system

Abstract

We provide the system. [Solution] A means for receiving messages input from a communication device, A means of analyzing received messages to assess the possibility of emotional or defamatory content, Means for generating warnings or suggestions based on evaluation results, Means for transmitting and displaying the aforementioned warning or suggestion to a communication device, 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 persona chatbot control method 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 a modern communication environment, there is a risk that messages including slander and harassment are unintentionally sent, imposing a psychological burden on the recipient and hindering sound communication. There is a need for means to prevent such situations in advance and promote appropriate communication.

Means for Solving the Problems

[0005] This invention receives messages input from a communication device, analyzes the received messages, and evaluates their potential for emotional or defamatory content. Furthermore, it generates warnings or suggestions based on the evaluation results, transmits them to the communication device, and displays them, thereby assisting users in appropriately correcting their messages before sending them. This reduces the psychological burden on recipients and creates a healthy communication environment.

[0006] "Communication device" refers to a device that allows a user to input, send, and receive messages, such as a smartphone, tablet, or computer.

[0007] A "message" is a piece of communication expressed in text format, and refers to a unit of information used in email, chat, or social networking services (SNS) platforms.

[0008] "Analysis" refers to the process of investigating and evaluating the content of a received message, and the act of determining whether it contains emotions or defamation based on specific criteria.

[0009] "Potential emotional or defamatory content" is an indicator of the psychological impact and danger that a particular message poses to the recipient, and refers to a criterion for evaluating the aggressiveness of the tone and content of the message.

[0010] "Evaluation results" refer to judgments regarding emotions and the potential for defamation obtained through the message analysis process.

[0011] "Warnings or suggestions" refer to information that draws the user's attention based on the content of the analyzed message, or specific instructions for correcting the message to make it more appropriate.

[0012] "Generation" refers to the process of creating new data or content from specific data or information. [Brief explanation of the drawing]

[0013] [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention provides a technology for suppressing inappropriate messages in communication systems and promoting healthy communication. Specific embodiments of this invention will be described below.

[0035] First, the user enters a message using their device via email, chat, or social networking application. During this time, the device continuously monitors the user's input, and when it detects a message that meets certain criteria, it sends its content to a server for analysis. The server uses generative AI to analyze the received message, evaluating its sentiment and potential for defamation. This evaluation utilizes natural language processing technology to examine the tone and content of the message in detail.

[0036] If the analysis determines that the message contains inappropriate elements, the server generates a warning message. At the same time, it generates suggestions for more appropriate wording and improvements to the message content and sends them to the terminal. The terminal then displays the warning message and suggestions on its user interface, prompting the user to revise the message.

[0037] Users can revise their messages based on suggestions provided by the device. The revised message is then sent to the recipient by the device. This allows users to correct inappropriate content before sending, thus avoiding unintentional defamation or harassment.

[0038] As a concrete example, consider a scenario where a user sends a business email stating, "Your proposal is completely meaningless." Because this message could give the recipient a negative impression, the server analyzes it and generates a warning. The terminal then displays a suggestion to "Please discuss the areas for improvement constructively," which the user can use to revise it to "I have a few questions regarding your proposal" and send it.

[0039] This invention makes it possible to send messages with appropriate content and facilitate communication, thereby reducing the psychological burden on the recipient.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user uses the device to type text into an email, chat, or social media message input field. The device monitors the user's input in real time, detecting the number of characters and the end of the input.

[0043] Step 2:

[0044] The terminal captures the incoming message and prepares it for transmission to the server. Specifically, it converts the message data into a format for analysis and applies security protocols.

[0045] Step 3:

[0046] The terminal sends the prepared message to the server via a secure communication channel.

[0047] Step 4:

[0048] The server passes the received message data to a generative AI engine for analysis. The generative AI uses natural language processing to analyze the message, evaluate its tone and expression, and generate a sentiment score.

[0049] Step 5:

[0050] The server determines the potential for defamation in a message based on the generated sentiment score. If it assesses the risk as high, it generates a warning message and correction suggestions.

[0051] Step 6:

[0052] The server sends a warning message and suggestions back to the terminal. Upon receiving it, the terminal displays a notification in the user interface. It provides the user with hints on what the problem is and how to fix it.

[0053] Step 7:

[0054] Users can check notifications and edit messages on their devices. They can re-select words or restructure sentences based on suggestions.

[0055] Step 8:

[0056] The user completes the revisions and decides to send. The terminal sends the final message to the intended recipient. The server records the sent message in a database and uses it as data for future improvements.

[0057] (Example 1)

[0058] 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."

[0059] In digital communication, there is a problem of unintentionally sending messages that cause offense, resulting in psychological distress to recipients. Furthermore, content containing inappropriate language, including defamation, can lead to social trouble. Therefore, a mechanism is needed to allow users to review and improve their communications before sending them.

[0060] 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.

[0061] In this invention, the server includes means for monitoring information from a communication terminal and transferring it when it meets certain criteria, means for analyzing the received information and evaluating the possibility of emotion or defamation, and means for generating warnings or suggestions based on the evaluation results using a generation AI module. This allows users to receive suggestions for improving their messages, review the content of their communications before sending them, and avoid unintended problems.

[0062] A "communication terminal" is a device used by a user to input, send, and receive information, and includes smartphones and computers.

[0063] "Information" refers to messages, text, or digital content that a user inputs or receives through a communication device.

[0064] A "server" is a central computing system that receives and processes information transmitted from communication terminals, and returns the results of analysis and generation.

[0065] A "generative AI module" refers to an artificial intelligence program used to analyze received information and generate evaluations and suggestions using natural language processing technology.

[0066] "Natural language processing technology" refers to techniques that enable computers to understand, analyze, and process human language, and is used for sentiment analysis and tone analysis of text.

[0067] A "warning" is a message generated to alert a user to information that may be inappropriate or offensive.

[0068] A "suggestion" is an instruction that provides alternative expressions or methods for modifying the content of information submitted by the user.

[0069] This invention is designed as a system to facilitate the suppression of inappropriate messages in communications and to realize healthy communication. Specifically, it uses a communication terminal, a server, and a generation AI module to perform real-time monitoring and analysis of message content.

[0070] Role of a communication terminal

[0071] Users use communication devices (such as smartphones or computers) to input messages via email, chat, or social networking applications. The device monitors the message content in real time as it is being entered, detecting potentially inappropriate keywords and context. If certain criteria are met, the message is sent to the server.

[0072] Server and generation AI module processing

[0073] The server receives messages sent from terminals and analyzes them using a generative AI module. The AI ​​model used incorporates widely used natural language processing techniques (e.g., GPT-3®, BERT). The server analyzes the sentiment of messages and assesses their potential for defamation, generating warnings or suggestions based on their tone and context.

[0074] User notifications and corrections

[0075] The generated warnings and suggestions are sent from the server to the communication terminal. The terminal displays them in the user interface and prompts the user to review the message content. The user can revise the message based on the displayed suggestions, and the final, confirmed message is sent to the recipient.

[0076] Examples of specific cases and prompt statements

[0077] As a concrete example, consider a scenario where a user attempts to send a business email stating, "Your proposal is completely meaningless." The server analyzes the negative tone of the message and suggests a revised version as an appropriate suggestion: "Let's constructively discuss areas for improvement."

[0078] An example of a prompt message would be: "We need suggestions to improve a negative business message. The specific situation is as follows: A user is about to send the message 'Your suggestion is completely meaningless.'"

[0079] This invention allows users to appropriately modify messages before sending them, thereby reducing the risk of unintentionally sending inappropriate communications.

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

[0081] Step 1:

[0082] The user enters a message using a communication terminal. The terminal has the capability to monitor the user's input in real time. It receives the input string data and detects specific keywords and negative contexts from it. This detection uses keyword matching algorithms and simple sentiment analysis methods. When a message that meets the criteria is entered, it prepares to transfer the data to the server. The output is a dataset of detected messages.

[0083] Step 2:

[0084] The terminal sends the detected message data to the server. The secure communication protocol HTTPS is used for transmission to ensure data security. The output is encrypted message data sent to the server.

[0085] Step 3:

[0086] The server receives message data sent from the terminal and analyzes it using a generative AI model. The input data is analyzed using natural language processing techniques (e.g., GPT-3 or BERT) to assess sentiment and the likelihood of defamation. Data processing involves tokenizing the text and then running it through the model for scoring. The output is the sentiment score and judgment result based on the analysis.

[0087] Step 4:

[0088] Based on the analysis results, the server generates a warning message and improvement suggestions if deemed inappropriate. The generating AI uses a model learned from past data to propose appropriate alternatives. This process involves text generation calculations to generate the suggested content. The output consists of the generated warning message and improvement suggestions.

[0089] Step 5:

[0090] The server sends the generated warning message and suggestions to the terminal. The transmitted data is again protected by a secure protocol and delivered to the terminal. The output is the transmitted data directed to the terminal.

[0091] Step 6:

[0092] The terminal displays received warnings and suggestions on the user interface. The user can review the displayed information and modify the message content. The modified data is saved again and ready to be sent. The output is the modified message data after user confirmation.

[0093] Step 7:

[0094] After the user reviews the modified message, they finally send it to the recipient. The terminal sends the reviewed message directly over the network without going through the server again. The output is the final message data that is sent.

[0095] (Application Example 1)

[0096] 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."

[0097] Sending inappropriate messages in a communication environment can lead to misunderstandings and conflicts among users, potentially degrading the service experience. However, it is not easy for users to anticipate and appropriately address this issue. In particular, there is a need for a mechanism to prevent inappropriate transmissions in real time, but current technology is insufficient to address this.

[0098] 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.

[0099] In this invention, the server includes means for receiving data input from a communication terminal, means for analyzing the received data to evaluate the possibility of emotion or defamation, and means for visually presenting the provided warnings or suggestions using an augmented reality device. This makes it possible for users to be alerted or given suggestions for improvement before sending inappropriate messages.

[0100] A "communication terminal" is an electronic device that has the function of sending and receiving information such as voice, video, and text.

[0101] "Data" refers to various types of information that are input and processed by a communication terminal.

[0102] "Analysis" is the process of understanding data and identifying specific patterns or characteristics.

[0103] "Emotion" refers to the psychological state or tone that can be inferred from the content of a message.

[0104] "Defamation" refers to expressions that are deemed to have the intent to criticize or insult others.

[0105] "Evaluation" is the process of determining the possibility of emotions or defamation based on data obtained through analysis.

[0106] A "warning" is a notification generated to alert a user to an inappropriate message.

[0107] A "suggestion" is an alternative expression presented to the user with the aim of improving the content of the message.

[0108] An "augmented reality device" is a device equipped with technology that overlays digital information onto the real environment.

[0109] The system for carrying out this invention consists of specific electronic devices. A detailed embodiment thereof is shown below.

[0110] The server receives message data sent from each user's communication terminal. This data is analyzed using natural language processing technology. Specifically, it uses Tensorflow® and Python, along with generative AI models, to analyze the sentiment of messages and evaluate their potential for defamation. This evaluation process deeply analyzes the tone and content of messages and generates warnings or suggestions for users as needed.

[0111] The user's device, such as smart glasses or augmented reality devices, displays warnings and suggestions received from the server in real time. This display is visual and provides immediate feedback to the user, preventing the sending of inappropriate messages.

[0112] For example, if a user tries to send a message to a friend saying "completely useless opinion," the system will display a suggestion on the glasses' screen saying, "Please elaborate on your opinion." This allows the user to revise their message into a more positive expression, taking alternative suggestions into consideration.

[0113] An example of a prompt message would be, "Please suggest a way to change the tone of this message to a positive one."

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] The user enters message data into the communication terminal. This entered message is temporarily stored on the terminal and sent to the server via the communication network. In this step, the input is the message entered by the user, and the output is the data transferred to the server.

