system

Abstract

We provide the system. [Solution] A means for analyzing input communication messages, detecting aggressive expressions, and converting them into polite expressions, A means of performing syntactic analysis and automatically correcting typographical errors and grammatical errors based on context, A means of adjusting the wording to be appropriate based on the recipient information, A means of presenting the corrected communication and enabling user verification, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In recent years, with the increase in online communication, there have been many cases where the text sent by users becomes aggressively unintentionally or contains typos and omissions. As a result, communication with the recipient often does not proceed smoothly. Also, if appropriate language usage is not employed according to the recipient, it may cause discomfort to the recipient. Although these problems are solved within a specific range by individual experiences, there is a need for a system that can solve them automatically and consistently. 【Means for Solving the Problems】 【0005】 This invention provides a means for analyzing communication text, detecting aggressive expressions and automatically converting them into polite expressions. Furthermore, it has a function for performing grammatical analysis and automatically correcting typographical errors and grammatical mistakes based on context. It also provides a means for automatically adjusting appropriate language based on the recipient. In a system with these functions, the corrected communication text can be presented to the user, allowing for necessary corrections and confirmations. This is expected to facilitate smooth communication between senders and receivers. 【0006】 A "message" is a text-based message sent via email or messaging application. 【0007】 "Aggressive language" refers to negative words or expressions that may cause offense or negative feelings in the recipient. 【0008】 "Polite language" refers to language that conveys respect and consideration, and is used to create a positive impression on the recipient. 【0009】 "Spelling errors" are writing mistakes that occur due to failure to follow correct spelling or grammar. 【0010】 "Context" refers to the meaning and background derived from the surrounding words and circumstances in which a particular word or sentence is written. 【0011】 "Recipient information" refers to information about the recipient to whom a message or email is sent. 【0012】 "Word choice" refers to the way words are selected and used in conversation and writing. 【0013】 A "user" is a person who uses a system or service to create, edit, and send messages. [Brief explanation of the drawing] 【0014】 [Figure 1]It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【MODE FOR CARRYING OUT THE INVENTION】 【0015】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0018】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0020】 In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like. 【0021】 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." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 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. 【0025】 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). 【0026】 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. 【0027】 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. 【0028】 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. 【0029】 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. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 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. 【0032】 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. 【0033】 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. 【0034】 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". 【0035】 This invention relates to a system that analyzes user-generated messages and automatically modifies them as needed. This system is implemented by a server, a terminal, and the user. 【0036】 First, the user enters the message using their device and prepares to send it. When the user presses the send button, the entered message is sent to the server. The server analyzes the received message, performs sentiment analysis using a specific method, and detects offensive language. 【0037】 The server utilizes a database to convert aggressive expressions into more positive and polite ones. This database contains common aggressive expressions and their corresponding polite equivalents. For example, the expression "What are you doing?" is converted to "Could you tell me what the current situation is?" 【0038】 Next, the server detects typographical errors in the communication. It evaluates the entire text using contextual analysis techniques and identifies the appropriate word by referring to a dictionary database. Once the typographical errors are corrected, a corrected version is generated while maintaining the consistency of the original communication. 【0039】 Furthermore, the server verifies the recipient information and evaluates whether the content of the message is appropriate for the recipient. By applying appropriate honorifics and language according to the recipient, communication is facilitated. 【0040】 Ultimately, the terminal receives the revised message from the server. The user can review the revisions and make further corrections as needed. This entire process ensures that the user can send reliable and polite messages. 【0041】 This system is useful not only for business purposes but also for individual email communication. The invention reduces the burden on the user and minimizes the possibility of misunderstanding, thereby enabling efficient communication. 【0042】 The following describes the processing flow. 【0043】 Step 1: 【0044】 The user enters the message on the terminal and specifies the required recipient. Once ready to send, the user presses the send button to send the message to the server. 