system

Abstract

We provide the system. [Solution] A means for analyzing received electronic messages on a computer terminal and evaluating the emotional tone of their content, Based on the analysis results, a means of displaying a positive message to the user, A means to monitor messages entered by users before sending them, determine if the content is offensive, and display a warning, A means of summarizing the content of received messages, generating a task list, and presenting it to the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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 the current business environment, business people often feel mental stress daily through chats and emails. Especially when receiving high-pressure or aggressive messages, the psychological burden increases, and productivity may decrease. Also, unconsciously sending aggressive messages may have an adverse impact on workplace human relationships. There is a need for a support system that can solve these problems and enable users to efficiently perform their work while maintaining a healthy mental state.

Means for Solving the Problems

[0005] This invention provides a computer terminal system that analyzes received electronic messages and evaluates the emotional tone of their content. Based on the analysis results, the system displays positive messages to the user, monitors user-entered messages before sending them to determine if the content is aggressive, and displays warnings as needed. Furthermore, it summarizes the content of received messages, automatically generates a task list with emotions omitted, and presents it to the user, thereby reducing mental stress and supporting increased work efficiency.

[0006] A "computer terminal" is a device that a user can operate and that has the functions of information processing and communication.

[0007] An "electronic message" is a means of communication that includes data in the form of information such as documents and images, which are sent and received via a computer terminal.

[0008] "Analysis" is the process of analyzing received data or documents using language models and other tools to reveal their content and characteristics.

[0009] "Emotional tone" refers to elements that indicate the type and intensity of emotions contained in a message, and has a psychological impact on the recipient.

[0010] A "positive message" is a form of information dissemination intended to promote the user's emotional well-being and provide encouragement and a sense of security.

[0011] "Monitoring" refers to the activity of observing user behavior and data in real time to proactively detect inappropriate content or behavior.

[0012] "Being aggressive" refers to a state of exhibiting expressions or actions that have a negative or hostile effect on the other party.

[0013] A "warning" is a cautionary message that points out to users that certain actions or expressions may be problematic, and encourages them to make more appropriate choices.

[0014] "Summarization" is the act of concisely summarizing the core of information and creating a shortened expression without losing the original meaning.

[0015] A "task list" is a tool that organizes and lists the tasks and activities that a user needs to perform, and supports efficient task management. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

[0019] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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), etc.

[0020] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the labeled 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, etc.

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] The present invention is implemented as a resident application installed on a user's computer terminal. This system includes a program for analyzing electronic messages received by the user and evaluating their emotional tone. The terminal utilizes natural language processing technology to analyze the content of the message and automatically identifies positive or negative emotions. If the analysis determines that the message is aggressive or condescending, the terminal automatically displays a positive message to the user to provide emotional support.

[0038] Furthermore, the device monitors user-entered messages in real time and analyzes their content before sending them. If an entered message is deemed offensive, the device displays a warning to the user, encouraging more appropriate communication. This process gives users time and opportunity to review and revise their messages.

[0039] Furthermore, the device summarizes received messages and generates an emotionless task list. This task list helps users manage their work efficiently. The generated list is displayed in a dedicated window on the desktop, allowing users to review and organize their tasks at any time.

[0040] For example, if a user receives a work-related chat message that is aggressive and pressure-inducing, the device will quickly display an encouraging message such as, "You are handling this well." Similarly, when a user is composing an email, if emotional language is detected, a warning such as, "We recommend softening this expression," will be displayed. This allows users to achieve better communication and stress management.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The device monitors the user's inbox and detects the arrival of new electronic messages. This prepares all messages the user receives for analysis.

[0044] Step 2:

[0045] The content of messages received by the device is analyzed using natural language processing techniques. The focus of the analysis is to evaluate the emotional tone based on keywords and sentence structure within the message.

[0046] Step 3:

[0047] The device determines, based on the analysis results, whether the message contains an aggressive or condescending tone. If so, feedback is provided to the user in the next step.

[0048] Step 4:

[0049] The device displays a pop-up message of encouragement to the user, providing psychological support to mitigate the negative impact of the received message.

[0050] Step 5:

[0051] The device monitors the user's message input in real time and evaluates the message content as it is being prepared to send. Natural language processing technology is again used to determine if it contains offensive content.

[0052] Step 6:

[0053] The device will display a warning message to the user for messages it deems offensive, as needed. This warning encourages the user to revise the message to a more appropriate form.

[0054] Step 7:

[0055] The device summarizes received messages and generates an emotionless task list. The summarization process shortens the main points of the message and organizes them into tasks.

[0056] Step 8:

[0057] The terminal displays the generated task list on the desktop, helping users manage their work efficiently. By referring to this list, users can plan their actions without losing sight of important tasks.

[0058] (Example 1)

[0059] 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."

[0060] In modern communication, electronic messaging is commonplace, but it can sometimes contain aggressive or condescending content, causing stress to users. Furthermore, users themselves may unconsciously send aggressive messages, hindering effective communication. In addition, there is a lack of efficient means to process received information and improve productivity. To address these issues, a system is needed that assesses emotional characteristics and provides users with appropriate feedback and support.

[0061] 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.

[0062] In this invention, the server includes means for analyzing received information on a computing device and evaluating the emotional characteristics of its content; means for presenting positive notifications to the user based on the analysis results; and means for monitoring information created by the user before transmission, determining whether the content is offensive, and providing advice. This reduces the stress experienced by the user through electronic messages and enables appropriate communication by allowing users to review the content before transmission. Furthermore, efficient management of received messages improves user productivity.

[0063] A "computer" is an electronic device designed for information processing, possessing the functions of collecting, analyzing, and processing data.

[0064] "Information" refers to content exchanged between users as electronic messages or data, and includes formats such as text, images, and audio.

[0065] "Emotional characteristics" refer to the psychological tone and nuances conveyed by a message or information, and include expressions of emotions such as positive, negative, and aggressive.

[0066] "Analysis" is a procedure used to examine and evaluate received information in detail in order to understand its content and structure.

[0067] "Positive notifications" are messages displayed to provide users with a sense of security and positive feedback, and their role is to reduce the user's mental burden.

[0068] "Monitoring" refers to the act of checking the trends of information in real time or in batch processing and taking necessary actions according to defined conditions.

[0069] "Advice" refers to guiding messages provided with the aim of encouraging users to improve the content of the information they post.

[0070] A "message" is a unit of information transmitted from a sender to a recipient, and is the basic form of communication, including email, chat, and text messages.

[0071] "Productivity" is an indicator that shows the output and efficiency generated within a certain time, and is an important element that supports the effective execution of work.

[0072] This invention is implemented as a resident application running on a computer. The system, installed on a computer terminal, analyzes information received by the user and evaluates its emotional characteristics. The system utilizes natural language processing techniques via a server to determine whether the information is positive or negative. By using software libraries such as Python's NLTK and TextBlob, it is possible to analyze the content of the information in detail.

[0073] If the terminal determines that the received information is aggressive or offensive, the server will quickly display a positive and reassuring message to the user, providing positive feedback. This approach can reduce the stress that receiving information causes the user.

[0074] Furthermore, the device monitors the information sent by the user in real time before transmission and evaluates its content using natural language processing. If the information is deemed offensive, the server provides the user with guidance, such as "We recommend softening this expression." This process allows users to review the content of their information before sending it, enabling appropriate communication.

[0075] Furthermore, the system summarizes incoming information, generates a task list free of emotional biases, and presents it to the user in a dedicated window on their terminal. This allows users to improve productivity while efficiently managing their tasks.

[0076] For example, if a user receives a work-related chat message and it is perceived as being aggressive, the server will display a positive message such as, "You are handling this well." Furthermore, if emotional language is detected while the user is composing an email, it will advise, "We recommend softening this expression." Throughout this entire system, better communication and stress management are achieved.

[0077] Example of a prompt:

[0078] "If a user receives an aggressive email from work after a long meeting, how can a positive message be displayed, and how can the program help the user?"

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The terminal monitors the information received by the user in real time. Received electronic messages are stored in a parsing buffer. The input is text data. This data undergoes preprocessing for natural language processing, including text cleaning and tokenization. The output is text data in a parsable format.

[0082] Step 2:

[0083] The server receives text data in a parseable format and analyzes its emotional characteristics using natural language processing techniques. Specifically, it uses a generative AI model to process the data and evaluate emotional attributes such as positive, negative, domineering, and aggressive. The input is cleaned text data, and the output is an emotional evaluation score. This score measures the tone of the information.

[0084] Step 3:

[0085] The server makes a decision to send a positive message to the user if the sentiment rating score is aggressive or condescending. The sentiment rating score is considered as input, and the output is a positive notification such as "You are coping well." This notification is immediately displayed on the terminal's user interface.

[0086] Step 4:

[0087] The terminal monitors and analyzes the information created by the user in real time. The input is the text the user is typing, and preprocessing and natural language processing are applied. If the server determines that the sentiment evaluation is negative, it generates advice such as, "We recommend softening this expression." The output is a real-time feedback message presented to the user.

[0088] Step 5:

[0089] The terminal extracts task-related elements from the received information and generates a task list. The input is the full text of the information received by the user. From this data, the terminal automatically summarizes the important task information and outputs a list that eliminates emotional elements. The generated task list is displayed in a dedicated window on the terminal, allowing the user to review it and organize their tasks.

[0090] (Application Example 1)

[0091] 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."

[0092] In today's business environment, communication via electronic messaging is crucial, but it often leads to emotional friction, negatively impacting work efficiency and workplace relationships. In particular, a high frequency of aggressive messages can increase the recipient's mental burden, leading to stress and decreased productivity. Furthermore, important business matters may be overlooked amidst emotional exchanges. Methods to address these challenges are needed.

[0093] 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.

[0094] In this invention, the server includes means for analyzing received electronic data on a computer terminal and evaluating the emotional tone of its content, means for displaying positive messages to users based on the analysis results, and means for analyzing the emotional tone in internal communications within a company and providing prompt emotional support based on aggressive content. This makes it possible to improve work efficiency and create a healthier workplace environment by managing the emotional aspects of electronic messages.

[0095] A "computer terminal" is a computing device used to process received electronic data, and it is a device that executes software to perform natural language processing.

[0096] "Electronic data" refers to textual information, messages, chats, and other communication content expressed in digital format.

[0097] "Emotional tone" refers to the emotional nuances and atmosphere that can be perceived from the content of a text, and is a characteristic that can be classified as positive, negative, neutral, etc.

[0098] A "natural language processing model" refers to the algorithms and libraries used by computers to understand and analyze human language.

[0099] A "positive message" refers to a message that gives the recipient positive feelings or a sense of security.

[0100] "Offensive content" refers to the characteristics of a message that includes words or expressions that may intimidate or offend the recipient.

[0101] "Mental support" refers to assistance or advice provided to support the mental health of the recipient.

[0102] This invention is a system implemented by a program running on a computer terminal. This system uses natural language processing technology to analyze the emotional tone of electronic data, providing positive feedback to users while promoting healthy internal communication.

[0103] The server collects received electronic data and evaluates its emotional tone using a natural language processing model. Specifically, it uses technologies such as Google® NLP and IBM Watson® for natural language processing to automatically identify positive, negative, or neutral emotions. In this process, it identifies not only emotional data but also whether the content is offensive.

[0104] Based on the analysis results, the device provides the user with appropriate positive messages or emotional support. For example, for aggressive messages that the recipient might find offensive, the device will display a message such as, "Try to relax and respond accordingly."

[0105] When a user enters a new message, the device monitors its content in real time before sending and provides warnings as needed. By offering feedback such as, "It would be more constructive to improve this expression," it helps prevent communication problems.