[0117] Step 2:

[0118] The server analyzes the received message data. This analysis includes using natural language processing techniques to evaluate the sentiment and potential for defamation in the message. The input is the transmitted message data, and the output is the evaluation result of the message. A generative AI model participates in this evaluation, measuring the tone of the message based on the prompt text.

[0119] Step 3:

[0120] Based on the evaluation results, the server generates warnings and improvement suggestions for messages deemed inappropriate or negative. The input is the evaluation result, and the output is the generated warning message and suggestion. For example, if a message is deemed offensive, a suggestion such as "Please add a positive comment" will be generated.

[0121] Step 4:

[0122] Warnings and suggestions are sent from the server to the user's device. The device, such as an augmented reality device, visually displays the warnings and suggestions to the user. The input is the suggestion message from the server, and the output is the display of the warnings and suggestions that the user sees. This visual presentation gives the user an opportunity to review and improve the message before sending it.

[0123] Step 5:

[0124] The user modifies the message on the device according to the provided suggestions. This inputs the newly modified message into the device, and it is finally ready to be sent. The input is the message modification performed by the user on the device, and the output is the improved message.

[0125] 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.

[0126] This invention provides a technology for managing messages that users intend to send in a communication system in a more comfortable and secure manner. This invention includes a function that combines message analysis with an emotion engine that recognizes the user's emotions.

[0127] When a user types a message on an email, chat, or social networking platform using their device, the device monitors the input in real time and prepares to send it to the server. During this process, an emotion engine analyzes the user's emotional state based on factors such as typing speed, touch pressure, and past messaging patterns. This determines the user's current emotional state, which is then further evaluated on the server.

[0128] Once a message is sent to the server, its content is analyzed using a generation AI. This analysis process evaluates the message's sentiment score and its potential for defamation. A key feature of this stage is that it incorporates the user's perceived sentiment information into the analysis, allowing for a more accurate determination of the message's appropriateness.

[0129] Based on these analysis results, the server generates warning messages and appropriate suggestions. The suggestions take into account the user's emotional state and may include personalized advice such as, "Please calm down and wait a little longer before replying." This makes it easier to prevent emotional communication errors that users may unconsciously cause.

[0130] The device displays these warnings and suggestions, prompting the user to re-edit the message. When the user modifies the message based on their emotions, this information is also fed back to the server and recorded in a database. This information is used as reference data for future improvements and more personalized suggestions.

[0131] For example, if a user enters a message like "Why are you taking so long to reply?" in an input style that suggests they were raising their voice, the server will evaluate it in conjunction with the emotion engine data and offer a revised suggestion in a calmer tone. For instance, it might suggest, "I'm sorry to bother you while you're busy, but could I ask when you expect to reply?" This promotes considerate communication towards the recipient.

[0132] This invention dramatically improves the quality of communication through messages and supports interactions that are sensitive to the user's emotions.

[0133] The following describes the processing flow.

[0134] Step 1:

[0135] The user uses the device to type messages via email, chat, or social networking apps. During this process, the device monitors the speed and frequency of message input, as well as the strength of keystrokes, in real time.

[0136] Step 2:

[0137] The device sends monitoring data to the emotion engine, which analyzes the user's emotional state. The emotion engine uses the data to infer the user's feelings and returns that information to the device.

[0138] Step 3:

[0139] The device prepares to send the captured message and user sentiment information to the server. Specifically, it converts the information into a secure format and sends it to the server.

[0140] Step 4:

[0141] The server passes the received messages and sentiment data to a generating AI, which evaluates the sentiment score of the message content and the likelihood of it being defamatory. Natural language processing techniques are used for the analysis.

[0142] Step 5:

[0143] Based on the analysis results, the server generates a warning message and appropriate message modification suggestions tailored to the user's emotional state. By taking emotional information into account, the suggestions might include phrases like, "Let's take a moment to calm down and think about this."

[0144] Step 6:

[0145] The server sends a warning message and correction suggestions to the terminal. The terminal receives this and displays it on the user interface. The user is shown the inappropriate parts along with the suggestions.

[0146] Step 7:

[0147] The user checks the display on their device and determines whether the message needs to be corrected. If corrections are needed, they can edit the message using the suggested corrections as a guide.

[0148] Step 8:

[0149] When a user edits a message and chooses to send it, the device sends the final version to the recipient. This ensures clear and unambiguous communication.

[0150] Step 9:

[0151] The server retains records of sent messages and user sentiment states, which are used to improve the system and provide more personalized services.

[0152] (Example 2)

[0153] 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".

[0154] In modern communications, users often send emotionally charged messages instantly, leading to misunderstandings and friction. There is a need to improve this situation and achieve comfortable and smooth communication. Furthermore, since overly emotional messages may contain inappropriate content, technologies are needed to prevent this from happening.

[0155] 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.

[0156] In this invention, the server includes means for collecting data input from a communication terminal, means for analyzing the user's emotional state based on the collected data, and means for evaluating the emotional score and the likelihood of defamation of a message, taking into account the emotional state obtained from the analysis. This enables the sending of appropriate messages that take into account the user's emotional state, thereby realizing comfortable and safe communication.

[0157] A "communication terminal" refers to a device that allows users to input messages and send and receive data through a communication network.

[0158] "Means of collecting data" refers to functions for collecting information entered by users through communication terminals.

[0159] "Means for analyzing the user's emotional state" refers to technologies used to identify the user's emotions and psychological state from collected data.

[0160] An "emotion score" refers to a numerical value or indicator that evaluates the degree to which a message contains emotion.

[0161] "Means of assessing the potential for defamation" refers to a function that determines whether a message contains offensive or disrespectful content towards others.

[0162] "Means for generating warnings or suggestions" refers to functions that, based on evaluation results, provide users with warnings or suggestions for improvement.

[0163] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and process human language.

[0164] A "machine learning algorithm" refers to a method used by computers to learn from data and discover patterns and rules.

[0165] "Making data editable and recording edited data" means that users can modify message content according to the warnings and suggestions presented, and that this modification information is saved for later analysis and feature improvement.

[0166] This system begins with the user typing a message using a terminal. The terminal monitors the user's input in real time and collects data. The collected data includes the user's typing speed, touch pressure, and past messaging patterns. This information is necessary to analyze the user's emotional state. The terminal uses an emotion engine to analyze this data and determine the user's emotional state. This emotion engine utilizes widely used machine learning algorithms to make accurate emotional judgments based on the collected data.

[0167] The server receives user messages and analyzed emotional states sent from the terminal and further analyzes them using a generative AI model. The AI ​​model employs natural language processing techniques to evaluate the message's sentiment score and potential for defamation. At this stage, the user's emotional data is integrated with the message content, enabling a more refined evaluation.

[0168] The server generates warnings or suggestions based on the analysis results. These suggestions take into account the user's emotional state and may include personalized advice such as "Think a little more before sending." The generated suggestions are sent to the terminal and displayed to the user. Based on this information, the user can edit the message if necessary, and the revised message is sent back to the server. This information is recorded in a database and used to improve the system and generate personalized suggestions in the future.

[0169] For example, if a user enters a somewhat aggressive message such as "Why are you taking so long to reply?", the AI ​​model can use sentiment data to suggest a revised version such as "I apologize for bothering you, but could you tell me when you expect to reply?". An example of a prompt entered into the generative AI model is "How should we evaluate the user's emotional response to this message?". In this way, the system provides users with effective support to promote appropriate and considerate communication.

[0170] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0171] Step 1:

[0172] The user enters a message using the device. The device monitors this in real time, collecting data such as typing speed, touch pressure, and past messaging patterns. This data is then used as input for sentiment analysis.

[0173] Step 2:

[0174] The device uses the collected data to activate an emotion engine and analyze the user's emotional state. The input data is processed by a machine learning algorithm, and an output indicating the user's emotional state, such as whether they are calm or irritated.

[0175] Step 3:

[0176] The terminal sends analyzed sentiment information to the server along with the message entered by the user. This transmission includes both the collected raw data and the analysis results.

[0177] Step 4:

[0178] The server inputs the user's message and emotional state received from the terminal into an AI model, which then analyzes the message content. Utilizing natural language processing techniques, it evaluates the message's emotional score and its potential for defamation, generating the results.

[0179] Step 5:

[0180] The server generates warnings or suggestions based on the analysis results. This output information includes specific improvement suggestions and advice that take into account the user's emotional state.

[0181] Step 6:

[0182] A warning or suggestion from the server is sent to the terminal, which then displays it to the user. The user can re-edit the message based on the suggested improvements, and the re-edited message is sent back to the server from the terminal.

[0183] Step 7:

[0184] The server receives the user's edited message and records the information in the database. This feedback is used for future system improvements and to provide more personalized suggestions.

[0185] (Application Example 2)

[0186] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0187] When users receive advertisements or messages, there is a challenge in that the display is not tailored to their individual emotional state, making effective information transmission difficult. Furthermore, there is a need for adaptive systems to avoid causing discomfort or misunderstanding among recipients due to the potential for fixed content.

[0188] 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.

[0189] In this invention, the server includes means for receiving information input from a communication terminal, means for analyzing the received information to evaluate the emotional state or the possibility of defamation, and means for analyzing the emotional state using observational data and making individual adjustments. This makes it possible to display information and make personalized suggestions that are tailored to the user's emotional state and past behavior.

[0190] A "communication terminal" is an electronic device used by a user to input or receive information.

[0191] "Information analysis" is the process of identifying and evaluating the content and related emotional states based on received data.

[0192] "Emotional state" refers to the user's current emotional or psychological state, which is inferred through their behavior during data entry and interactions.

[0193] "Potential for defamation" is an assessment indicating the possibility that the received or entered information may have the intent to attack or defame others.

[0194] A "notification or suggestion" is a message that draws attention to the user or provides options based on the results of information analysis.

[0195] "Individualized adjustments" refer to the process of adjusting information to display the most optimal information based on the user's specific emotional state and past data.

[0196] The system for realizing this invention is first configured to receive information input from a communication terminal. The terminal provides a user-operated interface, such as a smartphone or smart glasses. This terminal collects user input data and response data, which are then transmitted to a server in real time.

[0197] The server analyzes the received data, utilizing natural language processing techniques to assess emotional states and the potential for defamation. This process employs generative AI models such as OpenAI® to gain a deep understanding of user emotions and reactions. Machine learning frameworks like TensorFlow are used for data analysis, and the emotion engine identifies the user's current emotional tendencies.

[0198] Next, the server generates notifications or suggestions based on the analysis results, making individual adjustments to suit the user's emotional state. This adjusted information is displayed on the user's device, and if negative emotions are detected, it presents the user with calmer alternatives or options.

[0199] For example, if a user reacts with stress when viewing an advertisement, the server immediately adjusts the information and proposes an advertisement that is tailored to their emotional state. For instance, for a user interested in health, a prompt such as "Generate advertisement suggestions for new supplements for users interested in health" can be input into the AI ​​model, enabling the provision of customized information. This entire process makes the information received by the user more individualized, creating a more meaningful experience for the recipient.

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The device captures user input in real time. This input includes text data, touch patterns, and voice input, all of which are compiled into input data. The device then prepares this data and gets ready to send it to the server.

[0203] Step 2:

[0204] The server receives input data sent from the terminal. Based on the received data, it performs text analysis using natural language processing technology to evaluate the user's emotional state and the possibility of defamation. As a result of the analysis, the user's sentiment score and the detection of negative content are performed.

[0205] Step 3:

[0206] The server generates notifications or suggestions based on the analysis results. It uses a generative AI model to create appropriate alternative messages tailored to the user's emotional state. The user enters a prompt, such as "Generate advertising suggestions for new supplements," and the server generates customized suggestions for them.

[0207] Step 4:

[0208] The server sends the generated notification or suggestion to the terminal. The terminal displays this suggestion to the user, allowing the user to readjust their input and respond emotionally. Based on the displayed information, the user can further adjust their response and input.