【0045】 Step 2: 【0046】 The server analyzes the communication received from the user. It uses natural language processing techniques to deepen its understanding of the context and performs syntactic analysis to evaluate the entire text. 【0047】 Step 3: 【0048】 The server uses the analysis results to detect offensive expressions in the communication. It then compares them with a dedicated database and converts the detected expressions into appropriate, polite phrasing. 【0049】 Step 4: 【0050】 The server continues grammatical analysis, identifying typographical errors and grammatical mistakes in the communication. Based on the dictionary database, it automatically corrects typographical errors with words appropriate to the context. 【0051】 Step 5: 【0052】 The server checks the specified destination information and inserts or adjusts appropriate honorifics and language in the message according to the destination. 【0053】 Step 6: 【0054】 The terminal receives the revised communication from the server. The user reviews the revisions and makes any further corrections if necessary. 【0055】 Step 7: 【0056】 Once the user confirms that there are no problems with the revised message, they perform an approval operation, and the final transmission takes place. 【0057】 In this way, the system pays attention to the quality of the message and how the recipient receives it, supporting smooth communication. 【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, inappropriate expressions of emotion in messages can lead to misunderstandings and offense. Furthermore, typographical errors and inappropriate language use can hinder effective communication. Additionally, using appropriate honorifics for different recipients can be burdensome for users. The challenge lies in resolving these issues and achieving efficient and polite dialogue. 【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 input information and converting aggressive expressions into polite expressions, means for performing syntactic analysis and automatically correcting typographical errors and omissions based on context, and means for adjusting the expression to an appropriate one based on the recipient information. This enables users to send communications that are emotionally neutral, accurate, and respectful. 【0063】 "Inputted information" refers to the text and data that the user sends to the server via the system. 【0064】 "Aggressive language" refers to linguistic expressions that may cause discomfort or rejection in others. 【0065】 "Polite language" refers to courteous expressions used to show respect to the other person and to promote good communication. 【0066】 Syntactic analysis is a technique that analyzes the structure of a text and clarifies the relationships between words and phrases. 【0067】 "Typographical errors" refer to spelling mistakes or missing characters in the entered information. 【0068】 "Automatic correction" refers to a process in which a system corrects typographical errors and grammatical mistakes to an appropriate form based on the context. 【0069】 "Recipient information" refers to information about the destination of a message, and is data used to identify the recipient at the destination. 【0070】 "Sentiment analysis" is a technique that analyzes linguistic expressions in a text and evaluates their emotional tone and nuances. 【0071】 A "generative model" is an artificial intelligence model that learns from large amounts of data to generate or transform text. 【0072】 This invention is a system that analyzes information entered by a user using a generation terminal and modifies it into appropriate expressions. Upon receiving this information, the server first performs sentiment analysis using a generation AI model. If aggressive expressions are detected, the server consults a database for converting them into polite expressions and modifies the expressions appropriately. The software used includes a natural language processing library and a dictionary database. 【0073】 Next, the server performs syntactic analysis of the communication and automatically corrects typos and grammatical errors based on context. This process utilizes advanced natural language processing techniques to select the correct words while maintaining the overall coherence of the sentence. 【0074】 Furthermore, the system verifies recipient information and applies appropriate language based on the user's specified recipient. This ensures that respectful expressions are used, facilitating smoother communication. 【0075】 Finally, the server sends the corrected information to the terminal for the user to review. The user can make further corrections as needed. This system can be used with various communication tools, such as email and messaging applications. 【0076】 For example, if a user enters the sentence "What are you doing?", the server will correct it to "Could you tell me what the current situation is?". An example of a prompt from the generating AI model is "Please make this more polite: 'What are you doing?'". In this way, users can send information using polite language and avoid misunderstandings. 【0077】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0078】 Step 1: 【0079】 The user enters the message using the terminal. The entered data is temporarily stored on the terminal and sent to the server when the communication button is pressed. The input is passed to the server as text data. 【0080】 Step 2: 【0081】 The server processes the received message using a data analysis module and initiates sentiment analysis. In this step, a generative AI model is used to assign a sentiment score to each word in the message. The output is data with each word assigned a sentiment score. 【0082】 Step 3: 【0083】 The server identifies offensive language based on sentiment scores and converts it to polite language as needed. Here, the server consults a conversion database, finds offensive language, and replaces it with registered polite language. The output is the corrected text. 