[0106] For example, when a sales representative receives a customer complaint, the device may quickly analyze the email and display a message of reassurance such as, "Don't worry, we're doing our best." The aim is to facilitate smooth internal and external communication in this way.

[0107] Example of a prompt: "Analyze the emotional tone of this message and generate a positive response."

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The server receives electronic data from the terminal. The input is message data sent and received by the user, and the output is that data passed on to the next analysis step. The server stores it in a database and converts it into a format that can be read by the natural language processing model.

[0111] Step 2:

[0112] The server analyzes the emotional tone of received electronic data using a natural language processing model. The input is text data formatted in step 1, and the output is the evaluation result of the emotional tone. The server utilizes models such as Google NLP and IBM Watson to identify emotions as positive, negative, or neutral.

[0113] Step 3:

[0114] The device receives the analysis results and presents a message to the user based on them. The input is the evaluation result of the emotional tone obtained in step 2, and the output is the feedback message displayed to the user. If the content is positive, the device will display something like, "You're doing great."

[0115] Step 4:

[0116] When a user enters a new message, the device monitors the input in real time. The input is the message the user is creating, and the output is an evaluation of whether the message is offensive. The device uses a generative AI model to display a warning such as "This wording should be revised" if the tone of the message is offensive.

[0117] Step 5:

[0118] The terminal summarizes received messages and provides the user with an emotionless task list. Input is the electronic data from Step 1, and output is the summarized task list. The terminal uses keyword extraction and summarization algorithms to generate a concise list of key points. Accordingly, the user receives support to efficiently manage their tasks.

[0119] 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.

[0120] This invention is a resident application that runs on a computer terminal, combined with an emotion engine that recognizes user emotions. This system has the function of analyzing electronic messages received by the user and evaluating their emotional tone, and can further grasp the user's emotional state using user reactions and input data.

[0121] The device uses natural language processing technology to analyze incoming messages, and when it detects an aggressive or condescending tone, its emotion engine considers the user's current emotional state and displays the most appropriate positive message. This process provides personalized psychological support to each individual user.

[0122] Furthermore, the device monitors the user's typing speed and the frequency of message changes, and an emotion engine estimates their stress level. This data is reflected in the content of warnings and encouraging messages sent before messages are sent. For example, if a slower-than-usual typing speed is detected, the device may determine that the user is experiencing hesitation or anxiety and present a message such as, "Take a break and check again."

[0123] The emotion engine analyzes past user interaction data to provide personalized support. This allows the device to recognize regular user emotional patterns and predict future emotional responses.

[0124] For example, if a user receives harsh feedback during a stressful team project, the device uses its emotion engine to estimate the user's stress level and notify them with a message such as, "You're doing a great job, and this moment is important." It also provides alternative messages to the suggested message, giving the user time to calmly consider their next course of action.

[0125] Thus, the present invention is a multi-functional system that utilizes emotion recognition technology to help users have a better communication experience in the workplace.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The device monitors the user's inbox and detects the arrival of new electronic messages, which triggers message analysis.

[0129] Step 2:

[0130] The device uses natural language processing technology to analyze the content of incoming messages and evaluate their emotional tone. The analysis includes keywords and context of the message.

[0131] Step 3:

[0132] After the device evaluates the tone of an incoming message, if it determines it to be aggressive or condescending, the sentiment engine retrieves the user's reaction data and estimates the user's current emotional state.

[0133] Step 4:

[0134] Based on the emotional state estimated by the emotion engine, the device creates the most appropriate positive message and displays a pop-up notification to the user. This reduces the negative impact the user may experience.

[0135] Step 5:

[0136] When a user initiates an action on their desktop, the device monitors the user's typing speed and keystroke frequency, collecting data in real time.

[0137] Step 6:

[0138] The device analyzes the collected data using an emotion engine to estimate stress and anxiety levels. This information is particularly important when unusual input patterns are detected.

[0139] Step 7:

[0140] As the user types a message, the device monitors the content in real time and, if it detects an aggressive tone, uses its emotion engine to display a warning message. The warning also takes stress levels into consideration and responds flexibly.

[0141] Step 8:

[0142] By analyzing past user interaction data, the emotion engine updates its future prediction model, making feedback and positive messages to users more personalized. This process allows the device to deeply understand and respond to user characteristics.

[0143] (Example 2)

[0144] 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".

[0145] In our information-driven society, users receive a large volume of electronic messages, and sometimes their content can cause psychological stress. In particular, aggressive or condescending communication can negatively impact users' mental health. In such situations, there is a need to provide timely, emotionally supportive messages and offer users means to reduce stress.

[0146] 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.

[0147] In this invention, the server includes means for analyzing received information on an information processing device and evaluating the emotional characteristics of its content; means for displaying emotionally supportive sentences to the user based on the analysis results; and means for estimating the user's stress level based on past user behavior data and generating appropriate support sentences. As a result, the user can receive appropriate support according to the message they receive, thereby reducing their psychological burden and enabling them to have a better communication experience.

[0148] An "information processing device" is a combination of hardware and software for collecting, analyzing, and processing data, and is a device for providing information through interaction with the user.

[0149] "Received information" refers to text messages and data obtained from other users or systems, and is the information that is subject to analysis and evaluation.

[0150] "Emotional characteristics" refer to the emotional nature contained in a message or information, and are a concept that describes emotional states such as positive, negative, or neutral.

[0151] "Emotionally supportive messages" are text messages intended to alleviate a user's psychological distress by offering encouragement and comfort.

[0152] "Analysis results" refer to data on emotional characteristics and other evaluations obtained after an information processing device analyzes received information.

[0153] "Behavioral data" refers to information that includes a user's past actions and input history, and serves as the basis for determining a user's stress level.

[0154] "Estimating stress levels" is a process of evaluating how stressed a user is experiencing based on their behavioral data and message content.

[0155] This invention is implemented as a resident software application on an information processing device. It primarily has the function of analyzing electronic messages received by the user in real time and evaluating their emotional characteristics.

[0156] The terminal uses a natural language processing library implemented in Python or a similar programming language (e.g., NLTK or SpaCy) to analyze the received information. This analysis classifies the emotional characteristics of the message as "positive," "negative," or "neutral."

[0157] Based on the analysis results, the server uses a generative AI model to generate and display emotionally supportive messages tailored to the user. This model incorporates a pre-trained sentiment analysis model, presenting the most appropriate message considering the user's stress level. Furthermore, it provides individually customized support by referencing the user's past behavioral data.

[0158] For example, if a user receives an email at work that has an aggressive tone, the device will immediately analyze it and provide positive feedback such as, "Take a moment to think about it and check it again," thereby reducing the user's psychological burden.

[0159] As an example of a prompt, we use the following: "Analyze the emotional tone of the received message and display the most appropriate positive message." Based on this prompt, the generative AI model guides the generation of an appropriate support message.

[0160] Thus, this invention can improve the user experience by analyzing the emotional tone of messages received by the user and providing customized feedback to reduce stress.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The device acquires electronic messages received by the user in real time. The input is text data such as emails and chat messages. This data is formatted in text format for the next analysis step.

[0164] Step 2:

[0165] The terminal analyzes the acquired text data using a natural language processing library. Specifically, it uses the Python library NLTK to analyze the grammatical structure of the text and extract emotional characteristics. The generated output is information classifying each message as either "positive," "negative," or "neutral."

[0166] Step 3:

[0167] The server applies a generative AI model based on the analysis results to generate emotionally supportive messages for the user. The input is data on emotional characteristics, and the output is a supportive message optimized for the user. Here, the generative AI model references the user's past stress patterns to create a customized message.

[0168] Step 4:

[0169] The device notifies the user of the generated support message. This notification appears as a pop-up on the desktop or as a message in the chat window. Specifically, it presents the user with psychological support, which the user then uses to decide on their next course of action.

[0170] (Application Example 2)

[0171] 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".

[0172] A challenge is minimizing the impact of emotional influences on smooth communication when users receive communication information or create input data. In particular, in physical stores, where direct interactions between customers and staff are frequent, it is difficult to quickly detect and appropriately address customer dissatisfaction and stress, thus improving the customer experience is essential.

[0173] 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.

[0174] In this invention, the server includes means for presenting the user's emotional response in real time using a wearable display device and prompting an appropriate response, means for analyzing communication information and evaluating the emotional tone of its content, and means for monitoring data entered by the user before transmission, determining if it is offensive, and displaying a warning. This allows for real-time understanding of the customer's emotional state and prompting an appropriate response, thereby improving communication within the store and enabling smooth customer service.

[0175] A "computer device" is a computing system that processes user input and external information to support decision-making.

[0176] "Communication information" refers to messages and data that are sent and received through electronic means.

[0177] "Analysis" is the process of breaking down information to understand its structure and meaning, and then extracting the necessary information.

[0178] "Emotional tone" refers to the attitude and atmosphere of a message or communication, and is a characteristic related to emotional nuances.

[0179] A "user" refers to an individual or organization that uses a system or device.

[0180] "Positive information" refers to messages that aim to improve the recipient's emotions and mood.

[0181] "Offensive content" refers to information that may have a negative or hostile effect on the recipient.

[0182] "Advice" refers to suggestions or recommendations given with the aim of pointing out or encouraging improvement in actions or opinions.

[0183] A "wearable display device" is an electronic device that is worn by the user to display information and allow them to check real-time information while in operation.

[0184] The system that realizes this invention mainly consists of an emotion analysis engine, a natural language processing device, a wearable display device, and a user interface.

[0185] The server receives communication information sent from users and customers and analyzes that data. Specific analysis uses natural language processing technologies such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding. These technologies evaluate the emotional tone of the communication information and identify aggressive or condescending content.

[0186] The analysis results are displayed in real time via a wearable display device. This device, for example, is a pair of smart glasses, allowing users to quickly check information while serving customers. For instance, store staff can use the wearable display device to identify when a customer is expressing dissatisfaction and be immediately presented with appropriate solutions. This real-time information sharing enables staff to respond to customers quickly and appropriately.

[0187] The user interface is the part that users interact with directly, displaying information on the wearable display device while simultaneously accepting input and feedback. If aggressive input is detected, the system displays a warning message to the user, prompting them to reconfirm the content.

[0188] For example, if a customer says, "This product is a complete disappointment," when reporting a problem with a product, a message such as "We recommend apologizing and proposing a solution" will immediately appear on the store employee's wearable display device.

[0189] An example of an input prompt for a generative AI model might be, "Analyze the conversation with the customer, determine the emotional tone, and suggest a positive response message." Based on this prompt, the AI ​​model generates an appropriate response.

[0190] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0191] Step 1:

[0192] The server receives communication information sent from users and customers. The input is communication information such as emails and text messages, and the output is unanalyzed data in its original state.

[0193] Step 2:

[0194] The server sends the received unanalyzed data to a natural language processing unit, which then analyzes the data using natural language processing techniques. This analysis uses Google Cloud Natural Language API or IBM Watson Natural Language Understanding. The input is the unanalyzed data obtained in step 1, and the output is the analyzed data with an evaluation of emotional tone.

[0195] Step 3:

[0196] The terminal identifies aggressive or condescending content based on the analysis data obtained in Step 2. Specifically, it compares the natural language processing evaluation results with evaluation criteria and assigns appropriate sentiment tags. The input is the analysis data from Step 2, and the output is the data with sentiment tags assigned.

[0197] Step 4:

[0198] The device transmits emotion-tagged data to a wearable display device and displays a message prompting the user to take an appropriate action in real time. Specifically, it selects and displays a message. The input is the emotion-tagged data from step 3, and the output is the response message displayed on the display device.

[0199] Step 5:

[0200] The terminal monitors the data entered by the user and uses natural language processing technology to determine whether it is offensive before sending it. Specifically, it performs the same analysis process as in Step 1 to obtain the result. The input is the user's input data, and the output is a warning message based on the evaluation result.

