriate messages based on the results.

[0921] A "database" is a data storage system for storing analysis results and past data, facilitating data management and retrieval.

[0922] "Message generation" is the process of creating appropriate notification or response messages based on the analysis results.

[0923] "Push notification" is a technology that sends messages directly from a server to a user's device, enabling instant information transmission.

[0924] "Feedback" is a response or additional information from a user, including a reaction or impression of another user.

[0925] 1. Overview

[0926] This invention is a system for sharing thoughts and emotions between users to deepen mutual understanding and empathy. The purpose is to reduce misunderstandings and conflicts by having users input their emotions and thoughts and then appropriately convey the analyzed data to other users. Furthermore, this invention combines an emotion engine to enhance the recognition of users' emotions.

[0927] 2. System Configuration

[0928] This system consists of a user terminal, a server, a database, and an emotion engine. The user terminal is equipped with input and receiving means, and the server is responsible for analyzing data and generating messages. The database stores the analysis results and past interactions, and the emotion engine recognizes the user's emotions.

[0929] 3. The user enters the emotion and text on the device.

[0930] The user inputs emotions and text through the interface. The emotions are analyzed in real time by the emotion engine. The emotion engine integrates the selected emotion, text input, voice input, and facial expression analysis using facial recognition to determine a comprehensive emotion. For example, if a user inputs "Something very sad happened today," the emotion engine will recognize that the emotion "sadness" is strong.

[0931] Example: User (entered on the terminal)

[0932] Emotion selection: "Sadness"

[0933] Text: "Something very sad happened today."

[0934] 4. The device sends the input data to the server

[0935] The entered emotion and text data is encrypted on the device and then sent to the server using the SSL / TLS protocol.

[0936] Example: Terminal (data transmission)

[0937] encrypted_data = SSL / TLS(user_input)

[0938] Server (data reception)

[0939] decrypt(encrypted_data)

[0940] 5. The server analyzes the received data

[0941] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for emotion and text analysis. The analysis engine extracts emotions from the text in real time, and the emotion engine performs a comprehensive emotion determination by combining facial recognition and voice analysis. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database and compared with past data.

[0942] Example: Server (analysis)

[0943] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[0944] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[0945] Server (storing analysis results)

[0946] Database.save(user_id, comprehensive_emotion)

[0947] 6. The server generates the appropriate message

[0948] Based on the analysis results, the server generates appropriate feedback and notification messages for the user, such as "My friend is very sad. Please say some kind words to him."

[0949] Example: Server (message generation)

[0950] message = generateMessage(comprehensive_emotion)

[0951] 7. The server sends the message to another user device

[0952] The generated messages and notifications will be sent to the selected other users' devices via push notifications, emails, or other methods set by the user.

[0953] Example: Server (data transmission)

[0954] send_notification(recipient_id, message)

[0955] Terminal (data reception)

[0956] display_notification(message)

[0957] 8. The shared user receives the message

[0958] The receiving user reads the notification, prepares a response message if necessary, and sends it to the server via the terminal, which then sends the message back to the server and delivers it to the original user.

[0959] Example: Another user (entered in the terminal)

[0960] response_message = "What happened today? Let's talk and feel better."

[0961] Terminal (data transmission)

[0962] encrypted_response = SSL / TLS(response_message)

[0963] Server (data reception & analysis)

[0964] decrypt(encrypted_response)

[0965] 9. The original user receives feedback

[0966] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users as needed.

[0967] Example: Original user (displayed on terminal)

[0968] display_response(response_message)

[0969] Original user (entered on the terminal)

[0970] additional_feedback = "Thanks, I feel a little better now."

[0971] Terminal (data transmission)

[0972] send_feedback(additional_feedback)

[0973] 10. Specific examples of implementation

[0974] For example, if user A enters "Something very sad happened today," the emotion engine will determine this as "sadness." This data is encrypted and sent to the server, where it is analyzed by natural language processing and the emotion engine. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then displayed to user A via the server again. Through this process, users A and B share their emotions at a deep level, promoting mutual understanding and empathy.

[0975] As described above, the system of the present invention provides an embodiment that effectively shares users' emotions and thoughts and combines advanced emotion recognition technology, improving the quality of communication between users and facilitating the sharing of emotions.

[0976] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0977] Step 1: User enters emotion and text on device

[0978] The user inputs emotions and text through the device interface. By selecting an emotion and entering text, for example, "Something very sad happened today," the input data (emotion, text) is analyzed in real time by the emotion engine, and is integrated with facial recognition and voice analysis data to determine a comprehensive emotion.

[0979] Input: User emotion selection ("Sad") and text ("Something very sad happened today")

[0980] Output: Comprehensive emotion judgment data

[0981] Step 2: The device sends the input data to the server

[0982] The device encrypts the input emotion and text data using the SSL / TLS protocol and sends it to the server. Encryption ensures secure data transmission.

[0983] Input: User input data and emotion judgment data

[0984] Output: Encrypted data

[0985] Step 3: Parse the data received by the server

[0986] The server decrypts the received encrypted data using the SSL / TLS protocol and passes it to a natural language processing (NLP) engine and emotion engine for analysis. The NLP engine analyzes the text, and the emotion engine performs emotion analysis, including voice analysis and facial recognition data.

[0987] Input: Encrypted data, decrypted input data, and emotion judgment data

[0988] Output: Analyzed emotion data and text analysis results

[0989] Step 4: The server generates the appropriate message

[0990] The server generates appropriate feedback and notification messages for the user based on the analysis results, such as "My friend is very sad. Please say some kind words to him."

[0991] Input: Parsed sentiment data and text analysis results

[0992] Output: The generated feedback message

[0993] Step 5: The server sends the message to another user device

[0994] The server then sends the generated messages and notifications to the selected users' devices via push notification, email, or other methods set by the users.

[0995] Input: The generated feedback message

[0996] Output: Messages and notifications sent

[0997] Step 6: The person you shared with receives the message

[0998] Another user reads the notification and message sent, prepares an appropriate reply message based on the content, and sends the reply message to the server via the terminal.

[0999] Input: Messages and notifications sent

[1000] Output: Response message

[1001] Step 7: The original user receives feedback

[1002] The original user can read the reply message from the other user and send further feedback based on the content. This feedback is also sent via the server and notified to other users as needed.

[1003] Input: Response message

[1004] Output: More feedback messages

[1005] (Application example 2)

[1006] 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."

[1007] In factory work environments, it is difficult to grasp the health status and emotions of workers in real time, which is one of the factors that leads to a decrease in work efficiency and a worsening working environment. In particular, the lack of appropriate feedback and support for workers who are feeling fatigued or stressed is a problem.

[1008] 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 a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user terminal, means for receiving a response from another user and displaying it to the original user, means for analyzing the worker's facial expression, voice, and text and determining the worker's emotions, and means for generating appropriate feedback based on the determined emotions. This makes it possible to grasp the worker's emotions and state in real time and provide appropriate feedback and support.

[1009] A "means for user input of emotions and text" is a system or device that allows a user to input emotions and text through an interface.

[1010] The "means for transmitting user input data" refers to a communication means for transmitting data such as emotions and text input by the user to a server or other system.

[1011] "Means for analyzing received data" refers to analytical technology or software that processes the data received by the server from the user and determines their emotions or state.

[1012] The "means for generating optimal messages based on analysis results" refers to algorithms or programs for generating appropriate feedback or messages for users based on the results of data analysis.

[1013] The "means for transmitting the generated message to another user terminal" is a communication means for transmitting the generated message or feedback to the terminal of another designated user.

[1014] The "means for receiving a response from another user and displaying it to the original user" is a system or software for receiving a response or message from another user and displaying it to the original user.

[1015] "Means for analyzing the facial expressions, voice, and text of a worker and determining their emotions" refers to analytical technology and software for recognizing and determining the emotions of a worker using the worker's facial expressions, voice, and text data.

[1016] The "means for generating appropriate feedback based on the determined emotion" refers to an algorithm or program for generating appropriate feedback or support messages for the worker based on the determined emotion information.

[1017] The system for implementing this invention consists of a user terminal, a server, a database, and an emotion engine. The system analyzes the user's emotions and state in real time and provides appropriate feedback to improve the work environment and work efficiency.

[1018] System configuration

[1019] 1. User terminal: The user terminal provides an interface for the worker to input emotions and text. The emotion engine performs emotion analysis in real time, and the input data is sent to the server.

[1020] 2. Server: The server receives the data sent by the user and performs data analysis. Specifically, it performs sentiment analysis using a natural language processing (NLP) engine and an emotion engine, and generates appropriate messages and feedback based on the analysis results.

[1021] 3. Database: Includes a database for storing analysis results and past interactions, allowing historical data reference.

[1022] 4. Emotion engine: The emotion engine combines voice analysis, facial expression analysis, and text analysis to determine overall emotions.

[1023] Program processing

[1024] This system uses the following hardware and software:

[1025] Hardware:

[1026] Camera: for facial expression analysis

[1027] Microphone: For voice input

[1028] Computer: Data analysis and notification generation

[1029] software:

[1030] OpenCV: Camera image processing

[1031] EmotionEngine: Emotion recognition

[1032] NLPEngine: Text Analysis

[1033] Notification: Notification system

[1034] Processing flow and data calculation

[1035] 1. User input:

[1036] The user inputs emotions and text using the device, and the emotion engine analyzes the emotions in real time and sends the data to the server.

[1037] 2. Data transmission:

[1038] The data entered by the user is encrypted before being sent to the server. The SSL / TLS protocol is used.

[1039] 3. Data Analysis:

[1040] The server passes the received data to a natural language processing (NLP) engine and an emotion engine to perform emotion analysis and text analysis. The analysis results are stored in a database.

[1041] 4. Message Creation:

[1042] The server generates an appropriate feedback message for the user based on the analysis results. For example, if the emotion is determined to be "fatigue," an appropriate message (e.g., "You should take a break") is generated.

[1043] 5. Sending a message:

[1044] The server then sends the generated message to another user device via push notification, email, or other methods based on the user's settings.

[1045] 6. Receiving Response:

[1046] A response from another user is received and displayed to the original user.

[1047] Specific examples and prompts for the generative AI model

[1048] The system works as follows:

[1049] Examples:

[1050] The worker inputs "I'm tired," and the camera and microphone capture the situation. The results determine "fatigue" and "stress." The robot then notifies the worker, saying, "It's time to take a break."

[1051] Example prompt sentence:

[1052] "Worker has been detected as 'tired' based on facial expression, voice tone, and text input. Generate a notification to the worker suggesting a break."

[1053] This system makes it possible to grasp the emotions and state of workers in real time and provide appropriate feedback and support.

[1054] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1055] Step 1:

[1056] The user inputs emotions and text into the device. The input interface provides a text box and an emotion selection menu, and is also linked to a camera that detects facial expressions and a microphone that captures voice. The user's input includes the text data "Tired" and the emotion data "Tired," which are then analyzed in real time by the emotion engine.

[1057] Step 2:

[1058] The device encrypts the input emotion and text data and sends it to the server. The encryption uses the SSL / TLS protocol. If the input data is "tired" and "tired," the server receives it after encryption.

[1059] Step 3:

[1060] The server decrypts the received encrypted data and begins data analysis. The decrypted data is passed to a natural language processing (NLP) engine, which analyzes the text data "Tired." At the same time, the emotion engine analyzes the voice and facial expression data to determine a comprehensive emotion. For example, it may determine that "Tired" is very strong.

[1061] Step 4:

[1062] The server generates an appropriate message based on the analysis results. For example, if the result of emotion analysis is "fatigue," it generates a feedback message saying, "You should take a break." The analysis results and the generated message are stored in a database.

[1063] Step 5:

[1064] The server then sends the generated message to the worker using an appropriate notification method, such as push notification or email, and depending on the settings, a notification such as "It's best to take a break" is displayed on the worker's device.

[1065] Step 6:

[1066] The worker receives the notification and inputs a response, for example, "I'll continue working a little longer." This input data is then re-encrypted and sent to the server.

[1067] Step 7:

[1068] The server receives, decodes, and analyzes the worker's response, and determines how to address the original feedback using the results of the analysis, in this case generating a message to encourage further support.

[1069] Step 8:

[1070] The generated additional feedback message is then sent to the original worker. For example, a message saying, "Please take regular breaks and don't overexert yourself" is sent to the worker again. This process is repeated to manage the worker's health and work efficiency.