【0084】 Step 4: 【0085】 The server processes the corrected message through its syntactic analysis engine, correcting typos and grammatical errors based on the context. The entire sentence is analyzed, and errors are corrected with appropriate words from the existing dictionary. The output is a grammatically correct sentence. 【0086】 Step 5: 【0087】 The server analyzes the recipient information and applies appropriate language based on the recipient's attributes. During this process, polite expressions and greetings based on the recipient information are reflected in the message. The output is a message appropriately customized for the recipient. 【0088】 Step 6: 【0089】 The server sends the revised communication to the terminal and prompts the user to confirm its contents. The user reviews the revisions on the terminal and makes further manual corrections if necessary. The final output is the communication as reviewed or further modified by the user. 【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 electronic communication, preventing misunderstandings and aggression that can occur between individuals, and ensuring courteous communication, especially in important financial transactions, are crucial challenges. Furthermore, it is necessary to guarantee accuracy and smooth exchange of information through automatic correction of typographical errors and the adoption of appropriate expressions tailored to the recipient. 【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 input information, detecting offensive expressions and converting them into polite expressions; means for performing syntactic analysis and automatically correcting typographical errors and omissions based on context; means for adjusting the language to be appropriate based on recipient information; and means for politely translating communications with counterparties in financial transactions. This makes it possible to conduct smooth and polite communication between individuals. 【0095】 "Inputted information" refers to communication data that a user sends to the system using their device. 【0096】 "Aggressive language" refers to words or phrases that may cause offense or hostility in the recipient. 【0097】 "Polite expression" refers to a method of expression that shows respect to the recipient and facilitates smooth communication. 【0098】 "Syntactic analysis" refers to the technique of analyzing grammatical structure and performing accurate semantic interpretation. 【0099】 "Typographical errors" refer to spelling mistakes or omissions that occur when a user enters data. 【0100】 "Context-based automatic correction" refers to a process that performs optimal proofreading based on the context and meaning of the input content. 【0101】 "Recipient information" refers to data about the individual or group to whom the communication is being sent. 【0102】 "Counterparty in financial transactions" refers to the party involved in electronic payments, fund transfers, and other financial transactions. 【0103】 "To politely rephrase" refers to changing aggressive or inappropriate language into milder and more appropriate language. 【0104】 This invention is realized by having a server analyze and modify communication messages entered by a user using a communication terminal. Upon receiving a communication message, the server first performs linguistic analysis to detect offensive expressions. The detected expressions are converted to appropriate expressions by referring to a pre-prepared database of polite expressions. This process utilizes sentiment analysis software such as TextBlob and EmotionAnalyzer, which are natural language processing libraries. 【0105】 Next, the server detects typos and omissions in the communication and automatically corrects them based on the context. TextBlob is also utilized in this process. Furthermore, the content is adjusted to apply the most appropriate language to the user based on the recipient information. For this reason, expression conversion rules for each recipient are registered in the database. 【0106】 Furthermore, the server performs special processing on communications related to financial transactions, transforming the language into polite expressions to prevent misunderstandings with the other party. This allows users to proceed with transactions with peace of mind. 【0107】 Finally, the revised message is sent back to the terminal, where the user can review it and make further edits if necessary. For example, if a user tries to send the phrase "Give me a refund immediately!", this system will convert it to "Could I request a refund?", mitigating the impact on the recipient. 【0108】 An example of a prompt message is as follows: 【0109】 "Please implement a program that politely modifies messages sent by users in financial transactions. It will transform aggressive language into courteous expressions." 【0110】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0111】 Step 1: 【0112】 The server receives the communication message sent by the user. It obtains the communication message entered by the user from the terminal as input. In this step, the content of the communication message itself is the main data. 【0113】 Step 2: 【0114】 The server performs syntactic analysis on the received communication text using the TextBlob natural language processing library. The communication text received in step 1 is used as input, and its grammatical structure is analyzed. As a result, typos and omissions are detected, and a text with appropriate spelling corrections is output. 【0115】 Step 3: 【0116】 The server uses EmotionAnalyzer to perform sentiment analysis on the communication text. Here, the modified text from step 2 is input, and data processing is performed to assign a sentiment score to each word. As a result, aggressive expressions throughout the text are identified. 