[0201] Step 6:

[0202] Based on the findings in Step 5, the device will, if necessary, present a warning message to the user and prompt them to reconfirm the information. Specifically, this involves selecting and displaying a message containing the warning. The input is the evaluation result from Step 5, and the output is the warning message the user receives.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] [Second Embodiment]

[0207] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0208] 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.

[0209] 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).

[0210] 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.

[0211] 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.

[0212] 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).

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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".

[0219] The present invention is implemented as a resident application installed on a user's computer terminal. This system includes a program for analyzing electronic messages received by the user and evaluating their emotional tone. The terminal utilizes natural language processing technology to analyze the content of the message and automatically identifies positive or negative emotions. If the analysis determines that the message is aggressive or condescending, the terminal automatically displays a positive message to the user to provide emotional support.

[0220] Furthermore, the device monitors user-entered messages in real time and analyzes their content before sending them. If an entered message is deemed offensive, the device displays a warning to the user, encouraging more appropriate communication. This process gives users time and opportunity to review and revise their messages.

[0221] Furthermore, the device summarizes received messages and generates an emotionless task list. This task list helps users manage their work efficiently. The generated list is displayed in a dedicated window on the desktop, allowing users to review and organize their tasks at any time.

[0222] For example, if a user receives a work-related chat message that is aggressive and pressure-inducing, the device will quickly display an encouraging message such as, "You are handling this well." Similarly, when a user is composing an email, if emotional language is detected, a warning such as, "We recommend softening this expression," will be displayed. This allows users to achieve better communication and stress management.

[0223] The following describes the processing flow.

[0224] Step 1:

[0225] The device monitors the user's inbox and detects the arrival of new electronic messages. This prepares all messages the user receives for analysis.

[0226] Step 2:

[0227] The content of messages received by the device is analyzed using natural language processing techniques. The focus of the analysis is to evaluate the emotional tone based on keywords and sentence structure within the message.

[0228] Step 3:

[0229] The device determines, based on the analysis results, whether the message contains an aggressive or condescending tone. If so, feedback is provided to the user in the next step.

[0230] Step 4:

[0231] The device displays a pop-up message of encouragement to the user, providing psychological support to mitigate the negative impact of the received message.

[0232] Step 5:

[0233] The device monitors the user's message input in real time and evaluates the message content as it is being prepared to send. Natural language processing technology is again used to determine if it contains offensive content.

[0234] Step 6:

[0235] The device will display a warning message to the user for messages it deems offensive, as needed. This warning encourages the user to revise the message to a more appropriate form.

[0236] Step 7:

[0237] The device summarizes received messages and generates an emotionless task list. The summarization process shortens the main points of the message and organizes them into tasks.

[0238] Step 8:

[0239] The terminal displays the generated task list on the desktop, helping users manage their work efficiently. By referring to this list, users can plan their actions without losing sight of important tasks.

[0240] (Example 1)

[0241] 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."

[0242] In modern communication, electronic messaging is commonplace, but it can sometimes contain aggressive or condescending content, causing stress to users. Furthermore, users themselves may unconsciously send aggressive messages, hindering effective communication. In addition, there is a lack of efficient means to process received information and improve productivity. To address these issues, a system is needed that assesses emotional characteristics and provides users with appropriate feedback and support.

[0243] 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.

[0244] In this invention, the server includes means for analyzing received information on a computing device and evaluating the emotional characteristics of its content; means for presenting positive notifications to the user based on the analysis results; and means for monitoring information created by the user before transmission, determining whether the content is offensive, and providing advice. This reduces the stress experienced by the user through electronic messages and enables appropriate communication by allowing users to review the content before transmission. Furthermore, efficient management of received messages improves user productivity.

[0245] A "computer" is an electronic device designed for information processing, possessing the functions of collecting, analyzing, and processing data.

[0246] "Information" refers to content exchanged between users as electronic messages or data, and includes formats such as text, images, and audio.

[0247] "Emotional characteristics" refer to the psychological tone and nuances conveyed by a message or information, and include expressions of emotions such as positive, negative, and aggressive.

[0248] "Analysis" is a procedure used to examine and evaluate received information in detail in order to understand its content and structure.

[0249] "Positive notifications" are messages displayed to provide users with a sense of security and positive feedback, and their role is to reduce the user's mental burden.

[0250] "Monitoring" refers to the act of checking the trends of information in real time or in batch processing and taking necessary actions according to defined conditions.

[0251] "Advice" refers to guiding messages provided with the aim of encouraging users to improve the content of the information they post.

[0252] A "message" is a unit of information transmitted from a sender to a recipient, and is the basic form of communication, including email, chat, and text messages.

[0253] "Productivity" is an indicator that shows the output and efficiency generated within a certain time, and is an important element that supports the effective execution of work.

[0254] This invention is implemented as a resident application running on a computer. The system, installed on a computer terminal, analyzes information received by the user and evaluates its emotional characteristics. The system utilizes natural language processing techniques via a server to determine whether the information is positive or negative. By using software libraries such as Python's NLTK and TextBlob, it is possible to analyze the content of the information in detail.

[0255] If the terminal determines that the received information is aggressive or offensive, the server will quickly display a positive and reassuring message to the user, providing positive feedback. This approach can reduce the stress that receiving information causes the user.

[0256] Furthermore, the device monitors the information sent by the user in real time before transmission and evaluates its content using natural language processing. If the information is deemed offensive, the server provides the user with guidance, such as "We recommend softening this expression." This process allows users to review the content of their information before sending it, enabling appropriate communication.

[0257] Furthermore, the system summarizes incoming information, generates a task list free of emotional biases, and presents it to the user in a dedicated window on their terminal. This allows users to improve productivity while efficiently managing their tasks.

[0258] For example, if a user receives a work-related chat message and it is perceived as being aggressive, the server will display a positive message such as, "You are handling this well." Furthermore, if emotional language is detected while the user is composing an email, it will advise, "We recommend softening this expression." Throughout this entire system, better communication and stress management are achieved.

[0259] Example of a prompt:

[0260] "If a user receives an aggressive email from work after a long meeting, how can a positive message be displayed, and how can the program help the user?"

[0261] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0262] Step 1:

[0263] The terminal monitors the information received by the user in real time. Received electronic messages are stored in a parsing buffer. The input is text data. This data undergoes preprocessing for natural language processing, including text cleaning and tokenization. The output is text data in a parsable format.

[0264] Step 2:

[0265] The server receives text data in a parseable format and analyzes its emotional characteristics using natural language processing techniques. Specifically, it uses a generative AI model to process the data and evaluate emotional attributes such as positive, negative, domineering, and aggressive. The input is cleaned text data, and the output is an emotional evaluation score. This score measures the tone of the information.

[0266] Step 3:

[0267] The server makes a decision to send a positive message to the user if the sentiment rating score is aggressive or condescending. The sentiment rating score is considered as input, and the output is a positive notification such as "You are coping well." This notification is immediately displayed on the terminal's user interface.

[0268] Step 4:

[0269] The terminal monitors and analyzes the information created by the user in real time. The input is the text the user is typing, and preprocessing and natural language processing are applied. If the server determines that the sentiment evaluation is negative, it generates advice such as, "We recommend softening this expression." The output is a real-time feedback message presented to the user.

[0270] Step 5:

[0271] The terminal extracts task-related elements from the received information and generates a task list. The input is the full text of the information received by the user. From this data, the terminal automatically summarizes the important task information and outputs a list that eliminates emotional elements. The generated task list is displayed in a dedicated window on the terminal, allowing the user to review it and organize their tasks.

[0272] (Application Example 1)

[0273] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0274] In today's business environment, communication via electronic messaging is crucial, but it often leads to emotional friction, negatively impacting work efficiency and workplace relationships. In particular, a high frequency of aggressive messages can increase the recipient's mental burden, leading to stress and decreased productivity. Furthermore, important business matters may be overlooked amidst emotional exchanges. Methods to address these challenges are needed.

[0275] 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.

[0276] In this invention, the server includes means for analyzing received electronic data on a computer terminal and evaluating the emotional tone of its content, means for displaying positive messages to users based on the analysis results, and means for analyzing the emotional tone in internal communications within a company and providing prompt emotional support based on aggressive content. This makes it possible to improve work efficiency and create a healthier workplace environment by managing the emotional aspects of electronic messages.

[0277] A "computer terminal" is a computing device for processing received electronic data and is a device that executes software to perform natural language processing.

[0278] "Electronic data" refers to character information expressed in digital form and communication content such as messages and chats.

[0279] "Emotional tone" is the emotional nuance or atmosphere that can be felt from the content of the text and is a characteristic classified as positive, negative, neutral, etc.

[0280] A "natural language processing model" refers to algorithms and libraries used for a computer to understand and analyze human language.

[0281] A "positive message" means a message whose content gives the recipient a positive feeling or a sense of security.

[0282] "Aggressive content" refers to the characteristics of a message that includes words or expressions that may intimidate or give discomfort to the recipient.

[0283] "Mental support" means support or advice provided to support the mental health of the recipient.

[0284] This invention is a system realized by a program operating on a computer terminal. This system uses natural language processing technology to analyze the emotional tone of electronic data, provide positive feedback to the user, and aim to improve the soundness of internal communication.

[0285] The server collects the received electronic data and evaluates its emotional tone using a natural language processing model. Specifically, by using technologies such as Google NLP and IBM Watson for natural language processing, positive, negative, or neutral emotions are automatically identified. At this time, not only emotional data but also whether aggressive content is included is specified.

[0286] Based on the analysis results, the terminal provides appropriate positive messages or mental support to the user. For example, for an aggressive message that the recipient may complain about, a message such as "Let's respond relaxedly" will be displayed on the terminal.

[0287] When the user inputs a new message, the terminal monitors the content in real time before sending and presents advice if necessary. By providing feedback such as "It would be more constructive to improve this expression", it provides support to prevent troubles in communication.

[0288] As an example, when a salesperson receives a claim from a customer, the terminal may quickly analyze the email and display mental support such as "Rest assured, we are doing our best". In this way, it aims to make the internal and external exchanges run smoothly.

[0289] Specific example of a prompt sentence: "Analyze the emotional tone of this message and generate a positive response."

[0290] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0291] Step 1:

[0292] The server receives the electronic data received from the terminal. The input is the message data sent and received by the user, and as output, the data is passed to the next analysis step. The server stores it in the database and converts it into a format that can be read by the natural language processing model.

[0293] Step 2:

[0294] The server analyzes the emotional tone of received electronic data using a natural language processing model. The input is text data formatted in step 1, and the output is the evaluation result of the emotional tone. The server utilizes models such as Google NLP and IBM Watson to identify emotions as positive, negative, or neutral.

[0295] Step 3:

[0296] The device receives the analysis results and presents a message to the user based on them. The input is the evaluation result of the emotional tone obtained in step 2, and the output is the feedback message displayed to the user. If the content is positive, the device will display something like, "You're doing great."

[0297] Step 4:

[0298] When a user enters a new message, the device monitors the input in real time. The input is the message the user is creating, and the output is an evaluation of whether the message is offensive. The device uses a generative AI model to display a warning such as "This wording should be revised" if the tone of the message is offensive.

[0299] Step 5:

[0300] The terminal summarizes received messages and provides the user with an emotionless task list. Input is the electronic data from Step 1, and output is the summarized task list. The terminal uses keyword extraction and summarization algorithms to generate a concise list of key points. Accordingly, the user receives support to efficiently manage their tasks.

[0301] 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.

[0302] This invention is a resident application that runs on a computer terminal, combined with an emotion engine that recognizes user emotions. This system has the function of analyzing electronic messages received by the user and evaluating their emotional tone, and can further grasp the user's emotional state using user reactions and input data.