[1071] In this way, a system is realized that can grasp the emotions and state of the worker in real time and provide appropriate feedback.

[1072] 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.

[1073] 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.

[1074] 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.

[1075] [Third embodiment]

[1076] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1077] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1078] 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).

[1079] 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.

[1080] 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.

[1081] 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).

[1082] 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.

[1083] 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.

[1084] 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.

[1085] 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.

[1086] 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.

[1087] 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."

[1088] 1. Overview

[1089] This invention is a system for sharing thoughts and feelings between users to deepen mutual understanding and empathy. The aim is to reduce misunderstandings and conflicts by allowing users to input their feelings and text, and then appropriately convey the analyzed data to other users. The system is provided as a cloud-based platform and can be accessed through software.

[1090] 2. System Configuration

[1091] The system is mainly composed of three main components: a user terminal, a server, and a database. The user terminal has input and receiving means, the server is responsible for analysis and message generation, and the database is responsible for storing analysis results and past interactions.

[1092] 3. Program Processing

[1093] The user enters emotions and text on the device

[1094] Users have a dedicated interface for inputting their own emotions and thoughts. Emotion options include "joy," "sadness," and "anger," and they can enter any sentence they like in the text input field. For example, they can enter, "Something very sad happened today."

[1095] Example: User (entered on the terminal)

[1096] Emotion selection: "Sadness"

[1097] Text: "Something very sad happened today."

[1098] The device sends the input data to the server

[1099] The emotion and text data entered by the user is encrypted and sent to the server using security protocols such as SSL / TLS.

[1100] Example: Terminal (data transmission)

[1101] encrypted_data = SSL / TLS(user_input)

[1102] Server (data reception)

[1103] decrypt(encrypted_data)

[1104] The server analyzes the received data

[1105] The server passes the received data to a natural language processing (NLP) engine for sentiment and text analysis. For example, it can detect a strong emotion of "sadness" from the user's text. The analysis results are stored in a database and compared with past data.

[1106] Example: Server (analysis)

[1107] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1108] Server (storing analysis results)

[1109] Database.save(user_id, emotion_analysis)

[1110] The server generates the appropriate message

[1111] Based on the analysis results, appropriate feedback messages and notification messages are generated for the user, such as "Your friend is very sad. Please say something kind to him / her."

[1112] Example: Server (message generation)

[1113] message = "My friend is very sad. Please say something kind to him."

[1114] The server sends a message to another user's device.

[1115] The generated message will be sent to the selected user's device via push notification, email, or other method of their choice.

[1116] Example: Server (data transmission)

[1117] send_notification(recipient_id, message)

[1118] Terminal (data reception)

[1119] display_notification(message)

[1120] The shared user receives the message and responds.

[1121] The receiving user can read the notification and send an appropriate response, which is then sent back to the server and displayed to the original user.

[1122] Example: Another user (entered in the terminal)

[1123] response_message = "What happened today? Let's talk and feel better."

[1124] Terminal (data transmission)

[1125] encrypted_response = SSL / TLS(response_message)

[1126] Server (data reception & analysis)

[1127] decrypt(encrypted_response)

[1128] The original user receives feedback

[1129] The original user can read the response and provide further feedback, which is then passed back to the server and communicated to other users as needed.

[1130] Example: Original user (displayed on terminal)

[1131] display_response(response_message)

[1132] Original user (entered on the terminal)

[1133] additional_feedback = "Thanks, I feel a little better now."

[1134] Terminal (data transmission)

[1135] send_feedback(additional_feedback)

[1136] 4. Specific examples of implementation

[1137] For example, user A enters, "Something very sad happened today." This data is encrypted and sent to the server, where the emotion "sadness" is analyzed using natural language processing. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then sent back through the server and displayed to user A. This process allows users A and B to share their emotions at a deep level.

[1138] As described above, this system provides a means for users to effectively share their feelings and thoughts, promoting mutual understanding and empathy.

[1139] The processing flow will be explained below.

[1140] Step 1:

[1141] User enters emotion and text

[1142] The user inputs emotions and text into the interface that opens using the device. Emotions can be selected from options such as "joy," "sadness," and "anger," and thoughts and feelings can be freely entered into the text input field. For example, the user can input "Something very sad happened today."

[1143] User (typed on device): Emotion selection: "Sadness" Text: "Something very sad happened today."

[1144] Step 2:

[1145] The device sends the input data to the server

[1146] The entered emotion and text data are encrypted on the device and sent to the server using a network protocol (e.g., SSL / TLS).

[1147] Terminal (data transmission): encrypted_data = SSL / TLS(user_input)

[1148] Server (receiving data): decrypt(encrypted_data)

[1149] Step 3:

[1150] The server analyzes the received data

[1151] The server passes the received data to a natural language processing (NLP) engine for sentiment and text analysis. The analysis engine extracts the level and type of emotion from the text and summarizes the results. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database.

[1152] Server(analysis): emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1153] Server (saving analysis results): Database.save(user_id, emotion_analysis)

[1154] Step 4:

[1155] The server generates the appropriate message

[1156] Based on the analysis results, the server generates a default or customized feedback message, along with a notification message to share with other users. For example, a message like "My friend is very sad. Please say something kind to him / her."

[1157] Server (Message generation): message = generateMessage(emotion_analysis)

[1158] Step 5:

[1159] The server sends a message to another user's device.

[1160] The generated messages and notifications are sent to other selected users via push notifications, email, or other methods depending on the user's settings.

[1161] Server (data sending): send_notification(recipient_id, message)

[1162] Device (receiving data): display_notification(message)

[1163] Step 6:

[1164] The person you shared with will receive the message

[1165] The receiving user reads the notification and, if necessary, prepares a reply message, which is sent again to the server and delivered to the original user.

[1166] Another user (typed on device): response_message = "What happened today? Let's talk and clear things up."

[1167] Terminal (data transmission): encrypted_response = SSL / TLS(response_message)

[1168] Server (receiving and analyzing data): decrypt(encrypted_response)

[1169] Step 7:

[1170] The original user receives feedback

[1171] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users if necessary.

[1172] Original user (displayed on terminal): display_response(response_message)

[1173] Original user (typed on device): additional_feedback = "Thanks, I feel a little better now."

[1174] Terminal (data transmission): send_feedback(additional_feedback)

[1175] summary

[1176] Through these steps, the system allows users to share their thoughts and feelings in real time, fostering deep levels of mutual understanding and empathy. At each step, data encryption, analysis, and feedback loops function properly to achieve high-quality communication.

[1177] Example 1

[1178] 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."

[1179] Conventional emotion sharing systems have difficulty effectively analyzing users' emotions and thoughts and generating and notifying appropriate feedback. Furthermore, data security and privacy protection may not be adequately ensured, potentially hindering the building of trust between users. Furthermore, there is a need to promote real-time interaction between users while reducing misunderstandings and conflicts.

[1180] 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.

[1181] In this invention, the server includes a means for encrypting and transmitting user input data, a means for decrypting and analyzing received data, and a means for analyzing received emotions using natural language processing. This makes it possible to securely share the user's emotions and thoughts, and to generate and notify appropriate feedback messages based on the analysis results.

[1182] "User" refers to an individual who uses the system to input emotions and text and share and receive that data.

[1183] "Emotion" refers to the expression of specific feelings or sensations that the user inputs into the system, and includes options such as "joy," "sadness," and "anger."

[1184] "Text" refers to any sentence that a user can freely input into the system.

[1185] "Means for input" refers to an interface or tool that allows a user to input emotions and text on a terminal.

[1186] "Means for sending" refers to the process and technology for sending the data entered by the user to the server.

[1187] "Encryption" refers to the technical process used to secure user-entered data, typically using the SSL / TLS protocol.

[1188] "Decryption" refers to the process of restoring encrypted data to a readable state on the server side.

[1189] "Means of analysis" refers to the technology used by the server to process and analyze the data received and understand its meaning and sentiment.

[1190] "Natural language processing" refers to the AI ​​technology used by servers to understand the meaning and sentiment of text, typically an NLP engine.

[1191] "Feedback message" refers to a response or notification to the user that the server generates based on the analysis results.

[1192] "User terminal" refers to the device through which a user accesses the system and inputs emotions and text, typically a smartphone or computer.

[1193] "Notification" refers to the communication method used to notify the user of server-generated feedback messages, including push notifications and email.

[1194] "Secure" refers to a state in which data is kept private and secure and cannot be accessed without permission.

[1195] MODE FOR CARRYING OUT THE INVENTION

[1196] 1. Overview

[1197] This invention is a system for sharing thoughts and feelings between users to deepen mutual understanding and empathy. The aim is to reduce misunderstandings and conflicts by allowing users to input their feelings and text, and then appropriately convey the analyzed data to other users. The system is provided as a cloud-based platform and can be accessed through software.

[1198] 2. System Configuration

[1199] The system is mainly composed of three main components: a user terminal, a server, and a database. The user terminal has input and receiving means, the server is responsible for analysis and message generation, and the database is responsible for storing analysis results and past interactions.

[1200] 3. Hardware and Software Used

[1201] User device: A device such as a smartphone or PC that allows the user to access the system and input emotions and text.

[1202] Server: A cloud-based server with high-performance computing power that analyzes input data and generates messages.

[1203] Database: Cloud-based data storage for analysis results and past messages.

[1204] Software: Natural language processing (NLP) engines, data encryption software via SSL / TLS protocols, push notification services, etc.

[1205] 4. Program Processing

[1206] Input method: The user inputs emotions and text through a dedicated interface. Emotion options include "joy," "sadness," and "anger," and the user can enter any text in the text input field.

[1207] Data transmission: The data entered by the user is encrypted using the SSL / TLS protocol and sent to the server.

[1208] Data analysis: The server passes the received data to a natural language processing (NLP) engine for sentiment analysis and text analysis. The analysis results are stored in a database.

[1209] Message Generation: Based on the analysis results, the server generates an appropriate feedback message, for example, "My friend is very sad. Please say some kind words to him."

[1210] Message sending: The generated message is sent to the selected user's device via push notification, email, or other method of their choice.

[1211] Feedback reception: The shared user receives the message and can send an appropriate response. The response message is sent back to the server and displayed to the original user.

[1212] Show Feedback: The original user can read the response and provide further feedback.

[1213] 5. Specific Examples

[1214] For example, user A enters, "Something very sad happened today." This data is encrypted and sent to the server, where the emotion "sadness" is analyzed using natural language processing. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then sent back through the server and displayed to user A. This process allows users A and B to share their emotions at a deep level.

[1215] 6. Examples of prompts

[1216] 1. "Generate a message to communicate to User B that User A is sad."

[1217] 2. "Please explain the steps to perform sentiment analysis and generate an appropriate response message."

[1218] This will create a system that allows users to securely share their feelings and thoughts, promoting mutual understanding and empathy.

[1219] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1220] The flow of this system's program processing

[1221] Step 1:

[1222] The user enters emotions and text on the device

[1223] explanation:

[1224] Users use a dedicated interface on their device to input their own emotions and thoughts. Emotion options include "joy," "sadness," and "anger," and they can enter any text they like in the text input field.

[1225] Input and Output:

[1226] Input: Emotion (e.g., "Sad") and text (e.g., "Something very sad happened to me today.")

[1227] Output: User input data

[1228] Specific behavior:

[1229] The user selects "sadness" from the emotion selection list, enters "Something very sad happened today" in the text box, and clicks the send button.

[1230] Step 2:

[1231] The device sends the input data to the server

[1232] explanation:

[1233] The device encrypts the emotions and text data entered by the user using the SSL / TLS protocol and securely transmits them to the server.

[1234] Input and Output:

[1235] Input: User-entered data

[1236] Output: Encrypted data

[1237] Specific behavior:

[1238] The device encrypts the data "something very sad happened today" and "sadness," and makes a request to the server to send the data.

[1239] Step 3:

[1240] The server analyzes the received data

[1241] explanation:

[1242] The server decrypts the received data using the SSL / TLS protocol, then passes it to a natural language processing (NLP) engine for sentiment and text analysis, and stores the results in a database.

[1243] Input and Output:

[1244] Input: Encrypted data

[1245] Output: Analysis result data

[1246] Specific behavior:

[1247] The server passes the decoded data to the NLP engine, which analyzes the text "Something very sad happened today" and the emotion "sadness." The analysis results are stored in a database along with the user ID.