【0117】 Step 4: 【0118】 The server refers to a pre-configured database of polite expressions and performs a conversion process for aggressive language. Using the analysis results obtained in step 3 as input, it performs data conversion to replace aggressive language with polite language, and outputs the converted polite communication message. 【0119】 Step 5: 【0120】 The server compares the converted message with the destination information and adjusts the wording to suit the recipient. The input is the corrected message, which is the output of step 4, and appropriate corrections based on the destination are applied. The output is the final version of the message. 【0121】 Step 6: 【0122】 The server checks whether the language is polite, especially in the case of financial transactions, and makes any necessary corrections. The input is the communication obtained in step 5, and the output is the communication corrected to be appropriate for the other party. 【0123】 Step 7: 【0124】 The server then returns the final, corrected communication to the user's terminal. The user can review it and make further edits as needed. The output from step 6 is used as input and is presented to the user as a confirmation screen. 【0125】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0126】 This invention is a system that analyzes user-transmitted messages, incorporates an emotion engine, and automatically corrects the messages while recognizing the user's emotions. This system is particularly useful in today's world where online interactions are prevalent, as it facilitates smoother communication. The system is implemented via a server, terminal, and user. 【0127】 First, the user inputs a message using the device, and the emotion engine monitors the user's emotional state. The emotion engine recognizes emotions by analyzing the user's facial expressions, voice tone, input speed, etc., through the camera and microphone. Based on this analysis, it identifies the user's emotional state, and a corresponding correction process is then carried out. 【0128】 When a message is entered, the terminal sends the message and user sentiment information to the server. The server uses natural language processing technology to analyze the message, detect offensive language, and convert it into appropriate, polite language. It also corrects typos and adjusts the wording to be appropriate based on the recipient information. 【0129】 Furthermore, based on the emotion engine's evaluation, the tone and emphasis of the message are adjusted to match the user's emotions. For example, if the user is feeling anxious or irritated, the message is transformed into a calmer, more friendly tone to prevent misunderstandings. This process generates the final message. 【0130】 Finally, the terminal receives the revised message from the server and presents its contents to the user. The user reviews the revisions, makes any necessary additional corrections, and if there are no problems, sends the message for the final time. 【0131】 This system allows users to send precise messages while minimizing the influence of their own emotions. It contributes to more efficient business communication and the elimination of misunderstandings. 【0132】 The following describes the processing flow. 【0133】 Step 1: 【0134】 The user activates the emotion engine on their device while typing their message. The emotion engine analyzes the user's facial expressions and voice tone in real time through the camera and microphone, and determines their emotional state in conjunction with their typing speed. 【0135】 Step 2: 【0136】 The terminal sends the user's input message and emotional state data to the server. Emotional states include categories such as joy, anger, and sadness. 【0137】 Step 3: 【0138】 The server analyzes the received communication using natural language processing technology. It identifies aggressive expressions in the communication based on sentiment data and converts them into more polite expressions. 【0139】 Step 4: 【0140】 The server identifies typographical errors and grammatical mistakes in the communication using a dictionary database and independently corrects them with appropriate candidates based on the context. 【0141】 Step 5: 【0142】 The server adjusts the tone of its communication based on the user's emotional state. For example, if the user is irritated, it will change the language of the message to a more relaxed tone. 【0143】 Step 6: 【0144】 Based on the recipient information, the server incorporates appropriate honorifics and language into the message. If there are multiple recipients, adjustments are made individually to suit each recipient. 【0145】 Step 7: 【0146】 The terminal receives the modified communication message from the server. The user can review its contents and make further manual corrections if necessary. 【0147】 Step 8: 【0148】 After the user has made final confirmation of the revisions, they perform the send operation. The message is then sent to the specified recipient via the terminal. 【0149】 These steps make it easier for users to communicate their intended message accurately, without being influenced by their emotions. 【0150】 (Example 2) 【0151】 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 will be referred to as the "terminal." 【0152】 In modern digital communication, misunderstandings and inappropriate expressions influenced by emotions often occur, hindering smooth communication. This problem is particularly pronounced in email and chat communications, where the sender's emotional state can influence the tone and expression of the message. Therefore, there is a need for a system that automatically corrects emotionally-based misunderstandings and inappropriate expressions to ensure smooth and appropriate communication. 【0153】 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. 