system

Abstract

We provide the system. [Solution] A means for receiving text data entered via a user interface using a communication device, A processing device that uses a learning model for analyzing the aforementioned text data, A means for determining whether the text data contains inappropriate content using the aforementioned learning model, A means for displaying a warning on the user interface based on the determination result, A means for generating an instruction to stop the transmission of the text data when such inappropriate content is detected, A system that includes this.

Description

Technical Field

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

Background Art

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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, particularly, the problem of slander and inappropriate expressions on the Internet has been regarded as an issue. As a result, cases where an individual's dignity is damaged or a mental burden is imposed have been increasing. Especially in the current situation where the age group of Internet users is decreasing, the risk that the younger generation inadvertently posts inappropriate content is also increasing. Therefore, when users communicate online, there is a demand for a system that can detect inappropriate expressions in advance and prevent their use, thereby improving the quality of communication on the Internet.

Means for Solving the Problems

[0005] This invention provides a system for processing text data entered via a user interface. The system includes means for receiving text data via a communication device, means for text analysis using a processing device employing a learning model, means for determining whether the data contains inappropriate content, means for displaying a warning based on the determination result, and means for instructing the system to stop data transmission if inappropriate content is detected. Furthermore, the learning model is based on natural language processing and identifies inappropriate content, including insulting or defamatory expressions. The warning prompts the user to correct the text, preventing erroneous transmissions. This makes it possible to prevent inappropriate expressions during the text data transmission process.

[0006] A "user interface" is a means for a user to interact with a computer system or application, and is an interface for input and output.

[0007] A "communication device" is a hardware or software configuration for sending and receiving data, and is a device that has the function of transferring information over a network.

[0008] A "learning model" is an algorithm or artificial intelligence program that learns from data and has the ability to perform a specific task, and generally utilizes machine learning technology.

[0009] A "processing device" is a computing device or system for analyzing and processing data, and includes a computer processor and associated software.

[0010] "Inappropriate content" generally refers to expressions or words that may insult or offend others, and is usually considered socially or ethically unacceptable.

[0011] A "determination method" refers to a mechanism or algorithm for evaluating input data based on specific conditions or criteria and determining whether or not it applies.

[0012] A "warning display mechanism" is a function that visually or audibly notifies the user of a message or alert, prompting the user to pay attention or change their behavior.

[0013] A "transmission abort instruction" is a command to stop or cancel the transmission of data, and is a signal or command used to interrupt or stop processing.

[0014] "Natural language processing" is a technology that enables computers to understand, interpret, and generate human language. It is a field of artificial intelligence that involves analyzing text and audio data.

[0015] "Insulting or defamatory language" refers to language intended to identify and damage the reputation or attack the character of others, and which may be legally or socially problematic. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

[0019] <00001​​​​In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

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

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

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

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0037] The system of the present invention has the function of monitoring text data entered via a user interface and preventing inappropriate content from being entered. An embodiment thereof is described below.

[0038] First, the user uses the keyboard application on their device to input various messages and posts. The device provides an interface for the user's input and sends it to the server as needed after each input is completed.

[0039] The received text data is analyzed by a processing unit on the server. This analysis uses a learning model that applies natural language processing technology. The learning model is pre-trained to identify various defamatory and insulting expressions.

[0040] The server analyzes text data in real time and determines whether it contains inappropriate language. For example, if the word "idiot" is entered, the learning model recognizes that the word is insulting.

[0041] If inappropriate content is detected, the server immediately sends a warning message to the terminal. This warning message prompts the user to correct the input. In this process, the server also sends a command to the user interface to stop sending the relevant text.

[0042] The terminal receives a message from the server and displays an alert to the user. The user is required to correct the input string to the appropriate content or reconsider sending the message altogether, in response to this warning.

[0043] In this way, this system can prevent users from using defamatory language. For example, even if a user unintentionally uses problematic language, a warning will be displayed immediately, giving them an opportunity to make appropriate corrections. This system can be easily implemented on specific communication terminals and contributes to suppressing inappropriate language on the network and establishing healthy communication.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user uses a keyboard application to type a text message on the device. For example, the user types "You're the worst."

[0047] Step 2:

[0048] The terminal prepares to send the entered text data to the server via the computer network.

[0049] Step 3:

[0050] The server stores the text data received from the terminal in a queue for analysis.

[0051] Step 4:

[0052] The server analyzes the stored text data using a learning model based on natural language processing technology. This analysis determines whether the text data contains inappropriate content.

[0053] Step 5:

[0054] Based on the analysis results, the server generates a warning message if it determines that the text data contains inappropriate content. This message may include phrases such as, "This expression is inappropriate. Please correct it."

[0055] Step 6:

[0056] The server sends the generated warning message and a command to cancel transmission to the terminal.

[0057] Step 7:

[0058] The terminal receives a warning message from the server and displays it on the user interface. At the same time, it temporarily blocks user input and cancels transmission.

[0059] Step 8:

[0060] The user reviews the displayed warning message and either corrects the text and re-enters it, or cancels the input.

[0061] In this way, the entire system works together to prevent the use of inappropriate language.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] In today's information and communication society, inappropriate language and insulting comments on the internet and social media are on the rise. Such remarks not only hinder communication but can also cause social disruption and personal psychological damage. To prevent this problem, there is a need for a system that monitors text data transmitted by users over the network in real time and removes inappropriate content in advance. Furthermore, it is important to promptly point out problematic expressions that users may be using unknowingly and encourage them to correct them.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes means for receiving character data input via a user terminal using an information and communication device, a processing device that uses a machine learning model for analyzing the character data, and means for determining whether the character data contains inappropriate content. This effectively suppresses inappropriate expressions on the network and enables healthy communication.

[0067] A "user terminal" is an electronic device used by an individual to input data and communicate over a network.

[0068] An "information and communication device" is a device used to send and receive data and manage communication via a network.

[0069] "Text data" refers to information in text format that a user inputs for communication purposes.

[0070] A "machine learning model" is an algorithm that learns from large amounts of data and analyzes new data to extract specific patterns.

[0071] A "processing device" refers to a computer or related equipment used for computational processing, such as data analysis and model execution.

[0072] "Inappropriate content" refers to information that is insulting or defamatory and contains socially undesirable expressions.

[0073] "Means of determination" refers to methods or devices for analyzing input data, identifying its content, and making a judgment.

[0074] "Means of displaying warnings" refers to methods of displaying information, either visually or audibly, to draw the user's attention and prompt them to correct their input.

[0075] "Means for generating instructions to stop transmission" refers to a function that generates commands to stop the transmission of data deemed inappropriate.

[0076] This invention provides a system for preventing inappropriate expressions on the internet. The user inputs character data for communication using a keyboard application provided on their terminal. The terminal has the function of transmitting this character data to a server via a communication network.

[0077] The server utilizes a machine learning-based language processing model to analyze the received text data. Specifically, it uses a generative AI model that applies natural language processing technology to determine whether the text data contains inappropriate expressions. This language processing model is pre-trained to identify insulting and defamatory content. The processing unit within the server analyzes the data in real time, and if it determines that the content is inappropriate, it immediately sends a warning message to the terminal.

[0078] When a device receives a warning message, it displays an alert to the user. This gives the user an opportunity to recognize and correct any inappropriate content they may have entered by mistake. This system helps users to achieve healthy communication.

[0079] For example, if a user posts a comment on an online forum and enters negative language such as "This movie is terrible," the server will identify this language and send a stop command to the terminal. An example of a prompt message would be, "Please enter your comment to post on the online forum. Please be careful not to include inappropriate language. For example, please use expressions such as 'This is interesting, but you should think more before you comment!'" This would encourage the user to use appropriate language.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The server receives character data entered by the user using a keyboard application on the terminal. The input is text that the user wishes to send, and the server receives this data for analysis. The terminal performs this transmission process and transfers the data to the server.

[0083] Step 2:

[0084] The server analyzes the received text data using a machine learning model. Specifically, it uses natural language processing techniques to classify the content of the data. This process analyzes the text data received as input and detects the possibility of inappropriate expressions. As a result, a judgment is output indicating whether the data is safe or inappropriate.

[0085] Step 3:

[0086] Based on the analysis results described above, the server determines whether the text data contains inappropriate content. Using the results of this analysis, the server determines whether the data is inappropriate, and if it is determined to be inappropriate, it sets a flag to indicate this.

[0087] Step 4:

[0088] If inappropriate content is detected, the server generates and sends a warning message to the terminal. The input includes a judgment result, and since a warning is deemed necessary, the server creates a warning message for the user. The warning message may include, for example, "The input contains inappropriate language. Please correct the content."

[0089] Step 5:

[0090] The terminal displays warning messages received from the server through a user interface, allowing the user to recognize the warnings. The input is warning messages from the server, and the output is provided to the user as visual or audible alerts.

[0091] Step 6:

[0092] The user sees a warning message on their device and is given an opportunity to correct or reconsider their input. This process allows the user to re-edit the text data on their device and then decide whether to resend it. Ultimately, the goal is for the user to provide text data using appropriate language.

[0093] (Application Example 1)

[0094] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0095] In electronic transactions, the transmission of comments and messages containing inappropriate language can lead to trouble and misunderstandings between users. Preventing this is crucial. In particular, transaction feedback is important on electronic payment platforms, and inappropriate content in this feedback can affect the reliability of the service; therefore, this issue needs to be resolved.

[0096] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0097] In this invention, the server includes means for receiving text data input via a user interface using an information processing device, a computing device that uses a learning algorithm for analyzing the text data, and means for determining whether the text data contains inappropriate expressions using the learning algorithm. This makes it possible to prevent the transmission of text data containing inappropriate expressions while encouraging the user to correct them to appropriate expressions.

[0098] A "user interface" is a means used by a user to input data into an information processing device or to receive output from the device.

[0099] An "information processing device" is an electronic device used to perform processing such as receiving, calculating, and analyzing data.

[0100] A "learning algorithm" is a set of computational rules used to recognize patterns based on past data and to make certain judgments about future data.

[0101] A "processing unit" is a general term for devices and software used to perform calculations related to the analysis and determination of text data.

[0102] "Inappropriate language" refers to the use of language that is insulting or defamatory and that may cause problems in communication or business.

[0103] A "warning message" is information sent to users to alert them when inappropriate language is detected.

[0104] A "means for generating commands" is a mechanism that generates an instruction from an information processing device to perform a certain action when specific conditions are met.

[0105] "Transaction-related information" refers to the collective information and data generated through exchanges on electronic trading platforms.

[0106] The system that realizes this invention mainly consists of a server, an information processing device, and a user interface. The server is built using the Flask framework with Python and is responsible for processing text data received from the client terminal. The user interface uses JavaScript (registered trademark) to support data input and display.

[0107] The received text data is analyzed on the server side using a learning algorithm based on the Hugging Face Transformers package. This analysis determines in real time whether the text data contains inappropriate expressions. If inappropriate expressions are detected, the server sends a warning message to the terminal, prompting the user to correct the text data.

[0108] For example, if a user attempts to enter a comment about a transaction on an electronic payment platform, and the comment contains inappropriate language, the system will immediately detect this and issue a warning. This allows the user to revise the comment to appropriate language and re-enter it. A specific example of a prompt message would be: "A user is trying to write a review about their dissatisfaction with an online transaction. However, the language used is inappropriate. Please improve the phrasing so that we can provide more constructive feedback."

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] On the terminal, the user enters text data. This input is done through the user interface and is dynamically captured by JavaScript functionality. Specifically, the user enters a comment on the electronic payment platform, and that data is retrieved on the frontend.

[0112] Step 2:

[0113] The entered text data is sent from the terminal to the server. The server, which is an information processing device, analyzes the data received as an HTTP request. Data reception is performed securely and efficiently using a Flask server.