[1248] Step 4:

[1249] The server generates the appropriate message

[1250] explanation:

[1251] Based on the analysis, the server generates a feedback message, such as "Your friend is very sad. Please say something kind to him / her."

[1252] Input and Output:

[1253] Input: Analysis result data

[1254] Output: Feedback message

[1255] Specific behavior:

[1256] The server compares the analysis results with past data and generates a notification message saying, "Your friend is very sad. Please say some kind words to him."

[1257] Step 5:

[1258] The server sends a message to another user's device.

[1259] explanation:

[1260] The generated message will be sent to the selected user's device via push notification, email, or other method of their choice.

[1261] Input and Output:

[1262] Input: Feedback message

[1263] Output: Notification message sent

[1264] Specific behavior:

[1265] The server sends a notification message to User B. On User B's device, a message saying "Your friend is very sad. Please say something kind to him / her." is displayed in the notification bar.

[1266] Step 6:

[1267] The shared user receives the message and responds.

[1268] explanation:

[1269] The receiving user can read the notification and send an appropriate response, which is then sent back to the server and displayed to the original user.

[1270] Input and Output:

[1271] Input: Notification message

[1272] Output: Response message

[1273] Specific behavior:

[1274] User B types in "What happened today? Let's talk and feel better." and clicks the send button. The device encrypts this and sends it to the server.

[1275] Step 7:

[1276] The original user receives feedback

[1277] explanation:

[1278] The original user reads the reply message and can then send further messages as feedback, which are again routed through the server and notified to other users as needed.

[1279] Input and Output:

[1280] Input: Response message

[1281] Output: Feedback message

[1282] Specific behavior:

[1283] User A reads the response, "What happened today? Let's talk and feel better," on the device, and enters and sends feedback such as, "Thank you, I feel a little better now." The device then encrypts the feedback and sends it to the server.

[1284] The above steps provide a detailed explanation of the processing flow of a system that allows users to share emotions and text and promote mutual understanding and empathy.

[1285] (Application example 1)

[1286] 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."

[1287] Current security systems face the challenge of being unable to immediately detect and respond to abnormal emotions and behaviors. In particular, when strengthening security at work or home, there are limited means of monitoring changes in the emotions and abnormalities of employees and residents in real time, making it difficult to prevent serious incidents.

[1288] 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.

[1289] In this invention, the server includes means for a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user terminal, means for receiving a response from another user and displaying it to the original user, means for acquiring video and audio data, means for analyzing the acquired data in real time, and means for detecting abnormal emotions from the analysis results and generating a notification, thereby enabling abnormal emotions and behaviors to be detected quickly and appropriate measures to be taken.

[1290] "Means for users to input emotions and text" refers to an interface that allows users to freely input their own emotions and thoughts.

[1291] "Means for transmitting user input data" refers to a communication means for transmitting data input by a user to a server.

[1292] "Means for analyzing received data" refers to software or algorithms used by the server to analyze user input data received by the server.

[1293] "Means for generating optimal messages based on analysis results" refers to a system or process for generating appropriate messages for users based on analyzed data.

[1294] The "means for transmitting the generated message to another user terminal" refers to a communication means for transmitting the generated message to another user terminal.

[1295] "Means for receiving a response from another user and displaying it to the original user" refers to a system or process for receiving a response from another user and displaying the content to the original user.

[1296] "Means for acquiring video and audio data" refers to a device or system for collecting video and audio data using a camera or microphone.

[1297] "Means for analyzing acquired data in real time" refers to software or algorithms for analyzing collected video and audio data in real time.

[1298] "Means for detecting anomalous emotions from the analysis results and generating notifications" refers to a system or process for detecting anomalous emotions from data analyzed in real time and generating corresponding notifications.

[1299] Overall system configuration

[1300] This invention is a system designed to allow users to share their thoughts and feelings and deepen mutual understanding and empathy. The system is mainly composed of three main components: a user terminal, a server, and a database.

[1301] Hardware and Software Configuration

[1302] User terminal

[1303] The user terminal is equipped with an interface for inputting emotions and text, a camera and a microphone for collecting video and audio data, and a dedicated application installed on it, which transmits the data input by the user to a server.

[1304] server

[1305] The server uses an advanced natural language processing (NLP) engine and machine learning algorithms to analyze user input data in real time. The server has the following functions:

[1306] Parses the received data and generates the appropriate message.

[1307] Video and audio data is analyzed in real time to detect abnormal emotions.

[1308] The analysis results, generated messages, and notification contents are saved in a database.

[1309] Database

[1310] The database stores users' emotional data, past interactions, and analysis results, allowing it to compare with past data to more accurately detect abnormal emotions and generate appropriate feedback.

[1311] Specific examples of hardware and software used

[1312] Camera: A device for acquiring video data

[1313] Microphone: A device for collecting audio data

[1314] PC: A computer for analyzing video and audio data

[1315] NLP engine: Natural language processing (e.g. NLPEngine)

[1316] Communication protocol: Data encryption via SSL / TLS

[1317] How to operate the system

[1318] Users can input their feelings and thoughts using an interface for inputting emotions and text, and the system captures the user's video and audio data through a camera and microphone. This data is then encrypted and sent to a server.

[1319] The server analyzes the received data and generates an appropriate message or notification if it detects an abnormal emotion. The generated message is immediately sent to another user device. The user who receives this message can check the content of the notification and take appropriate action.

[1320] Specific examples

[1321] For example, if this system is implemented in a workplace security system, an employee can input "Something very sad happened today." This data is sent to the server along with video and audio data collected through cameras and microphones. The server analyzes this data in real time and generates a notification based on the analysis results saying, "An abnormal emotion has been detected. Please check immediately." This notification is then immediately sent to the security staff's device.

[1322] Prompt Sentence Examples

[1323] For example, you could use a prompt like, "We want to use emotion analysis to improve security in the workplace. Please propose an application that can quickly detect people's anger or fear and immediately notify security staff. Please also tell us the specific implementation method and technology used."

[1324] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1325] Step 1:

[1326] The user inputs emotions and text. The user inputs "Something very sad happened today" into a dedicated interface on the terminal. This input data includes the user's emotion options and text. Input: Emotion (sadness) and text (Something very sad happened today). Output: Input data.

[1327] Step 2:

[1328] The device sends the input data to the server. The device encrypts the input emotion and text data using the SSL / TLS protocol and then sends it to the server. Input: Emotion and text data. Output: Encrypted data.

[1329] Step 3:

[1330] The server decrypts and analyzes the received data. The server decrypts the received encrypted data and passes it to a natural language processing (NLP) engine for sentiment and text analysis. Input: Encrypted data. Output: Analysis results (e.g., "very sad").

[1331] Step 4:

[1332] The server generates the optimal message based on the analysis results. Based on the analysis results, the server automatically generates a recommended message such as "Your friend is very sad. Please say something kind to them." Input: Analysis results. Output: Generated message.

[1333] Step 5:

[1334] The server sends the generated message to another user's device. The server sends the generated message to another user's device. The sending method depends on the user's settings, such as push notification or email. Input: Generated message. Output: Notification to another user's device.

[1335] Step 6:

[1336] Another user receives the message and responds. Another user receives the message, types a response such as "What happened today? Let's talk and feel better," and sends it from their device. This response is encrypted and sent to the server. Input: Generated message. Output: Response message.

[1337] Step 7:

[1338] The server sends a response message to the original user. The server decrypts the received response message and sends it to the original user's terminal. Input: Response message. Output: Feedback message to the original user.

[1339] Step 8:

[1340] The original user receives the feedback. The original user receives the feedback message and can enter their own emotions and situation again if necessary to make a further response. Input: Feedback message. Output: New emotions and text data.

[1341] In this way, users can share their thoughts and feelings in real time, deepening mutual understanding and empathy.

[1342] 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.

[1343] 1. Overview

[1344] This invention is a system for sharing thoughts and emotions between users to deepen mutual understanding and empathy. The purpose is to reduce misunderstandings and conflicts by having users input their emotions and thoughts and then appropriately convey the analyzed data to other users. Furthermore, this invention combines an emotion engine to enhance the recognition of users' emotions.

[1345] 2. System Configuration

[1346] This system consists of a user terminal, a server, a database, and an emotion engine. The user terminal is equipped with input and receiving means, and the server is responsible for analyzing data and generating messages. The database stores the analysis results and past interactions, and the emotion engine recognizes the user's emotions.

[1347] 3. Program Processing

[1348] The user enters emotions and text on the device

[1349] The user inputs emotions and text through the interface. The emotions are analyzed in real time by the emotion engine. The emotion engine integrates the selected emotion, text input, voice input, and facial expression analysis using facial recognition to determine a comprehensive emotion. For example, if a user inputs "Something very sad happened today," the emotion engine will recognize that the emotion "sadness" is strong.

[1350] Example: User (entered on the terminal)

[1351] Emotion selection: "Sadness"

[1352] Text: "Something very sad happened today."

[1353] The device sends the input data to the server

[1354] The entered emotion and text data is encrypted on the device and then sent to the server using the SSL / TLS protocol.

[1355] Example: Terminal (data transmission)

[1356] encrypted_data = SSL / TLS(user_input)

[1357] Server (data reception)

[1358] decrypt(encrypted_data)

[1359] The server analyzes the received data

[1360] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for emotion and text analysis. The analysis engine extracts emotions from the text in real time, and the emotion engine performs a comprehensive emotion determination by combining facial recognition and voice analysis. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database and compared with past data.

[1361] Example: Server (analysis)

[1362] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1363] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[1364] Server (storing analysis results)

[1365] Database.save(user_id, comprehensive_emotion)

[1366] The server generates the appropriate message

[1367] Based on the analysis results, the server generates appropriate feedback and notification messages for the user, such as "My friend is very sad. Please say some kind words to him."

[1368] Example: Server (message generation)

[1369] message = generateMessage(comprehensive_emotion)

[1370] The server sends a message to another user's device.

[1371] The generated messages and notifications will be sent to the selected other users' devices via push notifications, emails, or other methods set by the user.

[1372] Example: Server (data transmission)

[1373] send_notification(recipient_id, message)

[1374] Terminal (data reception)

[1375] display_notification(message)

[1376] The person you shared with will receive the message

[1377] The receiving user reads the notification, prepares a response message if necessary, and sends it to the server via the terminal, which then sends the message back to the server and delivers it to the original user.

[1378] Example: Another user (entered in the terminal)

[1379] response_message = "What happened today? Let's talk and feel better."

[1380] Terminal (data transmission)

[1381] encrypted_response = SSL / TLS(response_message)

[1382] Server (data reception & analysis)

[1383] decrypt(encrypted_response)

[1384] The original user receives feedback

[1385] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users as needed.

[1386] Example: Original user (displayed on terminal)

[1387] display_response(response_message)

[1388] Original user (entered on the terminal)

[1389] additional_feedback = "Thanks, I feel a little better now."

[1390] Terminal (data transmission)

[1391] send_feedback(additional_feedback)

[1392] 4. Specific examples of implementation

[1393] For example, if user A enters "Something very sad happened today," the emotion engine will determine this as "sadness." This data is encrypted and sent to the server, where it is analyzed by natural language processing and the emotion engine. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then displayed to user A via the server again. Through this process, users A and B share their emotions at a deep level, promoting mutual understanding and empathy.

[1394] As described above, the system of the present invention provides an embodiment that effectively shares users' emotions and thoughts and combines advanced emotion recognition technology, improving the quality of communication between users and facilitating the sharing of emotions.

[1395] The processing flow will be explained below.

[1396] Step 1:

[1397] User enters emotion and text

[1398] The user inputs emotions and text through the device's interface. Emotions can be selected from options such as "joy," "sadness," and "anger," and thoughts and feelings can be freely entered in the text entry field. Furthermore, facial expressions can be captured using voice input or a camera, if necessary. For example, a user can select the emotion of sadness along with the text "Something very sad happened today."

[1399] User (typed on device): Emotion selection: "Sadness" Text: "Something very sad happened today."

[1400] Step 2:

[1401] The device sends the input data to the server

[1402] The input emotion and text data, as well as audio and image data, are encrypted on the device and sent to the server using the SSL / TLS protocol.