【0154】 In this invention, the server includes means for analyzing the input electronic message and converting aggressive expressions into polite language; means for automatically correcting typographical errors based on context using a natural language processing engine; means for adjusting the writing style to an appropriate style based on recipient information; means for identifying the sender's emotional state using facial recognition technology and voice analysis technology and adjusting the tone of the electronic message based on that emotion; and means for presenting the corrected electronic message and enabling the user to review and make further corrections to its content. This enables smooth and accurate messaging that is not influenced by the sender's emotions. 【0155】 "Electronic message" refers to text-based communication content transmitted via digital media. 【0156】 "Aggressive language" refers to words or phrases that may cause offense or hostility in the recipient. 【0157】 "Polite language" refers to expressions that are easy for the recipient to understand and are polite. 【0158】 A "natural language processing engine" is a system that utilizes technology to allow computer programs to analyze and understand human language. 【0159】 "Context-based automatic correction" refers to the process of analyzing the context of the input language data and correcting typos, grammatical errors, and other mistakes. 【0160】 "Recipient information" refers to information about the recipient of an electronic message, and an appropriate writing style is selected based on this information. 【0161】 "Facial recognition technology" refers to the technology that analyzes an individual's facial image to identify specific emotional states or characteristics. 【0162】 "Voice analysis technology" refers to the technology that analyzes voice data and detects the emotions and voice characteristics contained within it. 【0163】 "Emotional state" refers to a category that reflects the mental state an individual is experiencing in a particular situation. 【0164】 "Adjusting the tone" refers to the act of changing the tone or atmosphere of an electronic message to make it more appropriate for the recipient. 【0165】 "Additional modifications" refers to the process by which a user further edits the presented electronic message, adjusting it to best reflect their intended meaning. 【0166】 This system is a platform for facilitating digital communication. Specifically, it's a mechanism where terminals collect electronic messages entered by users, and servers process them. This process utilizes multiple hardware and software technologies. 【0167】 First, the user enters an electronic message using a terminal. This terminal is equipped with a camera and microphone for facial recognition and voice analysis. General image processing software (e.g., computer vision library) is used for facial recognition, and a voice analysis library (e.g., speech recognition engine) is used for voice analysis. This allows the user's emotional state to be captured in real time. 【0168】 Next, the device sends the acquired sentiment data and electronic message to the server. On the server, a natural language processing engine (e.g., a generative AI model) runs to analyze the message content. In this process, offensive language is detected and converted, the writing style is adjusted to an appropriate level based on the recipient information, and typographical errors are corrected. Furthermore, the tone and expression of the message are adjusted based on the acquired sentiment data. 【0169】 This allows the server to modify the message in a way that is not influenced by emotions and send it to the terminal. The terminal then presents the modified message from the server to the user, who can review it and make further modifications as needed. The message, once finally approved by the user, is sent to the specified recipient. 【0170】 For example, if a user reports being late for work and frantically types "I'm late! I'll be right there!", this system will convert it to "I'm sorry, I'm late. I'll be right on my way." An example of a prompt would be, "Please correct the message in the work report to a calm and polite tone." By using this prompt, the generative AI model helps construct an appropriate message. 【0171】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0172】 Step 1: 【0173】 The user enters electronic messages using the terminal. This input utilizes a text editor or messaging application. Simultaneously, the terminal's camera and microphone activate, capturing the user's facial expressions and voice in real time. This acquires facial expression and voice data. This input data is then used by facial recognition and voice analysis technologies to identify the user's emotional state. 【0174】 Step 2: 【0175】 The terminal sends the input electronic message and acquired emotional data (facial expressions and voice) to the server. This data is structured in a format such as JSON. The server uses a natural language processing engine to analyze the content of the received electronic message. It performs data processing such as grammatical analysis and keyword extraction on the text data received as input to detect aggressive expressions and typographical errors. 【0176】 Step 3: 【0177】 The server translates aggressive language into polite language based on data analyzed by a natural language processing engine. It also adjusts the style based on the recipient information. Furthermore, based on sentiment data, a generative AI model generates prompts to adjust the tone of the message. For example, if the user is expressing frustration, the message is rewritten to a calmer tone. The output is a modified and adjusted electronic message. 【0178】 Step 4: 【0179】 The server sends the revised electronic message to the terminal. The terminal displays the received message on its screen, allowing the user to review its contents. The user can make further revisions as needed. This interface includes visual elements such as drag-and-drop and click operations. 