[0303] The device uses natural language processing technology to analyze incoming messages, and when it detects an aggressive or condescending tone, its emotion engine considers the user's current emotional state and displays the most appropriate positive message. This process provides personalized psychological support to each individual user.

[0304] Furthermore, the device monitors the user's typing speed and the frequency of message changes, and an emotion engine estimates their stress level. This data is reflected in the content of warnings and encouraging messages sent before messages are sent. For example, if a slower-than-usual typing speed is detected, the device may determine that the user is experiencing hesitation or anxiety and present a message such as, "Take a break and check again."

[0305] The emotion engine analyzes past user interaction data to provide personalized support. This allows the device to recognize regular user emotional patterns and predict future emotional responses.

[0306] For example, if a user receives harsh feedback during a stressful team project, the device uses its emotion engine to estimate the user's stress level and notify them with a message such as, "You're doing a great job, and this moment is important." It also provides alternative messages to the suggested message, giving the user time to calmly consider their next course of action.

[0307] Thus, the present invention is a multifunctional system that utilizes emotion recognition technology to assist users in obtaining a better communication experience in the workplace.

[0308] The following describes the processing flow.

[0309] Step 1:

[0310] The terminal monitors the user's reception tray and detects the arrival of a new electronic message. This serves as a trigger for message analysis.

[0311] Step 2:

[0312] The terminal uses natural language processing technology to analyze the content of the received message and evaluate its emotional tone. The analysis targets include the keywords and context of the message.

[0313] Step 3:

[0314] After the terminal evaluates the tone of the received message, if it is determined to be high-pressure or aggressive, the emotion engine obtains the user's reaction data and estimates the user's current emotional state.

[0315] Step 4:

[0316] Based on the emotional state estimated by the emotion engine, the terminal creates an optimal positive message and displays a pop-up notification to the user. This reduces the negative impact on the user.

[0317] Step 5:

[0318] When the user starts an action on the desktop, the terminal monitors the user's input speed and key input frequency and collects data in real time.

[0319] Step 6:

[0320] The device analyzes the collected data using an emotion engine to estimate stress and anxiety levels. This information is particularly important when unusual input patterns are detected.

[0321] Step 7:

[0322] As the user types a message, the device monitors the content in real time and, if it detects an aggressive tone, uses its emotion engine to display a warning message. The warning also takes stress levels into consideration and responds flexibly.

[0323] Step 8:

[0324] By analyzing past user interaction data, the emotion engine updates its future prediction model, making feedback and positive messages to users more personalized. This process allows the device to deeply understand and respond to user characteristics.

[0325] (Example 2)

[0326] 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".

[0327] In our information-driven society, users receive a large volume of electronic messages, and sometimes their content can cause psychological stress. In particular, aggressive or condescending communication can negatively impact users' mental health. In such situations, there is a need to provide timely, emotionally supportive messages and offer users means to reduce stress.

[0328] 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.

[0329] In this invention, the server includes means for analyzing received information on an information processing device and evaluating the emotional characteristics of its content; means for displaying emotionally supportive sentences to the user based on the analysis results; and means for estimating the user's stress level based on past user behavior data and generating appropriate support sentences. As a result, the user can receive appropriate support according to the message they receive, thereby reducing their psychological burden and enabling them to have a better communication experience.

[0330] An "information processing device" is a combination of hardware and software for collecting, analyzing, and processing data, and is a device for providing information through interaction with the user.

[0331] "Received information" refers to text messages and data obtained from other users or systems, and is the information that is subject to analysis and evaluation.

[0332] "Emotional characteristics" refer to the emotional nature contained in a message or information, and are a concept that describes emotional states such as positive, negative, or neutral.

[0333] "Emotionally supportive messages" are text messages intended to alleviate a user's psychological distress by offering encouragement and comfort.

[0334] "Analysis results" refer to data on emotional characteristics and other evaluations obtained after an information processing device analyzes received information.

[0335] "Behavioral data" refers to information that includes a user's past actions and input history, and serves as the basis for determining a user's stress level.

[0336] "Estimating stress levels" is a process of evaluating how stressed a user is experiencing based on their behavioral data and message content.

[0337] This invention is implemented as a resident software application on an information processing device. It primarily has the function of analyzing electronic messages received by the user in real time and evaluating their emotional characteristics.

[0338] The terminal uses a natural language processing library implemented in Python or a similar programming language (e.g., NLTK or SpaCy) to analyze the received information. This analysis classifies the emotional characteristics of the message as "positive," "negative," or "neutral."

[0339] Based on the analysis results, the server uses a generative AI model to generate and display emotionally supportive messages tailored to the user. This model incorporates a pre-trained sentiment analysis model, presenting the most appropriate message considering the user's stress level. Furthermore, it provides individually customized support by referencing the user's past behavioral data.

[0340] For example, if a user receives an email at work that has an aggressive tone, the device will immediately analyze it and provide positive feedback such as, "Take a moment to think about it and check it again," thereby reducing the user's psychological burden.

[0341] As an example of a prompt, we use the following: "Analyze the emotional tone of the received message and display the most appropriate positive message." Based on this prompt, the generative AI model guides the generation of an appropriate support message.

[0342] Thus, this invention can improve the user experience by analyzing the emotional tone of messages received by the user and providing customized feedback to reduce stress.

[0343] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0344] Step 1:

[0345] The device acquires electronic messages received by the user in real time. The input is text data such as emails and chat messages. This data is formatted in text format for the next analysis step.

[0346] Step 2:

[0347] The terminal analyzes the acquired text data using a natural language processing library. Specifically, it uses the Python library NLTK to analyze the grammatical structure of the text and extract emotional characteristics. The generated output is information classifying each message as either "positive," "negative," or "neutral."

[0348] Step 3:

[0349] The server applies a generative AI model based on the analysis results to generate emotionally supportive messages for the user. The input is data on emotional characteristics, and the output is a supportive message optimized for the user. Here, the generative AI model references the user's past stress patterns to create a customized message.

[0350] Step 4:

[0351] The device notifies the user of the generated support message. This notification appears as a pop-up on the desktop or as a message in the chat window. Specifically, it presents the user with psychological support, which the user then uses to decide on their next course of action.

[0352] (Application Example 2)

[0353] 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."

[0354] A challenge is minimizing the impact of emotional influences on smooth communication when users receive communication information or create input data. In particular, in physical stores, where direct interactions between customers and staff are frequent, it is difficult to quickly detect and appropriately address customer dissatisfaction and stress, thus improving the customer experience is essential.

[0355] 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.

[0356] In this invention, the server includes means for presenting the user's emotional response in real time using a wearable display device and prompting an appropriate response, means for analyzing communication information and evaluating the emotional tone of its content, and means for monitoring data entered by the user before transmission, determining if it is offensive, and displaying a warning. This allows for real-time understanding of the customer's emotional state and prompting an appropriate response, thereby improving communication within the store and enabling smooth customer service.

[0357] A "computer device" is a computing system that processes user input and external information to support decision-making.

[0358] "Communication information" refers to messages and data that are sent and received through electronic means.

[0359] "Analysis" is the process of breaking down information to understand its structure and meaning, and then extracting the necessary information.

[0360] "Emotional tone" refers to the attitude and atmosphere of a message or communication, and is a characteristic related to emotional nuances.

[0361] A "user" refers to an individual or organization that uses a system or device.

[0362] "Positive information" refers to messages that aim to improve the recipient's emotions and mood.

[0363] "Offensive content" refers to information that may have a negative or hostile effect on the recipient.

[0364] "Advice" refers to suggestions or recommendations given with the aim of pointing out or encouraging improvement in actions or opinions.

[0365] A "wearable display device" is an electronic device that is worn by the user to display information and allow them to check real-time information while in operation.

[0366] The system that realizes this invention mainly consists of an emotion analysis engine, a natural language processing device, a wearable display device, and a user interface.

[0367] The server receives communication information sent from users and customers and analyzes that data. Specific analysis uses natural language processing technologies such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding. These technologies evaluate the emotional tone of the communication information and identify aggressive or condescending content.

[0368] The analysis results are displayed in real time via a wearable display device. This device, for example, is a pair of smart glasses, allowing users to quickly check information while serving customers. For instance, store staff can use the wearable display device to identify when a customer is expressing dissatisfaction and be immediately presented with appropriate solutions. This real-time information sharing enables staff to respond to customers quickly and appropriately.

[0369] The user interface is the part that users interact with directly, displaying information on the wearable display device while simultaneously accepting input and feedback. If aggressive input is detected, the system displays a warning message to the user, prompting them to reconfirm the content.

[0370] For example, if a customer says, "This product is a complete disappointment," when reporting a problem with a product, a message such as "We recommend apologizing and proposing a solution" will immediately appear on the store employee's wearable display device.

[0371] An example of an input prompt for a generative AI model might be, "Analyze the conversation with the customer, determine the emotional tone, and suggest a positive response message." Based on this prompt, the AI ​​model generates an appropriate response.

[0372] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0373] Step 1:

[0374] The server receives communication information sent from users and customers. The input is communication information such as emails and text messages, and the output is unanalyzed data in its original state.

[0375] Step 2:

[0376] The server sends the received unanalyzed data to a natural language processing unit, which then analyzes the data using natural language processing techniques. This analysis uses Google Cloud Natural Language API or IBM Watson Natural Language Understanding. The input is the unanalyzed data obtained in step 1, and the output is the analyzed data with an evaluation of emotional tone.

[0377] Step 3:

[0378] The terminal identifies aggressive or condescending content based on the analysis data obtained in Step 2. Specifically, it compares the natural language processing evaluation results with evaluation criteria and assigns appropriate sentiment tags. The input is the analysis data from Step 2, and the output is the data with sentiment tags assigned.

[0379] Step 4:

[0380] The device transmits emotion-tagged data to a wearable display device and displays a message prompting the user to take an appropriate action in real time. Specifically, it selects and displays a message. The input is the emotion-tagged data from step 3, and the output is the response message displayed on the display device.

[0381] Step 5:

[0382] The terminal monitors the data entered by the user and uses natural language processing technology to determine whether it is offensive before sending it. Specifically, it performs the same analysis process as in Step 1 to obtain the result. The input is the user's input data, and the output is a warning message based on the evaluation result.

[0383] Step 6:

[0384] Based on the findings in Step 5, the device will, if necessary, present a warning message to the user and prompt them to reconfirm the information. Specifically, this involves selecting and displaying a message containing the warning. The input is the evaluation result from Step 5, and the output is the warning message the user receives.

[0385] 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.

[0386] 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.

[0387] 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.

[0388] [Third Embodiment]

[0389] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0390] 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.

[0391] 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).

[0392] 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.

[0393] 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.

[0394] 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).

[0395] 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.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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".

[0401] The present invention is implemented as a resident application installed on a user's computer terminal. This system includes a program for analyzing electronic messages received by the user and evaluating their emotional tone. The terminal utilizes natural language processing technology to analyze the content of the message and automatically identifies positive or negative emotions. If the analysis determines that the message is aggressive or condescending, the terminal automatically displays a positive message to the user to provide emotional support.

[0402] Furthermore, the device monitors user-entered messages in real time and analyzes their content before sending them. If an entered message is deemed offensive, the device displays a warning to the user, encouraging more appropriate communication. This process gives users time and opportunity to review and revise their messages.

[0403] Furthermore, the device summarizes received messages and generates an emotionless task list. This task list helps users manage their work efficiently. The generated list is displayed in a dedicated window on the desktop, allowing users to review and organize their tasks at any time.

[0404] For example, if a user receives a work-related chat message that is aggressive and pressure-inducing, the device will quickly display an encouraging message such as, "You are handling this well." Similarly, when a user is composing an email, if emotional language is detected, a warning such as, "We recommend softening this expression," will be displayed. This allows users to achieve better communication and stress management.