[1403] Terminal (data transmission): encrypted_data = SSL / TLS(user_input)

[1404] Server (receiving data): decrypt(encrypted_data)

[1405] Step 3:

[1406] The server analyzes the received data

[1407] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for analysis. The natural language processing engine extracts emotions from the text, and the emotion engine performs voice analysis and facial recognition to comprehensively determine emotions. For example, text analysis may recognize strong "sadness," voice analysis may sense "sadness" from a low tone, and facial recognition may detect traces of tears.

[1408] Server(analysis): emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1409] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[1410] Server (saving analysis results): Database.save(user_id, comprehensive_emotion)

[1411] Step 4:

[1412] The server generates the appropriate message

[1413] Based on the analysis results, the server generates an appropriate feedback or notification message, such as "Your friend is very sad. Please say something kind to him / her."

[1414] Server (Message generation): message = generateMessage(comprehensive_emotion)

[1415] Step 5:

[1416] The server sends a message to another user's device.

[1417] The generated messages and notifications are sent to the selected users' devices via push notifications or emails, depending on the recipient's settings.

[1418] Server (data sending): send_notification(recipient_id, message)

[1419] Device (receiving data): display_notification(message)

[1420] Step 6:

[1421] The person you shared with will receive the message

[1422] The recipient user reads the notification, prepares a response message if necessary, and sends it from the terminal to the server, where it is again encrypted and sent to the server.

[1423] Another user (typed on device): response_message = "What happened today? Let's talk and clear things up."

[1424] Terminal (data transmission): encrypted_response = SSL / TLS(response_message)

[1425] Server (receiving and analyzing data): decrypt(encrypted_response)

[1426] Step 7:

[1427] The original user receives feedback

[1428] The original user can read the reply message from the other user and send additional feedback, which is then passed through the server again and may be notified to other users if necessary.

[1429] Original user (displayed on terminal): display_response(response_message)

[1430] Original user (typed on device): additional_feedback = "Thanks, I feel a little better now."

[1431] Terminal (data transmission): send_feedback(additional_feedback)

[1432] summary

[1433] Through these steps, the system allows users to share their thoughts and feelings in real time, fostering a deep level of mutual understanding and empathy. At each step, data encryption, analysis, and feedback loops function properly to achieve high-quality communication.

[1434] Example 2

[1435] 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."

[1436] In modern society, many people face misunderstandings and conflicts in communication. In particular, it is difficult to accurately convey emotions, resulting in a lack of mutual understanding and empathy. Therefore, a system that allows users to efficiently share their emotions and thoughts and deepen mutual understanding and empathy is needed.

[1437] 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 device for a user to input emotions and text, a device for encrypting and transmitting the input data, a device for analyzing the received data, a device for generating an appropriate message based on the analysis result, a device for transmitting the generated message to other terminals, and a device for receiving and displaying responses from other terminals. This enables users to effectively share emotions and thoughts, reducing misunderstandings and conflicts.

[1438] A "user" is an individual or group that uses the system and inputs emotions and text into a terminal.

[1439] A "device" is a combination of hardware and software that performs a specific function and is used to process data entered by a user.

[1440] "Encryption" is a technology that converts transmitted data so that it cannot be read by third parties, and is used to ensure secure data transmission.

[1441] The "SSL / TLS protocol" is an encryption protocol for securely transmitting data over the Internet, preventing data tampering and eavesdropping.

[1442] A "server" is a central processing unit that receives data sent by users and performs analysis and message generation.

[1443] A "natural language processing engine" is software that analyzes text data entered by a user and recognizes its meaning and emotion.

[1444] An "emotion engine" is software that evaluates and analyzes a user's emotions and generates appropriate messages based on the results.

[1445] A "database" is a data storage system for storing analysis results and past data, facilitating data management and retrieval.

[1446] "Message generation" is the process of creating appropriate notification or response messages based on the analysis results.

[1447] "Push notification" is a technology that sends messages directly from a server to a user's device, enabling instant information transmission.

[1448] "Feedback" is a response or additional information from a user, including a reaction or impression of another user.

[1449] 1. Overview

[1450] This invention is a system for sharing thoughts and emotions between users to deepen mutual understanding and empathy. The purpose is to reduce misunderstandings and conflicts by having users input their emotions and thoughts and then appropriately convey the analyzed data to other users. Furthermore, this invention combines an emotion engine to enhance the recognition of users' emotions.

[1451] 2. System Configuration

[1452] This system consists of a user terminal, a server, a database, and an emotion engine. The user terminal is equipped with input and receiving means, and the server is responsible for analyzing data and generating messages. The database stores the analysis results and past interactions, and the emotion engine recognizes the user's emotions.

[1453] 3. The user enters the emotion and text on the device.

[1454] The user inputs emotions and text through the interface. The emotions are analyzed in real time by the emotion engine. The emotion engine integrates the selected emotion, text input, voice input, and facial expression analysis using facial recognition to determine a comprehensive emotion. For example, if a user inputs "Something very sad happened today," the emotion engine will recognize that the emotion "sadness" is strong.

[1455] Example: User (entered on the terminal)

[1456] Emotion selection: "Sadness"

[1457] Text: "Something very sad happened today."

[1458] 4. The device sends the input data to the server

[1459] The entered emotion and text data is encrypted on the device and then sent to the server using the SSL / TLS protocol.

[1460] Example: Terminal (data transmission)

[1461] encrypted_data = SSL / TLS(user_input)

[1462] Server (data reception)

[1463] decrypt(encrypted_data)

[1464] 5. The server analyzes the received data

[1465] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for emotion and text analysis. The analysis engine extracts emotions from the text in real time, and the emotion engine performs a comprehensive emotion determination by combining facial recognition and voice analysis. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database and compared with past data.

[1466] Example: Server (analysis)

[1467] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1468] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[1469] Server (storing analysis results)

[1470] Database.save(user_id, comprehensive_emotion)

[1471] 6. The server generates the appropriate message

[1472] Based on the analysis results, the server generates appropriate feedback and notification messages for the user, such as "My friend is very sad. Please say some kind words to him."

[1473] Example: Server (message generation)

[1474] message = generateMessage(comprehensive_emotion)

[1475] 7. The server sends the message to another user device

[1476] The generated messages and notifications will be sent to the selected other users' devices via push notifications, emails, or other methods set by the user.

[1477] Example: Server (data transmission)

[1478] send_notification(recipient_id, message)

[1479] Terminal (data reception)

[1480] display_notification(message)

[1481] 8. The shared user receives the message

[1482] The receiving user reads the notification, prepares a response message if necessary, and sends it to the server via the terminal, which then sends the message back to the server and delivers it to the original user.

[1483] Example: Another user (entered in the terminal)

[1484] response_message = "What happened today? Let's talk and feel better."

[1485] Terminal (data transmission)

[1486] encrypted_response = SSL / TLS(response_message)

[1487] Server (data reception & analysis)

[1488] decrypt(encrypted_response)

[1489] 9. The original user receives feedback

[1490] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users as needed.

[1491] Example: Original user (displayed on terminal)

[1492] display_response(response_message)

[1493] Original user (entered on the terminal)

[1494] additional_feedback = "Thanks, I feel a little better now."

[1495] Terminal (data transmission)

[1496] send_feedback(additional_feedback)

[1497] 10. Specific examples of implementation

[1498] For example, if user A enters "Something very sad happened today," the emotion engine will determine this as "sadness." This data is encrypted and sent to the server, where it is analyzed by natural language processing and the emotion engine. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then displayed to user A via the server again. Through this process, users A and B share their emotions at a deep level, promoting mutual understanding and empathy.

[1499] As described above, the system of the present invention provides an embodiment that effectively shares users' emotions and thoughts and combines advanced emotion recognition technology, improving the quality of communication between users and facilitating the sharing of emotions.

[1500] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1501] Step 1: User enters emotion and text on device

[1502] The user inputs emotions and text through the device interface. By selecting an emotion and entering text, for example, "Something very sad happened today," the input data (emotion, text) is analyzed in real time by the emotion engine, and is integrated with facial recognition and voice analysis data to determine a comprehensive emotion.

[1503] Input: User emotion selection ("Sad") and text ("Something very sad happened today")

[1504] Output: Comprehensive emotion judgment data

[1505] Step 2: The device sends the input data to the server

[1506] The device encrypts the input emotion and text data using the SSL / TLS protocol and sends it to the server. Encryption ensures secure data transmission.

[1507] Input: User input data and emotion judgment data

[1508] Output: Encrypted data

[1509] Step 3: Parse the data received by the server

[1510] The server decrypts the received encrypted data using the SSL / TLS protocol and passes it to a natural language processing (NLP) engine and emotion engine for analysis. The NLP engine analyzes the text, and the emotion engine performs emotion analysis, including voice analysis and facial recognition data.

[1511] Input: Encrypted data, decrypted input data, and emotion judgment data

[1512] Output: Analyzed emotion data and text analysis results

[1513] Step 4: The server generates the appropriate message

[1514] The server generates appropriate feedback and notification messages for the user based on the analysis results, such as "My friend is very sad. Please say some kind words to him."

[1515] Input: Parsed sentiment data and text analysis results

[1516] Output: The generated feedback message

[1517] Step 5: The server sends the message to another user device

[1518] The server then sends the generated messages and notifications to the selected users' devices via push notification, email, or other methods set by the users.

[1519] Input: The generated feedback message

[1520] Output: Messages and notifications sent

[1521] Step 6: The person you shared with receives the message

[1522] Another user reads the notification and message sent, prepares an appropriate reply message based on the content, and sends the reply message to the server via the terminal.

[1523] Input: Messages and notifications sent

[1524] Output: Response message

[1525] Step 7: The original user receives feedback

[1526] The original user can read the reply message from the other user and send further feedback based on the content. This feedback is also sent via the server and notified to other users as needed.

[1527] Input: Response message

[1528] Output: More feedback messages

[1529] (Application example 2)

[1530] 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."

[1531] In factory work environments, it is difficult to grasp the health status and emotions of workers in real time, which is one of the factors that leads to a decrease in work efficiency and a worsening working environment. In particular, the lack of appropriate feedback and support for workers who are feeling fatigued or stressed is a problem.

[1532] 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 a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user terminal, means for receiving a response from another user and displaying it to the original user, means for analyzing the worker's facial expression, voice, and text and determining the worker's emotions, and means for generating appropriate feedback based on the determined emotions. This makes it possible to grasp the worker's emotions and state in real time and provide appropriate feedback and support.

[1533] A "means for user input of emotions and text" is a system or device that allows a user to input emotions and text through an interface.

[1534] The "means for transmitting user input data" refers to a communication means for transmitting data such as emotions and text input by the user to a server or other system.

[1535] "Means for analyzing received data" refers to analytical technology or software that processes the data received by the server from the user and determines their emotions or state.

[1536] The "means for generating optimal messages based on analysis results" refers to algorithms or programs for generating appropriate feedback or messages for users based on the results of data analysis.

[1537] The "means for transmitting the generated message to another user terminal" is a communication means for transmitting the generated message or feedback to the terminal of another designated user.

[1538] The "means for receiving a response from another user and displaying it to the original user" is a system or software for receiving a response or message from another user and displaying it to the original user.

[1539] "Means for analyzing the facial expressions, voice, and text of a worker and determining their emotions" refers to analytical technology and software for recognizing and determining the emotions of a worker using the worker's facial expressions, voice, and text data.

[1540] The "means for generating appropriate feedback based on the determined emotion" refers to an algorithm or program for generating appropriate feedback or support messages for the worker based on the determined emotion information.

[1541] The system for implementing this invention consists of a user terminal, a server, a database, and an emotion engine. The system analyzes the user's emotions and state in real time and provides appropriate feedback to improve the work environment and work efficiency.

[1542] System configuration

[1543] 1. User terminal: The user terminal provides an interface for the worker to input emotions and text. The emotion engine performs emotion analysis in real time, and the input data is sent to the server.

[1544] 2. Server: The server receives the data sent by the user and performs data analysis. Specifically, it performs sentiment analysis using a natural language processing (NLP) engine and an emotion engine, and generates appropriate messages and feedback based on the analysis results.

[1545] 3. Database: Includes a database for storing analysis results and past interactions, allowing historical data reference.

[1546] 4. Emotion engine: The emotion engine combines voice analysis, facial expression analysis, and text analysis to determine overall emotions.