[0114] Step 3:

[0115] The server performs natural language processing on the received text data using the Hugging Face Transformers library. This process determines whether the text contains inappropriate expressions using a learning algorithm. In this step, the text data is input into the model, and an inappropriateness score is obtained as the model's output.

[0116] Step 4:

[0117] If the server determines, based on the analysis results, that something is inappropriate, it will generate a warning message. This message indicates that correction is needed, and the prompt is automatically selected by the AI ​​generation model.

[0118] Step 5:

[0119] A warning message is sent to the device and displayed on the user interface. The user receives this message, reviews the entered text data, and makes corrections as needed. This prevents the submission of inappropriate content. Users can then modify their comments constructively by referring to the corresponding feedback.

[0120] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0121] The present invention aims to analyze the user's emotional state and provide appropriate feedback by combining a system that analyzes user text input and detects defamatory or inappropriate content in advance with an emotion engine. An embodiment of this system is described below.

[0122] First, the user enters a text message using a keyboard application on their device. The device records the user's input in real time and sends the text data to the server. This data transmission takes place via a communication device.

[0123] The server receives the input text data and analyzes it using a learning model based on natural language processing technology. The analysis initiates a process to determine whether the text contains inappropriate expressions. At the same time, the emotion engine recognizes the user's emotional state. For example, if a phrase like "I hate you" is entered, it will not only be detected as slander, but anger or dissatisfaction will also be recognized as emotions.

[0124] Based on this analysis, the server generates a warning message. The content and presentation of the warning message are adjusted according to the results of the emotion engine. For example, if it is determined that the user is emotionally agitated, a calmer message will be presented to soothe the user. Also, if the user's emotions exceed a certain threshold, the server will inform the user of this and display advice and suggestions for mental self-care.

[0125] When the terminal receives a message from the server, it displays a warning on the user interface. This warning prompts the user to correct inappropriate content and, if necessary, provides emotional care information. The user can then adjust the text content or take other actions based on this information.

[0126] Thus, this system not only prevents inappropriate expressions during text input but also enables appropriate responses that take into account the user's emotional state. This function is expected to improve the health of online communication and contribute to the mental well-being of users.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The user uses the device's keyboard application to enter a message. For example, they might enter a message like, "You're the worst."

[0130] Step 2:

[0131] The terminal collects the entered text data and prepares to send it to the server via the communication network.

[0132] Step 3:

[0133] The server receives text data sent from the terminal and places it in a parsing queue. The data is then processed sequentially according to this queue.

[0134] Step 4:

[0135] The server analyzes text data using a learning model that utilizes natural language processing technology. During this process, it determines whether the text contains inappropriate content.

[0136] Step 5:

[0137] The server simultaneously uses an emotion engine to analyze the user's emotions based on text data. For example, if anger is detected from the text, the emotion level is also evaluated.

[0138] Step 6:

[0139] Based on the analysis results, the server generates a warning message. If the content is inappropriate, it issues a warning and adjusts the message content according to the user's emotional state.

[0140] Step 7:

[0141] The server sends warning messages and suggestions to the terminal, including advice for mental self-care as needed.

[0142] Step 8:

[0143] The terminal receives a warning message from the server and displays it to the user through the user interface. The user reviews the message and reconsiders its content and actions.

[0144] This process allows the system to prevent inappropriate expressions from users and to provide responses that take into account the user's emotional state.

[0145] (Example 2)

[0146] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0147] In modern society, with the increase in online communication, the use of inappropriate language and defamation are becoming increasingly frequent. Such behavior can degrade the quality of communication and negatively impact mental health. Furthermore, there is a lack of appropriate support tailored to users' emotional states, and there is a need to prevent trouble and misunderstandings before they occur. Therefore, a system is needed that can detect inappropriate content in advance and provide feedback that takes into account the user's emotional state.

[0148] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0149] In this invention, the server includes means for receiving encoded data input via a user interface using a communication component; an information processing device that uses an artificial intelligence model for analyzing the encoded data; means for determining whether the encoded data contains inappropriate information using the artificial intelligence model; means for evaluating the user's emotional state using an emotion recognition engine; means for displaying a warning on the user interface and providing feedback according to the emotional state based on the determination result and the emotion evaluation; and means for generating an instruction to restrict the transmission of the encoded data when inappropriate information is detected. This enables the prior detection of inappropriate content and flexible responses according to the user's emotional state.

[0150] A "user interface" is an interface that allows a user to input information into a device or system and to operate it.

[0151] "Encoded data" refers to data in a format where user input is encoded and processed.

[0152] "Communication components" refer to hardware or software, including communication devices and network connections, used for sending and receiving data.

[0153] An "artificial intelligence model" is an artificial system that learns from large amounts of data, finds patterns and rules, and becomes capable of performing various tasks.

[0154] An "information processing device" is a device used for processing and analyzing data, and includes computers and servers.

[0155] "Inappropriate information" refers to information that contains insulting, defamatory, or libelous content that is undesirable or harmful in online communication.

[0156] An "emotion recognition engine" is a technology that identifies a user's emotional state from text and other inputs.

[0157] A "warning" is a message or alert that notifies the user and prompts them to take action when inappropriate information is detected.

[0158] "Feedback" refers to information or advice provided in response to user behavior to encourage correction or improvement.

[0159] A "transmission restriction instruction" is a command generated by the system to prevent or stop the transmission of detected inappropriate information.

[0160] This system is designed to improve the health of online communication. The process begins with the user typing a text message using a terminal. The terminal then transmits this encoded data to the server via a communication component.

[0161] The server uses an information processing device to analyze the received encoded data. This device is equipped with an artificial intelligence model based on natural language processing, which identifies whether the text contains inappropriate information, such as offensive language. In addition, the server uses an emotion recognition engine to evaluate the user's emotional state. This emotion analysis can detect whether the user is experiencing emotions such as anger or sadness.

[0162] Based on an analysis of inappropriate information and emotional states, the server generates a warning message. This message is displayed on the user interface, prompting the user to correct their behavior or engage in emotional self-care. For example, if a user enters "I hate you," the server will determine that the text is inappropriate, and its emotion recognition engine will detect anger. In this case, the server will generate a milder warning message such as "Avoid such language and let's discuss this calmly."

[0163] As an example of a prompt, by inputting the instruction "If a user uses inappropriate language, please provide an example of how to correct it" to the generative AI model, improved examples of language can be obtained.

[0164] User feedback is individually optimized. We hope this will improve the quality of online communication and protect users' mental well-being.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The user uses a terminal and enters a text message using a keyboard application. During this input process, the text is recorded on the terminal via the user interface. This step encompasses the entire process from the input text data being encoded to its transmission to the server via a communication device. The output is the encoded data sent to the server.

[0168] Step 2:

[0169] The server receives encoded data from the terminal via communication components and analyzes that data using an information processing device. Specifically, it uses an artificial intelligence model based on a generative AI model to determine whether the data contains inappropriate information, and simultaneously uses an emotion recognition engine to evaluate the user's emotional state. The input is encoded data, and the output is the result of the inappropriate information determination and the emotion evaluation result.

[0170] Step 3:

[0171] The server generates a warning message based on the analysis results. In this step, if inappropriate information is detected, a warning or feedback corresponding to that information is generated. For example, if it is determined that the user's emotions are heightened, a message encouraging calmness is prepared. The input is the analysis results obtained in step 2, and the output is the generated warning message.

[0172] Step 4:

[0173] The terminal displays warning messages received from the server in the user interface. These messages prompt the user to take appropriate action and provide advice on correcting inappropriate language and emotional care. The input is the warning message from the server, and the output is visual feedback to the user.

[0174] Step 5:

[0175] The user may modify the text message based on the displayed warning message. In this step, the user may re-enter or adjust the wording and send it back to the server as needed. The re-sent data is the output here and may be subjected to further analysis processes.

[0176] (Application Example 2)

[0177] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0178] With the widespread use of online communication, there has been an increase in defamatory and inappropriate text, which can threaten mental health. Furthermore, one-sided warnings that disregard users' feelings do not lead to a fundamental solution to the problem.

[0179] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0180] In this invention, the server includes means for receiving text information input via a user interface using a communication device, a processing unit that uses a learning model for analyzing the text information, and means for analyzing the user's emotional state using an emotion engine. This makes it possible not only to determine whether the text contains inappropriate expressions, but also to provide feedback and self-care advice that takes the user's emotional state into consideration.

[0181] "User interface" refers to the screen or means of operation that allows a user to input and output data to and from an information device.

[0182] A "communication device" is a device that uses digital or analog signals to send and receive information over a network.

[0183] "Text information" refers to data or message content composed of strings of characters, and specifically means the text information entered by the user.

[0184] A "learning model" is a statistical algorithm based on machine learning techniques using historical data, and is an artificial intelligence model trained to perform a specific task.

[0185] A "processing device" is a computer or a device with the functions of executing programs and analyzing and processing data.

[0186] An "emotion engine" is an algorithm or module used to analyze and classify emotional states from text sent by users.

[0187] "Defamation" refers to unfairly speaking ill of or belittling others, and is an expression that damages their reputation or credibility.

[0188] "Self-care advice" refers to information that provides guidelines and suggestions that users can implement to manage themselves and maintain or improve their mental health.

[0189] This invention provides a system aimed at maintaining the health of online communication and promoting the mental well-being of users. This system analyzes text information entered by users in real time to determine if it contains defamation or inappropriate content. Furthermore, it uses an emotion engine to analyze the user's emotional state and generate appropriate feedback.

[0190] The server uses a communication device to receive text information entered through the user interface. The received information is processed in real time by a learning model. This learning model uses natural language processing technology and incorporates a generative model to detect inappropriate expressions. The emotion engine analyzes the user's emotions and detects states such as anger and dissatisfaction.

[0191] Based on the analysis results, the server generates feedback and displays a warning in the user interface. This warning prompts the user to revise the message and, at the same time, can provide self-care advice depending on the user's emotional state. For example, if a user enters an aggressive message and the emotion engine detects anger, a message will be displayed encouraging them to calm down with gentle language.

[0192] This system incorporates natural language processing technology and sentiment analysis capabilities, and can be implemented via software such as TENSORFLOW® or Keras.

[0193] For example, if a user types "You are useless," the system will recognize this as a negative expression and offer suggestions such as "This message is inappropriate. Let's think of another way to say it." Furthermore, if the input is deemed emotionally intense, self-care advice, such as encouraging deep breathing, will also be provided.

[0194] An example of a prompt might be: "Design a system that analyzes user-entered text in real time for defamation and emotional state, and provides appropriate feedback."

[0195] This system allows users to participate in online interactions with peace of mind, and by preventing inappropriate remarks, it provides a healthy environment for communication.

[0196] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0197] Step 1:

[0198] The user inputs text information through the user interface. The terminal receives this input and transmits it to the server in real time via a communication device. The input data is the user's raw text information.

[0199] Step 2:

[0200] The server first uses a learning model to analyze the received text information. This model is a generative model based on natural language processing technology and is trained to detect inappropriate expressions. The input data is text information, and the server outputs a result of determining whether it contains inappropriate content through calculations.

[0201] Step 3:

[0202] The server then uses an emotion engine to analyze the user's emotional state. This engine detects emotional words and phrases in the text and infers the user's emotional state. The input data is text information, and the calculations output a result indicating the user's emotional state.

[0203] Step 4:

[0204] The server generates feedback based on the analysis results. If the judgment result indicates something inappropriate, a warning is displayed on the user interface, prompting the user to correct the content. Self-care advice is also provided depending on the emotional state. The input data for this step is the judgment result and the emotion analysis result, and a feedback message generated through calculations is output.