[0405] The following describes the processing flow.

[0406] Step 1:

[0407] The device monitors the user's inbox and detects the arrival of new electronic messages. This prepares all messages the user receives for analysis.

[0408] Step 2:

[0409] The content of messages received by the device is analyzed using natural language processing techniques. The focus of the analysis is to evaluate the emotional tone based on keywords and sentence structure within the message.

[0410] Step 3:

[0411] The device determines, based on the analysis results, whether the message contains an aggressive or condescending tone. If so, feedback is provided to the user in the next step.

[0412] Step 4:

[0413] The device displays a pop-up message of encouragement to the user, providing psychological support to mitigate the negative impact of the received message.

[0414] Step 5:

[0415] The device monitors the user's message input in real time and evaluates the message content as it is being prepared to send. Natural language processing technology is again used to determine if it contains offensive content.

[0416] Step 6:

[0417] The device will display a warning message to the user for messages it deems offensive, as needed. This warning encourages the user to revise the message to a more appropriate form.

[0418] Step 7:

[0419] The device summarizes received messages and generates an emotionless task list. The summarization process shortens the main points of the message and organizes them into tasks.

[0420] Step 8:

[0421] The terminal displays the generated task list on the desktop, helping users manage their work efficiently. By referring to this list, users can plan their actions without losing sight of important tasks.

[0422] (Example 1)

[0423] 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."

[0424] In modern communication, electronic messaging is commonplace, but it can sometimes contain aggressive or condescending content, causing stress to users. Furthermore, users themselves may unconsciously send aggressive messages, hindering effective communication. In addition, there is a lack of efficient means to process received information and improve productivity. To address these issues, a system is needed that assesses emotional characteristics and provides users with appropriate feedback and support.

[0425] 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.

[0426] In this invention, the server includes means for analyzing received information on a computing device and evaluating the emotional characteristics of its content; means for presenting positive notifications to the user based on the analysis results; and means for monitoring information created by the user before transmission, determining whether the content is offensive, and providing advice. This reduces the stress experienced by the user through electronic messages and enables appropriate communication by allowing users to review the content before transmission. Furthermore, efficient management of received messages improves user productivity.

[0427] A "computer" is an electronic device designed for information processing, possessing the functions of collecting, analyzing, and processing data.

[0428] "Information" refers to content exchanged between users as electronic messages or data, and includes formats such as text, images, and audio.

[0429] "Emotional characteristics" refer to the psychological tone and nuances conveyed by a message or information, and include expressions of emotions such as positive, negative, and aggressive.

[0430] "Analysis" is a procedure used to examine and evaluate received information in detail in order to understand its content and structure.

[0431] "Positive notifications" are messages displayed to provide users with a sense of security and positive feedback, and their role is to reduce the user's mental burden.

[0432] "Monitoring" refers to the act of checking the trends of information in real time or in batch processing and taking necessary actions according to defined conditions.

[0433] "Advice" refers to guiding messages provided with the aim of encouraging users to improve the content of the information they post.

[0434] A "message" is a unit of information transmitted from a sender to a recipient, and is the basic form of communication, including email, chat, and text messages.

[0435] "Productivity" is an indicator that shows the output and efficiency generated within a certain time, and is an important element that supports the effective execution of work.

[0436] This invention is implemented as a resident application running on a computer. The system, installed on a computer terminal, analyzes information received by the user and evaluates its emotional characteristics. The system utilizes natural language processing techniques via a server to determine whether the information is positive or negative. By using software libraries such as Python's NLTK and TextBlob, it is possible to analyze the content of the information in detail.

[0437] If the terminal determines that the received information is aggressive or offensive, the server will quickly display a positive and reassuring message to the user, providing positive feedback. This approach can reduce the stress that receiving information causes the user.

[0438] Furthermore, the device monitors the information sent by the user in real time before transmission and evaluates its content using natural language processing. If the information is deemed offensive, the server provides the user with guidance, such as "We recommend softening this expression." This process allows users to review the content of their information before sending it, enabling appropriate communication.

[0439] Furthermore, the system summarizes incoming information, generates a task list free of emotional biases, and presents it to the user in a dedicated window on their terminal. This allows users to improve productivity while efficiently managing their tasks.

[0440] For example, if a user receives a work-related chat message and it is perceived as being aggressive, the server will display a positive message such as, "You are handling this well." Furthermore, if emotional language is detected while the user is composing an email, it will advise, "We recommend softening this expression." Throughout this entire system, better communication and stress management are achieved.

[0441] Example of a prompt:

[0442] "If a user receives an aggressive email from work after a long meeting, how can a positive message be displayed, and how can the program help the user?"

[0443] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0444] Step 1:

[0445] The terminal monitors the information received by the user in real time. Received electronic messages are stored in a parsing buffer. The input is text data. This data undergoes preprocessing for natural language processing, including text cleaning and tokenization. The output is text data in a parsable format.

[0446] Step 2:

[0447] The server receives text data in a parseable format and analyzes its emotional characteristics using natural language processing techniques. Specifically, it uses a generative AI model to process the data and evaluate emotional attributes such as positive, negative, domineering, and aggressive. The input is cleaned text data, and the output is an emotional evaluation score. This score measures the tone of the information.

[0448] Step 3:

[0449] The server makes a decision to send a positive message to the user if the sentiment rating score is aggressive or condescending. The sentiment rating score is considered as input, and the output is a positive notification such as "You are coping well." This notification is immediately displayed on the terminal's user interface.

[0450] Step 4:

[0451] The terminal monitors and analyzes the information created by the user in real time. The input is the text the user is typing, and preprocessing and natural language processing are applied. If the server determines that the sentiment evaluation is negative, it generates advice such as, "We recommend softening this expression." The output is a real-time feedback message presented to the user.

[0452] Step 5:

[0453] The terminal extracts task-related elements from the received information and generates a task list. The input is the full text of the information received by the user. From this data, the terminal automatically summarizes the important task information and outputs a list that eliminates emotional elements. The generated task list is displayed in a dedicated window on the terminal, allowing the user to review it and organize their tasks.

[0454] (Application Example 1)

[0455] 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."

[0456] In today's business environment, communication via electronic messaging is crucial, but it often leads to emotional friction, negatively impacting work efficiency and workplace relationships. In particular, a high frequency of aggressive messages can increase the recipient's mental burden, leading to stress and decreased productivity. Furthermore, important business matters may be overlooked amidst emotional exchanges. Methods to address these challenges are needed.

[0457] 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.

[0458] In this invention, the server includes means for analyzing received electronic data on a computer terminal and evaluating the emotional tone of its content, means for displaying positive messages to users based on the analysis results, and means for analyzing the emotional tone in internal communications within a company and providing prompt emotional support based on aggressive content. This makes it possible to improve work efficiency and create a healthier workplace environment by managing the emotional aspects of electronic messages.

[0459] A "computer terminal" is a computing device used to process received electronic data, and it is a device that executes software to perform natural language processing.

[0460] "Electronic data" refers to textual information, messages, chats, and other communication content expressed in digital format.

[0461] "Emotional tone" refers to the emotional nuances and atmosphere that can be perceived from the content of a text, and is a characteristic that can be classified as positive, negative, neutral, etc.

[0462] A "natural language processing model" refers to the algorithms and libraries used by computers to understand and analyze human language.

[0463] A "positive message" refers to a message that gives the recipient positive feelings or a sense of security.

[0464] "Offensive content" refers to the characteristics of a message that includes words or expressions that may intimidate or offend the recipient.

[0465] "Mental support" refers to assistance or advice provided to support the mental health of the recipient.

[0466] This invention is a system implemented by a program running on a computer terminal. This system uses natural language processing technology to analyze the emotional tone of electronic data, providing positive feedback to users while promoting healthy internal communication.

[0467] The server collects received electronic data and evaluates its emotional tone using a natural language processing model. Specifically, it uses technologies such as Google NLP and IBM Watson for natural language processing to automatically identify positive, negative, or neutral emotions. In this process, it also identifies whether the data contains offensive content.

[0468] Based on the analysis results, the device provides the user with appropriate positive messages or emotional support. For example, for aggressive messages that the recipient might find offensive, the device will display a message such as, "Try to relax and respond accordingly."

[0469] When a user enters a new message, the device monitors its content in real time before sending and provides warnings as needed. By offering feedback such as, "It would be more constructive to improve this expression," it helps prevent communication problems.

[0470] For example, when a sales representative receives a customer complaint, the device may quickly analyze the email and display a message of reassurance such as, "Don't worry, we're doing our best." The aim is to facilitate smooth internal and external communication in this way.

[0471] Example of a prompt: "Analyze the emotional tone of this message and generate a positive response."

[0472] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0473] Step 1:

[0474] The server receives electronic data from the terminal. The input is message data sent and received by the user, and the output is that data passed on to the next analysis step. The server stores it in a database and converts it into a format that can be read by the natural language processing model.

[0475] Step 2:

[0476] The server analyzes the emotional tone of received electronic data using a natural language processing model. The input is text data formatted in step 1, and the output is the evaluation result of the emotional tone. The server utilizes models such as Google NLP and IBM Watson to identify emotions as positive, negative, or neutral.

[0477] Step 3:

[0478] The device receives the analysis results and presents a message to the user based on them. The input is the evaluation result of the emotional tone obtained in step 2, and the output is the feedback message displayed to the user. If the content is positive, the device will display something like, "You're doing great."

[0479] Step 4:

[0480] When a user enters a new message, the device monitors the input in real time. The input is the message the user is creating, and the output is an evaluation of whether the message is offensive. The device uses a generative AI model to display a warning such as "This wording should be revised" if the tone of the message is offensive.

[0481] Step 5:

[0482] The terminal summarizes received messages and provides the user with an emotionless task list. Input is the electronic data from Step 1, and output is the summarized task list. The terminal uses keyword extraction and summarization algorithms to generate a concise list of key points. Accordingly, the user receives support to efficiently manage their tasks.

[0483] 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.

[0484] This invention is a resident application that runs on a computer terminal, combined with an emotion engine that recognizes user emotions. This system has the function of analyzing electronic messages received by the user and evaluating their emotional tone, and can further grasp the user's emotional state using user reactions and input data.

[0485] The device uses natural language processing technology to analyze incoming messages, and when it detects an aggressive or condescending tone, its emotion engine considers the user's current emotional state and displays the most appropriate positive message. This process provides personalized psychological support to each individual user.

[0486] Furthermore, the device monitors the user's typing speed and the frequency of message changes, and an emotion engine estimates their stress level. This data is reflected in the content of warnings and encouraging messages sent before messages are sent. For example, if a slower-than-usual typing speed is detected, the device may determine that the user is experiencing hesitation or anxiety and present a message such as, "Take a break and check again."

[0487] The emotion engine analyzes past user interaction data to provide personalized support. This allows the device to recognize regular user emotional patterns and predict future emotional responses.

[0488] For example, if a user receives harsh feedback during a stressful team project, the device uses its emotion engine to estimate the user's stress level and notify them with a message such as, "You're doing a great job, and this moment is important." It also provides alternative messages to the suggested message, giving the user time to calmly consider their next course of action.

[0489] Thus, the present invention is a multi-functional system that utilizes emotion recognition technology to help users have a better communication experience in the workplace.

[0490] The following describes the processing flow.

[0491] Step 1:

[0492] The device monitors the user's inbox and detects the arrival of new electronic messages, which triggers message analysis.

[0493] Step 2:

[0494] The device uses natural language processing technology to analyze the content of incoming messages and evaluate their emotional tone. The analysis includes keywords and context of the message.

[0495] Step 3:

[0496] After the device evaluates the tone of an incoming message, if it determines it to be aggressive or condescending, the sentiment engine retrieves the user's reaction data and estimates the user's current emotional state.