[0209] Step 5:

[0210] The device records the changes the user makes based on the suggestions as data and sends feedback to the server. This feedback information is stored in a database and used for future analysis and to improve the accuracy of suggestions. The user's behavioral data is then used as input for the next cycle.

[0211] 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.

[0212] 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.

[0213] 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.

[0214] [Second Embodiment]

[0215] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0216] 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.

[0217] 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).

[0218] 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.

[0219] 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.

[0220] 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).

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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".

[0227] This invention provides a technology for suppressing inappropriate messages in communication systems and promoting healthy communication. Specific embodiments of this invention will be described below.

[0228] First, the user enters a message using their device via email, chat, or social networking application. During this time, the device continuously monitors the user's input, and when it detects a message that meets certain criteria, it sends its content to a server for analysis. The server uses generative AI to analyze the received message, evaluating its sentiment and potential for defamation. This evaluation utilizes natural language processing technology to examine the tone and content of the message in detail.

[0229] If the analysis determines that the message contains inappropriate elements, the server generates a warning message. At the same time, it generates suggestions for more appropriate wording and improvements to the message content and sends them to the terminal. The terminal then displays the warning message and suggestions on its user interface, prompting the user to revise the message.

[0230] Users can revise their messages based on suggestions provided by the device. The revised message is then sent to the recipient by the device. This allows users to correct inappropriate content before sending, thus avoiding unintentional defamation or harassment.

[0231] As a concrete example, consider a scenario where a user sends a business email stating, "Your proposal is completely meaningless." Because this message could give the recipient a negative impression, the server analyzes it and generates a warning. The terminal then displays a suggestion to "Please discuss the areas for improvement constructively," which the user can use to revise it to "I have a few questions regarding your proposal" and send it.

[0232] This invention makes it possible to send messages with appropriate content and facilitate communication, thereby reducing the psychological burden on the recipient.

[0233] The following describes the processing flow.

[0234] Step 1:

[0235] The user uses the device to type text into an email, chat, or social media message input field. The device monitors the user's input in real time, detecting the number of characters and the end of the input.

[0236] Step 2:

[0237] The terminal captures the incoming message and prepares it for transmission to the server. Specifically, it converts the message data into a format for analysis and applies security protocols.

[0238] Step 3:

[0239] The terminal sends the prepared message to the server via a secure communication channel.

[0240] Step 4:

[0241] The server passes the received message data to a generative AI engine for analysis. The generative AI uses natural language processing to analyze the message, evaluate its tone and expression, and generate a sentiment score.

[0242] Step 5:

[0243] The server determines the potential for defamation in a message based on the generated sentiment score. If it assesses the risk as high, it generates a warning message and correction suggestions.

[0244] Step 6:

[0245] The server sends a warning message and suggestions back to the terminal. Upon receiving it, the terminal displays a notification in the user interface. It provides the user with hints on what the problem is and how to fix it.

[0246] Step 7:

[0247] Users can check notifications and edit messages on their devices. They can re-select words or restructure sentences based on suggestions.

[0248] Step 8:

[0249] The user completes the revisions and decides to send. The terminal sends the final message to the intended recipient. The server records the sent message in a database and uses it as data for future improvements.

[0250] (Example 1)

[0251] 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."

[0252] In digital communication, there is a problem of unintentionally sending messages that cause offense, resulting in psychological distress to recipients. Furthermore, content containing inappropriate language, including defamation, can lead to social trouble. Therefore, a mechanism is needed to allow users to review and improve their communications before sending them.

[0253] 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.

[0254] In this invention, the server includes means for monitoring information from a communication terminal and transferring it when it meets certain criteria, means for analyzing the received information and evaluating the possibility of emotion or defamation, and means for generating warnings or suggestions based on the evaluation results using a generation AI module. This allows users to receive suggestions for improving their messages, review the content of their communications before sending them, and avoid unintended problems.

[0255] A "communication terminal" is a device used by a user to input, send, and receive information, and includes smartphones and computers.

[0256] "Information" refers to messages, text, or digital content that a user inputs or receives through a communication device.

[0257] A "server" is a central computing system that receives and processes information transmitted from communication terminals, and returns the results of analysis and generation.

[0258] A "generative AI module" refers to an artificial intelligence program used to analyze received information and generate evaluations and suggestions using natural language processing technology.

[0259] "Natural language processing technology" refers to techniques that enable computers to understand, analyze, and process human language, and is used for sentiment analysis and tone analysis of text.

[0260] A "warning" is a message generated to alert a user to information that may be inappropriate or offensive.

[0261] A "suggestion" is an instruction that provides alternative expressions or methods for modifying the content of information submitted by the user.

[0262] This invention is designed as a system to facilitate the suppression of inappropriate messages in communications and to realize healthy communication. Specifically, it uses a communication terminal, a server, and a generation AI module to perform real-time monitoring and analysis of message content.

[0263] Role of a communication terminal

[0264] Users use communication devices (such as smartphones or computers) to input messages via email, chat, or social networking applications. The device monitors the message content in real time as it is being entered, detecting potentially inappropriate keywords and context. If certain criteria are met, the message is sent to the server.

[0265] Server and generation AI module processing

[0266] The server receives messages sent from terminals and analyzes them using a generative AI module. The AI ​​model used incorporates widely used natural language processing techniques (e.g., GPT-3, BERT). The server analyzes the sentiment of messages and assesses their potential for defamation, generating warnings or suggestions based on their tone and context.

[0267] User notifications and corrections

[0268] The generated warnings and suggestions are sent from the server to the communication terminal. The terminal displays them in the user interface and prompts the user to review the message content. The user can revise the message based on the displayed suggestions, and the final, confirmed message is sent to the recipient.

[0269] Examples of specific cases and prompt statements

[0270] As a concrete example, consider a scenario where a user attempts to send a business email stating, "Your proposal is completely meaningless." The server analyzes the negative tone of the message and suggests a revised version as an appropriate suggestion: "Let's constructively discuss areas for improvement."

[0271] An example of a prompt message would be: "We need suggestions to improve a negative business message. The specific situation is as follows: A user is about to send the message 'Your suggestion is completely meaningless.'"

[0272] This invention allows users to appropriately modify messages before sending them, thereby reducing the risk of unintentionally sending inappropriate communications.

[0273] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0274] Step 1:

[0275] The user enters a message using a communication terminal. The terminal has the capability to monitor the user's input in real time. It receives the input string data and detects specific keywords and negative contexts from it. This detection uses keyword matching algorithms and simple sentiment analysis methods. When a message that meets the criteria is entered, it prepares to transfer the data to the server. The output is a dataset of detected messages.

[0276] Step 2:

[0277] The terminal sends the detected message data to the server. The secure communication protocol HTTPS is used for transmission to ensure data security. The output is encrypted message data sent to the server.

[0278] Step 3:

[0279] The server receives message data sent from the terminal and analyzes it using a generative AI model. The input data is analyzed using natural language processing techniques (e.g., GPT-3 or BERT) to assess sentiment and the likelihood of defamation. Data processing involves tokenizing the text and then running it through the model for scoring. The output is the sentiment score and judgment result based on the analysis.

[0280] Step 4:

[0281] Based on the analysis results, the server generates a warning message and improvement suggestions if deemed inappropriate. The generating AI uses a model learned from past data to propose appropriate alternatives. This process involves text generation calculations to generate the suggested content. The output consists of the generated warning message and improvement suggestions.

[0282] Step 5:

[0283] The server sends the generated warning messages and suggestions to the terminal. The transmitted data is protected again by a secure protocol and delivered to the terminal. The output is the transmission data directed to the terminal.

[0284] Step 6:

[0285] The terminal displays the received warnings and suggestions on the user interface. The user can check the displayed information and modify the content of the message. The modified data is saved again and is ready for transmission. The output is the modified message data after user confirmation.

[0286] Step 7:

[0287] After the user checks the modified message, the user finally sends it to the recipient. The terminal directly transmits the confirmed message through the network without going through the server again. The output is the finally transmitted message data.

[0288] (Application Example 1)

[0289] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0290] The transmission of inappropriate messages in the communication environment may cause misunderstandings and conflicts among users and deteriorate the service usage environment. However, it is not easy for users themselves to grasp this in advance and deal with it appropriately. In particular, a mechanism to prevent inappropriate transmissions in real time is required, but the current technology cannot fully address this.

[0291] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0292] In this invention, the server includes means for receiving data input from a communication terminal, means for analyzing the received data to evaluate the possibility of emotion or defamation, and means for visually presenting the provided warnings or suggestions using an augmented reality device. This makes it possible for users to be alerted or given suggestions for improvement before sending inappropriate messages.

[0293] A "communication terminal" is an electronic device that has the function of sending and receiving information such as voice, video, and text.

[0294] "Data" refers to various types of information that are input and processed by a communication terminal.

[0295] "Analysis" is the process of understanding data and identifying specific patterns or characteristics.

[0296] "Emotion" refers to the psychological state or tone that can be inferred from the content of a message.

[0297] "Defamation" refers to expressions that are deemed to have the intent to criticize or insult others.

[0298] "Evaluation" is the process of determining the possibility of emotions or defamation based on data obtained through analysis.

[0299] A "warning" is a notification generated to alert a user to an inappropriate message.

[0300] A "suggestion" is an alternative expression presented to the user with the aim of improving the content of the message.

[0301] An "augmented reality device" is a device equipped with technology that overlays digital information onto the real environment.

[0302] The system for carrying out this invention consists of specific electronic devices. A detailed embodiment thereof is shown below.

[0303] The server receives message data transmitted from the communication terminals of each user. This data is analyzed by making full use of natural language processing technology. Specifically, TensorFlow and Python are used, and a generative AI model is utilized to evaluate the sentiment analysis of messages and the possibility of slander. In this evaluation process, the tone and content of the messages are deeply analyzed, and warnings and suggestions for users are generated as needed.

[0304] The user's terminal, such as smart glasses or augmented reality devices, displays the warnings and suggestions received from the server in real time. This display is performed visually, providing immediate feedback to the user, thereby preventing the transmission of inappropriate messages.

[0305] For example, when a user attempts to send a message "completely useless opinion" to a friend, this system displays a suggestion "Please convey your opinion in more detail" on the display of the glasses. This enables the user to refer to alternatives and modify the message into a positive expression.

[0306] Examples of prompt sentences include "Please present a way to convert the tone of this message into a positive one."

[0307] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0308] Step 1:

[0309] The user inputs message data into the communication terminal. The input message is temporarily stored in the terminal and transmitted to the server via the communication network. The input in this step is the message entered by the user, and the output is the data transferred to the server.

[0310] Step 2:

[0311] The server analyzes the received message data. This analysis includes using natural language processing techniques to evaluate the sentiment and potential for defamation in the message. The input is the transmitted message data, and the output is the evaluation result of the message. A generative AI model participates in this evaluation, measuring the tone of the message based on the prompt text.

[0312] Step 3:

[0313] Based on the evaluation results, the server generates warnings and improvement suggestions for messages deemed inappropriate or negative. The input is the evaluation result, and the output is the generated warning message and suggestion. For example, if a message is deemed offensive, a suggestion such as "Please add a positive comment" will be generated.

[0314] Step 4:

[0315] Warnings and suggestions are sent from the server to the user's device. The device, such as an augmented reality device, visually displays the warnings and suggestions to the user. The input is the suggestion message from the server, and the output is the display of the warnings and suggestions that the user sees. This visual presentation gives the user an opportunity to review and improve the message before sending it.

[0316] Step 5:

[0317] The user modifies the message on the device according to the provided suggestions. This inputs the newly modified message into the device, and it is finally ready to be sent. The input is the message modification performed by the user on the device, and the output is the improved message.

[0318] 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.

[0319] This invention provides a technology for managing messages that users intend to send in a communication system in a more comfortable and secure manner. This invention includes a function that combines message analysis with an emotion engine that recognizes the user's emotions.