[0205] Step 5:

[0206] The terminal receives feedback messages from the server and displays them on the user interface. Users can view these messages and, if necessary, modify them or take action based on the advice. The input data is the feedback message, which is output in its original format.

[0207] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0208] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0209] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0210] [Second Embodiment]

[0211] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0212] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0213] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0214] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0215] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0216] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0217] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0218] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0219] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0220] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0221] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0222] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0223] The system of the present invention has the function of monitoring text data entered via a user interface and preventing inappropriate content from being entered. An embodiment thereof is described below.

[0224] First, the user uses the keyboard application on their device to input various messages and posts. The device provides an interface for the user's input and sends it to the server as needed after each input is completed.

[0225] The received text data is analyzed by a processing unit on the server. This analysis uses a learning model that applies natural language processing technology. The learning model is pre-trained to identify various defamatory and insulting expressions.

[0226] The server analyzes text data in real time and determines whether it contains inappropriate language. For example, if the word "idiot" is entered, the learning model recognizes that the word is insulting.

[0227] If inappropriate content is detected, the server immediately sends a warning message to the terminal. This warning message prompts the user to correct the input. In this process, the server also sends a command to the user interface to stop sending the relevant text.

[0228] The terminal receives a message from the server and displays an alert to the user. The user is required to correct the input string to the appropriate content or reconsider sending the message altogether, in response to this warning.

[0229] In this way, this system can prevent users from using defamatory language. For example, even if a user unintentionally uses problematic language, a warning will be displayed immediately, giving them an opportunity to make appropriate corrections. This system can be easily implemented on specific communication terminals and contributes to suppressing inappropriate language on the network and establishing healthy communication.

[0230] The following describes the processing flow.

[0231] Step 1:

[0232] The user uses a keyboard application to type a text message on the device. For example, the user types "You're the worst."

[0233] Step 2:

[0234] The terminal prepares to send the entered text data to the server via the computer network.

[0235] Step 3:

[0236] The server stores the text data received from the terminal in a queue for analysis.

[0237] Step 4:

[0238] The server analyzes the stored text data using a learning model based on natural language processing technology. This analysis determines whether the text data contains inappropriate content.

[0239] Step 5:

[0240] Based on the analysis results, the server generates a warning message if it determines that the text data contains inappropriate content. This message may include phrases such as, "This expression is inappropriate. Please correct it."

[0241] Step 6:

[0242] The server sends the generated warning message and a command to cancel transmission to the terminal.

[0243] Step 7:

[0244] The terminal receives a warning message from the server and displays it on the user interface. At the same time, it temporarily blocks user input and cancels transmission.

[0245] Step 8:

[0246] The user reviews the displayed warning message and either corrects the text and re-enters it, or cancels the input.

[0247] In this way, the entire system works together to prevent the use of inappropriate language.

[0248] (Example 1)

[0249] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0250] In today's information and communication society, inappropriate language and insulting comments on the internet and social media are on the rise. Such remarks not only hinder communication but can also cause social disruption and personal psychological damage. To prevent this problem, there is a need for a system that monitors text data transmitted by users over the network in real time and removes inappropriate content in advance. Furthermore, it is important to promptly point out problematic expressions that users may be using unknowingly and encourage them to correct them.

[0251] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0252] In this invention, the server includes means for receiving character data input via a user terminal using an information and communication device, a processing device that uses a machine learning model for analyzing the character data, and means for determining whether the character data contains inappropriate content. This effectively suppresses inappropriate expressions on the network and enables healthy communication.

[0253] A "user terminal" is an electronic device used by an individual to input data and communicate over a network.

[0254] An "information and communication device" is a device used to send and receive data and manage communication via a network.

[0255] "Text data" refers to information in text format that a user inputs for communication purposes.

[0256] A "machine learning model" is an algorithm that learns from large amounts of data and analyzes new data to extract specific patterns.

[0257] A "processing device" refers to a computer or related equipment used for computational processing, such as data analysis and model execution.

[0258] "Inappropriate content" refers to information that is insulting or defamatory and contains socially undesirable expressions.

[0259] "Means of determination" refers to methods or devices for analyzing input data, identifying its content, and making a judgment.

[0260] "Means of displaying warnings" refers to methods of displaying information, either visually or audibly, to draw the user's attention and prompt them to correct their input.

[0261] "Means for generating instructions to stop transmission" refers to a function that generates commands to stop the transmission of data deemed inappropriate.

[0262] This invention provides a system for preventing inappropriate expressions on the internet. The user inputs character data for communication using a keyboard application provided on their terminal. The terminal has the function of transmitting this character data to a server via a communication network.

[0263] The server utilizes a machine learning-based language processing model to analyze the received text data. Specifically, it uses a generative AI model that applies natural language processing technology to determine whether the text data contains inappropriate expressions. This language processing model is pre-trained to identify insulting and defamatory content. The processing unit within the server analyzes the data in real time, and if it determines that the content is inappropriate, it immediately sends a warning message to the terminal.

[0264] When a device receives a warning message, it displays an alert to the user. This gives the user an opportunity to recognize and correct any inappropriate content they may have entered by mistake. This system helps users to achieve healthy communication.

[0265] For example, if a user posts a comment on an online forum and enters negative language such as "This movie is terrible," the server will identify this language and send a stop command to the terminal. An example of a prompt message would be, "Please enter your comment to post on the online forum. Please be careful not to include inappropriate language. For example, please use expressions such as 'This is interesting, but you should think more before you comment!'" This would encourage the user to use appropriate language.

[0266] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0267] Step 1:

[0268] The server receives character data entered by the user using a keyboard application on the terminal. The input is text that the user wishes to send, and the server receives this data for analysis. The terminal performs this transmission process and transfers the data to the server.

[0269] Step 2:

[0270] The server analyzes the received text data using a machine learning model. Specifically, it uses natural language processing techniques to classify the content of the data. This process analyzes the text data received as input and detects the possibility of inappropriate expressions. As a result, a judgment is output indicating whether the data is safe or inappropriate.

[0271] Step 3:

[0272] Based on the analysis results described above, the server determines whether the text data contains inappropriate content. Using the results of this analysis, the server determines whether the data is inappropriate, and if it is determined to be inappropriate, it sets a flag to indicate this.

[0273] Step 4:

[0274] If inappropriate content is detected, the server generates and sends a warning message to the terminal. The input includes a judgment result, and since a warning is deemed necessary, the server creates a warning message for the user. The warning message may include, for example, "The input contains inappropriate language. Please correct the content."

[0275] Step 5:

[0276] The terminal displays warning messages received from the server through a user interface, allowing the user to recognize the warnings. The input is warning messages from the server, and the output is provided to the user as visual or audible alerts.

[0277] Step 6:

[0278] The user sees a warning message on their device and is given an opportunity to correct or reconsider their input. This process allows the user to re-edit the text data on their device and then decide whether to resend it. Ultimately, the goal is for the user to provide text data using appropriate language.

[0279] (Application Example 1)

[0280] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0281] In electronic transactions, there is a problem that the transmission of comments and messages containing inappropriate expressions may cause troubles and misunderstandings among users. It is required to prevent this. In particular, in an electronic payment platform, feedback regarding transactions is important. If inappropriate content is included here, it will affect the reliability of the service, so it is necessary to solve this problem.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0283] In this invention, the server includes means for receiving text data input via a user interface by an information processing device, an arithmetic unit that uses a learning algorithm for analyzing the text data, and means for determining whether the text data contains inappropriate expressions using the learning algorithm. As a result, it is possible to prevent the transmission of text data containing inappropriate expressions and encourage the user to correct it to an appropriate expression.

[0284] The "user interface" is a means used for a user to input data to an information processing device or receive an output from the device.

[0285] The "information processing device" is an electronic device used for performing processes such as receiving, calculating, and analyzing data.

[0286] The "learning algorithm" is a series of calculation rules used for recognizing patterns based on past data and making a certain judgment on future data.

[0287] A "processing unit" is a general term for devices and software used to perform calculations related to the analysis and determination of text data.

[0288] "Inappropriate language" refers to the use of language that is insulting or defamatory and that may cause problems in communication or business.

[0289] A "warning message" is information sent to users to alert them when inappropriate language is detected.

[0290] A "means for generating commands" is a mechanism that generates an instruction from an information processing device to perform a certain action when specific conditions are met.

[0291] "Transaction-related information" refers to the collective information and data generated through exchanges on electronic trading platforms.

[0292] The system that realizes this invention mainly consists of a server, an information processing device, and a user interface. The server is built using the Flask framework with Python and is responsible for processing text data received from the client terminal. The user interface uses JavaScript to support data input and display.

[0293] The received text data is analyzed on the server side using a learning algorithm based on the Hugging Face Transformers package. This analysis determines in real time whether the text data contains inappropriate expressions. If inappropriate expressions are detected, the server sends a warning message to the terminal, prompting the user to correct the text data.

[0294] For example, if a user attempts to enter a comment about a transaction on an electronic payment platform, and the comment contains inappropriate language, the system will immediately detect this and issue a warning. This allows the user to revise the comment to appropriate language and re-enter it. A specific example of a prompt message would be: "A user is trying to write a review about their dissatisfaction with an online transaction. However, the language used is inappropriate. Please improve the phrasing so that we can provide more constructive feedback."

[0295] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0296] Step 1:

[0297] On the terminal, the user enters text data. This input is done through the user interface and is dynamically captured by JavaScript functionality. Specifically, the user enters a comment on the electronic payment platform, and that data is retrieved on the frontend.

[0298] Step 2:

[0299] The entered text data is sent from the terminal to the server. The server, which is an information processing device, analyzes the data received as an HTTP request. Data reception is performed securely and efficiently using a Flask server.

[0300] Step 3:

[0301] The server performs natural language processing on the received text data using the Hugging Face Transformers library. This process determines whether the text contains inappropriate expressions using a learning algorithm. In this step, the text data is input into the model, and an inappropriateness score is obtained as the model's output.

[0302] Step 4:

[0303] If the server determines that it is inappropriate based on the analysis result, it generates a warning message. This message conveys that correction is necessary, and the prompt sentence is automatically selected by the generative AI model.

[0304] Step 5:

[0305] The warning message is sent to the terminal and displayed on the user interface. The user receives this message, checks the input text data, and makes corrections if necessary. This prevents the transmission of inappropriate content in advance. The user can change the comment to something constructive while referring to the corresponding feedback.

[0306] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0307] An object of the present invention is to analyze the user's text input, detect slander and inappropriate content in advance, and further combine an emotion engine to also analyze the user's emotional state and provide appropriate feedback. Embodiments of this system will be described below.

[0308] First, the user inputs a text message using the keyboard application on the terminal. The terminal records the user's input in real time and sends the text data to the server. This data transmission is performed via a communication device.

[0309] The server receives the input text data and analyzes it using a learning model based on natural language processing technology. The analysis initiates a process to determine whether the text contains inappropriate expressions. At the same time, the emotion engine recognizes the user's emotional state. For example, if a phrase like "I hate you" is entered, it will not only be detected as slander, but anger or dissatisfaction will also be recognized as emotions.

[0310] Based on this analysis, the server generates a warning message. The content and presentation of the warning message are adjusted according to the results of the emotion engine. For example, if it is determined that the user is emotionally agitated, a calmer message will be presented to soothe the user. Also, if the user's emotions exceed a certain threshold, the server will inform the user of this and display advice and suggestions for mental self-care.

[0311] When the terminal receives a message from the server, it displays a warning on the user interface. This warning prompts the user to correct inappropriate content and, if necessary, provides emotional care information. The user can then adjust the text content or take other actions based on this information.