[1547] Program processing

[1548] This system uses the following hardware and software:

[1549] Hardware:

[1550] Camera: for facial expression analysis

[1551] Microphone: For voice input

[1552] Computer: Data analysis and notification generation

[1553] software:

[1554] OpenCV: Camera image processing

[1555] EmotionEngine: Emotion recognition

[1556] NLPEngine: Text Analysis

[1557] Notification: Notification system

[1558] Processing flow and data calculation

[1559] 1. User input:

[1560] The user inputs emotions and text using the device, and the emotion engine analyzes the emotions in real time and sends the data to the server.

[1561] 2. Data transmission:

[1562] The data entered by the user is encrypted before being sent to the server. The SSL / TLS protocol is used.

[1563] 3. Data Analysis:

[1564] The server passes the received data to a natural language processing (NLP) engine and an emotion engine to perform emotion analysis and text analysis. The analysis results are stored in a database.

[1565] 4. Message Creation:

[1566] The server generates an appropriate feedback message for the user based on the analysis results. For example, if the emotion is determined to be "fatigue," an appropriate message (e.g., "You should take a break") is generated.

[1567] 5. Sending a message:

[1568] The server then sends the generated message to another user device via push notification, email, or other methods based on the user's settings.

[1569] 6. Receiving Response:

[1570] A response from another user is received and displayed to the original user.

[1571] Specific examples and prompts for the generative AI model

[1572] The system works as follows:

[1573] Examples:

[1574] The worker inputs "I'm tired," and the camera and microphone capture the situation. The results determine "fatigue" and "stress." The robot then notifies the worker, saying, "It's time to take a break."

[1575] Example prompt sentence:

[1576] "Worker has been detected as 'tired' based on facial expression, voice tone, and text input. Generate a notification to the worker suggesting a break."

[1577] This system makes it possible to grasp the emotions and state of workers in real time and provide appropriate feedback and support.

[1578] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1579] Step 1:

[1580] The user inputs emotions and text into the device. The input interface provides a text box and an emotion selection menu, and is also linked to a camera that detects facial expressions and a microphone that captures voice. The user's input includes the text data "Tired" and the emotion data "Tired," which are then analyzed in real time by the emotion engine.

[1581] Step 2:

[1582] The device encrypts the input emotion and text data and sends it to the server. The encryption uses the SSL / TLS protocol. If the input data is "tired" and "tired," the server receives it after encryption.

[1583] Step 3:

[1584] The server decrypts the received encrypted data and begins data analysis. The decrypted data is passed to a natural language processing (NLP) engine, which analyzes the text data "Tired." At the same time, the emotion engine analyzes the voice and facial expression data to determine a comprehensive emotion. For example, it may determine that "Tired" is very strong.

[1585] Step 4:

[1586] The server generates an appropriate message based on the analysis results. For example, if the result of emotion analysis is "fatigue," it generates a feedback message saying, "You should take a break." The analysis results and the generated message are stored in a database.

[1587] Step 5:

[1588] The server then sends the generated message to the worker using an appropriate notification method, such as push notification or email, and depending on the settings, a notification such as "It's best to take a break" is displayed on the worker's device.

[1589] Step 6:

[1590] The worker receives the notification and inputs a response, for example, "I'll continue working a little longer." This input data is then re-encrypted and sent to the server.

[1591] Step 7:

[1592] The server receives, decodes, and analyzes the worker's response, and determines how to address the original feedback using the results of the analysis, in this case generating a message to encourage further support.

[1593] Step 8:

[1594] The generated additional feedback message is then sent to the original worker. For example, a message saying, "Please take regular breaks and don't overexert yourself" is sent to the worker again. This process is repeated to manage the worker's health and work efficiency.

[1595] In this way, a system is realized that can grasp the emotions and state of the worker in real time and provide appropriate feedback.

[1596] 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.

[1597] 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.

[1598] 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.

[1599] [Fourth embodiment]

[1600] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1601] 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.

[1602] 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).

[1603] 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.

[1604] 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.

[1605] 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).

[1606] 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.

[1607] 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.

[1608] 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.

[1609] 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.

[1610] 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.

[1611] 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.

[1612] 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."

[1613] 1. Overview

[1614] This invention is a system for sharing thoughts and feelings between users to deepen mutual understanding and empathy. The aim is to reduce misunderstandings and conflicts by allowing users to input their feelings and text, and then appropriately convey the analyzed data to other users. The system is provided as a cloud-based platform and can be accessed through software.

[1615] 2. System Configuration

[1616] The system is mainly composed of three main components: a user terminal, a server, and a database. The user terminal has input and receiving means, the server is responsible for analysis and message generation, and the database is responsible for storing analysis results and past interactions.

[1617] 3. Program Processing

[1618] The user enters emotions and text on the device

[1619] Users have a dedicated interface for inputting their own emotions and thoughts. Emotion options include "joy," "sadness," and "anger," and they can enter any sentence they like in the text input field. For example, they can enter, "Something very sad happened today."

[1620] Example: User (entered on the terminal)

[1621] Emotion selection: "Sadness"

[1622] Text: "Something very sad happened today."

[1623] The device sends the input data to the server

[1624] The emotion and text data entered by the user is encrypted and sent to the server using security protocols such as SSL / TLS.

[1625] Example: Terminal (data transmission)

[1626] encrypted_data = SSL / TLS(user_input)

[1627] Server (data reception)

[1628] decrypt(encrypted_data)

[1629] The server analyzes the received data

[1630] The server passes the received data to a natural language processing (NLP) engine for sentiment and text analysis. For example, it can detect a strong emotion of "sadness" from the user's text. The analysis results are stored in a database and compared with past data.

[1631] Example: Server (analysis)

[1632] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1633] Server (storing analysis results)

[1634] Database.save(user_id, emotion_analysis)

[1635] The server generates the appropriate message

[1636] Based on the analysis results, appropriate feedback messages and notification messages are generated for the user, such as "Your friend is very sad. Please say something kind to him / her."

[1637] Example: Server (message generation)

[1638] message = "My friend is very sad. Please say something kind to him."

[1639] The server sends a message to another user's device.

[1640] The generated message will be sent to the selected user's device via push notification, email, or other method of their choice.

[1641] Example: Server (data transmission)

[1642] send_notification(recipient_id, message)

[1643] Terminal (data reception)

[1644] display_notification(message)

[1645] The shared user receives the message and responds.

[1646] The receiving user can read the notification and send an appropriate response, which is then sent back to the server and displayed to the original user.

[1647] Example: Another user (entered in the terminal)

[1648] response_message = "What happened today? Let's talk and feel better."

[1649] Terminal (data transmission)

[1650] encrypted_response = SSL / TLS(response_message)

[1651] Server (data reception & analysis)

[1652] decrypt(encrypted_response)

[1653] The original user receives feedback

[1654] The original user can read the response and provide further feedback, which is then passed back to the server and communicated to other users as needed.

[1655] Example: Original user (displayed on terminal)

[1656] display_response(response_message)

[1657] Original user (entered on the terminal)

[1658] additional_feedback = "Thanks, I feel a little better now."

[1659] Terminal (data transmission)

[1660] send_feedback(additional_feedback)

[1661] 4. Specific examples of implementation

[1662] For example, user A enters, "Something very sad happened today." This data is encrypted and sent to the server, where the emotion "sadness" is analyzed using natural language processing. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then sent back through the server and displayed to user A. This process allows users A and B to share their emotions at a deep level.

[1663] As described above, this system provides a means for users to effectively share their feelings and thoughts, promoting mutual understanding and empathy.

[1664] The processing flow will be explained below.

[1665] Step 1:

[1666] User enters emotion and text

[1667] The user inputs emotions and text into the interface that opens using the device. Emotions can be selected from options such as "joy," "sadness," and "anger," and thoughts and feelings can be freely entered into the text input field. For example, the user can input "Something very sad happened today."

[1668] User (typed on device): Emotion selection: "Sadness" Text: "Something very sad happened today."

[1669] Step 2:

[1670] The device sends the input data to the server

[1671] The entered emotion and text data are encrypted on the device and sent to the server using a network protocol (e.g., SSL / TLS).

[1672] Terminal (data transmission): encrypted_data = SSL / TLS(user_input)

[1673] Server (receiving data): decrypt(encrypted_data)

[1674] Step 3:

[1675] The server analyzes the received data

[1676] The server passes the received data to a natural language processing (NLP) engine for sentiment and text analysis. The analysis engine extracts the level and type of emotion from the text and summarizes the results. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database.

[1677] Server(analysis): emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1678] Server (saving analysis results): Database.save(user_id, emotion_analysis)

[1679] Step 4:

[1680] The server generates the appropriate message

[1681] Based on the analysis results, the server generates a default or customized feedback message, along with a notification message to share with other users. For example, a message like "My friend is very sad. Please say something kind to him / her."

[1682] Server (Message generation): message = generateMessage(emotion_analysis)

[1683] Step 5:

[1684] The server sends a message to another user's device.

[1685] The generated messages and notifications are sent to other selected users via push notifications, email, or other methods depending on the user's settings.

[1686] Server (data sending): send_notification(recipient_id, message)

[1687] Device (receiving data): display_notification(message)

[1688] Step 6:

[1689] The person you shared with will receive the message

[1690] The receiving user reads the notification and, if necessary, prepares a reply message, which is sent again to the server and delivered to the original user.

[1691] Another user (typed on device): response_message = "What happened today? Let's talk and clear things up."

[1692] Terminal (data transmission): encrypted_response = SSL / TLS(response_message)

[1693] Server (receiving and analyzing data): decrypt(encrypted_response)

[1694] Step 7:

[1695] The original user receives feedback

[1696] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users if necessary.

[1697] Original user (displayed on terminal): display_response(response_message)

[1698] Original user (typed on device): additional_feedback = "Thanks, I feel a little better now."

[1699] Terminal (data transmission): send_feedback(additional_feedback)

[1700] summary

[1701] Through these steps, the system allows users to share their thoughts and feelings in real time, fostering deep levels of mutual understanding and empathy. At each step, data encryption, analysis, and feedback loops function properly to achieve high-quality communication.

[1702] Example 1

[1703] 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."

[1704] Conventional emotion sharing systems have difficulty effectively analyzing users' emotions and thoughts and generating and notifying appropriate feedback. Furthermore, data security and privacy protection may not be adequately ensured, potentially hindering the building of trust between users. Furthermore, there is a need to promote real-time interaction between users while reducing misunderstandings and conflicts.

[1705] 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.

[1706] In this invention, the server includes a means for encrypting and transmitting user input data, a means for decrypting and analyzing received data, and a means for analyzing received emotions using natural language processing. This makes it possible to securely share the user's emotions and thoughts, and to generate and notify appropriate feedback messages based on the analysis results.

[1707] "User" refers to an individual who uses the system to input emotions and text and share and receive that data.

[1708] "Emotion" refers to the expression of specific feelings or sensations that the user inputs into the system, and includes options such as "joy," "sadness," and "anger."

[1709] "Text" refers to any sentence that a user can freely input into the system.

[1710] "Means for input" refers to an interface or tool that allows a user to input emotions and text on a terminal.

[1711] "Means for sending" refers to the process and technology for sending the data entered by the user to the server.

[1712] "Encryption" refers to the technical process used to secure user-entered data, typically using the SSL / TLS protocol.

[1713] "Decryption" refers to the process of restoring encrypted data to a readable state on the server side.

[1714] "Means of analysis" refers to the technology used by the server to process and analyze the data received and understand its meaning and sentiment.

[1715] "Natural language processing" refers to the AI ​​technology used by servers to understand the meaning and sentiment of text, typically an NLP engine.

[1716] "Feedback message" refers to a response or notification to the user that the server generates based on the analysis results.

[1717] "User terminal" refers to the device through which a user accesses the system and inputs emotions and text, typically a smartphone or computer.

[1718] "Notification" refers to the communication method used to notify the user of server-generated feedback messages, including push notifications and email.

[1719] "Secure" refers to a state in which data is kept private and secure and cannot be accessed without permission.

[1720] MODE FOR CARRYING OUT THE INVENTION

[1721] 1. Overview

[1722] This invention is a system for sharing thoughts and feelings between users to deepen mutual understanding and empathy. The aim is to reduce misunderstandings and conflicts by allowing users to input their feelings and text, and then appropriately convey the analyzed data to other users. The system is provided as a cloud-based platform and can be accessed through software.