[0497] Step 4:

[0498] Based on the emotional state estimated by the emotion engine, the device creates the most appropriate positive message and displays a pop-up notification to the user. This reduces the negative impact the user may experience.

[0499] Step 5:

[0500] When a user initiates an action on their desktop, the device monitors the user's typing speed and keystroke frequency, collecting data in real time.

[0501] Step 6:

[0502] The device analyzes the collected data using an emotion engine to estimate stress and anxiety levels. This information is particularly important when unusual input patterns are detected.

[0503] Step 7:

[0504] As the user types a message, the device monitors the content in real time and, if it detects an aggressive tone, uses its emotion engine to display a warning message. The warning also takes stress levels into consideration and responds flexibly.

[0505] Step 8:

[0506] By analyzing past user interaction data, the emotion engine updates its future prediction model, making feedback and positive messages to users more personalized. This process allows the device to deeply understand and respond to user characteristics.

[0507] (Example 2)

[0508] 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."

[0509] In our information-driven society, users receive a large volume of electronic messages, and sometimes their content can cause psychological stress. In particular, aggressive or condescending communication can negatively impact users' mental health. In such situations, there is a need to provide timely, emotionally supportive messages and offer users means to reduce stress.

[0510] 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.

[0511] In this invention, the server includes means for analyzing received information on an information processing device and evaluating the emotional characteristics of its content; means for displaying emotionally supportive sentences to the user based on the analysis results; and means for estimating the user's stress level based on past user behavior data and generating appropriate support sentences. As a result, the user can receive appropriate support according to the message they receive, thereby reducing their psychological burden and enabling them to have a better communication experience.

[0512] An "information processing device" is a combination of hardware and software for collecting, analyzing, and processing data, and is a device for providing information through interaction with the user.

[0513] "Received information" refers to text messages and data obtained from other users or systems, and is the information that is subject to analysis and evaluation.

[0514] "Emotional characteristics" refer to the emotional nature contained in a message or information, and are a concept that describes emotional states such as positive, negative, or neutral.

[0515] "Emotionally supportive messages" are text messages intended to alleviate a user's psychological distress by offering encouragement and comfort.

[0516] "Analysis results" refer to data on emotional characteristics and other evaluations obtained after an information processing device analyzes received information.

[0517] "Behavioral data" refers to information that includes a user's past actions and input history, and serves as the basis for determining a user's stress level.

[0518] "Estimating stress levels" is a process of evaluating how stressed a user is experiencing based on their behavioral data and message content.

[0519] This invention is implemented as a resident software application on an information processing device. It primarily has the function of analyzing electronic messages received by the user in real time and evaluating their emotional characteristics.

[0520] The terminal uses a natural language processing library implemented in Python or a similar programming language (e.g., NLTK or SpaCy) to analyze the received information. This analysis classifies the emotional characteristics of the message as "positive," "negative," or "neutral."

[0521] Based on the analysis results, the server uses a generative AI model to generate and display emotionally supportive messages tailored to the user. This model incorporates a pre-trained sentiment analysis model, presenting the most appropriate message considering the user's stress level. Furthermore, it provides individually customized support by referencing the user's past behavioral data.

[0522] For example, if a user receives an email at work that has an aggressive tone, the device will immediately analyze it and provide positive feedback such as, "Take a moment to think about it and check it again," thereby reducing the user's psychological burden.

[0523] As an example of a prompt, we use the following: "Analyze the emotional tone of the received message and display the most appropriate positive message." Based on this prompt, the generative AI model guides the generation of an appropriate support message.

[0524] Thus, this invention can improve the user experience by analyzing the emotional tone of messages received by the user and providing customized feedback to reduce stress.

[0525] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0526] Step 1:

[0527] The device acquires electronic messages received by the user in real time. The input is text data such as emails and chat messages. This data is formatted in text format for the next analysis step.

[0528] Step 2:

[0529] The terminal analyzes the acquired text data using a natural language processing library. Specifically, it uses the Python library NLTK to analyze the grammatical structure of the text and extract emotional characteristics. The generated output is information classifying each message as either "positive," "negative," or "neutral."

[0530] Step 3:

[0531] The server applies a generative AI model based on the analysis results to generate emotionally supportive messages for the user. The input is data on emotional characteristics, and the output is a supportive message optimized for the user. Here, the generative AI model references the user's past stress patterns to create a customized message.

[0532] Step 4:

[0533] The device notifies the user of the generated support message. This notification appears as a pop-up on the desktop or as a message in the chat window. Specifically, it presents the user with psychological support, which the user then uses to decide on their next course of action.

[0534] (Application Example 2)

[0535] 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."

[0536] A challenge is minimizing the impact of emotional influences on smooth communication when users receive communication information or create input data. In particular, in physical stores, where direct interactions between customers and staff are frequent, it is difficult to quickly detect and appropriately address customer dissatisfaction and stress, thus improving the customer experience is essential.

[0537] 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.

[0538] In this invention, the server includes means for presenting the user's emotional response in real time using a wearable display device and prompting an appropriate response, means for analyzing communication information and evaluating the emotional tone of its content, and means for monitoring data entered by the user before transmission, determining if it is offensive, and displaying a warning. This allows for real-time understanding of the customer's emotional state and prompting an appropriate response, thereby improving communication within the store and enabling smooth customer service.

[0539] A "computer device" is a computing system that processes user input and external information to support decision-making.

[0540] "Communication information" refers to messages and data that are sent and received through electronic means.

[0541] "Analysis" is the process of breaking down information to understand its structure and meaning, and then extracting the necessary information.

[0542] "Emotional tone" refers to the attitude and atmosphere of a message or communication, and is a characteristic related to emotional nuances.

[0543] A "user" refers to an individual or organization that uses a system or device.

[0544] "Positive information" refers to messages that aim to improve the recipient's emotions and mood.

[0545] "Offensive content" refers to information that may have a negative or hostile effect on the recipient.

[0546] "Advice" refers to suggestions or recommendations given with the aim of pointing out or encouraging improvement in actions or opinions.

[0547] A "wearable display device" is an electronic device that is worn by the user to display information and allow them to check real-time information while in operation.

[0548] The system that realizes this invention mainly consists of an emotion analysis engine, a natural language processing device, a wearable display device, and a user interface.

[0549] The server receives communication information sent from users and customers and analyzes that data. Specific analysis uses natural language processing technologies such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding. These technologies evaluate the emotional tone of the communication information and identify aggressive or condescending content.

[0550] The analysis results are displayed in real time via a wearable display device. This device, for example, is a pair of smart glasses, allowing users to quickly check information while serving customers. For instance, store staff can use the wearable display device to identify when a customer is expressing dissatisfaction and be immediately presented with appropriate solutions. This real-time information sharing enables staff to respond to customers quickly and appropriately.

[0551] The user interface is the part that users interact with directly, displaying information on the wearable display device while simultaneously accepting input and feedback. If aggressive input is detected, the system displays a warning message to the user, prompting them to reconfirm the content.

[0552] For example, if a customer says, "This product is a complete disappointment," when reporting a problem with a product, a message such as "We recommend apologizing and proposing a solution" will immediately appear on the store employee's wearable display device.

[0553] An example of an input prompt for a generative AI model might be, "Analyze the conversation with the customer, determine the emotional tone, and suggest a positive response message." Based on this prompt, the AI ​​model generates an appropriate response.

[0554] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0555] Step 1:

[0556] The server receives communication information sent from users and customers. The input is communication information such as emails and text messages, and the output is unanalyzed data in its original state.

[0557] Step 2:

[0558] The server sends the received unanalyzed data to a natural language processing unit, which then analyzes the data using natural language processing techniques. This analysis uses Google Cloud Natural Language API or IBM Watson Natural Language Understanding. The input is the unanalyzed data obtained in step 1, and the output is the analyzed data with an evaluation of emotional tone.

[0559] Step 3:

[0560] The terminal identifies aggressive or condescending content based on the analysis data obtained in Step 2. Specifically, it compares the natural language processing evaluation results with evaluation criteria and assigns appropriate sentiment tags. The input is the analysis data from Step 2, and the output is the data with sentiment tags assigned.

[0561] Step 4:

[0562] The device transmits emotion-tagged data to a wearable display device and displays a message prompting the user to take an appropriate action in real time. Specifically, it selects and displays a message. The input is the emotion-tagged data from step 3, and the output is the response message displayed on the display device.

[0563] Step 5:

[0564] The terminal monitors the data entered by the user and uses natural language processing technology to determine whether it is offensive before sending it. Specifically, it performs the same analysis process as in Step 1 to obtain the result. The input is the user's input data, and the output is a warning message based on the evaluation result.

[0565] Step 6:

[0566] Based on the findings in Step 5, the device will, if necessary, present a warning message to the user and prompt them to reconfirm the information. Specifically, this involves selecting and displaying a message containing the warning. The input is the evaluation result from Step 5, and the output is the warning message the user receives.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] [Fourth Embodiment]

[0571] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0572] 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.

[0573] 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).

[0574] 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.

[0575] 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.

[0576] 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).

[0577] 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.

[0578] 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.

[0579] 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.

[0580] 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.

[0581] 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.

[0582] 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.

[0583] 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".

[0584] The present invention is implemented as a resident application installed on a user's computer terminal. This system includes a program for analyzing electronic messages received by the user and evaluating their emotional tone. The terminal utilizes natural language processing technology to analyze the content of the message and automatically identifies positive or negative emotions. If the analysis determines that the message is aggressive or condescending, the terminal automatically displays a positive message to the user to provide emotional support.

[0585] Furthermore, the device monitors user-entered messages in real time and analyzes their content before sending them. If an entered message is deemed offensive, the device displays a warning to the user, encouraging more appropriate communication. This process gives users time and opportunity to review and revise their messages.

[0586] Furthermore, the device summarizes received messages and generates an emotionless task list. This task list helps users manage their work efficiently. The generated list is displayed in a dedicated window on the desktop, allowing users to review and organize their tasks at any time.

[0587] For example, if a user receives a work-related chat message that is aggressive and pressure-inducing, the device will quickly display an encouraging message such as, "You are handling this well." Similarly, when a user is composing an email, if emotional language is detected, a warning such as, "We recommend softening this expression," will be displayed. This allows users to achieve better communication and stress management.

[0588] The following describes the processing flow.

[0589] Step 1:

[0590] The device monitors the user's inbox and detects the arrival of new electronic messages. This prepares all messages the user receives for analysis.

[0591] Step 2:

[0592] The content of messages received by the device is analyzed using natural language processing techniques. The focus of the analysis is to evaluate the emotional tone based on keywords and sentence structure within the message.

[0593] Step 3:

[0594] The device determines, based on the analysis results, whether the message contains an aggressive or condescending tone. If so, feedback is provided to the user in the next step.

[0595] Step 4:

[0596] The device displays a pop-up message of encouragement to the user, providing psychological support to mitigate the negative impact of the received message.

[0597] Step 5:

[0598] The device monitors the user's message input in real time and evaluates the message content as it is being prepared to send. Natural language processing technology is again used to determine if it contains offensive content.

[0599] Step 6:

[0600] The device will display a warning message to the user for messages it deems offensive, as needed. This warning encourages the user to revise the message to a more appropriate form.

[0601] Step 7:

[0602] The device summarizes received messages and generates an emotionless task list. The summarization process shortens the main points of the message and organizes them into tasks.

[0603] Step 8:

[0604] The terminal displays the generated task list on the desktop, helping users manage their work efficiently. By referring to this list, users can plan their actions without losing sight of important tasks.

[0605] (Example 1)

[0606] 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".