[0320] When a user types a message on an email, chat, or social networking platform using their device, the device monitors the input in real time and prepares to send it to the server. During this process, an emotion engine analyzes the user's emotional state based on factors such as typing speed, touch pressure, and past messaging patterns. This determines the user's current emotional state, which is then further evaluated on the server.

[0321] Once a message is sent to the server, its content is analyzed using a generation AI. This analysis process evaluates the message's sentiment score and its potential for defamation. A key feature of this stage is that it incorporates the user's perceived sentiment information into the analysis, allowing for a more accurate determination of the message's appropriateness.

[0322] Based on these analysis results, the server generates warning messages and appropriate suggestions. The suggestions take into account the user's emotional state and may include personalized advice such as, "Please calm down and wait a little longer before replying." This makes it easier to prevent emotional communication errors that users may unconsciously cause.

[0323] The device displays these warnings and suggestions, prompting the user to re-edit the message. When the user modifies the message based on their emotions, this information is also fed back to the server and recorded in a database. This information is used as reference data for future improvements and more personalized suggestions.

[0324] For example, if a user enters a message like "Why are you taking so long to reply?" in an input style that suggests they were raising their voice, the server will evaluate it in conjunction with the emotion engine data and offer a revised suggestion in a calmer tone. For instance, it might suggest, "I'm sorry to bother you while you're busy, but could I ask when you expect to reply?" This promotes considerate communication towards the recipient.

[0325] This invention dramatically improves the quality of communication through messages and supports interactions that are sensitive to the user's emotions.

[0326] The following describes the processing flow.

[0327] Step 1:

[0328] The user uses the device to type messages via email, chat, or social networking apps. During this process, the device monitors the speed and frequency of message input, as well as the strength of keystrokes, in real time.

[0329] Step 2:

[0330] The device sends monitoring data to the emotion engine, which analyzes the user's emotional state. The emotion engine uses the data to infer the user's feelings and returns that information to the device.

[0331] Step 3:

[0332] The device prepares to send the captured message and user sentiment information to the server. Specifically, it converts the information into a secure format and sends it to the server.

[0333] Step 4:

[0334] The server passes the received messages and sentiment data to a generating AI, which evaluates the sentiment score of the message content and the likelihood of it being defamatory. Natural language processing techniques are used for the analysis.

[0335] Step 5:

[0336] Based on the analysis results, the server generates a warning message and appropriate message modification suggestions tailored to the user's emotional state. By taking emotional information into account, the suggestions might include phrases like, "Let's take a moment to calm down and think about this."

[0337] Step 6:

[0338] The server sends a warning message and correction suggestions to the terminal. The terminal receives this and displays it on the user interface. The user is shown the inappropriate parts along with the suggestions.

[0339] Step 7:

[0340] The user checks the display on their device and determines whether the message needs to be corrected. If corrections are needed, they can edit the message using the suggested corrections as a guide.

[0341] Step 8:

[0342] When a user edits a message and chooses to send it, the device sends the final version to the recipient. This ensures clear and unambiguous communication.

[0343] Step 9:

[0344] The server retains records of sent messages and user sentiment states, which are used to improve the system and provide more personalized services.

[0345] (Example 2)

[0346] 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".

[0347] In modern communications, users often send emotionally charged messages instantly, leading to misunderstandings and friction. There is a need to improve this situation and achieve comfortable and smooth communication. Furthermore, since overly emotional messages may contain inappropriate content, technologies are needed to prevent this from happening.

[0348] 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.

[0349] In this invention, the server includes means for collecting data input from a communication terminal, means for analyzing the user's emotional state based on the collected data, and means for evaluating the emotional score and the likelihood of defamation of a message, taking into account the emotional state obtained from the analysis. This enables the sending of appropriate messages that take into account the user's emotional state, thereby realizing comfortable and safe communication.

[0350] A "communication terminal" refers to a device that allows users to input messages and send and receive data through a communication network.

[0351] "Means of collecting data" refers to functions for collecting information entered by users through communication terminals.

[0352] "Means for analyzing the user's emotional state" refers to technologies used to identify the user's emotions and psychological state from collected data.

[0353] An "emotion score" refers to a numerical value or indicator that evaluates the degree to which a message contains emotion.

[0354] "Means of assessing the potential for defamation" refers to a function that determines whether a message contains offensive or disrespectful content towards others.

[0355] "Means for generating warnings or suggestions" refers to functions that, based on evaluation results, provide users with warnings or suggestions for improvement.

[0356] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and process human language.

[0357] A "machine learning algorithm" refers to a method used by computers to learn from data and discover patterns and rules.

[0358] "Making data editable and recording edited data" means that users can modify message content according to the warnings and suggestions presented, and that this modification information is saved for later analysis and feature improvement.

[0359] This system begins with the user typing a message using a terminal. The terminal monitors the user's input in real time and collects data. The collected data includes the user's typing speed, touch pressure, and past messaging patterns. This information is necessary to analyze the user's emotional state. The terminal uses an emotion engine to analyze this data and determine the user's emotional state. This emotion engine utilizes widely used machine learning algorithms to make accurate emotional judgments based on the collected data.

[0360] The server receives user messages and analyzed emotional states sent from the terminal and further analyzes them using a generative AI model. The AI ​​model employs natural language processing techniques to evaluate the message's sentiment score and potential for defamation. At this stage, the user's emotional data is integrated with the message content, enabling a more refined evaluation.

[0361] The server generates warnings or suggestions based on the analysis results. These suggestions take into account the user's emotional state and may include personalized advice such as "Think a little more before sending." The generated suggestions are sent to the terminal and displayed to the user. Based on this information, the user can edit the message if necessary, and the revised message is sent back to the server. This information is recorded in a database and used to improve the system and generate personalized suggestions in the future.

[0362] For example, if a user enters a somewhat aggressive message such as "Why are you taking so long to reply?", the AI ​​model can use sentiment data to suggest a revised version such as "I apologize for bothering you, but could you tell me when you expect to reply?". An example of a prompt entered into the generative AI model is "How should we evaluate the user's emotional response to this message?". In this way, the system provides users with effective support to promote appropriate and considerate communication.

[0363] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0364] Step 1:

[0365] The user enters a message using the device. The device monitors this in real time, collecting data such as typing speed, touch pressure, and past messaging patterns. This data is then used as input for sentiment analysis.

[0366] Step 2:

[0367] The device uses the collected data to activate an emotion engine and analyze the user's emotional state. The input data is processed by a machine learning algorithm, and an output indicating the user's emotional state, such as whether they are calm or irritated.

[0368] Step 3:

[0369] The terminal sends analyzed sentiment information to the server along with the message entered by the user. This transmission includes both the collected raw data and the analysis results.

[0370] Step 4:

[0371] The server inputs the user's message and emotional state received from the terminal into an AI model, which then analyzes the message content. Utilizing natural language processing techniques, it evaluates the message's emotional score and its potential for defamation, generating the results.

[0372] Step 5:

[0373] The server generates warnings or suggestions based on the analysis results. This output information includes specific improvement suggestions and advice that take into account the user's emotional state.

[0374] Step 6:

[0375] A warning or suggestion from the server is sent to the terminal, which then displays it to the user. The user can re-edit the message based on the suggested improvements, and the re-edited message is sent back to the server from the terminal.

[0376] Step 7:

[0377] The server receives the user's edited message and records the information in the database. This feedback is used for future system improvements and to provide more personalized suggestions.

[0378] (Application Example 2)

[0379] 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."

[0380] When users receive advertisements or messages, there is a challenge in that the display is not tailored to their individual emotional state, making effective information transmission difficult. Furthermore, there is a need for adaptive systems to avoid causing discomfort or misunderstanding among recipients due to the potential for fixed content.

[0381] 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.

[0382] In this invention, the server includes means for receiving information input from a communication terminal, means for analyzing the received information to evaluate the emotional state or the possibility of defamation, and means for analyzing the emotional state using observational data and making individual adjustments. This makes it possible to display information and make personalized suggestions that are tailored to the user's emotional state and past behavior.

[0383] A "communication terminal" is an electronic device used by a user to input or receive information.

[0384] "Information analysis" is the process of identifying and evaluating the content and related emotional states based on received data.

[0385] "Emotional state" refers to the user's current emotional or psychological state, which is inferred through their behavior during data entry and interactions.

[0386] "Potential for defamation" is an assessment indicating the possibility that the received or entered information may have the intent to attack or defame others.

[0387] A "notification or suggestion" is a message that draws attention to the user or provides options based on the results of information analysis.

[0388] "Individualized adjustments" refer to the process of adjusting information to display the most optimal information based on the user's specific emotional state and past data.

[0389] The system for realizing this invention is first configured to receive information input from a communication terminal. The terminal provides a user-operated interface, such as a smartphone or smart glasses. This terminal collects user input data and response data, which are then transmitted to a server in real time.

[0390] The server analyzes the received data, utilizing natural language processing techniques to assess emotional states and the potential for defamation. This process employs generative AI models like OpenAI to gain a deep understanding of user emotions and reactions. Machine learning frameworks such as TensorFlow are used for data analysis, and the emotion engine identifies the user's current emotional tendencies.

[0391] Next, the server generates notifications or suggestions based on the analysis results, making individual adjustments to suit the user's emotional state. This adjusted information is displayed on the user's device, and if negative emotions are detected, it presents the user with calmer alternatives or options.

[0392] For example, if a user reacts with stress when viewing an advertisement, the server immediately adjusts the information and proposes an advertisement that is tailored to their emotional state. For instance, for a user interested in health, a prompt such as "Generate advertisement suggestions for new supplements for users interested in health" can be input into the AI ​​model, enabling the provision of customized information. This entire process makes the information received by the user more individualized, creating a more meaningful experience for the recipient.

[0393] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0394] Step 1:

[0395] The device captures user input in real time. This input includes text data, touch patterns, and voice input, all of which are compiled into input data. The device then prepares this data and gets ready to send it to the server.

[0396] Step 2:

[0397] The server receives input data sent from the terminal. Based on the received data, it performs text analysis using natural language processing technology to evaluate the user's emotional state and the possibility of defamation. As a result of the analysis, the user's sentiment score and the detection of negative content are performed.

[0398] Step 3:

[0399] The server generates notifications or suggestions based on the analysis results. It uses a generative AI model to create appropriate alternative messages tailored to the user's emotional state. The user enters a prompt, such as "Generate advertising suggestions for new supplements," and the server generates customized suggestions for them.

[0400] Step 4:

[0401] The server sends the generated notification or suggestion to the terminal. The terminal displays this suggestion to the user, allowing the user to readjust their input and respond emotionally. Based on the displayed information, the user can further adjust their response and input.

[0402] Step 5:

[0403] The device records the changes the user makes based on the suggestions as data and sends feedback to the server. This feedback information is stored in a database and used for future analysis and to improve the accuracy of suggestions. The user's behavioral data is then used as input for the next cycle.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] [Third Embodiment]

[0408] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0409] 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.

[0410] 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).

[0411] 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.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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".

[0420] This invention provides a technology for suppressing inappropriate messages in communication systems and promoting healthy communication. Specific embodiments of this invention will be described below.

[0421] First, the user enters a message using their device via email, chat, or social networking application. During this time, the device continuously monitors the user's input, and when it detects a message that meets certain criteria, it sends its content to a server for analysis. The server uses generative AI to analyze the received message, evaluating its sentiment and potential for defamation. This evaluation utilizes natural language processing technology to examine the tone and content of the message in detail.

[0422] If the analysis determines that the message contains inappropriate elements, the server generates a warning message. At the same time, it generates suggestions for more appropriate wording and improvements to the message content and sends them to the terminal. The terminal then displays the warning message and suggestions on its user interface, prompting the user to revise the message.

[0423] Users can revise their messages based on suggestions provided by the device. The revised message is then sent to the recipient by the device. This allows users to correct inappropriate content before sending, thus avoiding unintentional defamation or harassment.