[1723] 2. System Configuration

[1724] The system is mainly composed of three main components: a user terminal, a server, and a database. The user terminal has input and receiving means, the server is responsible for analysis and message generation, and the database is responsible for storing analysis results and past interactions.

[1725] 3. Hardware and Software Used

[1726] User device: A device such as a smartphone or PC that allows the user to access the system and input emotions and text.

[1727] Server: A cloud-based server with high-performance computing power that analyzes input data and generates messages.

[1728] Database: Cloud-based data storage for analysis results and past messages.

[1729] Software: Natural language processing (NLP) engines, data encryption software via SSL / TLS protocols, push notification services, etc.

[1730] 4. Program Processing

[1731] Input method: The user inputs emotions and text through a dedicated interface. Emotion options include "joy," "sadness," and "anger," and the user can enter any text in the text input field.

[1732] Data transmission: The data entered by the user is encrypted using the SSL / TLS protocol and sent to the server.

[1733] Data analysis: The server passes the received data to a natural language processing (NLP) engine for sentiment analysis and text analysis. The analysis results are stored in a database.

[1734] Message Generation: Based on the analysis results, the server generates an appropriate feedback message, for example, "My friend is very sad. Please say some kind words to him."

[1735] Message sending: The generated message is sent to the selected user's device via push notification, email, or other method of their choice.

[1736] Feedback reception: The shared user receives the message and can send an appropriate response. The response message is sent back to the server and displayed to the original user.

[1737] Show Feedback: The original user can read the response and provide further feedback.

[1738] 5. Specific Examples

[1739] For example, user A enters, "Something very sad happened today." This data is encrypted and sent to the server, where the emotion "sadness" is analyzed using natural language processing. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then sent back through the server and displayed to user A. This process allows users A and B to share their emotions at a deep level.

[1740] 6. Examples of prompts

[1741] 1. "Generate a message to communicate to User B that User A is sad."

[1742] 2. "Please explain the steps to perform sentiment analysis and generate an appropriate response message."

[1743] This will create a system that allows users to securely share their feelings and thoughts, promoting mutual understanding and empathy.

[1744] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1745] The flow of this system's program processing

[1746] Step 1:

[1747] The user enters emotions and text on the device

[1748] explanation:

[1749] Users use a dedicated interface on their device to input their own emotions and thoughts. Emotion options include "joy," "sadness," and "anger," and they can enter any text they like in the text input field.

[1750] Input and Output:

[1751] Input: Emotion (e.g., "Sad") and text (e.g., "Something very sad happened to me today.")

[1752] Output: User input data

[1753] Specific behavior:

[1754] The user selects "sadness" from the emotion selection list, enters "Something very sad happened today" in the text box, and clicks the send button.

[1755] Step 2:

[1756] The device sends the input data to the server

[1757] explanation:

[1758] The device encrypts the emotions and text data entered by the user using the SSL / TLS protocol and securely transmits them to the server.

[1759] Input and Output:

[1760] Input: User-entered data

[1761] Output: Encrypted data

[1762] Specific behavior:

[1763] The device encrypts the data "something very sad happened today" and "sadness," and makes a request to the server to send the data.

[1764] Step 3:

[1765] The server analyzes the received data

[1766] explanation:

[1767] The server decrypts the received data using the SSL / TLS protocol, then passes it to a natural language processing (NLP) engine for sentiment and text analysis, and stores the results in a database.

[1768] Input and Output:

[1769] Input: Encrypted data

[1770] Output: Analysis result data

[1771] Specific behavior:

[1772] The server passes the decoded data to the NLP engine, which analyzes the text "Something very sad happened today" and the emotion "sadness." The analysis results are stored in a database along with the user ID.

[1773] Step 4:

[1774] The server generates the appropriate message

[1775] explanation:

[1776] Based on the analysis, the server generates a feedback message, such as "Your friend is very sad. Please say something kind to him / her."

[1777] Input and Output:

[1778] Input: Analysis result data

[1779] Output: Feedback message

[1780] Specific behavior:

[1781] The server compares the analysis results with past data and generates a notification message saying, "Your friend is very sad. Please say some kind words to him."

[1782] Step 5:

[1783] The server sends a message to another user's device.

[1784] explanation:

[1785] The generated message will be sent to the selected user's device via push notification, email, or other method of their choice.

[1786] Input and Output:

[1787] Input: Feedback message

[1788] Output: Notification message sent

[1789] Specific behavior:

[1790] The server sends a notification message to User B. On User B's device, a message saying "Your friend is very sad. Please say something kind to him / her." is displayed in the notification bar.

[1791] Step 6:

[1792] The shared user receives the message and responds.

[1793] explanation:

[1794] The receiving user can read the notification and send an appropriate response, which is then sent back to the server and displayed to the original user.

[1795] Input and Output:

[1796] Input: Notification message

[1797] Output: Response message

[1798] Specific behavior:

[1799] User B types in "What happened today? Let's talk and feel better." and clicks the send button. The device encrypts this and sends it to the server.

[1800] Step 7:

[1801] The original user receives feedback

[1802] explanation:

[1803] The original user reads the reply message and can then send further messages as feedback, which are again routed through the server and notified to other users as needed.

[1804] Input and Output:

[1805] Input: Response message

[1806] Output: Feedback message

[1807] Specific behavior:

[1808] User A reads the response, "What happened today? Let's talk and feel better," on the device, and enters and sends feedback such as, "Thank you, I feel a little better now." The device then encrypts the feedback and sends it to the server.

[1809] The above steps provide a detailed explanation of the processing flow of a system that allows users to share emotions and text and promote mutual understanding and empathy.

[1810] (Application example 1)

[1811] 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."

[1812] Current security systems face the challenge of being unable to immediately detect and respond to abnormal emotions and behaviors. In particular, when strengthening security at work or home, there are limited means of monitoring changes in the emotions and abnormalities of employees and residents in real time, making it difficult to prevent serious incidents.

[1813] 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.

[1814] In this invention, the server includes means for a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user terminal, means for receiving a response from another user and displaying it to the original user, means for acquiring video and audio data, means for analyzing the acquired data in real time, and means for detecting abnormal emotions from the analysis results and generating a notification, thereby enabling abnormal emotions and behaviors to be detected quickly and appropriate measures to be taken.

[1815] "Means for users to input emotions and text" refers to an interface that allows users to freely input their own emotions and thoughts.

[1816] "Means for transmitting user input data" refers to a communication means for transmitting data input by a user to a server.

[1817] "Means for analyzing received data" refers to software or algorithms used by the server to analyze user input data received by the server.

[1818] "Means for generating optimal messages based on analysis results" refers to a system or process for generating appropriate messages for users based on analyzed data.

[1819] The "means for transmitting the generated message to another user terminal" refers to a communication means for transmitting the generated message to another user terminal.

[1820] "Means for receiving a response from another user and displaying it to the original user" refers to a system or process for receiving a response from another user and displaying the content to the original user.

[1821] "Means for acquiring video and audio data" refers to a device or system for collecting video and audio data using a camera or microphone.

[1822] "Means for analyzing acquired data in real time" refers to software or algorithms for analyzing collected video and audio data in real time.

[1823] "Means for detecting anomalous emotions from the analysis results and generating notifications" refers to a system or process for detecting anomalous emotions from data analyzed in real time and generating corresponding notifications.

[1824] Overall system configuration

[1825] This invention is a system designed to allow users to share their thoughts and feelings and deepen mutual understanding and empathy. The system is mainly composed of three main components: a user terminal, a server, and a database.

[1826] Hardware and Software Configuration

[1827] User terminal

[1828] The user terminal is equipped with an interface for inputting emotions and text, a camera and a microphone for collecting video and audio data, and a dedicated application installed on it, which transmits the data input by the user to a server.

[1829] server

[1830] The server uses an advanced natural language processing (NLP) engine and machine learning algorithms to analyze user input data in real time. The server has the following functions:

[1831] Parses the received data and generates the appropriate message.

[1832] Video and audio data is analyzed in real time to detect abnormal emotions.

[1833] The analysis results, generated messages, and notification contents are saved in a database.

[1834] Database

[1835] The database stores users' emotional data, past interactions, and analysis results, allowing it to compare with past data to more accurately detect abnormal emotions and generate appropriate feedback.

[1836] Specific examples of hardware and software used

[1837] Camera: A device for acquiring video data

[1838] Microphone: A device for collecting audio data

[1839] PC: A computer for analyzing video and audio data

[1840] NLP engine: Natural language processing (e.g. NLPEngine)

[1841] Communication protocol: Data encryption via SSL / TLS

[1842] How to operate the system

[1843] Users can input their feelings and thoughts using an interface for inputting emotions and text, and the system captures the user's video and audio data through a camera and microphone. This data is then encrypted and sent to a server.

[1844] The server analyzes the received data and generates an appropriate message or notification if it detects an abnormal emotion. The generated message is immediately sent to another user device. The user who receives this message can check the content of the notification and take appropriate action.

[1845] Specific examples

[1846] For example, if this system is implemented in a workplace security system, an employee can input "Something very sad happened today." This data is sent to the server along with video and audio data collected through cameras and microphones. The server analyzes this data in real time and generates a notification based on the analysis results saying, "An abnormal emotion has been detected. Please check immediately." This notification is then immediately sent to the security staff's device.

[1847] Prompt Sentence Examples

[1848] For example, you could use a prompt like, "We want to use emotion analysis to improve security in the workplace. Please propose an application that can quickly detect people's anger or fear and immediately notify security staff. Please also tell us the specific implementation method and technology used."

[1849] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1850] Step 1:

[1851] The user inputs emotions and text. The user inputs "Something very sad happened today" into a dedicated interface on the terminal. This input data includes the user's emotion options and text. Input: Emotion (sadness) and text (Something very sad happened today). Output: Input data.

[1852] Step 2:

[1853] The device sends the input data to the server. The device encrypts the input emotion and text data using the SSL / TLS protocol and then sends it to the server. Input: Emotion and text data. Output: Encrypted data.

[1854] Step 3:

[1855] The server decrypts and analyzes the received data. The server decrypts the received encrypted data and passes it to a natural language processing (NLP) engine for sentiment and text analysis. Input: Encrypted data. Output: Analysis results (e.g., "very sad").

[1856] Step 4:

[1857] The server generates the optimal message based on the analysis results. Based on the analysis results, the server automatically generates a recommended message such as "Your friend is very sad. Please say something kind to them." Input: Analysis results. Output: Generated message.

[1858] Step 5:

[1859] The server sends the generated message to another user's device. The server sends the generated message to another user's device. The sending method depends on the user's settings, such as push notification or email. Input: Generated message. Output: Notification to another user's device.

[1860] Step 6:

[1861] Another user receives the message and responds. Another user receives the message, types a response such as "What happened today? Let's talk and feel better," and sends it from their device. This response is encrypted and sent to the server. Input: Generated message. Output: Response message.

[1862] Step 7:

[1863] The server sends a response message to the original user. The server decrypts the received response message and sends it to the original user's terminal. Input: Response message. Output: Feedback message to the original user.

[1864] Step 8:

[1865] The original user receives the feedback. The original user receives the feedback message and can enter their own emotions and situation again if necessary to make a further response. Input: Feedback message. Output: New emotions and text data.

[1866] In this way, users can share their thoughts and feelings in real time, deepening mutual understanding and empathy.

[1867] 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.

[1868] 1. Overview

[1869] This invention is a system for sharing thoughts and emotions between users to deepen mutual understanding and empathy. The purpose is to reduce misunderstandings and conflicts by having users input their emotions and thoughts and then appropriately convey the analyzed data to other users. Furthermore, this invention combines an emotion engine to enhance the recognition of users' emotions.

[1870] 2. System Configuration

[1871] This system consists of a user terminal, a server, a database, and an emotion engine. The user terminal is equipped with input and receiving means, and the server is responsible for analyzing data and generating messages. The database stores the analysis results and past interactions, and the emotion engine recognizes the user's emotions.

[1872] 3. Program Processing

[1873] The user enters emotions and text on the device

[1874] The user inputs emotions and text through the interface. The emotions are analyzed in real time by the emotion engine. The emotion engine integrates the selected emotion, text input, voice input, and facial expression analysis using facial recognition to determine a comprehensive emotion. For example, if a user inputs "Something very sad happened today," the emotion engine will recognize that the emotion "sadness" is strong.