[0312] Thus, this system not only prevents inappropriate expressions during text input but also enables appropriate responses that take into account the user's emotional state. This function is expected to improve the health of online communication and contribute to the mental well-being of users.

[0313] The following describes the processing flow.

[0314] Step 1:

[0315] The user uses the device's keyboard application to enter a message. For example, they might enter a message like, "You're the worst."

[0316] Step 2:

[0317] The terminal collects the entered text data and prepares to send it to the server via the communication network.

[0318] Step 3:

[0319] The server receives text data sent from the terminal and places it in a parsing queue. The data is then processed sequentially according to this queue.

[0320] Step 4:

[0321] The server analyzes text data using a learning model that utilizes natural language processing technology. During this process, it determines whether the text contains inappropriate content.

[0322] Step 5:

[0323] The server simultaneously uses an emotion engine to analyze the user's emotions based on text data. For example, if anger is detected from the text, the emotion level is also evaluated.

[0324] Step 6:

[0325] Based on the analysis results, the server generates a warning message. If the content is inappropriate, it issues a warning and adjusts the message content according to the user's emotional state.

[0326] Step 7:

[0327] The server sends warning messages and suggestions to the terminal, including advice for mental self-care as needed.

[0328] Step 8:

[0329] The terminal receives a warning message from the server and displays it to the user through the user interface. The user reviews the message and reconsiders its content and actions.

[0330] This process allows the system to prevent inappropriate expressions from users and to provide responses that take into account the user's emotional state.

[0331] (Example 2)

[0332] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0333] In modern society, with the increase in online communication, the use of inappropriate language and defamation are becoming increasingly frequent. Such behavior can degrade the quality of communication and negatively impact mental health. Furthermore, there is a lack of appropriate support tailored to users' emotional states, and there is a need to prevent trouble and misunderstandings before they occur. Therefore, a system is needed that can detect inappropriate content in advance and provide feedback that takes into account the user's emotional state.

[0334] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0335] In this invention, the server includes means for receiving encoded data input via a user interface using a communication component; an information processing device that uses an artificial intelligence model for analyzing the encoded data; means for determining whether the encoded data contains inappropriate information using the artificial intelligence model; means for evaluating the user's emotional state using an emotion recognition engine; means for displaying a warning on the user interface and providing feedback according to the emotional state based on the determination result and the emotion evaluation; and means for generating an instruction to restrict the transmission of the encoded data when inappropriate information is detected. This enables the prior detection of inappropriate content and flexible responses according to the user's emotional state.

[0336] A "user interface" is an interface that allows a user to input information into a device or system and to operate it.

[0337] "Encoded data" refers to data in a format where user input is encoded and processed.

[0338] "Communication components" refer to hardware or software, including communication devices and network connections, used for sending and receiving data.

[0339] An "artificial intelligence model" is an artificial system that learns from large amounts of data, finds patterns and rules, and becomes capable of performing various tasks.

[0340] An "information processing device" is a device used for processing and analyzing data, and includes computers and servers.

[0341] "Inappropriate information" refers to information that contains insulting, defamatory, or libelous content that is undesirable or harmful in online communication.

[0342] An "emotion recognition engine" is a technology that identifies a user's emotional state from text and other inputs.

[0343] A "warning" is a message or alert that notifies the user and prompts them to take action when inappropriate information is detected.

[0344] "Feedback" refers to information or advice provided in response to user behavior to encourage correction or improvement.

[0345] A "transmission restriction instruction" is a command generated by the system to prevent or stop the transmission of detected inappropriate information.

[0346] This system is designed to improve the health of online communication. The process begins with the user typing a text message using a terminal. The terminal then transmits this encoded data to the server via a communication component.

[0347] The server uses an information processing device to analyze the received encoded data. This device is equipped with an artificial intelligence model based on natural language processing, which identifies whether the text contains inappropriate information, such as offensive language. In addition, the server uses an emotion recognition engine to evaluate the user's emotional state. This emotion analysis can detect whether the user is experiencing emotions such as anger or sadness.

[0348] Based on an analysis of inappropriate information and emotional states, the server generates a warning message. This message is displayed on the user interface, prompting the user to correct their behavior or engage in emotional self-care. For example, if a user enters "I hate you," the server will determine that the text is inappropriate, and its emotion recognition engine will detect anger. In this case, the server will generate a milder warning message such as "Avoid such language and let's discuss this calmly."

[0349] As an example of a prompt, by inputting the instruction "If a user uses inappropriate language, please provide an example of how to correct it" to the generative AI model, improved examples of language can be obtained.

[0350] User feedback is individually optimized. We hope this will improve the quality of online communication and protect users' mental well-being.

[0351] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0352] Step 1:

[0353] The user uses a terminal and enters a text message using a keyboard application. During this input process, the text is recorded on the terminal via the user interface. This step encompasses the entire process from the input text data being encoded to its transmission to the server via a communication device. The output is the encoded data sent to the server.

[0354] Step 2:

[0355] The server receives encoded data from the terminal via communication components and analyzes that data using an information processing device. Specifically, it uses an artificial intelligence model based on a generative AI model to determine whether the data contains inappropriate information, and simultaneously uses an emotion recognition engine to evaluate the user's emotional state. The input is encoded data, and the output is the result of the inappropriate information determination and the emotion evaluation result.

[0356] Step 3:

[0357] The server generates a warning message based on the analysis results. In this step, if inappropriate information is detected, a warning or feedback corresponding to that information is generated. For example, if it is determined that the user's emotions are heightened, a message encouraging calmness is prepared. The input is the analysis results obtained in step 2, and the output is the generated warning message.

[0358] Step 4:

[0359] The terminal displays warning messages received from the server in the user interface. These messages prompt the user to take appropriate action and provide advice on correcting inappropriate language and emotional care. The input is the warning message from the server, and the output is visual feedback to the user.

[0360] Step 5:

[0361] The user may modify the text message based on the displayed warning message. In this step, the user may re-enter or adjust the wording and send it back to the server as needed. The re-sent data is the output here and may be subjected to further analysis processes.

[0362] (Application Example 2)

[0363] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0364] With the widespread use of online communication, there has been an increase in defamatory and inappropriate text, which can threaten mental health. Furthermore, one-sided warnings that disregard users' feelings do not lead to a fundamental solution to the problem.

[0365] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0366] In this invention, the server includes means for receiving text information input via a user interface using a communication device, a processing unit that uses a learning model for analyzing the text information, and means for analyzing the user's emotional state using an emotion engine. This makes it possible not only to determine whether the text contains inappropriate expressions, but also to provide feedback and self-care advice that takes the user's emotional state into consideration.

[0367] "User interface" refers to the screen or means of operation that allows a user to input and output data to and from an information device.

[0368] A "communication device" is a device that uses digital or analog signals to send and receive information over a network.

[0369] "Text information" refers to data or message content composed of strings of characters, and specifically means the text information entered by the user.

[0370] A "learning model" is a statistical algorithm based on machine learning techniques using historical data, and is an artificial intelligence model trained to perform a specific task.

[0371] A "processing device" is a computer or a device with the functions of executing programs and analyzing and processing data.

[0372] An "emotion engine" is an algorithm or module used to analyze and classify emotional states from text sent by users.

[0373] "Defamation" refers to unfairly speaking ill of or belittling others, and is an expression that damages their reputation or credibility.

[0374] "Self-care advice" refers to information that provides guidelines and suggestions that users can implement to manage themselves and maintain or improve their mental health.

[0375] This invention provides a system aimed at maintaining the health of online communication and promoting the mental well-being of users. This system analyzes text information entered by users in real time to determine if it contains defamation or inappropriate content. Furthermore, it uses an emotion engine to analyze the user's emotional state and generate appropriate feedback.

[0376] The server uses a communication device to receive text information entered through the user interface. The received information is processed in real time by a learning model. This learning model uses natural language processing technology and incorporates a generative model to detect inappropriate expressions. The emotion engine analyzes the user's emotions and detects states such as anger and dissatisfaction.

[0377] Based on the analysis results, the server generates feedback and displays a warning in the user interface. This warning prompts the user to revise the message and, at the same time, can provide self-care advice depending on the user's emotional state. For example, if a user enters an aggressive message and the emotion engine detects anger, a message will be displayed encouraging them to calm down with gentle language.

[0378] This system incorporates natural language processing technology and sentiment analysis capabilities, and can be implemented using software such as TensorFlow or Keras.

[0379] For example, if a user types "You are useless," the system will recognize this as a negative expression and offer suggestions such as "This message is inappropriate. Let's think of another way to say it." Furthermore, if the input is deemed emotionally intense, self-care advice, such as encouraging deep breathing, will also be provided.

[0380] An example of a prompt might be: "Design a system that analyzes user-entered text in real time for defamation and emotional state, and provides appropriate feedback."

[0381] This system allows users to participate in online interactions with peace of mind, and by preventing inappropriate remarks, it provides a healthy environment for communication.

[0382] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0383] Step 1:

[0384] The user inputs text information through the user interface. The terminal receives this input and transmits it to the server in real time via a communication device. The input data is the user's raw text information.

[0385] Step 2:

[0386] The server first uses a learning model to analyze the received text information. This model is a generative model based on natural language processing technology and is trained to detect inappropriate expressions. The input data is text information, and the server outputs a result of determining whether it contains inappropriate content through calculations.

[0387] Step 3:

[0388] The server then uses an emotion engine to analyze the user's emotional state. This engine detects emotional words and phrases in the text and infers the user's emotional state. The input data is text information, and the calculations output a result indicating the user's emotional state.

[0389] Step 4:

[0390] The server generates feedback based on the analysis results. If the judgment result indicates something inappropriate, a warning is displayed on the user interface, prompting the user to correct the content. Self-care advice is also provided depending on the emotional state. The input data for this step is the judgment result and the emotion analysis result, and a feedback message generated through calculations is output.

[0391] Step 5:

[0392] The terminal receives feedback messages from the server and displays them on the user interface. Users can view these messages and, if necessary, modify them or take action based on the advice. The input data is the feedback message, which is output in its original format.

[0393] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0394] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0395] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0396] [Third Embodiment]

[0397] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0398] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0399] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0400] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0401] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0402] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0403] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0404] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0405] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0406] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0407] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0408] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0409] The system of the present invention has the function of monitoring text data entered via a user interface and preventing inappropriate content from being entered. An embodiment thereof is described below.

[0410] First, the user uses the keyboard application on their device to input various messages and posts. The device provides an interface for the user's input and sends it to the server as needed after each input is completed.

[0411] The received text data is analyzed by a processing unit on the server. This analysis uses a learning model that applies natural language processing technology. The learning model is pre-trained to identify various defamatory and insulting expressions.

[0412] The server analyzes text data in real time and determines whether it contains inappropriate language. For example, if the word "idiot" is entered, the learning model recognizes that the word is insulting.

[0413] If inappropriate content is detected, the server immediately sends a warning message to the terminal. This warning message prompts the user to correct the input. In this process, the server also sends a command to the user interface to stop sending the relevant text.

[0414] The terminal receives a message from the server and displays an alert to the user. The user is required to correct the input string to the appropriate content or reconsider sending the message altogether, in response to this warning.

[0415] In this way, this system can prevent users from using defamatory language. For example, even if a user unintentionally uses problematic language, a warning will be displayed immediately, giving them an opportunity to make appropriate corrections. This system can be easily implemented on specific communication terminals and contributes to suppressing inappropriate language on the network and establishing healthy communication.

[0416] The following describes the processing flow.

[0417] Step 1:

[0418] The user uses a keyboard application to type a text message on the device. For example, the user types "You're the worst."

[0419] Step 2:

[0420] The terminal prepares to send the entered text data to the server via the computer network.