[0607] In modern communication, electronic messaging is commonplace, but it can sometimes contain aggressive or condescending content, causing stress to users. Furthermore, users themselves may unconsciously send aggressive messages, hindering effective communication. In addition, there is a lack of efficient means to process received information and improve productivity. To address these issues, a system is needed that assesses emotional characteristics and provides users with appropriate feedback and support.

[0608] 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.

[0609] In this invention, the server includes means for analyzing received information on a computing device and evaluating the emotional characteristics of its content; means for presenting positive notifications to the user based on the analysis results; and means for monitoring information created by the user before transmission, determining whether the content is offensive, and providing advice. This reduces the stress experienced by the user through electronic messages and enables appropriate communication by allowing users to review the content before transmission. Furthermore, efficient management of received messages improves user productivity.

[0610] A "computer" is an electronic device designed for information processing, possessing the functions of collecting, analyzing, and processing data.

[0611] "Information" refers to content exchanged between users as electronic messages or data, and includes formats such as text, images, and audio.

[0612] "Emotional characteristics" refer to the psychological tone and nuances conveyed by a message or information, and include expressions of emotions such as positive, negative, and aggressive.

[0613] "Analysis" is a procedure used to examine and evaluate received information in detail in order to understand its content and structure.

[0614] "Positive notifications" are messages displayed to provide users with a sense of security and positive feedback, and their role is to reduce the user's mental burden.

[0615] "Monitoring" refers to the act of checking the trends of information in real time or in batch processing and taking necessary actions according to defined conditions.

[0616] "Advice" refers to guiding messages provided with the aim of encouraging users to improve the content of the information they post.

[0617] A "message" is a unit of information transmitted from a sender to a recipient, and is the basic form of communication, including email, chat, and text messages.

[0618] "Productivity" is an indicator that shows the output and efficiency generated within a certain time, and is an important element that supports the effective execution of work.

[0619] This invention is implemented as a resident application running on a computer. The system, installed on a computer terminal, analyzes information received by the user and evaluates its emotional characteristics. The system utilizes natural language processing techniques via a server to determine whether the information is positive or negative. By using software libraries such as Python's NLTK and TextBlob, it is possible to analyze the content of the information in detail.

[0620] If the terminal determines that the received information is aggressive or offensive, the server will quickly display a positive and reassuring message to the user, providing positive feedback. This approach can reduce the stress that receiving information causes the user.

[0621] Furthermore, the device monitors the information sent by the user in real time before transmission and evaluates its content using natural language processing. If the information is deemed offensive, the server provides the user with guidance, such as "We recommend softening this expression." This process allows users to review the content of their information before sending it, enabling appropriate communication.

[0622] Furthermore, the system summarizes incoming information, generates a task list free of emotional biases, and presents it to the user in a dedicated window on their terminal. This allows users to improve productivity while efficiently managing their tasks.

[0623] For example, if a user receives a work-related chat message and it is perceived as being aggressive, the server will display a positive message such as, "You are handling this well." Furthermore, if emotional language is detected while the user is composing an email, it will advise, "We recommend softening this expression." Throughout this entire system, better communication and stress management are achieved.

[0624] Example of a prompt:

[0625] "If a user receives an aggressive email from work after a long meeting, how can a positive message be displayed, and how can the program help the user?"

[0626] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0627] Step 1:

[0628] The terminal monitors the information received by the user in real time. Received electronic messages are stored in a parsing buffer. The input is text data. This data undergoes preprocessing for natural language processing, including text cleaning and tokenization. The output is text data in a parsable format.

[0629] Step 2:

[0630] The server receives text data in a parseable format and analyzes its emotional characteristics using natural language processing techniques. Specifically, it uses a generative AI model to process the data and evaluate emotional attributes such as positive, negative, domineering, and aggressive. The input is cleaned text data, and the output is an emotional evaluation score. This score measures the tone of the information.

[0631] Step 3:

[0632] The server makes a decision to send a positive message to the user if the sentiment rating score is aggressive or condescending. The sentiment rating score is considered as input, and the output is a positive notification such as "You are coping well." This notification is immediately displayed on the terminal's user interface.

[0633] Step 4:

[0634] The terminal monitors and analyzes the information created by the user in real time. The input is the text the user is typing, and preprocessing and natural language processing are applied. If the server determines that the sentiment evaluation is negative, it generates advice such as, "We recommend softening this expression." The output is a real-time feedback message presented to the user.

[0635] Step 5:

[0636] The terminal extracts task-related elements from the received information and generates a task list. The input is the full text of the information received by the user. From this data, the terminal automatically summarizes the important task information and outputs a list that eliminates emotional elements. The generated task list is displayed in a dedicated window on the terminal, allowing the user to review it and organize their tasks.

[0637] (Application Example 1)

[0638] 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".

[0639] In today's business environment, communication via electronic messaging is crucial, but it often leads to emotional friction, negatively impacting work efficiency and workplace relationships. In particular, a high frequency of aggressive messages can increase the recipient's mental burden, leading to stress and decreased productivity. Furthermore, important business matters may be overlooked amidst emotional exchanges. Methods to address these challenges are needed.

[0640] 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.

[0641] In this invention, the server includes means for analyzing received electronic data on a computer terminal and evaluating the emotional tone of its content, means for displaying positive messages to users based on the analysis results, and means for analyzing the emotional tone in internal communications within a company and providing prompt emotional support based on aggressive content. This makes it possible to improve work efficiency and create a healthier workplace environment by managing the emotional aspects of electronic messages.

[0642] A "computer terminal" is a computing device used to process received electronic data, and it is a device that executes software to perform natural language processing.

[0643] "Electronic data" refers to textual information, messages, chats, and other communication content expressed in digital format.

[0644] "Emotional tone" refers to the emotional nuances and atmosphere that can be perceived from the content of a text, and is a characteristic that can be classified as positive, negative, neutral, etc.

[0645] A "natural language processing model" refers to the algorithms and libraries used by computers to understand and analyze human language.

[0646] A "positive message" refers to a message that gives the recipient positive feelings or a sense of security.

[0647] "Offensive content" refers to the characteristics of a message that includes words or expressions that may intimidate or offend the recipient.

[0648] "Mental support" refers to assistance or advice provided to support the mental health of the recipient.

[0649] This invention is a system implemented by a program running on a computer terminal. This system uses natural language processing technology to analyze the emotional tone of electronic data, providing positive feedback to users while promoting healthy internal communication.

[0650] The server collects received electronic data and evaluates its emotional tone using a natural language processing model. Specifically, it uses technologies such as Google NLP and IBM Watson for natural language processing to automatically identify positive, negative, or neutral emotions. In this process, it also identifies whether the data contains offensive content.

[0651] Based on the analysis results, the device provides the user with appropriate positive messages or emotional support. For example, for aggressive messages that the recipient might find offensive, the device will display a message such as, "Try to relax and respond accordingly."

[0652] When a user enters a new message, the device monitors its content in real time before sending and provides warnings as needed. By offering feedback such as, "It would be more constructive to improve this expression," it helps prevent communication problems.

[0653] For example, when a sales representative receives a customer complaint, the device may quickly analyze the email and display a message of reassurance such as, "Don't worry, we're doing our best." The aim is to facilitate smooth internal and external communication in this way.

[0654] Example of a prompt: "Analyze the emotional tone of this message and generate a positive response."

[0655] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0656] Step 1:

[0657] The server receives electronic data from the terminal. The input is message data sent and received by the user, and the output is that data passed on to the next analysis step. The server stores it in a database and converts it into a format that can be read by the natural language processing model.

[0658] Step 2:

[0659] The server analyzes the emotional tone of received electronic data using a natural language processing model. The input is text data formatted in step 1, and the output is the evaluation result of the emotional tone. The server utilizes models such as Google NLP and IBM Watson to identify emotions as positive, negative, or neutral.

[0660] Step 3:

[0661] The device receives the analysis results and presents a message to the user based on them. The input is the evaluation result of the emotional tone obtained in step 2, and the output is the feedback message displayed to the user. If the content is positive, the device will display something like, "You're doing great."

[0662] Step 4:

[0663] When a user enters a new message, the device monitors the input in real time. The input is the message the user is creating, and the output is an evaluation of whether the message is offensive. The device uses a generative AI model to display a warning such as "This wording should be revised" if the tone of the message is offensive.

[0664] Step 5:

[0665] The terminal summarizes received messages and provides the user with an emotionless task list. Input is the electronic data from Step 1, and output is the summarized task list. The terminal uses keyword extraction and summarization algorithms to generate a concise list of key points. Accordingly, the user receives support to efficiently manage their tasks.

[0666] 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.

[0667] This invention is a resident application that runs on a computer terminal, combined with an emotion engine that recognizes user emotions. This system has the function of analyzing electronic messages received by the user and evaluating their emotional tone, and can further grasp the user's emotional state using user reactions and input data.

[0668] The device uses natural language processing technology to analyze incoming messages, and when it detects an aggressive or condescending tone, its emotion engine considers the user's current emotional state and displays the most appropriate positive message. This process provides personalized psychological support to each individual user.

[0669] Furthermore, the device monitors the user's typing speed and the frequency of message changes, and an emotion engine estimates their stress level. This data is reflected in the content of warnings and encouraging messages sent before messages are sent. For example, if a slower-than-usual typing speed is detected, the device may determine that the user is experiencing hesitation or anxiety and present a message such as, "Take a break and check again."

[0670] The emotion engine analyzes past user interaction data to provide personalized support. This allows the device to recognize regular user emotional patterns and predict future emotional responses.

[0671] For example, if a user receives harsh feedback during a stressful team project, the device uses its emotion engine to estimate the user's stress level and notify them with a message such as, "You're doing a great job, and this moment is important." It also provides alternative messages to the suggested message, giving the user time to calmly consider their next course of action.

[0672] Thus, the present invention is a multi-functional system that utilizes emotion recognition technology to help users have a better communication experience in the workplace.

[0673] The following describes the processing flow.

[0674] Step 1:

[0675] The device monitors the user's inbox and detects the arrival of new electronic messages, which triggers message analysis.

[0676] Step 2:

[0677] The device uses natural language processing technology to analyze the content of incoming messages and evaluate their emotional tone. The analysis includes keywords and context of the message.

[0678] Step 3:

[0679] After the device evaluates the tone of an incoming message, if it determines it to be aggressive or condescending, the sentiment engine retrieves the user's reaction data and estimates the user's current emotional state.

[0680] Step 4:

[0681] Based on the emotional state estimated by the emotion engine, the device creates the most appropriate positive message and displays a pop-up notification to the user. This reduces the negative impact the user may experience.

[0682] Step 5:

[0683] When a user initiates an action on their desktop, the device monitors the user's typing speed and keystroke frequency, collecting data in real time.

[0684] Step 6:

[0685] The device analyzes the collected data using an emotion engine to estimate stress and anxiety levels. This information is particularly important when unusual input patterns are detected.

[0686] Step 7:

[0687] As the user types a message, the device monitors the content in real time and, if it detects an aggressive tone, uses its emotion engine to display a warning message. The warning also takes stress levels into consideration and responds flexibly.

[0688] Step 8:

[0689] By analyzing past user interaction data, the emotion engine updates its future prediction model, making feedback and positive messages to users more personalized. This process allows the device to deeply understand and respond to user characteristics.

[0690] (Example 2)

[0691] 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".

[0692] In our information-driven society, users receive a large volume of electronic messages, and sometimes their content can cause psychological stress. In particular, aggressive or condescending communication can negatively impact users' mental health. In such situations, there is a need to provide timely, emotionally supportive messages and offer users means to reduce stress.

[0693] 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.