[1875] Example: User (entered on the terminal)

[1876] Emotion selection: "Sadness"

[1877] Text: "Something very sad happened today."

[1878] The device sends the input data to the server

[1879] The entered emotion and text data is encrypted on the device and then sent to the server using the SSL / TLS protocol.

[1880] Example: Terminal (data transmission)

[1881] encrypted_data = SSL / TLS(user_input)

[1882] Server (data reception)

[1883] decrypt(encrypted_data)

[1884] The server analyzes the received data

[1885] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for emotion and text analysis. The analysis engine extracts emotions from the text in real time, and the emotion engine performs a comprehensive emotion determination by combining facial recognition and voice analysis. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database and compared with past data.

[1886] Example: Server (analysis)

[1887] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1888] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[1889] Server (storing analysis results)

[1890] Database.save(user_id, comprehensive_emotion)

[1891] The server generates the appropriate message

[1892] Based on the analysis results, the server generates appropriate feedback and notification messages for the user, such as "My friend is very sad. Please say some kind words to him."

[1893] Example: Server (message generation)

[1894] message = generateMessage(comprehensive_emotion)

[1895] The server sends a message to another user's device.

[1896] The generated messages and notifications will be sent to the selected other users' devices via push notifications, emails, or other methods set by the user.

[1897] Example: Server (data transmission)

[1898] send_notification(recipient_id, message)

[1899] Terminal (data reception)

[1900] display_notification(message)

[1901] The person you shared with will receive the message

[1902] The receiving user reads the notification, prepares a response message if necessary, and sends it to the server via the terminal, which then sends the message back to the server and delivers it to the original user.

[1903] Example: Another user (entered in the terminal)

[1904] response_message = "What happened today? Let's talk and feel better."

[1905] Terminal (data transmission)

[1906] encrypted_response = SSL / TLS(response_message)

[1907] Server (data reception & analysis)

[1908] decrypt(encrypted_response)

[1909] The original user receives feedback

[1910] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users as needed.

[1911] Example: Original user (displayed on terminal)

[1912] display_response(response_message)

[1913] Original user (entered on the terminal)

[1914] additional_feedback = "Thanks, I feel a little better now."

[1915] Terminal (data transmission)

[1916] send_feedback(additional_feedback)

[1917] 4. Specific examples of implementation

[1918] For example, if user A enters "Something very sad happened today," the emotion engine will determine this as "sadness." This data is encrypted and sent to the server, where it is analyzed by natural language processing and the emotion engine. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then displayed to user A via the server again. Through this process, users A and B share their emotions at a deep level, promoting mutual understanding and empathy.

[1919] As described above, the system of the present invention provides an embodiment that effectively shares users' emotions and thoughts and combines advanced emotion recognition technology, improving the quality of communication between users and facilitating the sharing of emotions.

[1920] The processing flow will be explained below.

[1921] Step 1:

[1922] User enters emotion and text

[1923] The user inputs emotions and text through the device's interface. Emotions can be selected from options such as "joy," "sadness," and "anger," and thoughts and feelings can be freely entered in the text entry field. Furthermore, facial expressions can be captured using voice input or a camera, if necessary. For example, a user can select the emotion of sadness along with the text "Something very sad happened today."

[1924] User (typed on device): Emotion selection: "Sadness" Text: "Something very sad happened today."

[1925] Step 2:

[1926] The device sends the input data to the server

[1927] The input emotion and text data, as well as audio and image data, are encrypted on the device and sent to the server using the SSL / TLS protocol.

[1928] Terminal (data transmission): encrypted_data = SSL / TLS(user_input)

[1929] Server (receiving data): decrypt(encrypted_data)

[1930] Step 3:

[1931] The server analyzes the received data

[1932] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for analysis. The natural language processing engine extracts emotions from the text, and the emotion engine performs voice analysis and facial recognition to comprehensively determine emotions. For example, text analysis may recognize strong "sadness," voice analysis may sense "sadness" from a low tone, and facial recognition may detect traces of tears.

[1933] Server(analysis): emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1934] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[1935] Server (saving analysis results): Database.save(user_id, comprehensive_emotion)

[1936] Step 4:

[1937] The server generates the appropriate message

[1938] Based on the analysis results, the server generates an appropriate feedback or notification message, such as "Your friend is very sad. Please say something kind to him / her."

[1939] Server (Message generation): message = generateMessage(comprehensive_emotion)

[1940] Step 5:

[1941] The server sends a message to another user's device.

[1942] The generated messages and notifications are sent to the selected users' devices via push notifications or emails, depending on the recipient's settings.

[1943] Server (data sending): send_notification(recipient_id, message)

[1944] Device (receiving data): display_notification(message)

[1945] Step 6:

[1946] The person you shared with will receive the message

[1947] The recipient user reads the notification, prepares a response message if necessary, and sends it from the terminal to the server, where it is again encrypted and sent to the server.

[1948] Another user (typed on device): response_message = "What happened today? Let's talk and clear things up."

[1949] Terminal (data transmission): encrypted_response = SSL / TLS(response_message)

[1950] Server (receiving and analyzing data): decrypt(encrypted_response)

[1951] Step 7:

[1952] The original user receives feedback

[1953] The original user can read the reply message from the other user and send additional feedback, which is then passed through the server again and may be notified to other users if necessary.

[1954] Original user (displayed on terminal): display_response(response_message)

[1955] Original user (typed on device): additional_feedback = "Thanks, I feel a little better now."

[1956] Terminal (data transmission): send_feedback(additional_feedback)

[1957] summary

[1958] Through these steps, the system allows users to share their thoughts and feelings in real time, fostering a deep level of mutual understanding and empathy. At each step, data encryption, analysis, and feedback loops function properly to achieve high-quality communication.

[1959] Example 2

[1960] 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."

[1961] In modern society, many people face misunderstandings and conflicts in communication. In particular, it is difficult to accurately convey emotions, resulting in a lack of mutual understanding and empathy. Therefore, a system that allows users to efficiently share their emotions and thoughts and deepen mutual understanding and empathy is needed.

[1962] 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 device for a user to input emotions and text, a device for encrypting and transmitting the input data, a device for analyzing the received data, a device for generating an appropriate message based on the analysis result, a device for transmitting the generated message to other terminals, and a device for receiving and displaying responses from other terminals. This enables users to effectively share emotions and thoughts, reducing misunderstandings and conflicts.

[1963] A "user" is an individual or group that uses the system and inputs emotions and text into a terminal.

[1964] A "device" is a combination of hardware and software that performs a specific function and is used to process data entered by a user.

[1965] "Encryption" is a technology that converts transmitted data so that it cannot be read by third parties, and is used to ensure secure data transmission.

[1966] The "SSL / TLS protocol" is an encryption protocol for securely transmitting data over the Internet, preventing data tampering and eavesdropping.

[1967] A "server" is a central processing unit that receives data sent by users and performs analysis and message generation.

[1968] A "natural language processing engine" is software that analyzes text data entered by a user and recognizes its meaning and emotion.

[1969] An "emotion engine" is software that evaluates and analyzes a user's emotions and generates appropriate messages based on the results.

[1970] A "database" is a data storage system for storing analysis results and past data, facilitating data management and retrieval.

[1971] "Message generation" is the process of creating appropriate notification or response messages based on the analysis results.

[1972] "Push notification" is a technology that sends messages directly from a server to a user's device, enabling instant information transmission.

[1973] "Feedback" is a response or additional information from a user, including a reaction or impression of another user.

[1974] 1. Overview

[1975] This invention is a system for sharing thoughts and emotions between users to deepen mutual understanding and empathy. The purpose is to reduce misunderstandings and conflicts by having users input their emotions and thoughts and then appropriately convey the analyzed data to other users. Furthermore, this invention combines an emotion engine to enhance the recognition of users' emotions.

[1976] 2. System Configuration

[1977] This system consists of a user terminal, a server, a database, and an emotion engine. The user terminal is equipped with input and receiving means, and the server is responsible for analyzing data and generating messages. The database stores the analysis results and past interactions, and the emotion engine recognizes the user's emotions.

[1978] 3. The user enters the emotion and text on the device.

[1979] The user inputs emotions and text through the interface. The emotions are analyzed in real time by the emotion engine. The emotion engine integrates the selected emotion, text input, voice input, and facial expression analysis using facial recognition to determine a comprehensive emotion. For example, if a user inputs "Something very sad happened today," the emotion engine will recognize that the emotion "sadness" is strong.

[1980] Example: User (entered on the terminal)

[1981] Emotion selection: "Sadness"

[1982] Text: "Something very sad happened today."

[1983] 4. The device sends the input data to the server

[1984] The entered emotion and text data is encrypted on the device and then sent to the server using the SSL / TLS protocol.

[1985] Example: Terminal (data transmission)

[1986] encrypted_data = SSL / TLS(user_input)

[1987] Server (data reception)

[1988] decrypt(encrypted_data)

[1989] 5. The server analyzes the received data

[1990] The server passes the received data to a natural language processing (NLP) engine and an emotion engine for emotion and text analysis. The analysis engine extracts emotions from the text in real time, and the emotion engine performs a comprehensive emotion determination by combining facial recognition and voice analysis. For example, it may be analyzed that "sadness" is particularly strong. The analysis results are stored in a database and compared with past data.

[1991] Example: Server (analysis)

[1992] emotion_analysis = NLPEngine.analyze_emotion(user_input)

[1993] comprehensive_emotion = EmotionEngine.combine_audio_visual(emotion_analysis)

[1994] Server (storing analysis results)

[1995] Database.save(user_id, comprehensive_emotion)

[1996] 6. The server generates the appropriate message

[1997] Based on the analysis results, the server generates appropriate feedback and notification messages for the user, such as "My friend is very sad. Please say some kind words to him."

[1998] Example: Server (message generation)

[1999] message = generateMessage(comprehensive_emotion)

[2000] 7. The server sends the message to another user device

[2001] The generated messages and notifications will be sent to the selected other users' devices via push notifications, emails, or other methods set by the user.

[2002] Example: Server (data transmission)

[2003] send_notification(recipient_id, message)

[2004] Terminal (data reception)

[2005] display_notification(message)

[2006] 8. The shared user receives the message

[2007] The receiving user reads the notification, prepares a response message if necessary, and sends it to the server via the terminal, which then sends the message back to the server and delivers it to the original user.

[2008] Example: Another user (entered in the terminal)

[2009] response_message = "What happened today? Let's talk and feel better."

[2010] Terminal (data transmission)

[2011] encrypted_response = SSL / TLS(response_message)

[2012] Server (data reception & analysis)

[2013] decrypt(encrypted_response)

[2014] 9. The original user receives feedback

[2015] The original user can read the response from the other user and provide further feedback, which will be resubmitted and notified to other users as needed.

[2016] Example: Original user (displayed on terminal)

[2017] display_response(response_message)

[2018] Original user (entered on the terminal)

[2019] additional_feedback = "Thanks, I feel a little better now."

[2020] Terminal (data transmission)

[2021] send_feedback(additional_feedback)

[2022] 10. Specific examples of implementation

[2023] For example, if user A enters "Something very sad happened today," the emotion engine will determine this as "sadness." This data is encrypted and sent to the server, where it is analyzed by natural language processing and the emotion engine. The server then generates a message saying, "My friend is very sad. Please say some kind words to him / her," and notifies user B. User B receives the notification and responds, "What happened today? Let's talk and feel better." This response message is then displayed to user A via the server again. Through this process, users A and B share their emotions at a deep level, promoting mutual understanding and empathy.

[2024] As described above, the system of the present invention provides an embodiment that effectively shares users' emotions and thoughts and combines advanced emotion recognition technology, improving the quality of communication between users and facilitating the sharing of emotions.

[2025] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2026] Step 1: User enters emotion and text on device

[2027] The user inputs emotions and text through the device interface. By selecting an emotion and entering text, for example, "Something very sad happened today," the input data (emotion, text) is analyzed in real time by the emotion engine, and is integrated with facial recognition and voice analysis data to determine a comprehensive emotion.

[2028] Input: User emotion selection ("Sad") and text ("Something very sad happened today")

[2029] Output: Comprehensive emotion judgment data

[2030] Step 2: The device sends the input data to the server

[2031] The device encrypts the input emotion and text data using the SSL / TLS protocol and sends it to the server. Encryption ensures secure data transmission.