[0421] Step 3:

[0422] The server stores the text data received from the terminal in a queue for analysis.

[0423] Step 4:

[0424] The server analyzes the stored text data using a learning model based on natural language processing technology. This analysis determines whether the text data contains inappropriate content.

[0425] Step 5:

[0426] Based on the analysis results, the server generates a warning message if it determines that the text data contains inappropriate content. This message may include phrases such as, "This expression is inappropriate. Please correct it."

[0427] Step 6:

[0428] The server sends the generated warning message and a command to cancel transmission to the terminal.

[0429] Step 7:

[0430] The terminal receives a warning message from the server and displays it on the user interface. At the same time, it temporarily blocks user input and cancels transmission.

[0431] Step 8:

[0432] The user reviews the displayed warning message and either corrects the text and re-enters it, or cancels the input.

[0433] In this way, the entire system works together to prevent the use of inappropriate language.

[0434] (Example 1)

[0435] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0436] In today's information and communication society, inappropriate language and insulting comments on the internet and social media are on the rise. Such remarks not only hinder communication but can also cause social disruption and personal psychological damage. To prevent this problem, there is a need for a system that monitors text data transmitted by users over the network in real time and removes inappropriate content in advance. Furthermore, it is important to promptly point out problematic expressions that users may be using unknowingly and encourage them to correct them.

[0437] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0438] In this invention, the server includes means for receiving character data input via a user terminal using an information and communication device, a processing device that uses a machine learning model for analyzing the character data, and means for determining whether the character data contains inappropriate content. This effectively suppresses inappropriate expressions on the network and enables healthy communication.

[0439] A "user terminal" is an electronic device used by an individual to input data and communicate over a network.

[0440] An "information and communication device" is a device used to send and receive data and manage communication via a network.

[0441] "Text data" refers to information in text format that a user inputs for communication purposes.

[0442] A "machine learning model" is an algorithm that learns from large amounts of data and analyzes new data to extract specific patterns.

[0443] A "processing device" refers to a computer or related equipment used for computational processing, such as data analysis and model execution.

[0444] "Inappropriate content" refers to information that is insulting or defamatory and contains socially undesirable expressions.

[0445] "Means of determination" refers to methods or devices for analyzing input data, identifying its content, and making a judgment.

[0446] "Means of displaying warnings" refers to methods of displaying information, either visually or audibly, to draw the user's attention and prompt them to correct their input.

[0447] "Means for generating instructions to stop transmission" refers to a function that generates commands to stop the transmission of data deemed inappropriate.

[0448] This invention provides a system for preventing inappropriate expressions on the internet. The user inputs character data for communication using a keyboard application provided on their terminal. The terminal has the function of transmitting this character data to a server via a communication network.

[0449] The server utilizes a machine learning-based language processing model to analyze the received text data. Specifically, it uses a generative AI model that applies natural language processing technology to determine whether the text data contains inappropriate expressions. This language processing model is pre-trained to identify insulting and defamatory content. The processing unit within the server analyzes the data in real time, and if it determines that the content is inappropriate, it immediately sends a warning message to the terminal.

[0450] When a device receives a warning message, it displays an alert to the user. This gives the user an opportunity to recognize and correct any inappropriate content they may have entered by mistake. This system helps users to achieve healthy communication.

[0451] For example, if a user posts a comment on an online forum and enters negative language such as "This movie is terrible," the server will identify this language and send a stop command to the terminal. An example of a prompt message would be, "Please enter your comment to post on the online forum. Please be careful not to include inappropriate language. For example, please use expressions such as 'This is interesting, but you should think more before you comment!'" This would encourage the user to use appropriate language.

[0452] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0453] Step 1:

[0454] The server receives character data entered by the user using a keyboard application on the terminal. The input is text that the user wishes to send, and the server receives this data for analysis. The terminal performs this transmission process and transfers the data to the server.

[0455] Step 2:

[0456] The server analyzes the received text data using a machine learning model. Specifically, it uses natural language processing techniques to classify the content of the data. This process analyzes the text data received as input and detects the possibility of inappropriate expressions. As a result, a judgment is output indicating whether the data is safe or inappropriate.

[0457] Step 3:

[0458] Based on the analysis results described above, the server determines whether the text data contains inappropriate content. Using the results of this analysis, the server determines whether the data is inappropriate, and if it is determined to be inappropriate, it sets a flag to indicate this.

[0459] Step 4:

[0460] If inappropriate content is detected, the server generates and sends a warning message to the terminal. The input includes a judgment result, and since a warning is deemed necessary, the server creates a warning message for the user. The warning message may include, for example, "The input contains inappropriate language. Please correct the content."

[0461] Step 5:

[0462] The terminal displays warning messages received from the server through a user interface, allowing the user to recognize the warnings. The input is warning messages from the server, and the output is provided to the user as visual or audible alerts.

[0463] Step 6:

[0464] The user sees a warning message on their device and is given an opportunity to correct or reconsider their input. This process allows the user to re-edit the text data on their device and then decide whether to resend it. Ultimately, the goal is for the user to provide text data using appropriate language.

[0465] (Application Example 1)

[0466] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0467] In electronic transactions, the transmission of comments and messages containing inappropriate language can lead to trouble and misunderstandings between users. Preventing this is crucial. In particular, transaction feedback is important on electronic payment platforms, and inappropriate content in this feedback can affect the reliability of the service; therefore, this issue needs to be resolved.

[0468] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0469] In this invention, the server includes means for receiving text data input via a user interface using an information processing device, a computing device that uses a learning algorithm for analyzing the text data, and means for determining whether the text data contains inappropriate expressions using the learning algorithm. This makes it possible to prevent the transmission of text data containing inappropriate expressions while encouraging the user to correct them to appropriate expressions.

[0470] A "user interface" is a means used by a user to input data into an information processing device or to receive output from the device.

[0471] An "information processing device" is an electronic device used to perform processing such as receiving, calculating, and analyzing data.

[0472] A "learning algorithm" is a set of computational rules used to recognize patterns based on past data and to make certain judgments about future data.

[0473] A "processing unit" is a general term for devices and software used to perform calculations related to the analysis and determination of text data.

[0474] "Inappropriate language" refers to the use of language that is insulting or defamatory and that may cause problems in communication or business.

[0475] A "warning message" is information sent to users to alert them when inappropriate language is detected.

[0476] A "means for generating commands" is a mechanism that generates an instruction from an information processing device to perform a certain action when specific conditions are met.

[0477] "Transaction-related information" refers to the collective information and data generated through exchanges on electronic trading platforms.

[0478] The system that realizes this invention mainly consists of a server, an information processing device, and a user interface. The server is built using the Flask framework with Python and is responsible for processing text data received from the client terminal. The user interface uses JavaScript to support data input and display.

[0479] The received text data is analyzed on the server side using a learning algorithm based on the Hugging Face Transformers package. This analysis determines in real time whether the text data contains inappropriate expressions. If inappropriate expressions are detected, the server sends a warning message to the terminal, prompting the user to correct the text data.

[0480] For example, if a user attempts to enter a comment about a transaction on an electronic payment platform, and the comment contains inappropriate language, the system will immediately detect this and issue a warning. This allows the user to revise the comment to appropriate language and re-enter it. A specific example of a prompt message would be: "A user is trying to write a review about their dissatisfaction with an online transaction. However, the language used is inappropriate. Please improve the phrasing so that we can provide more constructive feedback."

[0481] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0482] Step 1:

[0483] On the terminal, the user enters text data. This input is done through the user interface and is dynamically captured by JavaScript functionality. Specifically, the user enters a comment on the electronic payment platform, and that data is retrieved on the frontend.

[0484] Step 2:

[0485] The entered text data is sent from the terminal to the server. The server, which is an information processing device, analyzes the data received as an HTTP request. Data reception is performed securely and efficiently using a Flask server.

[0486] Step 3:

[0487] The server performs natural language processing on the received text data using the Hugging Face Transformers library. This process determines whether the text contains inappropriate expressions using a learning algorithm. In this step, the text data is input into the model, and an inappropriateness score is obtained as the model's output.

[0488] Step 4:

[0489] If the server determines, based on the analysis results, that something is inappropriate, it will generate a warning message. This message indicates that correction is needed, and the prompt is automatically selected by the AI ​​generation model.

[0490] Step 5:

[0491] A warning message is sent to the device and displayed on the user interface. The user receives this message, reviews the entered text data, and makes corrections as needed. This prevents the submission of inappropriate content. Users can then modify their comments constructively by referring to the corresponding feedback.

[0492] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0493] The present invention aims to analyze the user's emotional state and provide appropriate feedback by combining a system that analyzes user text input and detects defamatory or inappropriate content in advance with an emotion engine. An embodiment of this system is described below.

[0494] First, the user enters a text message using a keyboard application on their device. The device records the user's input in real time and sends the text data to the server. This data transmission takes place via a communication device.

[0495] The server receives the input text data and analyzes it using a learning model based on natural language processing technology. The analysis initiates a process to determine whether the text contains inappropriate expressions. At the same time, the emotion engine recognizes the user's emotional state. For example, if a phrase like "I hate you" is entered, it will not only be detected as slander, but anger or dissatisfaction will also be recognized as emotions.

[0496] Based on this analysis, the server generates a warning message. The content and presentation of the warning message are adjusted according to the results of the emotion engine. For example, if it is determined that the user is emotionally agitated, a calmer message will be presented to soothe the user. Also, if the user's emotions exceed a certain threshold, the server will inform the user of this and display advice and suggestions for mental self-care.

[0497] When the terminal receives a message from the server, it displays a warning on the user interface. This warning prompts the user to correct inappropriate content and, if necessary, provides emotional care information. The user can then adjust the text content or take other actions based on this information.

[0498] Thus, this system not only prevents inappropriate expressions during text input but also enables appropriate responses that take into account the user's emotional state. This function is expected to improve the health of online communication and contribute to the mental well-being of users.

[0499] The following describes the processing flow.

[0500] Step 1:

[0501] The user uses the device's keyboard application to enter a message. For example, they might enter a message like, "You're the worst."

[0502] Step 2:

[0503] The terminal collects the entered text data and prepares to send it to the server via the communication network.

[0504] Step 3:

[0505] The server receives text data sent from the terminal and places it in a parsing queue. The data is then processed sequentially according to this queue.

[0506] Step 4:

[0507] The server analyzes text data using a learning model that utilizes natural language processing technology. During this process, it determines whether the text contains inappropriate content.

[0508] Step 5:

[0509] The server simultaneously uses an emotion engine to analyze the user's emotions based on text data. For example, if anger is detected from the text, the emotion level is also evaluated.

[0510] Step 6:

[0511] Based on the analysis results, the server generates a warning message. If the content is inappropriate, it issues a warning and adjusts the message content according to the user's emotional state.

[0512] Step 7:

[0513] The server sends warning messages and suggestions to the terminal, including advice for mental self-care as needed.

[0514] Step 8:

[0515] The terminal receives a warning message from the server and displays it to the user through the user interface. The user reviews the message and reconsiders its content and actions.

[0516] This process allows the system to prevent inappropriate expressions from users and to provide responses that take into account the user's emotional state.

[0517] (Example 2)

[0518] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0519] In modern society, with the increase in online communication, the use of inappropriate language and defamation are becoming increasingly frequent. Such behavior can degrade the quality of communication and negatively impact mental health. Furthermore, there is a lack of appropriate support tailored to users' emotional states, and there is a need to prevent trouble and misunderstandings before they occur. Therefore, a system is needed that can detect inappropriate content in advance and provide feedback that takes into account the user's emotional state.