[0424] As a concrete example, consider a scenario where a user sends a business email stating, "Your proposal is completely meaningless." Because this message could give the recipient a negative impression, the server analyzes it and generates a warning. The terminal then displays a suggestion to "Please discuss the areas for improvement constructively," which the user can use to revise it to "I have a few questions regarding your proposal" and send it.

[0425] This invention makes it possible to send messages with appropriate content and facilitate communication, thereby reducing the psychological burden on the recipient.

[0426] The following describes the processing flow.

[0427] Step 1:

[0428] The user uses the device to type text into an email, chat, or social media message input field. The device monitors the user's input in real time, detecting the number of characters and the end of the input.

[0429] Step 2:

[0430] The terminal captures the incoming message and prepares it for transmission to the server. Specifically, it converts the message data into a format for analysis and applies security protocols.

[0431] Step 3:

[0432] The terminal sends the prepared message to the server via a secure communication channel.

[0433] Step 4:

[0434] The server passes the received message data to a generative AI engine for analysis. The generative AI uses natural language processing to analyze the message, evaluate its tone and expression, and generate a sentiment score.

[0435] Step 5:

[0436] The server determines the potential for defamation in a message based on the generated sentiment score. If it assesses the risk as high, it generates a warning message and correction suggestions.

[0437] Step 6:

[0438] The server sends a warning message and suggestions back to the terminal. Upon receiving it, the terminal displays a notification in the user interface. It provides the user with hints on what the problem is and how to fix it.

[0439] Step 7:

[0440] Users can check notifications and edit messages on their devices. They can re-select words or restructure sentences based on suggestions.

[0441] Step 8:

[0442] The user completes the revisions and decides to send. The terminal sends the final message to the intended recipient. The server records the sent message in a database and uses it as data for future improvements.

[0443] (Example 1)

[0444] 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."

[0445] In digital communication, there is a problem of unintentionally sending messages that cause offense, resulting in psychological distress to recipients. Furthermore, content containing inappropriate language, including defamation, can lead to social trouble. Therefore, a mechanism is needed to allow users to review and improve their communications before sending them.

[0446] 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.

[0447] In this invention, the server includes means for monitoring information from a communication terminal and transferring it when it meets certain criteria, means for analyzing the received information and evaluating the possibility of emotion or defamation, and means for generating warnings or suggestions based on the evaluation results using a generation AI module. This allows users to receive suggestions for improving their messages, review the content of their communications before sending them, and avoid unintended problems.

[0448] A "communication terminal" is a device used by a user to input, send, and receive information, and includes smartphones and computers.

[0449] "Information" refers to messages, text, or digital content that a user inputs or receives through a communication device.

[0450] A "server" is a central computing system that receives and processes information transmitted from communication terminals, and returns the results of analysis and generation.

[0451] A "generative AI module" refers to an artificial intelligence program used to analyze received information and generate evaluations and suggestions using natural language processing technology.

[0452] "Natural language processing technology" refers to techniques that enable computers to understand, analyze, and process human language, and is used for sentiment analysis and tone analysis of text.

[0453] A "warning" is a message generated to alert a user to information that may be inappropriate or offensive.

[0454] A "suggestion" is an instruction that provides alternative expressions or methods for modifying the content of information submitted by the user.

[0455] This invention is designed as a system to facilitate the suppression of inappropriate messages in communications and to realize healthy communication. Specifically, it uses a communication terminal, a server, and a generation AI module to perform real-time monitoring and analysis of message content.

[0456] Role of a communication terminal

[0457] Users use communication devices (such as smartphones or computers) to input messages via email, chat, or social networking applications. The device monitors the message content in real time as it is being entered, detecting potentially inappropriate keywords and context. If certain criteria are met, the message is sent to the server.

[0458] Server and generation AI module processing

[0459] The server receives messages sent from terminals and analyzes them using a generative AI module. The AI ​​model used incorporates widely used natural language processing techniques (e.g., GPT-3, BERT). The server analyzes the sentiment of messages and assesses their potential for defamation, generating warnings or suggestions based on their tone and context.

[0460] User notifications and corrections

[0461] The generated warnings and suggestions are sent from the server to the communication terminal. The terminal displays them in the user interface and prompts the user to review the message content. The user can revise the message based on the displayed suggestions, and the final, confirmed message is sent to the recipient.

[0462] Examples of specific cases and prompt statements

[0463] As a concrete example, consider a scenario where a user attempts to send a business email stating, "Your proposal is completely meaningless." The server analyzes the negative tone of the message and suggests a revised version as an appropriate suggestion: "Let's constructively discuss areas for improvement."

[0464] An example of a prompt message would be: "We need suggestions to improve a negative business message. The specific situation is as follows: A user is about to send the message 'Your suggestion is completely meaningless.'"

[0465] This invention allows users to appropriately modify messages before sending them, thereby reducing the risk of unintentionally sending inappropriate communications.

[0466] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0467] Step 1:

[0468] The user enters a message using a communication terminal. The terminal has the capability to monitor the user's input in real time. It receives the input string data and detects specific keywords and negative contexts from it. This detection uses keyword matching algorithms and simple sentiment analysis methods. When a message that meets the criteria is entered, it prepares to transfer the data to the server. The output is a dataset of detected messages.

[0469] Step 2:

[0470] The terminal sends the detected message data to the server. The secure communication protocol HTTPS is used for transmission to ensure data security. The output is encrypted message data sent to the server.

[0471] Step 3:

[0472] The server receives message data sent from the terminal and analyzes it using a generative AI model. The input data is analyzed using natural language processing techniques (e.g., GPT-3 or BERT) to assess sentiment and the likelihood of defamation. Data processing involves tokenizing the text and then running it through the model for scoring. The output is the sentiment score and judgment result based on the analysis.

[0473] Step 4:

[0474] Based on the analysis results, the server generates a warning message and improvement suggestions if deemed inappropriate. The generating AI uses a model learned from past data to propose appropriate alternatives. This process involves text generation calculations to generate the suggested content. The output consists of the generated warning message and improvement suggestions.

[0475] Step 5:

[0476] The server sends the generated warning message and suggestions to the terminal. The transmitted data is again protected by a secure protocol and delivered to the terminal. The output is the transmitted data directed to the terminal.

[0477] Step 6:

[0478] The terminal displays received warnings and suggestions on the user interface. The user can review the displayed information and modify the message content. The modified data is saved again and ready to be sent. The output is the modified message data after user confirmation.

[0479] Step 7:

[0480] After the user reviews the modified message, they finally send it to the recipient. The terminal sends the reviewed message directly over the network without going through the server again. The output is the final message data that is sent.

[0481] (Application Example 1)

[0482] 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."

[0483] Sending inappropriate messages in a communication environment can lead to misunderstandings and conflicts among users, potentially degrading the service experience. However, it is not easy for users to anticipate and appropriately address this issue. In particular, there is a need for a mechanism to prevent inappropriate transmissions in real time, but current technology is insufficient to address this.

[0484] 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.

[0485] In this invention, the server includes means for receiving data input from a communication terminal, means for analyzing the received data to evaluate the possibility of emotion or defamation, and means for visually presenting the provided warnings or suggestions using an augmented reality device. This makes it possible for users to be alerted or given suggestions for improvement before sending inappropriate messages.

[0486] A "communication terminal" is an electronic device that has the function of sending and receiving information such as voice, video, and text.

[0487] "Data" refers to various types of information that are input and processed by a communication terminal.

[0488] "Analysis" is the process of understanding data and identifying specific patterns or characteristics.

[0489] "Emotion" refers to the psychological state or tone that can be inferred from the content of a message.

[0490] "Defamation" refers to expressions that are deemed to have the intent to criticize or insult others.

[0491] "Evaluation" is the process of determining the possibility of emotions or defamation based on data obtained through analysis.

[0492] A "warning" is a notification generated to alert a user to an inappropriate message.

[0493] A "suggestion" is an alternative expression presented to the user with the aim of improving the content of the message.

[0494] An "augmented reality device" is a device equipped with technology that overlays digital information onto the real environment.

[0495] The system for carrying out this invention consists of specific electronic devices. A detailed embodiment thereof is shown below.

[0496] The server receives message data sent from each user's communication terminal. This data is analyzed using natural language processing techniques. Specifically, TensorFlow and Python are used, and generative AI models are employed to analyze the sentiment of messages and evaluate the possibility of defamation. This evaluation process involves a deep analysis of the tone and content of messages, and generates warnings and suggestions for the user as needed.

[0497] The user's device, such as smart glasses or augmented reality devices, displays warnings and suggestions received from the server in real time. This display is visual and provides immediate feedback to the user, preventing the sending of inappropriate messages.

[0498] For example, if a user tries to send a message to a friend saying "completely useless opinion," the system will display a suggestion on the glasses' screen saying, "Please elaborate on your opinion." This allows the user to revise their message into a more positive expression, taking alternative suggestions into consideration.

[0499] An example of a prompt message would be, "Please suggest a way to change the tone of this message to a positive one."

[0500] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0501] Step 1:

[0502] The user enters message data into the communication terminal. This entered message is temporarily stored on the terminal and sent to the server via the communication network. In this step, the input is the message entered by the user, and the output is the data transferred to the server.

[0503] Step 2:

[0504] The server analyzes the received message data. This analysis includes using natural language processing techniques to evaluate the sentiment and potential for defamation in the message. The input is the transmitted message data, and the output is the evaluation result of the message. A generative AI model participates in this evaluation, measuring the tone of the message based on the prompt text.

[0505] Step 3:

[0506] Based on the evaluation results, the server generates warnings and improvement suggestions for messages deemed inappropriate or negative. The input is the evaluation result, and the output is the generated warning message and suggestion. For example, if a message is deemed offensive, a suggestion such as "Please add a positive comment" will be generated.

[0507] Step 4:

[0508] Warnings and suggestions are sent from the server to the user's device. The device, such as an augmented reality device, visually displays the warnings and suggestions to the user. The input is the suggestion message from the server, and the output is the display of the warnings and suggestions that the user sees. This visual presentation gives the user an opportunity to review and improve the message before sending it.

[0509] Step 5:

[0510] The user modifies the message on the device according to the provided suggestions. This inputs the newly modified message into the device, and it is finally ready to be sent. The input is the message modification performed by the user on the device, and the output is the improved message.

[0511] 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.

[0512] This invention provides a technology for managing messages that users intend to send in a communication system in a more comfortable and secure manner. This invention includes a function that combines message analysis with an emotion engine that recognizes the user's emotions.

[0513] When a user types a message on an email, chat, or social networking platform using their device, the device monitors the input in real time and prepares to send it to the server. During this process, an emotion engine analyzes the user's emotional state based on factors such as typing speed, touch pressure, and past messaging patterns. This determines the user's current emotional state, which is then further evaluated on the server.

[0514] Once a message is sent to the server, its content is analyzed using a generation AI. This analysis process evaluates the message's sentiment score and its potential for defamation. A key feature of this stage is that it incorporates the user's perceived sentiment information into the analysis, allowing for a more accurate determination of the message's appropriateness.

[0515] Based on these analysis results, the server generates warning messages and appropriate suggestions. The suggestions take into account the user's emotional state and may include personalized advice such as, "Please calm down and wait a little longer before replying." This makes it easier to prevent emotional communication errors that users may unconsciously cause.

[0516] The device displays these warnings and suggestions, prompting the user to re-edit the message. When the user modifies the message based on their emotions, this information is also fed back to the server and recorded in a database. This information is used as reference data for future improvements and more personalized suggestions.

[0517] For example, if a user enters a message like "Why are you taking so long to reply?" in an input style that suggests they were raising their voice, the server will evaluate it in conjunction with the emotion engine data and offer a revised suggestion in a calmer tone. For instance, it might suggest, "I'm sorry to bother you while you're busy, but could I ask when you expect to reply?" This promotes considerate communication towards the recipient.

[0518] This invention dramatically improves the quality of communication through messages and supports interactions that are sensitive to the user's emotions.

[0519] The following describes the processing flow.