[2032] Input: User input data and emotion judgment data

[2033] Output: Encrypted data

[2034] Step 3: Parse the data received by the server

[2035] The server decrypts the received encrypted data using the SSL / TLS protocol and passes it to a natural language processing (NLP) engine and emotion engine for analysis. The NLP engine analyzes the text, and the emotion engine performs emotion analysis, including voice analysis and facial recognition data.

[2036] Input: Encrypted data, decrypted input data, and emotion judgment data

[2037] Output: Analyzed emotion data and text analysis results

[2038] Step 4: The server generates the appropriate message

[2039] The server generates appropriate feedback and notification messages for the user based on the analysis results, such as "My friend is very sad. Please say some kind words to him."

[2040] Input: Parsed sentiment data and text analysis results

[2041] Output: The generated feedback message

[2042] Step 5: The server sends the message to another user device

[2043] The server then sends the generated messages and notifications to the selected users' devices via push notification, email, or other methods set by the users.

[2044] Input: The generated feedback message

[2045] Output: Messages and notifications sent

[2046] Step 6: The person you shared with receives the message

[2047] Another user reads the notification and message sent, prepares an appropriate reply message based on the content, and sends the reply message to the server via the terminal.

[2048] Input: Messages and notifications sent

[2049] Output: Response message

[2050] Step 7: The original user receives feedback

[2051] The original user can read the reply message from the other user and send further feedback based on the content. This feedback is also sent via the server and notified to other users as needed.

[2052] Input: Response message

[2053] Output: More feedback messages

[2054] (Application example 2)

[2055] 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."

[2056] In factory work environments, it is difficult to grasp the health status and emotions of workers in real time, which is one of the factors that leads to a decrease in work efficiency and a worsening working environment. In particular, the lack of appropriate feedback and support for workers who are feeling fatigued or stressed is a problem.

[2057] 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 a user to input emotions and text, means for transmitting the user's input data, means for analyzing the received data, means for generating an optimal message based on the analysis results, means for transmitting the generated message to another user terminal, means for receiving a response from another user and displaying it to the original user, means for analyzing the worker's facial expression, voice, and text and determining the worker's emotions, and means for generating appropriate feedback based on the determined emotions. This makes it possible to grasp the worker's emotions and state in real time and provide appropriate feedback and support.

[2058] A "means for user input of emotions and text" is a system or device that allows a user to input emotions and text through an interface.

[2059] The "means for transmitting user input data" refers to a communication means for transmitting data such as emotions and text input by the user to a server or other system.

[2060] "Means for analyzing received data" refers to analytical technology or software that processes the data received by the server from the user and determines their emotions or state.

[2061] The "means for generating optimal messages based on analysis results" refers to algorithms or programs for generating appropriate feedback or messages for users based on the results of data analysis.

[2062] The "means for transmitting the generated message to another user terminal" is a communication means for transmitting the generated message or feedback to the terminal of another designated user.

[2063] The "means for receiving a response from another user and displaying it to the original user" is a system or software for receiving a response or message from another user and displaying it to the original user.

[2064] "Means for analyzing the facial expressions, voice, and text of a worker and determining their emotions" refers to analytical technology and software for recognizing and determining the emotions of a worker using the worker's facial expressions, voice, and text data.

[2065] The "means for generating appropriate feedback based on the determined emotion" refers to an algorithm or program for generating appropriate feedback or support messages for the worker based on the determined emotion information.

[2066] The system for implementing this invention consists of a user terminal, a server, a database, and an emotion engine. The system analyzes the user's emotions and state in real time and provides appropriate feedback to improve the work environment and work efficiency.

[2067] System configuration

[2068] 1. User terminal: The user terminal provides an interface for the worker to input emotions and text. The emotion engine performs emotion analysis in real time, and the input data is sent to the server.

[2069] 2. Server: The server receives the data sent by the user and performs data analysis. Specifically, it performs sentiment analysis using a natural language processing (NLP) engine and an emotion engine, and generates appropriate messages and feedback based on the analysis results.

[2070] 3. Database: Includes a database for storing analysis results and past interactions, allowing historical data reference.

[2071] 4. Emotion engine: The emotion engine combines voice analysis, facial expression analysis, and text analysis to determine overall emotions.

[2072] Program processing

[2073] This system uses the following hardware and software:

[2074] Hardware:

[2075] Camera: for facial expression analysis

[2076] Microphone: For voice input

[2077] Computer: Data analysis and notification generation

[2078] software:

[2079] OpenCV: Camera image processing

[2080] EmotionEngine: Emotion recognition

[2081] NLPEngine: Text Analysis

[2082] Notification: Notification system

[2083] Processing flow and data calculation

[2084] 1. User input:

[2085] The user inputs emotions and text using the device, and the emotion engine analyzes the emotions in real time and sends the data to the server.

[2086] 2. Data transmission:

[2087] The data entered by the user is encrypted before being sent to the server. The SSL / TLS protocol is used.

[2088] 3. Data Analysis:

[2089] The server passes the received data to a natural language processing (NLP) engine and an emotion engine to perform emotion analysis and text analysis. The analysis results are stored in a database.

[2090] 4. Message Creation:

[2091] The server generates an appropriate feedback message for the user based on the analysis results. For example, if the emotion is determined to be "fatigue," an appropriate message (e.g., "You should take a break") is generated.

[2092] 5. Sending a message:

[2093] The server then sends the generated message to another user device via push notification, email, or other methods based on the user's settings.

[2094] 6. Receiving Response:

[2095] A response from another user is received and displayed to the original user.

[2096] Specific examples and prompts for the generative AI model

[2097] The system works as follows:

[2098] Examples:

[2099] The worker inputs "I'm tired," and the camera and microphone capture the situation. The results determine "fatigue" and "stress." The robot then notifies the worker, saying, "It's time to take a break."

[2100] Example prompt sentence:

[2101] "Worker has been detected as 'tired' based on facial expression, voice tone, and text input. Generate a notification to the worker suggesting a break."

[2102] This system makes it possible to grasp the emotions and state of workers in real time and provide appropriate feedback and support.

[2103] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2104] Step 1:

[2105] The user inputs emotions and text into the device. The input interface provides a text box and an emotion selection menu, and is also linked to a camera that detects facial expressions and a microphone that captures voice. The user's input includes the text data "Tired" and the emotion data "Tired," which are then analyzed in real time by the emotion engine.

[2106] Step 2:

[2107] The device encrypts the input emotion and text data and sends it to the server. The encryption uses the SSL / TLS protocol. If the input data is "tired" and "tired," the server receives it after encryption.

[2108] Step 3:

[2109] The server decrypts the received encrypted data and begins data analysis. The decrypted data is passed to a natural language processing (NLP) engine, which analyzes the text data "Tired." At the same time, the emotion engine analyzes the voice and facial expression data to determine a comprehensive emotion. For example, it may determine that "Tired" is very strong.

[2110] Step 4:

[2111] The server generates an appropriate message based on the analysis results. For example, if the result of emotion analysis is "fatigue," it generates a feedback message saying, "You should take a break." The analysis results and the generated message are stored in a database.

[2112] Step 5:

[2113] The server then sends the generated message to the worker using an appropriate notification method, such as push notification or email, and depending on the settings, a notification such as "It's best to take a break" is displayed on the worker's device.

[2114] Step 6:

[2115] The worker receives the notification and inputs a response, for example, "I'll continue working a little longer." This input data is then re-encrypted and sent to the server.

[2116] Step 7:

[2117] The server receives, decodes, and analyzes the worker's response, and determines how to address the original feedback using the results of the analysis, in this case generating a message to encourage further support.

[2118] Step 8:

[2119] The generated additional feedback message is then sent to the original worker. For example, a message saying, "Please take regular breaks and don't overexert yourself" is sent to the worker again. This process is repeated to manage the worker's health and work efficiency.

[2120] In this way, a system is realized that can grasp the emotions and state of the worker in real time and provide appropriate feedback.

[2121] 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.

[2122] 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.

[2123] 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.

[2124] 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.

[2125] 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.

[2126] 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.

[2127] 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).

[2128] 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.

[2129] 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."

[2130] 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.

[2131] 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).

[2132] 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.

[2133] 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.

[2134] 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.

[2135] 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.

[2136] 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.

[2137] 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.

[2138] 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.

[2139] 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.

[2140] 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.

[2141] 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.

[2142] The following is further disclosed regarding the above embodiment.

[2143] (Claim 1)

[2144] means for a user to input emotions and text;

[2145] means for transmitting user input data;

[2146] means for analyzing the received data;

[2147] A means for generating optimal messages based on the analysis results;

[2148] means for transmitting the generated message to another user terminal;

[2149] means for receiving and displaying to the original user a response from the other user;

[2150] A system including:

[2151] (Claim 2)

[2152] 10. The system of claim 1, wherein the data is transmitted encrypted.

[2153] (Claim 3)

[2154] 10. The system of claim 1, further comprising means for analyzing the received emotion using natural language processing.

[2155]

[2156] "Example 1"

[2157] (Claim 1)

[2158] means for a user to input emotions and text;

[2159] means for transmitting user input data;

[2160] means for encrypting the transmitted data and transmitting it to a server;

[2161] means for decoding and analyzing the received data;

[2162] means for analyzing the received emotion using natural language processing;

[2163] A means for generating an optimal feedback message based on the analysis results;

[2164] means for transmitting the generated message to another user terminal;

[2165] means for receiving and displaying to the original user a response from the other user;

[2166] A system including:

[2167] (Claim 2)

[2168] 10. The system of claim 1, wherein the data is transmitted encrypted.

[2169] (Claim 3)

[2170] 10. The system of claim 1, further comprising means for notifying a user when the generated feedback message is received.

[2171] "Application Example 1"

[2172] (Claim 1)

[2173] means for a user to input emotions and text;

[2174] means for transmitting user input data;

[2175] means for analyzing the received data;

[2176] A means for generating optimal messages based on the analysis results;

[2177] means for transmitting the generated message to another user terminal;

[2178] means for receiving and displaying to the original user a response from the other user;

[2179] means for acquiring video and audio data;

[2180] A means for analyzing the acquired data in real time;

[2181] a means for detecting abnormal emotions from the analysis results and generating a notification;

[2182] A system including:

[2183] (Claim 2)

[2184] 10. The system of claim 1, wherein the data is transmitted encrypted.

[2185] (Claim 3)

[2186] 10. The system of claim 1, further comprising means for analyzing the received emotion using natural language processing.

[2187] "Example 2: Combining Emotion Engines"

[2188] (Claim 1)

[2189] a device for a user to input emotions and text;

[2190] A device for encrypting and transmitting input data;

[2191] a device for analyzing the received data;

[2192] a device for generating an appropriate message based on the analysis results;

[2193] a device for transmitting the generated message to another terminal;

[2194] a device for receiving and displaying responses from other terminals;

[2195] A system including:

[2196] (Claim 2)

[2197] 10. The system of claim 1, wherein the encryption uses the SSL / TLS protocol.

[2198] (Claim 3)

[2199] 10. The system of claim 1, further comprising a device for analyzing the received emotions using a natural language processing engine and an emotion engine.

[2200] "Application example 2 when combining emotion engines"

[2201] (Claim 1)

[2202] means for a user to input emotions and text;

[2203] means for transmitting user input data;

[2204] means for analyzing the received data;

[2205] A means for generating optimal messages based on the analysis results;

[2206] means for transmitting the generated message to another user terminal;

[2207] means for receiving and displaying to the original user a response from the other user;

[2208] A means for analyzing the worker's facial expressions, voice, and text to determine their emotions;

[2209] means for generating appropriate feedback based on the determined emotion;

[2210] A system including:

[2211] (Claim 2)

[2212] 10. The system of claim 1, wherein the data is transmitted encrypted.

[2213] (Claim 3)

[2214] 10. The system of claim 1, further comprising means for analyzing the received emotion using natural language processing. [Explanation of symbols]

[2215] 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 a user to input emotions and text; means for transmitting user input data; means for analyzing the received data; A means for generating optimal messages based on the analysis results; means for transmitting the generated message to another user terminal; means for receiving and displaying to the original user a response from the other user; A system including:

2. 2. The system of claim 1, wherein the data is transmitted encrypted.

3. 10. The system of claim 1, further comprising means for analyzing the received emotions using natural language processing.

Images