[0520] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0521] In this invention, the server includes means for receiving encoded data input via a user interface using a communication component; an information processing device that uses an artificial intelligence model for analyzing the encoded data; means for determining whether the encoded data contains inappropriate information using the artificial intelligence model; means for evaluating the user's emotional state using an emotion recognition engine; means for displaying a warning on the user interface and providing feedback according to the emotional state based on the determination result and the emotion evaluation; and means for generating an instruction to restrict the transmission of the encoded data when inappropriate information is detected. This enables the prior detection of inappropriate content and flexible responses according to the user's emotional state.

[0522] A "user interface" is an interface that allows a user to input information into a device or system and to operate it.

[0523] "Encoded data" refers to data in a format where user input is encoded and processed.

[0524] "Communication components" refer to hardware or software, including communication devices and network connections, used for sending and receiving data.

[0525] An "artificial intelligence model" is an artificial system that learns from large amounts of data, finds patterns and rules, and becomes capable of performing various tasks.

[0526] An "information processing device" is a device used for processing and analyzing data, and includes computers and servers.

[0527] "Inappropriate information" refers to information that contains insulting, defamatory, or libelous content that is undesirable or harmful in online communication.

[0528] An "emotion recognition engine" is a technology that identifies a user's emotional state from text and other inputs.

[0529] A "warning" is a message or alert that notifies the user and prompts them to take action when inappropriate information is detected.

[0530] "Feedback" refers to information or advice provided in response to user behavior to encourage correction or improvement.

[0531] A "transmission restriction instruction" is a command generated by the system to prevent or stop the transmission of detected inappropriate information.

[0532] This system is designed to improve the health of online communication. The process begins with the user typing a text message using a terminal. The terminal then transmits this encoded data to the server via a communication component.

[0533] The server uses an information processing device to analyze the received encoded data. This device is equipped with an artificial intelligence model based on natural language processing, which identifies whether the text contains inappropriate information, such as offensive language. In addition, the server uses an emotion recognition engine to evaluate the user's emotional state. This emotion analysis can detect whether the user is experiencing emotions such as anger or sadness.

[0534] Based on an analysis of inappropriate information and emotional states, the server generates a warning message. This message is displayed on the user interface, prompting the user to correct their behavior or engage in emotional self-care. For example, if a user enters "I hate you," the server will determine that the text is inappropriate, and its emotion recognition engine will detect anger. In this case, the server will generate a milder warning message such as "Avoid such language and let's discuss this calmly."

[0535] As an example of a prompt, by inputting the instruction "If a user uses inappropriate language, please provide an example of how to correct it" to the generative AI model, improved examples of language can be obtained.

[0536] User feedback is individually optimized. We hope this will improve the quality of online communication and protect users' mental well-being.

[0537] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0538] Step 1:

[0539] The user uses a terminal and enters a text message using a keyboard application. During this input process, the text is recorded on the terminal via the user interface. This step encompasses the entire process from the input text data being encoded to its transmission to the server via a communication device. The output is the encoded data sent to the server.

[0540] Step 2:

[0541] The server receives encoded data from the terminal via communication components and analyzes that data using an information processing device. Specifically, it uses an artificial intelligence model based on a generative AI model to determine whether the data contains inappropriate information, and simultaneously uses an emotion recognition engine to evaluate the user's emotional state. The input is encoded data, and the output is the result of the inappropriate information determination and the emotion evaluation result.

[0542] Step 3:

[0543] The server generates a warning message based on the analysis results. In this step, if inappropriate information is detected, a warning or feedback corresponding to that information is generated. For example, if it is determined that the user's emotions are heightened, a message encouraging calmness is prepared. The input is the analysis results obtained in step 2, and the output is the generated warning message.

[0544] Step 4:

[0545] The terminal displays warning messages received from the server in the user interface. These messages prompt the user to take appropriate action and provide advice on correcting inappropriate language and emotional care. The input is the warning message from the server, and the output is visual feedback to the user.

[0546] Step 5:

[0547] The user may modify the text message based on the displayed warning message. In this step, the user may re-enter or adjust the wording and send it back to the server as needed. The re-sent data is the output here and may be subjected to further analysis processes.

[0548] (Application Example 2)

[0549] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0550] With the widespread use of online communication, there has been an increase in defamatory and inappropriate text, which can threaten mental health. Furthermore, one-sided warnings that disregard users' feelings do not lead to a fundamental solution to the problem.

[0551] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0552] In this invention, the server includes means for receiving text information input via a user interface using a communication device, a processing unit that uses a learning model for analyzing the text information, and means for analyzing the user's emotional state using an emotion engine. This makes it possible not only to determine whether the text contains inappropriate expressions, but also to provide feedback and self-care advice that takes the user's emotional state into consideration.

[0553] "User interface" refers to the screen or means of operation that allows a user to input and output data to and from an information device.

[0554] A "communication device" is a device that uses digital or analog signals to send and receive information over a network.

[0555] "Text information" refers to data or message content composed of strings of characters, and specifically means the text information entered by the user.

[0556] A "learning model" is a statistical algorithm based on machine learning techniques using historical data, and is an artificial intelligence model trained to perform a specific task.

[0557] A "processing device" is a computer or a device with the functions of executing programs and analyzing and processing data.

[0558] An "emotion engine" is an algorithm or module used to analyze and classify emotional states from text sent by users.

[0559] "Defamation" refers to unfairly speaking ill of or belittling others, and is an expression that damages their reputation or credibility.

[0560] "Self-care advice" refers to information that provides guidelines and suggestions that users can implement to manage themselves and maintain or improve their mental health.

[0561] This invention provides a system aimed at maintaining the health of online communication and promoting the mental well-being of users. This system analyzes text information entered by users in real time to determine if it contains defamation or inappropriate content. Furthermore, it uses an emotion engine to analyze the user's emotional state and generate appropriate feedback.

[0562] The server uses a communication device to receive text information entered through the user interface. The received information is processed in real time by a learning model. This learning model uses natural language processing technology and incorporates a generative model to detect inappropriate expressions. The emotion engine analyzes the user's emotions and detects states such as anger and dissatisfaction.

[0563] Based on the analysis results, the server generates feedback and displays a warning in the user interface. This warning prompts the user to revise the message and, at the same time, can provide self-care advice depending on the user's emotional state. For example, if a user enters an aggressive message and the emotion engine detects anger, a message will be displayed encouraging them to calm down with gentle language.

[0564] This system incorporates natural language processing technology and sentiment analysis capabilities, and can be implemented using software such as TensorFlow or Keras.

[0565] For example, if a user types "You are useless," the system will recognize this as a negative expression and offer suggestions such as "This message is inappropriate. Let's think of another way to say it." Furthermore, if the input is deemed emotionally intense, self-care advice, such as encouraging deep breathing, will also be provided.

[0566] An example of a prompt might be: "Design a system that analyzes user-entered text in real time for defamation and emotional state, and provides appropriate feedback."

[0567] This system allows users to participate in online interactions with peace of mind, and by preventing inappropriate remarks, it provides a healthy environment for communication.

[0568] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0569] Step 1:

[0570] The user inputs text information through the user interface. The terminal receives this input and transmits it to the server in real time via a communication device. The input data is the user's raw text information.

[0571] Step 2:

[0572] The server first uses a learning model to analyze the received text information. This model is a generative model based on natural language processing technology and is trained to detect inappropriate expressions. The input data is text information, and the server outputs a result of determining whether it contains inappropriate content through calculations.

[0573] Step 3:

[0574] The server then uses an emotion engine to analyze the user's emotional state. This engine detects emotional words and phrases in the text and infers the user's emotional state. The input data is text information, and the calculations output a result indicating the user's emotional state.

[0575] Step 4:

[0576] The server generates feedback based on the analysis results. If the judgment result indicates something inappropriate, a warning is displayed on the user interface, prompting the user to correct the content. Self-care advice is also provided depending on the emotional state. The input data for this step is the judgment result and the emotion analysis result, and a feedback message generated through calculations is output.

[0577] Step 5:

[0578] The terminal receives feedback messages from the server and displays them on the user interface. Users can view these messages and, if necessary, modify them or take action based on the advice. The input data is the feedback message, which is output in its original format.

[0579] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0580] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0581] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0582] [Fourth Embodiment]

[0583] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0584] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0585] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0586] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0587] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0588] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0589] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0590] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0591] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0592] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0593] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0594] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0595] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0596] The system of the present invention has the function of monitoring text data entered via a user interface and preventing inappropriate content from being entered. An embodiment thereof is described below.

[0597] First, the user uses the keyboard application on their device to input various messages and posts. The device provides an interface for the user's input and sends it to the server as needed after each input is completed.

[0598] The received text data is analyzed by a processing unit on the server. This analysis uses a learning model that applies natural language processing technology. The learning model is pre-trained to identify various defamatory and insulting expressions.

[0599] The server analyzes text data in real time and determines whether it contains inappropriate language. For example, if the word "idiot" is entered, the learning model recognizes that the word is insulting.

[0600] If inappropriate content is detected, the server immediately sends a warning message to the terminal. This warning message prompts the user to correct the input. In this process, the server also sends a command to the user interface to stop sending the relevant text.

[0601] The terminal receives a message from the server and displays an alert to the user. The user is required to correct the input string to the appropriate content or reconsider sending the message altogether, in response to this warning.

[0602] In this way, this system can prevent users from using defamatory language. For example, even if a user unintentionally uses problematic language, a warning will be displayed immediately, giving them an opportunity to make appropriate corrections. This system can be easily implemented on specific communication terminals and contributes to suppressing inappropriate language on the network and establishing healthy communication.

[0603] The following describes the processing flow.

[0604] Step 1:

[0605] The user uses a keyboard application to type a text message on the device. For example, the user types "You're the worst."

[0606] Step 2:

[0607] The terminal prepares to send the entered text data to the server via the computer network.

[0608] Step 3:

[0609] The server stores the text data received from the terminal in a queue for analysis.

[0610] Step 4:

[0611] The server analyzes the stored text data using a learning model based on natural language processing technology. This analysis determines whether the text data contains inappropriate content.

[0612] Step 5:

[0613] Based on the analysis results, the server generates a warning message if it determines that the text data contains inappropriate content. This message may include phrases such as, "This expression is inappropriate. Please correct it."

[0614] Step 6:

[0615] The server sends the generated warning message and a command to cancel transmission to the terminal.

[0616] Step 7:

[0617] The terminal receives a warning message from the server and displays it on the user interface. At the same time, it temporarily blocks user input and cancels transmission.

[0618] Step 8:

[0619] The user reviews the displayed warning message and either corrects the text and re-enters it, or cancels the input.

[0620] In this way, the entire system works together to prevent the use of inappropriate language.

[0621] (Example 1)

[0622] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0623] In today's information and communication society, inappropriate language and insulting comments on the internet and social media are on the rise. Such remarks not only hinder communication but can also cause social disruption and personal psychological damage. To prevent this problem, there is a need for a system that monitors text data transmitted by users over the network in real time and removes inappropriate content in advance. Furthermore, it is important to promptly point out problematic expressions that users may be using unknowingly and encourage them to correct them.

[0624] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0625] In this invention, the server includes means for receiving character data input via a user terminal using an information and communication device, a processing device that uses a machine learning model for analyzing the character data, and means for determining whether the character data contains inappropriate content. This effectively suppresses inappropriate expressions on the network and enables healthy communication.

[0626] A "user terminal" is an electronic device used by an individual to input data and communicate over a network.

[0627] An "information and communication device" is a device used to send and receive data and manage communication via a network.

[0628] "Text data" refers to information in text format that a user inputs for communication purposes.

[0629] A "machine learning model" is an algorithm that learns from large amounts of data and analyzes new data to extract specific patterns.

[0630] A "processing device" refers to a computer or related equipment used for computational processing, such as data analysis and model execution.