[0520] Step 1:

[0521] The user uses the device to type messages via email, chat, or social networking apps. During this process, the device monitors the speed and frequency of message input, as well as the strength of keystrokes, in real time.

[0522] Step 2:

[0523] The device sends monitoring data to the emotion engine, which analyzes the user's emotional state. The emotion engine uses the data to infer the user's feelings and returns that information to the device.

[0524] Step 3:

[0525] The device prepares to send the captured message and user sentiment information to the server. Specifically, it converts the information into a secure format and sends it to the server.

[0526] Step 4:

[0527] The server passes the received messages and sentiment data to a generating AI, which evaluates the sentiment score of the message content and the likelihood of it being defamatory. Natural language processing techniques are used for the analysis.

[0528] Step 5:

[0529] Based on the analysis results, the server generates a warning message and appropriate message modification suggestions tailored to the user's emotional state. By taking emotional information into account, the suggestions might include phrases like, "Let's take a moment to calm down and think about this."

[0530] Step 6:

[0531] The server sends a warning message and correction suggestions to the terminal. The terminal receives this and displays it on the user interface. The user is shown the inappropriate parts along with the suggestions.

[0532] Step 7:

[0533] The user checks the display on their device and determines whether the message needs to be corrected. If corrections are needed, they can edit the message using the suggested corrections as a guide.

[0534] Step 8:

[0535] When a user edits a message and chooses to send it, the device sends the final version to the recipient. This ensures clear and unambiguous communication.

[0536] Step 9:

[0537] The server retains records of sent messages and user sentiment states, which are used to improve the system and provide more personalized services.

[0538] (Example 2)

[0539] 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."

[0540] In modern communications, users often send emotionally charged messages instantly, leading to misunderstandings and friction. There is a need to improve this situation and achieve comfortable and smooth communication. Furthermore, since overly emotional messages may contain inappropriate content, technologies are needed to prevent this from happening.

[0541] 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.

[0542] In this invention, the server includes means for collecting data input from a communication terminal, means for analyzing the user's emotional state based on the collected data, and means for evaluating the emotional score and the likelihood of defamation of a message, taking into account the emotional state obtained from the analysis. This enables the sending of appropriate messages that take into account the user's emotional state, thereby realizing comfortable and safe communication.

[0543] A "communication terminal" refers to a device that allows users to input messages and send and receive data through a communication network.

[0544] "Means of collecting data" refers to functions for collecting information entered by users through communication terminals.

[0545] "Means for analyzing the user's emotional state" refers to technologies used to identify the user's emotions and psychological state from collected data.

[0546] An "emotion score" refers to a numerical value or indicator that evaluates the degree to which a message contains emotion.

[0547] "Means of assessing the potential for defamation" refers to a function that determines whether a message contains offensive or disrespectful content towards others.

[0548] "Means for generating warnings or suggestions" refers to functions that, based on evaluation results, provide users with warnings or suggestions for improvement.

[0549] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and process human language.

[0550] A "machine learning algorithm" refers to a method used by computers to learn from data and discover patterns and rules.

[0551] "Making data editable and recording edited data" means that users can modify message content according to the warnings and suggestions presented, and that this modification information is saved for later analysis and feature improvement.

[0552] This system begins with the user typing a message using a terminal. The terminal monitors the user's input in real time and collects data. The collected data includes the user's typing speed, touch pressure, and past messaging patterns. This information is necessary to analyze the user's emotional state. The terminal uses an emotion engine to analyze this data and determine the user's emotional state. This emotion engine utilizes widely used machine learning algorithms to make accurate emotional judgments based on the collected data.

[0553] The server receives user messages and analyzed emotional states sent from the terminal and further analyzes them using a generative AI model. The AI ​​model employs natural language processing techniques to evaluate the message's sentiment score and potential for defamation. At this stage, the user's emotional data is integrated with the message content, enabling a more refined evaluation.

[0554] The server generates warnings or suggestions based on the analysis results. These suggestions take into account the user's emotional state and may include personalized advice such as "Think a little more before sending." The generated suggestions are sent to the terminal and displayed to the user. Based on this information, the user can edit the message if necessary, and the revised message is sent back to the server. This information is recorded in a database and used to improve the system and generate personalized suggestions in the future.

[0555] For example, if a user enters a somewhat aggressive message such as "Why are you taking so long to reply?", the AI ​​model can use sentiment data to suggest a revised version such as "I apologize for bothering you, but could you tell me when you expect to reply?". An example of a prompt entered into the generative AI model is "How should we evaluate the user's emotional response to this message?". In this way, the system provides users with effective support to promote appropriate and considerate communication.

[0556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0557] Step 1:

[0558] The user enters a message using the device. The device monitors this in real time, collecting data such as typing speed, touch pressure, and past messaging patterns. This data is then used as input for sentiment analysis.

[0559] Step 2:

[0560] The device uses the collected data to activate an emotion engine and analyze the user's emotional state. The input data is processed by a machine learning algorithm, and an output indicating the user's emotional state, such as whether they are calm or irritated.

[0561] Step 3:

[0562] The terminal sends analyzed sentiment information to the server along with the message entered by the user. This transmission includes both the collected raw data and the analysis results.

[0563] Step 4:

[0564] The server inputs the user's message and emotional state received from the terminal into an AI model, which then analyzes the message content. Utilizing natural language processing techniques, it evaluates the message's emotional score and its potential for defamation, generating the results.

[0565] Step 5:

[0566] The server generates warnings or suggestions based on the analysis results. This output information includes specific improvement suggestions and advice that take into account the user's emotional state.

[0567] Step 6:

[0568] A warning or suggestion from the server is sent to the terminal, which then displays it to the user. The user can re-edit the message based on the suggested improvements, and the re-edited message is sent back to the server from the terminal.

[0569] Step 7:

[0570] The server receives the user's edited message and records the information in the database. This feedback is used for future system improvements and to provide more personalized suggestions.

[0571] (Application Example 2)

[0572] 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."

[0573] When users receive advertisements or messages, there is a challenge in that the display is not tailored to their individual emotional state, making effective information transmission difficult. Furthermore, there is a need for adaptive systems to avoid causing discomfort or misunderstanding among recipients due to the potential for fixed content.

[0574] 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.

[0575] In this invention, the server includes means for receiving information input from a communication terminal, means for analyzing the received information to evaluate the emotional state or the possibility of defamation, and means for analyzing the emotional state using observational data and making individual adjustments. This makes it possible to display information and make personalized suggestions that are tailored to the user's emotional state and past behavior.

[0576] A "communication terminal" is an electronic device used by a user to input or receive information.

[0577] "Information analysis" is the process of identifying and evaluating the content and related emotional states based on received data.

[0578] "Emotional state" refers to the user's current emotional or psychological state, which is inferred through their behavior during data entry and interactions.

[0579] "Potential for defamation" is an assessment indicating the possibility that the received or entered information may have the intent to attack or defame others.

[0580] A "notification or suggestion" is a message that draws attention to the user or provides options based on the results of information analysis.

[0581] "Individualized adjustments" refer to the process of adjusting information to display the most optimal information based on the user's specific emotional state and past data.

[0582] The system for realizing this invention is first configured to receive information input from a communication terminal. The terminal provides a user-operated interface, such as a smartphone or smart glasses. This terminal collects user input data and response data, which are then transmitted to a server in real time.

[0583] The server analyzes the received data, utilizing natural language processing techniques to assess emotional states and the potential for defamation. This process employs generative AI models like OpenAI to gain a deep understanding of user emotions and reactions. Machine learning frameworks such as TensorFlow are used for data analysis, and the emotion engine identifies the user's current emotional tendencies.

[0584] Next, the server generates notifications or suggestions based on the analysis results, making individual adjustments to suit the user's emotional state. This adjusted information is displayed on the user's device, and if negative emotions are detected, it presents the user with calmer alternatives or options.

[0585] For example, if a user reacts with stress when viewing an advertisement, the server immediately adjusts the information and proposes an advertisement that is tailored to their emotional state. For instance, for a user interested in health, a prompt such as "Generate advertisement suggestions for new supplements for users interested in health" can be input into the AI ​​model, enabling the provision of customized information. This entire process makes the information received by the user more individualized, creating a more meaningful experience for the recipient.

[0586] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0587] Step 1:

[0588] The device captures user input in real time. This input includes text data, touch patterns, and voice input, all of which are compiled into input data. The device then prepares this data and gets ready to send it to the server.

[0589] Step 2:

[0590] The server receives input data sent from the terminal. Based on the received data, it performs text analysis using natural language processing technology to evaluate the user's emotional state and the possibility of defamation. As a result of the analysis, the user's sentiment score and the detection of negative content are performed.

[0591] Step 3:

[0592] The server generates notifications or suggestions based on the analysis results. It uses a generative AI model to create appropriate alternative messages tailored to the user's emotional state. The user enters a prompt, such as "Generate advertising suggestions for new supplements," and the server generates customized suggestions for them.

[0593] Step 4:

[0594] The server sends the generated notification or suggestion to the terminal. The terminal displays this suggestion to the user, allowing the user to readjust their input and respond emotionally. Based on the displayed information, the user can further adjust their response and input.

[0595] Step 5:

[0596] The device records the changes the user makes based on the suggestions as data and sends feedback to the server. This feedback information is stored in a database and used for future analysis and to improve the accuracy of suggestions. The user's behavioral data is then used as input for the next cycle.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] [Fourth Embodiment]

[0601] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0602] 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.

[0603] 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).

[0604] 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.

[0605] 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.

[0606] 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).

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] 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".

[0614] This invention provides a technology for suppressing inappropriate messages in communication systems and promoting healthy communication. Specific embodiments of this invention will be described below.

[0615] First, the user enters a message using their device via email, chat, or social networking application. During this time, the device continuously monitors the user's input, and when it detects a message that meets certain criteria, it sends its content to a server for analysis. The server uses generative AI to analyze the received message, evaluating its sentiment and potential for defamation. This evaluation utilizes natural language processing technology to examine the tone and content of the message in detail.

[0616] If the analysis determines that the message contains inappropriate elements, the server generates a warning message. At the same time, it generates suggestions for more appropriate wording and improvements to the message content and sends them to the terminal. The terminal then displays the warning message and suggestions on its user interface, prompting the user to revise the message.

[0617] Users can revise their messages based on suggestions provided by the device. The revised message is then sent to the recipient by the device. This allows users to correct inappropriate content before sending, thus avoiding unintentional defamation or harassment.

[0618] As a concrete example, consider a scenario where a user sends a business email stating, "Your proposal is completely meaningless." Because this message could give the recipient a negative impression, the server analyzes it and generates a warning. The terminal then displays a suggestion to "Please discuss the areas for improvement constructively," which the user can use to revise it to "I have a few questions regarding your proposal" and send it.

[0619] This invention makes it possible to send messages with appropriate content and facilitate communication, thereby reducing the psychological burden on the recipient.

[0620] The following describes the processing flow.

[0621] Step 1:

[0622] The user uses the device to type text into an email, chat, or social media message input field. The device monitors the user's input in real time, detecting the number of characters and the end of the input.

[0623] Step 2:

[0624] The terminal captures the incoming message and prepares it for transmission to the server. Specifically, it converts the message data into a format for analysis and applies security protocols.

[0625] Step 3:

[0626] The terminal sends the prepared message to the server via a secure communication channel.

[0627] Step 4:

[0628] The server passes the received message data to a generative AI engine for analysis. The generative AI uses natural language processing to analyze the message, evaluate its tone and expression, and generate a sentiment score.

[0629] Step 5:

[0630] The server determines the potential for defamation in a message based on the generated sentiment score. If it assesses the risk as high, it generates a warning message and correction suggestions.

[0631] Step 6:

[0632] The server sends a warning message and suggestions back to the terminal. Upon receiving it, the terminal displays a notification in the user interface. It provides the user with hints on what the problem is and how to fix it.