[0694] In this invention, the server includes means for analyzing received information on an information processing device and evaluating the emotional characteristics of its content; means for displaying emotionally supportive sentences to the user based on the analysis results; and means for estimating the user's stress level based on past user behavior data and generating appropriate support sentences. As a result, the user can receive appropriate support according to the message they receive, thereby reducing their psychological burden and enabling them to have a better communication experience.

[0695] An "information processing device" is a combination of hardware and software for collecting, analyzing, and processing data, and is a device for providing information through interaction with the user.

[0696] "Received information" refers to text messages and data obtained from other users or systems, and is the information that is subject to analysis and evaluation.

[0697] "Emotional characteristics" refer to the emotional nature contained in a message or information, and are a concept that describes emotional states such as positive, negative, or neutral.

[0698] "Emotionally supportive messages" are text messages intended to alleviate a user's psychological distress by offering encouragement and comfort.

[0699] "Analysis results" refer to data on emotional characteristics and other evaluations obtained after an information processing device analyzes received information.

[0700] "Behavioral data" refers to information that includes a user's past actions and input history, and serves as the basis for determining a user's stress level.

[0701] "Estimating stress levels" is a process of evaluating how stressed a user is experiencing based on their behavioral data and message content.

[0702] This invention is implemented as a resident software application on an information processing device. It primarily has the function of analyzing electronic messages received by the user in real time and evaluating their emotional characteristics.

[0703] The terminal uses a natural language processing library implemented in Python or a similar programming language (e.g., NLTK or SpaCy) to analyze the received information. This analysis classifies the emotional characteristics of the message as "positive," "negative," or "neutral."

[0704] Based on the analysis results, the server uses a generative AI model to generate and display emotionally supportive messages tailored to the user. This model incorporates a pre-trained sentiment analysis model, presenting the most appropriate message considering the user's stress level. Furthermore, it provides individually customized support by referencing the user's past behavioral data.

[0705] For example, if a user receives an email at work that has an aggressive tone, the device will immediately analyze it and provide positive feedback such as, "Take a moment to think about it and check it again," thereby reducing the user's psychological burden.

[0706] As an example of a prompt, we use the following: "Analyze the emotional tone of the received message and display the most appropriate positive message." Based on this prompt, the generative AI model guides the generation of an appropriate support message.

[0707] Thus, this invention can improve the user experience by analyzing the emotional tone of messages received by the user and providing customized feedback to reduce stress.

[0708] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0709] Step 1:

[0710] The device acquires electronic messages received by the user in real time. The input is text data such as emails and chat messages. This data is formatted in text format for the next analysis step.

[0711] Step 2:

[0712] The terminal analyzes the acquired text data using a natural language processing library. Specifically, it uses the Python library NLTK to analyze the grammatical structure of the text and extract emotional characteristics. The generated output is information classifying each message as either "positive," "negative," or "neutral."

[0713] Step 3:

[0714] The server applies a generative AI model based on the analysis results to generate emotionally supportive messages for the user. The input is data on emotional characteristics, and the output is a supportive message optimized for the user. Here, the generative AI model references the user's past stress patterns to create a customized message.

[0715] Step 4:

[0716] The device notifies the user of the generated support message. This notification appears as a pop-up on the desktop or as a message in the chat window. Specifically, it presents the user with psychological support, which the user then uses to decide on their next course of action.

[0717] (Application Example 2)

[0718] 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".

[0719] A challenge is minimizing the impact of emotional influences on smooth communication when users receive communication information or create input data. In particular, in physical stores, where direct interactions between customers and staff are frequent, it is difficult to quickly detect and appropriately address customer dissatisfaction and stress, thus improving the customer experience is essential.

[0720] 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.

[0721] In this invention, the server includes means for presenting the user's emotional response in real time using a wearable display device and prompting an appropriate response, means for analyzing communication information and evaluating the emotional tone of its content, and means for monitoring data entered by the user before transmission, determining if it is offensive, and displaying a warning. This allows for real-time understanding of the customer's emotional state and prompting an appropriate response, thereby improving communication within the store and enabling smooth customer service.

[0722] A "computer device" is a computing system that processes user input and external information to support decision-making.

[0723] "Communication information" refers to messages and data that are sent and received through electronic means.

[0724] "Analysis" is the process of breaking down information to understand its structure and meaning, and then extracting the necessary information.

[0725] "Emotional tone" refers to the attitude and atmosphere of a message or communication, and is a characteristic related to emotional nuances.

[0726] A "user" refers to an individual or organization that uses a system or device.

[0727] "Positive information" refers to messages that aim to improve the recipient's emotions and mood.

[0728] "Offensive content" refers to information that may have a negative or hostile effect on the recipient.

[0729] "Advice" refers to suggestions or recommendations given with the aim of pointing out or encouraging improvement in actions or opinions.

[0730] A "wearable display device" is an electronic device that is worn by the user to display information and allow them to check real-time information while in operation.

[0731] The system that realizes this invention mainly consists of an emotion analysis engine, a natural language processing device, a wearable display device, and a user interface.

[0732] The server receives communication information sent from users and customers and analyzes that data. Specific analysis uses natural language processing technologies such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding. These technologies evaluate the emotional tone of the communication information and identify aggressive or condescending content.

[0733] The analysis results are displayed in real time via a wearable display device. This device, for example, is a pair of smart glasses, allowing users to quickly check information while serving customers. For instance, store staff can use the wearable display device to identify when a customer is expressing dissatisfaction and be immediately presented with appropriate solutions. This real-time information sharing enables staff to respond to customers quickly and appropriately.

[0734] The user interface is the part that users interact with directly, displaying information on the wearable display device while simultaneously accepting input and feedback. If aggressive input is detected, the system displays a warning message to the user, prompting them to reconfirm the content.

[0735] For example, if a customer says, "This product is a complete disappointment," when reporting a problem with a product, the store employee's wearable display device will immediately show a message such as, "We recommend apologizing and proposing a solution."

[0736] An example of an input prompt for a generative AI model might be, "Analyze the conversation with the customer, determine the emotional tone, and suggest a positive response message." Based on this prompt, the AI ​​model generates an appropriate response.

[0737] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0738] Step 1:

[0739] The server receives communication information sent from users and customers. The input is communication information such as emails and text messages, and the output is unanalyzed data in its original state.

[0740] Step 2:

[0741] The server sends the received unanalyzed data to a natural language processing unit, which then analyzes the data using natural language processing techniques. This analysis uses Google Cloud Natural Language API or IBM Watson Natural Language Understanding. The input is the unanalyzed data obtained in step 1, and the output is the analyzed data with an evaluation of emotional tone.

[0742] Step 3:

[0743] The terminal identifies aggressive or condescending content based on the analysis data obtained in Step 2. Specifically, it compares the natural language processing evaluation results with evaluation criteria and assigns appropriate sentiment tags. The input is the analysis data from Step 2, and the output is the data with sentiment tags assigned.

[0744] Step 4:

[0745] The device transmits emotion-tagged data to a wearable display device and displays a message prompting the user to take an appropriate action in real time. Specifically, it selects and displays a message. The input is the emotion-tagged data from step 3, and the output is the response message displayed on the display device.

[0746] Step 5:

[0747] The terminal monitors the data entered by the user and uses natural language processing technology to determine whether it is offensive before sending it. Specifically, it performs the same analysis process as in Step 1 to obtain the result. The input is the user's input data, and the output is a warning message based on the evaluation result.

[0748] Step 6:

[0749] Based on the findings in Step 5, the device will, if necessary, present a warning message to the user and prompt them to reconfirm the information. Specifically, this involves selecting and displaying a message containing the warning. The input is the evaluation result from Step 5, and the output is the warning message the user receives.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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."

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] The following is further disclosed regarding the embodiments described above.

[0772] (Claim 1)

[0773] A means for analyzing received electronic messages on a computer terminal and evaluating the emotional tone of their content,

[0774] Based on the analysis results, a means of displaying a positive message to the user,

[0775] A means to monitor messages entered by users before sending them, determine if the content is offensive, and display a warning,

[0776] A means of summarizing the content of received messages, generating a task list, and presenting it to the user,

[0777] A system that includes this.

[0778] (Claim 2)

[0779] The system according to claim 1, which uses a natural language processing model to identify an aggressive tone in a received electronic message.

[0780] (Claim 3)

[0781] The system according to claim 1, which provides feedback on emotional content in an easily editable format before the user sends a message.

[0782] "Example 1"

[0783] (Claim 1)

[0784] A means for analyzing received information on a computing device and evaluating the emotional characteristics of its content,

[0785] A means of presenting positive notifications to users based on the analysis results,

[0786] A means of monitoring user-created information before it is sent, determining whether the content is offensive, and providing advice.

[0787] A means of summarizing the content of the received information, generating a task list, and presenting it to the user,

[0788] A system that includes this.

[0789] (Claim 2)

[0790] The system according to claim 1, which uses a natural language processing model to identify the high-pressure characteristics of the received information.

[0791] (Claim 3)

[0792] The system according to claim 1, which provides users with feedback on emotional content in an easily editable format before they submit information, thereby giving users an opportunity to review it.

[0793] "Application Example 1"

[0794] (Claim 1)

[0795] A means for analyzing received electronic data on a computer terminal and evaluating the emotional tone of its content,

[0796] A means of displaying a positive message to the user based on the analysis results,

[0797] A means of monitoring data entered by users before transmission, determining whether the content is offensive, and displaying a warning,

[0798] A means of summarizing the content of received messages, generating a task list, and presenting it to the user,

[0799] In internal corporate communication, a means of analyzing emotional tone and providing rapid psychological support based on aggressive content,

[0800] A system that includes this.

[0801] (Claim 2)

[0802] The system according to claim 1, which uses a natural language processing model to identify an aggressive tone in the received electronic data.

[0803] (Claim 3)

[0804] The system according to claim 1, which provides feedback on emotional content in an easily editable format before the user submits the data.

[0805] "Example 2 of combining an emotion engine"

[0806] (Claim 1)

[0807] An information processing device provides means for analyzing received information and evaluating the emotional characteristics of its content,

[0808] Based on the analysis results, a means of displaying emotionally supportive sentences to the user,

[0809] A means of monitoring information entered by the user before it is sent, determining whether the content is offensive, and displaying a warning,

[0810] A means for estimating stress levels based on past user behavior data and generating appropriate support messages,

[0811] A system that includes this.

[0812] (Claim 2)

[0813] The system according to claim 1, which uses a natural language processing model to identify the high-pressure characteristics of the received information.

[0814] (Claim 3)

[0815] The system according to claim 1, which provides feedback on emotional content in an easily editable format before the user submits the information.

[0816] "Application example 2 when combining with an emotional engine"

[0817] (Claim 1)

[0818] A means for analyzing received communication information on a computer device and evaluating the emotional tone of its content,

[0819] A means of displaying positive information to users based on the analysis results,

[0820] A means of monitoring data entered by users before transmission, determining whether the content is offensive, and displaying a warning,

[0821] In physical stores, a means of presenting users' emotional responses in real time using wearable display devices and prompting appropriate responses,

[0822] A system that includes this.

[0823] (Claim 2)

[0824] The system according to claim 1, which uses a natural language processing device to identify an aggressive tone in the received communication information.

[0825] (Claim 3)

[0826] The system according to claim 1, which provides feedback on emotional content in an easily editable format before the user submits the data. [Explanation of Symbols]

[0827] 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 analyzing received electronic messages on a computer terminal and evaluating the emotional tone of their content, Based on the analysis results, a means of displaying a positive message to the user, A means to monitor messages entered by users before sending them, determine if the content is offensive, and display a warning, A means of summarizing the content of received messages, generating a task list, and presenting it to the user, A system that includes this.

2. The system according to claim 1, which uses a natural language processing model to identify an aggressive tone in a received electronic message.

3. The system according to claim 1, which provides feedback on the emotional content in an easily editable format before the user sends the message.

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