[0631] "Inappropriate content" refers to information that is insulting or defamatory and contains socially undesirable expressions.

[0632] "Means of determination" refers to methods or devices for analyzing input data, identifying its content, and making a judgment.

[0633] "Means of displaying warnings" refers to methods of displaying information, either visually or audibly, to draw the user's attention and prompt them to correct their input.

[0634] "Means for generating instructions to stop transmission" refers to a function that generates commands to stop the transmission of data deemed inappropriate.

[0635] This invention provides a system for preventing inappropriate expressions on the internet. The user inputs character data for communication using a keyboard application provided on their terminal. The terminal has the function of transmitting this character data to a server via a communication network.

[0636] The server utilizes a machine learning-based language processing model to analyze the received text data. Specifically, it uses a generative AI model that applies natural language processing technology to determine whether the text data contains inappropriate expressions. This language processing model is pre-trained to identify insulting and defamatory content. The processing unit within the server analyzes the data in real time, and if it determines that the content is inappropriate, it immediately sends a warning message to the terminal.

[0637] When a device receives a warning message, it displays an alert to the user. This gives the user an opportunity to recognize and correct any inappropriate content they may have entered by mistake. This system helps users to achieve healthy communication.

[0638] For example, if a user posts a comment on an online forum and enters negative language such as "This movie is terrible," the server will identify this language and send a stop command to the terminal. An example of a prompt message would be, "Please enter your comment to post on the online forum. Please be careful not to include inappropriate language. For example, please use expressions such as 'This is interesting, but you should think more before you comment!'" This would encourage the user to use appropriate language.

[0639] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0640] Step 1:

[0641] The server receives character data entered by the user using a keyboard application on the terminal. The input is text that the user wishes to send, and the server receives this data for analysis. The terminal performs this transmission process and transfers the data to the server.

[0642] Step 2:

[0643] The server analyzes the received text data using a machine learning model. Specifically, it uses natural language processing techniques to classify the content of the data. This process analyzes the text data received as input and detects the possibility of inappropriate expressions. As a result, a judgment is output indicating whether the data is safe or inappropriate.

[0644] Step 3:

[0645] Based on the analysis results described above, the server determines whether the text data contains inappropriate content. Using the results of this analysis, the server determines whether the data is inappropriate, and if it is determined to be inappropriate, it sets a flag to indicate this.

[0646] Step 4:

[0647] If inappropriate content is detected, the server generates and sends a warning message to the terminal. The input includes a judgment result, and since a warning is deemed necessary, the server creates a warning message for the user. The warning message may include, for example, "The input contains inappropriate language. Please correct the content."

[0648] Step 5:

[0649] The terminal displays warning messages received from the server through a user interface, allowing the user to recognize the warnings. The input is warning messages from the server, and the output is provided to the user as visual or audible alerts.

[0650] Step 6:

[0651] The user sees a warning message on their device and is given an opportunity to correct or reconsider their input. This process allows the user to re-edit the text data on their device and then decide whether to resend it. Ultimately, the goal is for the user to provide text data using appropriate language.

[0652] (Application Example 1)

[0653] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0654] In electronic transactions, the transmission of comments and messages containing inappropriate language can lead to trouble and misunderstandings between users. Preventing this is crucial. In particular, transaction feedback is important on electronic payment platforms, and inappropriate content in this feedback can affect the reliability of the service; therefore, this issue needs to be resolved.

[0655] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0656] In this invention, the server includes means for receiving text data input via a user interface using an information processing device, a computing device that uses a learning algorithm for analyzing the text data, and means for determining whether the text data contains inappropriate expressions using the learning algorithm. This makes it possible to prevent the transmission of text data containing inappropriate expressions while encouraging the user to correct them to appropriate expressions.

[0657] A "user interface" is a means used by a user to input data into an information processing device or to receive output from the device.

[0658] An "information processing device" is an electronic device used to perform processing such as receiving, calculating, and analyzing data.

[0659] A "learning algorithm" is a set of computational rules used to recognize patterns based on past data and to make certain judgments about future data.

[0660] A "processing unit" is a general term for devices and software used to perform calculations related to the analysis and determination of text data.

[0661] "Inappropriate language" refers to the use of language that is insulting or defamatory and that may cause problems in communication or business.

[0662] A "warning message" is information sent to users to alert them when inappropriate language is detected.

[0663] A "means for generating commands" is a mechanism that generates an instruction from an information processing device to perform a certain action when specific conditions are met.

[0664] "Transaction-related information" refers to the collective information and data generated through exchanges on electronic trading platforms.

[0665] The system that realizes this invention mainly consists of a server, an information processing device, and a user interface. The server is built using the Flask framework with Python and is responsible for processing text data received from the client terminal. The user interface uses JavaScript to support data input and display.

[0666] The received text data is analyzed on the server side using a learning algorithm based on the Hugging Face Transformers package. This analysis determines in real time whether the text data contains inappropriate expressions. If inappropriate expressions are detected, the server sends a warning message to the terminal, prompting the user to correct the text data.

[0667] For example, if a user attempts to enter a comment about a transaction on an electronic payment platform, and the comment contains inappropriate language, the system will immediately detect this and issue a warning. This allows the user to revise the comment to appropriate language and re-enter it. A specific example of a prompt message would be: "A user is trying to write a review about their dissatisfaction with an online transaction. However, the language used is inappropriate. Please improve the phrasing so that we can provide more constructive feedback."

[0668] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0669] Step 1:

[0670] On the terminal, the user enters text data. This input is done through the user interface and is dynamically captured by JavaScript functionality. Specifically, the user enters a comment on the electronic payment platform, and that data is retrieved on the frontend.

[0671] Step 2:

[0672] The entered text data is sent from the terminal to the server. The server, which is an information processing device, analyzes the data received as an HTTP request. Data reception is performed securely and efficiently using a Flask server.

[0673] Step 3:

[0674] The server performs natural language processing on the received text data using the Hugging Face Transformers library. This process determines whether the text contains inappropriate expressions using a learning algorithm. In this step, the text data is input into the model, and an inappropriateness score is obtained as the model's output.

[0675] Step 4:

[0676] If the server determines, based on the analysis results, that something is inappropriate, it will generate a warning message. This message indicates that correction is needed, and the prompt is automatically selected by the AI ​​generation model.

[0677] Step 5:

[0678] A warning message is sent to the device and displayed on the user interface. The user receives this message, reviews the entered text data, and makes corrections as needed. This prevents the submission of inappropriate content. Users can then modify their comments constructively by referring to the corresponding feedback.

[0679] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0680] The present invention aims to analyze the user's emotional state and provide appropriate feedback by combining a system that analyzes user text input and detects defamatory or inappropriate content in advance with an emotion engine. An embodiment of this system is described below.

[0681] First, the user enters a text message using a keyboard application on their device. The device records the user's input in real time and sends the text data to the server. This data transmission takes place via a communication device.

[0682] The server receives the input text data and analyzes it using a learning model based on natural language processing technology. The analysis initiates a process to determine whether the text contains inappropriate expressions. At the same time, the emotion engine recognizes the user's emotional state. For example, if a phrase like "I hate you" is entered, it will not only be detected as slander, but anger or dissatisfaction will also be recognized as emotions.

[0683] Based on this analysis, the server generates a warning message. The content and presentation of the warning message are adjusted according to the results of the emotion engine. For example, if it is determined that the user is emotionally agitated, a calmer message will be presented to soothe the user. Also, if the user's emotions exceed a certain threshold, the server will inform the user of this and display advice and suggestions for mental self-care.

[0684] When the terminal receives a message from the server, it displays a warning on the user interface. This warning prompts the user to correct inappropriate content and, if necessary, provides emotional care information. The user can then adjust the text content or take other actions based on this information.

[0685] Thus, this system not only prevents inappropriate expressions during text input but also enables appropriate responses that take into account the user's emotional state. This function is expected to improve the health of online communication and contribute to the mental well-being of users.

[0686] The following describes the processing flow.

[0687] Step 1:

[0688] The user uses the device's keyboard application to enter a message. For example, they might enter a message like, "You're the worst."

[0689] Step 2:

[0690] The terminal collects the entered text data and prepares to send it to the server via the communication network.

[0691] Step 3:

[0692] The server receives text data sent from the terminal and places it in a parsing queue. The data is then processed sequentially according to this queue.

[0693] Step 4:

[0694] The server analyzes text data using a learning model that utilizes natural language processing technology. During this process, it determines whether the text contains inappropriate content.

[0695] Step 5:

[0696] The server simultaneously uses an emotion engine to analyze the user's emotions based on text data. For example, if anger is detected from the text, the emotion level is also evaluated.

[0697] Step 6:

[0698] Based on the analysis results, the server generates a warning message. If the content is inappropriate, it issues a warning and adjusts the message content according to the user's emotional state.

[0699] Step 7:

[0700] The server sends warning messages and suggestions to the terminal, including advice for mental self-care as needed.

[0701] Step 8:

[0702] The terminal receives a warning message from the server and displays it to the user through the user interface. The user reviews the message and reconsiders its content and actions.

[0703] This process allows the system to prevent inappropriate expressions from users and to provide responses that take into account the user's emotional state.

[0704] (Example 2)

[0705] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] In modern society, with the increase in online communication, the use of inappropriate language and defamation are becoming increasingly frequent. Such behavior can degrade the quality of communication and negatively impact mental health. Furthermore, there is a lack of appropriate support tailored to users' emotional states, and there is a need to prevent trouble and misunderstandings before they occur. Therefore, a system is needed that can detect inappropriate content in advance and provide feedback that takes into account the user's emotional state.

[0707] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0708] In this invention, the server includes means for receiving encoded data input via a user interface using a communication component; an information processing device that uses an artificial intelligence model for analyzing the encoded data; means for determining whether the encoded data contains inappropriate information using the artificial intelligence model; means for evaluating the user's emotional state using an emotion recognition engine; means for displaying a warning on the user interface and providing feedback according to the emotional state based on the determination result and the emotion evaluation; and means for generating an instruction to restrict the transmission of the encoded data when inappropriate information is detected. This enables the prior detection of inappropriate content and flexible responses according to the user's emotional state.

[0709] A "user interface" is an interface that allows a user to input information into a device or system and to operate it.

[0710] "Encoded data" refers to data in a format where user input is encoded and processed.

[0711] "Communication components" refer to hardware or software, including communication devices and network connections, used for sending and receiving data.

[0712] An "artificial intelligence model" is an artificial system that learns from large amounts of data, finds patterns and rules, and becomes capable of performing various tasks.

[0713] An "information processing device" is a device used for processing and analyzing data, and includes computers and servers.

[0714] "Inappropriate information" refers to information that contains insulting, defamatory, or libelous content that is undesirable or harmful in online communication.

[0715] An "emotion recognition engine" is a technology that identifies a user's emotional state from text and other inputs.

[0716] A "warning" is a message or alert that notifies the user and prompts them to take action when inappropriate information is detected.

[0717] "Feedback" refers to information or advice provided in response to user behavior to encourage correction or improvement.

[0718] A "transmission restriction instruction" is a command generated by the system to prevent or stop the transmission of detected inappropriate information.

[0719] This system is designed to improve the health of online communication. The process begins with the user typing a text message using a terminal. The terminal then transmits this encoded data to the server via a communication component.

[0720] The server uses an information processing device to analyze the received encoded data. This device is equipped with an artificial intelligence model based on natural language processing, which identifies whether the text contains inappropriate information, such as offensive language. In addition, the server uses an emotion recognition engine to evaluate the user's emotional state. This emotion analysis can detect whether the user is experiencing emotions such as anger or sadness.