[0633] Step 7:

[0634] Users can check notifications and edit messages on their devices. They can re-select words or restructure sentences based on suggestions.

[0635] Step 8:

[0636] The user completes the revisions and decides to send. The terminal sends the final message to the intended recipient. The server records the sent message in a database and uses it as data for future improvements.

[0637] (Example 1)

[0638] 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".

[0639] In digital communication, there is a problem of unintentionally sending messages that cause offense, resulting in psychological distress to recipients. Furthermore, content containing inappropriate language, including defamation, can lead to social trouble. Therefore, a mechanism is needed to allow users to review and improve their communications before sending them.

[0640] 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.

[0641] In this invention, the server includes means for monitoring information from a communication terminal and transferring it when it meets certain criteria, means for analyzing the received information and evaluating the possibility of emotion or defamation, and means for generating warnings or suggestions based on the evaluation results using a generation AI module. This allows users to receive suggestions for improving their messages, review the content of their communications before sending them, and avoid unintended problems.

[0642] A "communication terminal" is a device used by a user to input, send, and receive information, and includes smartphones and computers.

[0643] "Information" refers to messages, text, or digital content that a user inputs or receives through a communication device.

[0644] A "server" is a central computing system that receives and processes information transmitted from communication terminals, and returns the results of analysis and generation.

[0645] A "generative AI module" refers to an artificial intelligence program used to analyze received information and generate evaluations and suggestions using natural language processing technology.

[0646] "Natural language processing technology" refers to techniques that enable computers to understand, analyze, and process human language, and is used for sentiment analysis and tone analysis of text.

[0647] A "warning" is a message generated to alert a user to information that may be inappropriate or offensive.

[0648] A "suggestion" is an instruction that provides alternative expressions or methods for modifying the content of information submitted by the user.

[0649] This invention is designed as a system to facilitate the suppression of inappropriate messages in communications and to realize healthy communication. Specifically, it uses a communication terminal, a server, and a generation AI module to perform real-time monitoring and analysis of message content.

[0650] Role of a communication terminal

[0651] Users use communication devices (such as smartphones or computers) to input messages via email, chat, or social networking applications. The device monitors the message content in real time as it is being entered, detecting potentially inappropriate keywords and context. If certain criteria are met, the message is sent to the server.

[0652] Server and generation AI module processing

[0653] The server receives messages sent from terminals and analyzes them using a generative AI module. The AI ​​model used incorporates widely used natural language processing techniques (e.g., GPT-3, BERT). The server analyzes the sentiment of messages and assesses their potential for defamation, generating warnings or suggestions based on their tone and context.

[0654] User notifications and corrections

[0655] The generated warnings and suggestions are sent from the server to the communication terminal. The terminal displays them in the user interface and prompts the user to review the message content. The user can revise the message based on the displayed suggestions, and the final, confirmed message is sent to the recipient.

[0656] Examples of specific cases and prompt statements

[0657] As a concrete example, consider a scenario where a user attempts to send a business email stating, "Your proposal is completely meaningless." The server analyzes the negative tone of the message and suggests a revised version as an appropriate suggestion: "Let's constructively discuss areas for improvement."

[0658] An example of a prompt message would be: "We need suggestions to improve a negative business message. The specific situation is as follows: A user is about to send the message 'Your suggestion is completely meaningless.'"

[0659] This invention allows users to appropriately modify messages before sending them, thereby reducing the risk of unintentionally sending inappropriate communications.

[0660] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0661] Step 1:

[0662] The user enters a message using a communication terminal. The terminal has the capability to monitor the user's input in real time. It receives the input string data and detects specific keywords and negative contexts from it. This detection uses keyword matching algorithms and simple sentiment analysis methods. When a message that meets the criteria is entered, it prepares to transfer the data to the server. The output is a dataset of detected messages.

[0663] Step 2:

[0664] The terminal sends the detected message data to the server. The secure communication protocol HTTPS is used for transmission to ensure data security. The output is encrypted message data sent to the server.

[0665] Step 3:

[0666] The server receives message data sent from the terminal and analyzes it using a generative AI model. The input data is analyzed using natural language processing techniques (e.g., GPT-3 or BERT) to assess sentiment and the likelihood of defamation. Data processing involves tokenizing the text and then running it through the model for scoring. The output is the sentiment score and judgment result based on the analysis.

[0667] Step 4:

[0668] Based on the analysis results, the server generates a warning message and improvement suggestions if deemed inappropriate. The generating AI uses a model learned from past data to propose appropriate alternatives. This process involves text generation calculations to generate the suggested content. The output consists of the generated warning message and improvement suggestions.

[0669] Step 5:

[0670] The server sends the generated warning message and suggestions to the terminal. The transmitted data is again protected by a secure protocol and delivered to the terminal. The output is the transmitted data directed to the terminal.

[0671] Step 6:

[0672] The terminal displays received warnings and suggestions on the user interface. The user can review the displayed information and modify the message content. The modified data is saved again and ready to be sent. The output is the modified message data after user confirmation.

[0673] Step 7:

[0674] After the user reviews the modified message, they finally send it to the recipient. The terminal sends the reviewed message directly over the network without going through the server again. The output is the final message data that is sent.

[0675] (Application Example 1)

[0676] 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".

[0677] Sending inappropriate messages in a communication environment can lead to misunderstandings and conflicts among users, potentially degrading the service experience. However, it is not easy for users to anticipate and appropriately address this issue. In particular, there is a need for a mechanism to prevent inappropriate transmissions in real time, but current technology is insufficient to address this.

[0678] 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.

[0679] In this invention, the server includes means for receiving data input from a communication terminal, means for analyzing the received data to evaluate the possibility of emotion or defamation, and means for visually presenting the provided warnings or suggestions using an augmented reality device. This makes it possible for users to be alerted or given suggestions for improvement before sending inappropriate messages.

[0680] A "communication terminal" is an electronic device that has the function of sending and receiving information such as voice, video, and text.

[0681] "Data" refers to various types of information that are input and processed by a communication terminal.

[0682] "Analysis" is the process of understanding data and identifying specific patterns or characteristics.

[0683] "Emotion" refers to the psychological state or tone that can be inferred from the content of a message.

[0684] "Defamation" refers to expressions that are deemed to have the intent to criticize or insult others.

[0685] "Evaluation" is the process of determining the possibility of emotions or defamation based on data obtained through analysis.

[0686] A "warning" is a notification generated to alert a user to an inappropriate message.

[0687] A "suggestion" is an alternative expression presented to the user with the aim of improving the content of the message.

[0688] An "augmented reality device" is a device equipped with technology that overlays digital information onto the real environment.

[0689] The system for carrying out this invention consists of specific electronic devices. A detailed embodiment thereof is shown below.

[0690] The server receives message data sent from each user's communication terminal. This data is analyzed using natural language processing techniques. Specifically, TensorFlow and Python are used, and generative AI models are employed to analyze the sentiment of messages and evaluate the possibility of defamation. This evaluation process involves a deep analysis of the tone and content of messages, and generates warnings and suggestions for the user as needed.

[0691] The user's device, such as smart glasses or augmented reality devices, displays warnings and suggestions received from the server in real time. This display is visual and provides immediate feedback to the user, preventing the sending of inappropriate messages.

[0692] For example, if a user tries to send a message to a friend saying "completely useless opinion," the system will display a suggestion on the glasses' screen saying, "Please elaborate on your opinion." This allows the user to revise their message into a more positive expression, taking alternative suggestions into consideration.

[0693] An example of a prompt message would be, "Please suggest a way to change the tone of this message to a positive one."

[0694] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0695] Step 1:

[0696] The user enters message data into the communication terminal. This entered message is temporarily stored on the terminal and sent to the server via the communication network. In this step, the input is the message entered by the user, and the output is the data transferred to the server.

[0697] Step 2:

[0698] The server analyzes the received message data. This analysis includes using natural language processing techniques to evaluate the sentiment and potential for defamation in the message. The input is the transmitted message data, and the output is the evaluation result of the message. A generative AI model participates in this evaluation, measuring the tone of the message based on the prompt text.

[0699] Step 3:

[0700] Based on the evaluation results, the server generates warnings and improvement suggestions for messages deemed inappropriate or negative. The input is the evaluation result, and the output is the generated warning message and suggestion. For example, if a message is deemed offensive, a suggestion such as "Please add a positive comment" will be generated.

[0701] Step 4:

[0702] Warnings and suggestions are sent from the server to the user's device. The device, such as an augmented reality device, visually displays the warnings and suggestions to the user. The input is the suggestion message from the server, and the output is the display of the warnings and suggestions that the user sees. This visual presentation gives the user an opportunity to review and improve the message before sending it.

[0703] Step 5:

[0704] The user modifies the message on the device according to the provided suggestions. This inputs the newly modified message into the device, and it is finally ready to be sent. The input is the message modification performed by the user on the device, and the output is the improved message.

[0705] 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.

[0706] This invention provides a technology for managing messages that users intend to send in a communication system in a more comfortable and secure manner. This invention includes a function that combines message analysis with an emotion engine that recognizes the user's emotions.

[0707] When a user types a message on an email, chat, or social networking platform using their device, the device monitors the input in real time and prepares to send it to the server. During this process, an emotion engine analyzes the user's emotional state based on factors such as typing speed, touch pressure, and past messaging patterns. This determines the user's current emotional state, which is then further evaluated on the server.

[0708] Once a message is sent to the server, its content is analyzed using a generation AI. This analysis process evaluates the message's sentiment score and its potential for defamation. A key feature of this stage is that it incorporates the user's perceived sentiment information into the analysis, allowing for a more accurate determination of the message's appropriateness.

[0709] Based on these analysis results, the server generates warning messages and appropriate suggestions. The suggestions take into account the user's emotional state and may include personalized advice such as, "Please calm down and wait a little longer before replying." This makes it easier to prevent emotional communication errors that users may unconsciously cause.

[0710] The device displays these warnings and suggestions, prompting the user to re-edit the message. When the user modifies the message based on their emotions, this information is also fed back to the server and recorded in a database. This information is used as reference data for future improvements and more personalized suggestions.

[0711] For example, if a user enters a message like "Why are you taking so long to reply?" in an input style that suggests they were raising their voice, the server will evaluate it in conjunction with the emotion engine data and offer a revised suggestion in a calmer tone. For instance, it might suggest, "I'm sorry to bother you while you're busy, but could I ask when you expect to reply?" This promotes considerate communication towards the recipient.

[0712] This invention dramatically improves the quality of communication through messages and supports interactions that are sensitive to the user's emotions.

[0713] The following describes the processing flow.

[0714] Step 1:

[0715] The user uses the device to type messages via email, chat, or social networking apps. During this process, the device monitors the speed and frequency of message input, as well as the strength of keystrokes, in real time.

[0716] Step 2:

[0717] The device sends monitoring data to the emotion engine, which analyzes the user's emotional state. The emotion engine uses the data to infer the user's feelings and returns that information to the device.

[0718] Step 3:

[0719] The device prepares to send the captured message and user sentiment information to the server. Specifically, it converts the information into a secure format and sends it to the server.

[0720] Step 4:

[0721] The server passes the received messages and sentiment data to a generating AI, which evaluates the sentiment score of the message content and the likelihood of it being defamatory. Natural language processing techniques are used for the analysis.

[0722] Step 5:

[0723] Based on the analysis results, the server generates a warning message and appropriate message modification suggestions tailored to the user's emotional state. By taking emotional information into account, the suggestions might include phrases like, "Let's take a moment to calm down and think about this."

[0724] Step 6:

[0725] The server sends a warning message and correction suggestions to the terminal. The terminal receives this and displays it on the user interface. The user is shown the inappropriate parts along with the suggestions.

[0726] Step 7:

[0727] The user checks the display on their device and determines whether the message needs to be corrected. If corrections are needed, they can edit the message using the suggested corrections as a guide.

[0728] Step 8:

[0729] When a user edits a message and chooses to send it, the device sends the final version to the recipient. This ensures clear and unambiguous communication.