[0721] Based on an analysis of inappropriate information and emotional states, the server generates a warning message. This message is displayed on the user interface, prompting the user to correct their behavior or engage in emotional self-care. For example, if a user enters "I hate you," the server will determine that the text is inappropriate, and its emotion recognition engine will detect anger. In this case, the server will generate a milder warning message such as "Avoid such language and let's discuss this calmly."

[0722] As an example of a prompt, by inputting the instruction "If a user uses inappropriate language, please provide an example of how to correct it" to the generative AI model, improved examples of language can be obtained.

[0723] User feedback is individually optimized. We hope this will improve the quality of online communication and protect users' mental well-being.

[0724] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0725] Step 1:

[0726] The user uses a terminal and enters a text message using a keyboard application. During this input process, the text is recorded on the terminal via the user interface. This step encompasses the entire process from the input text data being encoded to its transmission to the server via a communication device. The output is the encoded data sent to the server.

[0727] Step 2:

[0728] The server receives encoded data from the terminal via communication components and analyzes that data using an information processing device. Specifically, it uses an artificial intelligence model based on a generative AI model to determine whether the data contains inappropriate information, and simultaneously uses an emotion recognition engine to evaluate the user's emotional state. The input is encoded data, and the output is the result of the inappropriate information determination and the emotion evaluation result.

[0729] Step 3:

[0730] The server generates a warning message based on the analysis results. In this step, if inappropriate information is detected, a warning or feedback corresponding to that information is generated. For example, if it is determined that the user's emotions are heightened, a message encouraging calmness is prepared. The input is the analysis results obtained in step 2, and the output is the generated warning message.

[0731] Step 4:

[0732] The terminal displays warning messages received from the server in the user interface. These messages prompt the user to take appropriate action and provide advice on correcting inappropriate language and emotional care. The input is the warning message from the server, and the output is visual feedback to the user.

[0733] Step 5:

[0734] The user may modify the text message based on the displayed warning message. In this step, the user may re-enter or adjust the wording and send it back to the server as needed. The re-sent data is the output here and may be subjected to further analysis processes.

[0735] (Application Example 2)

[0736] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0737] With the widespread use of online communication, there has been an increase in defamatory and inappropriate text, which can threaten mental health. Furthermore, one-sided warnings that disregard users' feelings do not lead to a fundamental solution to the problem.

[0738] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0739] In this invention, the server includes means for receiving text information input via a user interface using a communication device, a processing unit that uses a learning model for analyzing the text information, and means for analyzing the user's emotional state using an emotion engine. This makes it possible not only to determine whether the text contains inappropriate expressions, but also to provide feedback and self-care advice that takes the user's emotional state into consideration.

[0740] "User interface" refers to the screen or means of operation that allows a user to input and output data to and from an information device.

[0741] A "communication device" is a device that uses digital or analog signals to send and receive information over a network.

[0742] "Text information" refers to data or message content composed of strings of characters, and specifically means the text information entered by the user.

[0743] A "learning model" is a statistical algorithm based on machine learning techniques using historical data, and is an artificial intelligence model trained to perform a specific task.

[0744] A "processing device" is a computer or a device with the functions of executing programs and analyzing and processing data.

[0745] An "emotion engine" is an algorithm or module used to analyze and classify emotional states from text sent by users.

[0746] "Defamation" refers to unfairly speaking ill of or belittling others, and is an expression that damages their reputation or credibility.

[0747] "Self-care advice" refers to information that provides guidelines and suggestions that users can implement to manage themselves and maintain or improve their mental health.

[0748] This invention provides a system aimed at maintaining the health of online communication and promoting the mental well-being of users. This system analyzes text information entered by users in real time to determine if it contains defamation or inappropriate content. Furthermore, it uses an emotion engine to analyze the user's emotional state and generate appropriate feedback.

[0749] The server uses a communication device to receive text information entered through the user interface. The received information is processed in real time by a learning model. This learning model uses natural language processing technology and incorporates a generative model to detect inappropriate expressions. The emotion engine analyzes the user's emotions and detects states such as anger and dissatisfaction.

[0750] Based on the analysis results, the server generates feedback and displays a warning in the user interface. This warning prompts the user to revise the message and, at the same time, can provide self-care advice depending on the user's emotional state. For example, if a user enters an aggressive message and the emotion engine detects anger, a message will be displayed encouraging them to calm down with gentle language.

[0751] This system incorporates natural language processing technology and sentiment analysis capabilities, and can be implemented using software such as TensorFlow or Keras.

[0752] For example, if a user types "You are useless," the system will recognize this as a negative expression and offer suggestions such as "This message is inappropriate. Let's think of another way to say it." Furthermore, if the input is deemed emotionally intense, self-care advice, such as encouraging deep breathing, will also be provided.

[0753] An example of a prompt might be: "Design a system that analyzes user-entered text in real time for defamation and emotional state, and provides appropriate feedback."

[0754] This system allows users to participate in online interactions with peace of mind, and by preventing inappropriate remarks, it provides a healthy environment for communication.

[0755] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0756] Step 1:

[0757] The user inputs text information through the user interface. The terminal receives this input and transmits it to the server in real time via a communication device. The input data is the user's raw text information.

[0758] Step 2:

[0759] The server first uses a learning model to analyze the received text information. This model is a generative model based on natural language processing technology and is trained to detect inappropriate expressions. The input data is text information, and the server outputs a result of determining whether it contains inappropriate content through calculations.

[0760] Step 3:

[0761] The server then uses an emotion engine to analyze the user's emotional state. This engine detects emotional words and phrases in the text and infers the user's emotional state. The input data is text information, and the calculations output a result indicating the user's emotional state.

[0762] Step 4:

[0763] The server generates feedback based on the analysis results. If the judgment result indicates something inappropriate, a warning is displayed on the user interface, prompting the user to correct the content. Self-care advice is also provided depending on the emotional state. The input data for this step is the judgment result and the emotion analysis result, and a feedback message generated through calculations is output.

[0764] Step 5:

[0765] The terminal receives feedback messages from the server and displays them on the user interface. Users can view these messages and, if necessary, modify them or take action based on the advice. The input data is the feedback message, which is output in its original format.

[0766] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0767] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0768] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0769] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0770] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0771] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0772] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0773] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0774] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0775] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0776] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0777] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0778] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0779] 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.

[0780] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0781] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0782] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0783] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0784] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0785] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0786] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0787] The following is further disclosed regarding the embodiments described above.

[0788] (Claim 1)

[0789] A means for receiving text data entered via a user interface using a communication device,

[0790] A processing device that uses a learning model for analyzing the aforementioned text data,

[0791] A means for determining whether the text data contains inappropriate content using the aforementioned learning model,

[0792] A means for displaying a warning on the user interface based on the determination result,

[0793] A means for generating an instruction to stop the transmission of the text data when such inappropriate content is detected,

[0794] A system that includes this.

[0795] (Claim 2)

[0796] The aforementioned learning model is a generative model based on natural language processing,

[0797] The system according to claim 1, characterized in that the aforementioned inappropriate content includes insulting or defamatory expressions.

[0798] (Claim 3)

[0799] The system according to claim 1, characterized in that the warning provides information prompting the user to correct and re-enter the text data.

[0800] "Example 1"

[0801] (Claim 1)

[0802] A means for receiving character data entered via a user terminal using an information and communication device,

[0803] A processing unit that uses a machine learning model for analyzing the aforementioned character data,

[0804] A means for determining whether the character data contains inappropriate content using the aforementioned machine learning model,

[0805] A means for displaying a warning on the user terminal based on the determination result,

[0806] A means for generating an instruction to stop the transmission of the character data when such inappropriate content is detected,

[0807] A means of sending a warning message to the terminal and promoting the display of a warning on the user interface,

[0808] A means of providing instructions to allow users to modify the content they have entered,

[0809] A system that includes this.

[0810] (Claim 2)

[0811] The aforementioned machine learning model is a generative model based on language processing technology.

[0812] The system according to claim 1, characterized in that the aforementioned inappropriate content includes insulting or defamatory expressions.

[0813] (Claim 3)

[0814] The system according to claim 1, characterized in that the warning provides information prompting the user to correct and re-enter the text data.

[0815] "Application Example 1"

[0816] (Claim 1)

[0817] A means for receiving text data entered via a user interface using an information processing device,

[0818] A computing device that uses a learning algorithm for analyzing the aforementioned text data,

[0819] A means for determining whether the text data contains inappropriate expressions using the aforementioned learning algorithm,

[0820] A means for displaying a warning on the user interface based on the determination result,

[0821] A means for generating a command to stop transmitting the text data when such inappropriate expression is detected,

[0822] The means is characterized in that the warning message includes information to allow the user to review information regarding the transaction entered by the user,

[0823] A system that includes this.

[0824] (Claim 2)

[0825] The aforementioned learning algorithm is a generative algorithm based on natural language processing,

[0826] The system according to claim 1, characterized in that the aforementioned inappropriate expressions include insulting or defamatory phrases.

[0827] (Claim 3)

[0828] The system according to claim 1, characterized in that the warning provides information prompting the user to correct and re-enter information regarding the transaction.

[0829] "Example 2 of combining an emotion engine"

[0830] (Claim 1)

[0831] A means for receiving encoded data input via a user interface using a communication component,

[0832] An information processing device that uses an artificial intelligence model for analyzing the encoded data,

[0833] A means for determining whether the encoded data contains inappropriate information using the aforementioned artificial intelligence model,

[0834] A means for evaluating a user's emotional state using an emotion recognition engine,

[0835] A means for displaying a warning on the user interface and providing feedback according to the emotional state based on the judgment result and emotional evaluation,

[0836] Means for generating an instruction to restrict the transmission of the encoded data when such inappropriate information is detected,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The aforementioned artificial intelligence model is a generative model based on natural language processing,

[0840] The system according to claim 1 is characterized in that the inappropriate information includes insulting or defamatory expressions, and further provides warnings that take into account the user's emotional state.

[0841] (Claim 3)

[0842] The system according to claim 1, characterized in that the warning prompts the user to correct and re-enter the encoded data and provides information recommending emotional self-care and changes to more considerate expressions.

[0843] "Application example 2 of combining emotional engines"

[0844] (Claim 1)

[0845] A means for receiving text information entered via a user interface using a communication device,

[0846] A processing device that uses a learning model for analyzing the aforementioned text information,

[0847] A means for determining whether the text information contains inappropriate content using the aforementioned learning model,

[0848] A means of analyzing a user's emotional state using an emotion engine,

[0849] A means for displaying a warning on the user interface and generating feedback corresponding to the user's emotional state, based on the judgment result and the emotion analysis result,

[0850] A means for generating an instruction to stop transmitting the text information when such inappropriate content is detected,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The aforementioned learning model is a generative model based on natural language processing,

[0854] The system according to claim 1, wherein the inappropriate content includes insulting or defamatory expressions, and the emotion engine detects feelings of anger or dissatisfaction.

[0855] (Claim 3)

[0856] The system according to claim 1, characterized in that the warning not only provides information prompting the user to correct and re-enter the text information, but also suggests self-care advice based on the user's emotional state. [Explanation of Symbols]

[0857] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving text data entered via a user interface using a communication device, A processing device that uses a learning model for analyzing the aforementioned text data, A means for determining whether the text data contains inappropriate content using the aforementioned learning model, A means for displaying a warning on the user interface based on the determination result, A means for generating an instruction to stop the transmission of the text data when such inappropriate content is detected, A system that includes this.

2. The aforementioned learning model is a generative model based on natural language processing, The system according to claim 1, characterized in that the aforementioned inappropriate content includes insulting or defamatory expressions.

3. The system according to claim 1, characterized in that the warning provides information prompting the user to correct and re-enter the text data.

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