[0730] Step 9:

[0731] The server retains records of sent messages and user sentiment states, which are used to improve the system and provide more personalized services.

[0732] (Example 2)

[0733] 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".

[0734] In modern communications, users often send emotionally charged messages instantly, leading to misunderstandings and friction. There is a need to improve this situation and achieve comfortable and smooth communication. Furthermore, since overly emotional messages may contain inappropriate content, technologies are needed to prevent this from happening.

[0735] 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.

[0736] In this invention, the server includes means for collecting data input from a communication terminal, means for analyzing the user's emotional state based on the collected data, and means for evaluating the emotional score and the likelihood of defamation of a message, taking into account the emotional state obtained from the analysis. This enables the sending of appropriate messages that take into account the user's emotional state, thereby realizing comfortable and safe communication.

[0737] A "communication terminal" refers to a device that allows users to input messages and send and receive data through a communication network.

[0738] "Means of collecting data" refers to functions for collecting information entered by users through communication terminals.

[0739] "Means for analyzing the user's emotional state" refers to technologies used to identify the user's emotions and psychological state from collected data.

[0740] An "emotion score" refers to a numerical value or indicator that evaluates the degree to which a message contains emotion.

[0741] "Means of assessing the potential for defamation" refers to a function that determines whether a message contains offensive or disrespectful content towards others.

[0742] "Means for generating warnings or suggestions" refers to functions that, based on evaluation results, provide users with warnings or suggestions for improvement.

[0743] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and process human language.

[0744] A "machine learning algorithm" refers to a method used by computers to learn from data and discover patterns and rules.

[0745] "Making data editable and recording edited data" means that users can modify message content according to the warnings and suggestions presented, and that this modification information is saved for later analysis and feature improvement.

[0746] This system begins with the user typing a message using a terminal. The terminal monitors the user's input in real time and collects data. The collected data includes the user's typing speed, touch pressure, and past messaging patterns. This information is necessary to analyze the user's emotional state. The terminal uses an emotion engine to analyze this data and determine the user's emotional state. This emotion engine utilizes widely used machine learning algorithms to make accurate emotional judgments based on the collected data.

[0747] The server receives user messages and analyzed emotional states sent from the terminal and further analyzes them using a generative AI model. The AI ​​model employs natural language processing techniques to evaluate the message's sentiment score and potential for defamation. At this stage, the user's emotional data is integrated with the message content, enabling a more refined evaluation.

[0748] The server generates warnings or suggestions based on the analysis results. These suggestions take into account the user's emotional state and may include personalized advice such as "Think a little more before sending." The generated suggestions are sent to the terminal and displayed to the user. Based on this information, the user can edit the message if necessary, and the revised message is sent back to the server. This information is recorded in a database and used to improve the system and generate personalized suggestions in the future.

[0749] For example, if a user enters a somewhat aggressive message such as "Why are you taking so long to reply?", the AI ​​model can use sentiment data to suggest a revised version such as "I apologize for bothering you, but could you tell me when you expect to reply?". An example of a prompt entered into the generative AI model is "How should we evaluate the user's emotional response to this message?". In this way, the system provides users with effective support to promote appropriate and considerate communication.

[0750] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0751] Step 1:

[0752] The user enters a message using the device. The device monitors this in real time, collecting data such as typing speed, touch pressure, and past messaging patterns. This data is then used as input for sentiment analysis.

[0753] Step 2:

[0754] The device uses the collected data to activate an emotion engine and analyze the user's emotional state. The input data is processed by a machine learning algorithm, and an output indicating the user's emotional state, such as whether they are calm or irritated.

[0755] Step 3:

[0756] The terminal sends analyzed sentiment information to the server along with the message entered by the user. This transmission includes both the collected raw data and the analysis results.

[0757] Step 4:

[0758] The server inputs the user's message and emotional state received from the terminal into an AI model, which then analyzes the message content. Utilizing natural language processing techniques, it evaluates the message's emotional score and its potential for defamation, generating the results.

[0759] Step 5:

[0760] The server generates warnings or suggestions based on the analysis results. This output information includes specific improvement suggestions and advice that take into account the user's emotional state.

[0761] Step 6:

[0762] A warning or suggestion from the server is sent to the terminal, which then displays it to the user. The user can re-edit the message based on the suggested improvements, and the re-edited message is sent back to the server from the terminal.

[0763] Step 7:

[0764] The server receives the user's edited message and records the information in the database. This feedback is used for future system improvements and to provide more personalized suggestions.

[0765] (Application Example 2)

[0766] 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".

[0767] When users receive advertisements or messages, there is a challenge in that the display is not tailored to their individual emotional state, making effective information transmission difficult. Furthermore, there is a need for adaptive systems to avoid causing discomfort or misunderstanding among recipients due to the potential for fixed content.

[0768] 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.

[0769] In this invention, the server includes means for receiving information input from a communication terminal, means for analyzing the received information to evaluate the emotional state or the possibility of defamation, and means for analyzing the emotional state using observational data and making individual adjustments. This makes it possible to display information and make personalized suggestions that are tailored to the user's emotional state and past behavior.

[0770] A "communication terminal" is an electronic device used by a user to input or receive information.

[0771] "Information analysis" is the process of identifying and evaluating the content and related emotional states based on received data.

[0772] "Emotional state" refers to the user's current emotional or psychological state, which is inferred through their behavior during data entry and interactions.

[0773] "Potential for defamation" is an assessment indicating the possibility that the received or entered information may have the intent to attack or defame others.

[0774] A "notification or suggestion" is a message that draws attention to the user or provides options based on the results of information analysis.

[0775] "Individualized adjustments" refer to the process of adjusting information to display the most optimal information based on the user's specific emotional state and past data.

[0776] The system for realizing this invention is first configured to receive information input from a communication terminal. The terminal provides a user-operated interface, such as a smartphone or smart glasses. This terminal collects user input data and response data, which are then transmitted to a server in real time.

[0777] The server analyzes the received data, utilizing natural language processing techniques to assess emotional states and the potential for defamation. This process employs generative AI models like OpenAI to gain a deep understanding of user emotions and reactions. Machine learning frameworks such as TensorFlow are used for data analysis, and the emotion engine identifies the user's current emotional tendencies.

[0778] Next, the server generates notifications or suggestions based on the analysis results, making individual adjustments to suit the user's emotional state. This adjusted information is displayed on the user's device, and if negative emotions are detected, it presents the user with calmer alternatives or options.

[0779] For example, if a user reacts with stress when viewing an advertisement, the server immediately adjusts the information and proposes an advertisement that is tailored to their emotional state. For instance, for a user interested in health, a prompt such as "Generate advertisement suggestions for new supplements for users interested in health" can be input into the AI ​​model, enabling the provision of customized information. This entire process makes the information received by the user more individualized, creating a more meaningful experience for the recipient.

[0780] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0781] Step 1:

[0782] The device captures user input in real time. This input includes text data, touch patterns, and voice input, all of which are compiled into input data. The device then prepares this data and gets ready to send it to the server.

[0783] Step 2:

[0784] The server receives input data sent from the terminal. Based on the received data, it performs text analysis using natural language processing technology to evaluate the user's emotional state and the possibility of defamation. As a result of the analysis, the user's sentiment score and the detection of negative content are performed.

[0785] Step 3:

[0786] The server generates notifications or suggestions based on the analysis results. It uses a generative AI model to create appropriate alternative messages tailored to the user's emotional state. The user enters a prompt, such as "Generate advertising suggestions for new supplements," and the server generates customized suggestions for them.

[0787] Step 4:

[0788] The server sends the generated notification or suggestion to the terminal. The terminal displays this suggestion to the user, allowing the user to readjust their input and respond emotionally. Based on the displayed information, the user can further adjust their response and input.

[0789] Step 5:

[0790] The device records the changes the user makes based on the suggestions as data and sends feedback to the server. This feedback information is stored in a database and used for future analysis and to improve the accuracy of suggestions. The user's behavioral data is then used as input for the next cycle.

[0791] 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.

[0792] 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.

[0793] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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."

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0812] The following is further disclosed regarding the embodiments described above.

[0813] (Claim 1)

[0814] A means for receiving messages input from a communication device,

[0815] A means of analyzing received messages to assess the possibility of emotional or defamatory content,

[0816] Means for generating warnings or suggestions based on evaluation results,

[0817] Means for transmitting and displaying the aforementioned warning or suggestion to a communication device,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, which uses natural language processing technology when evaluating the possibility of emotion or defamation.

[0821] (Claim 3)

[0822] The system according to claim 1, characterized in that the user can edit the message based on the aforementioned warning or suggestion.

[0823] "Example 1"

[0824] (Claim 1)

[0825] A means of monitoring information input from a communication terminal and transferring that information if it meets certain criteria,

[0826] A means of analyzing the transmitted information to assess the potential for emotions and defamation,

[0827] A means for generating warnings or suggestions based on evaluation results and transferring them to a communication terminal,

[0828] A means of refining evaluation and proposals using a generative AI module,

[0829] A system that includes this.

[0830] (Claim 2)

[0831] The system according to claim 1, which uses natural language processing technology to analyze the tone and content of information.

[0832] (Claim 3)

[0833] The system according to claim 1, characterized in that the user can revise the content before sending the information based on a warning or suggestion.

[0834] "Application Example 1"

[0835] (Claim 1)

[0836] A means of receiving data input from a communication terminal,

[0837] A means of analyzing received data to assess the possibility of emotional or defamatory content,

[0838] Means for generating warnings or suggestions based on evaluation results,

[0839] A means for sending and displaying the aforementioned warning or suggestion to an external terminal,

[0840] A means of visually presenting the provided warning or suggestion using an augmented reality device,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, which uses natural language processing technology when evaluating the possibility of emotion or defamation.

[0844] (Claim 3)

[0845] The system according to claim 1, characterized in that an individual can input corrected data based on the aforementioned warning or suggestion.

[0846] "Example 2 of combining an emotion engine"

[0847] (Claim 1)

[0848] A means of collecting data input from a communication terminal,

[0849] A means of analyzing the user's emotional state based on the collected data,

[0850] A means for evaluating the emotional score of a message and the possibility of defamation, taking into account the emotional state obtained from the above analysis,

[0851] Means for generating warnings or suggestions based on evaluation results,

[0852] A means for transmitting and displaying the generated warning or suggestion to a communication terminal,

[0853] A system that includes this.

[0854] (Claim 2)

[0855] The system according to claim 1, which uses natural language processing technology and machine learning algorithms to evaluate the potential for emotion and defamation.

[0856] (Claim 3)

[0857] The system according to claim 1, wherein the user can edit data based on the generated warnings or suggestions, and the edited data is recorded.

[0858] "Application example 2 when combining with an emotional engine"

[0859] (Claim 1)

[0860] A means of receiving information input from a communication terminal,

[0861] A means of analyzing received information to assess emotional state or the possibility of defamation,

[0862] Means for generating notifications or suggestions based on evaluation results,

[0863] Means for transmitting and displaying the aforementioned notification or proposal to a receiving device,

[0864] A means of analyzing emotional states using observational data and making individual adjustments,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, which uses natural language processing technology to evaluate emotional states or the possibility of defamation, and analyzes reactions when information is displayed.

[0868] (Claim 3)

[0869] The system according to claim 1, characterized in that users can readjust their information based on the aforementioned notification or suggestion, and personalized suggestions are made. [Explanation of Symbols]

[0870] 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 messages input from a communication device, A means of analyzing received messages to assess the possibility of emotional or defamatory content, Means for generating warnings or suggestions based on evaluation results, Means for transmitting and displaying the aforementioned warning or suggestion to a communication device, A system that includes this.

2. The system according to claim 1, which uses natural language processing technology when evaluating the possibility of emotion or defamation.

3. The system according to claim 1, characterized in that the user can edit the message based on the aforementioned warning or suggestion.

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