【0180】 Step 5: 【0181】 Finally, once the user approves the revisions, the device sends the finalized electronic message to the designated recipient. The output is the appropriately revised message delivered to the recipient. This ensures that communication accurately reflects the sender's intent. 【0182】 (Application Example 2) 【0183】 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". 【0184】 Modern online communication frequently leads to misunderstandings and unnecessary conflicts. This problem is particularly pronounced when information is transmitted while emotions are heightened. Inappropriate expressions and aggressive language based on emotions can hinder communication and cause serious problems in business and personal relationships. To solve these problems, there is a need for technology that accurately analyzes users' emotions and generates information that appropriately reflects them. 【0185】 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. 【0186】 In this invention, the server includes means for analyzing input information and converting aggressive expressions into polite expressions, means for performing grammatical analysis and automatically correcting typographical errors and omissions based on context, means for adjusting the language to be appropriate based on the information to be received, and means for identifying the user's emotional state and changing the expression according to the emotion based on a predetermined expression style. As a result, the information entered by the user can be converted into appropriate and refined content so as not to cause misunderstandings. 【0187】 "Inputted information" refers to strings of characters or sentences of data provided by the user to the information processing device. 【0188】 "Aggressive language" refers to language that may cause offense or hostility in the recipient. 【0189】 "Polite expression" refers to an expression that has been adjusted to be received respectfully and favorably by the recipient. 【0190】 "Grammar analysis" is the process of analyzing the linguistic structure of input information and organizing it into a normalized format. 【0191】 "Typographical errors" refer to incorrect or missing characters included in information. 【0192】 "Recipient information" refers to data about a specific individual or organization to which the information is being sent. 【0193】 "Emotional state" refers to the psychological state of a user, as judged from their facial expressions, tone of voice, and other factors. 【0194】 "Expressive style" refers to a set of methods of expression that include the tone and intonation of information. 【0195】 A description of the embodiment for carrying out the invention will be provided. 【0196】 This system begins with the user entering information into a terminal. The entered information is immediately sent to a server where it is processed. The server first uses a camera and microphone to collect the user's facial expressions and voice tone in order to analyze the emotions contained in the input information. This emotion data is processed using OpenCV and TENSORFLOW® technologies. Once the emotion analysis is complete, natural language processing technology is used to detect aggressive expressions in the input information and convert them into polite expressions. Grammatical analysis is also performed at this time, and typos and omissions are automatically corrected. In this way, the information is adjusted so that it uses language appropriate for the recipient. 【0197】 It is also the server's role to change the style of information presentation based on the user's emotions. If the user is feeling anxious or frustrated, the server will transform the content into a calm and friendly tone to prevent those emotions from being misunderstood. The final information is sent from the server to the terminal and presented to the user. The user reviews the revised information and, if satisfied, can finally submit it. This process enables users to submit accurate and courteous information that is not influenced by emotions. 【0198】 As a concrete example, consider comments on a video streaming service. If a user tries to send a message like, "I don't understand why they did this!", this system detects that emotion and transforms it into a friendly and constructive tone such as, "I'd like to know more about this part. Could you tell me?" 【0199】 An example of a prompt to input into a generative AI model is: "Please suggest how to edit a comment entered by a user in an angry state to avoid misunderstandings, transforming it into a friendly and constructive tone." 【0200】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0201】 Step 1: 【0202】 The user enters information into the terminal. The entered strings and sentences are sent to the server as basic data for subsequent processing. At this stage, the data is structured according to a specific format and protocol, and prepared for the server to receive. 【0203】 Step 2: 【0204】 The server first collects user emotion data in order to analyze the received information. It captures the user's facial expressions and voice information using the device's camera and microphone, and processes this data using TensorFlow or OpenCV. The input is audio and video data, and the output is an evaluation value indicating the user's emotional state. 【0205】 Step 3: 【0206】 The server performs natural language processing on the input string based on sentiment evaluation. The input is data that combines the user's string information with sentiment evaluation, and the output is the result of identifying offensive expressions. It uses Python and the NLTK library to detect offensive words and phrases. 【0207】 Step 4: 【0208】 If offensive language is detected, the server converts it into polite language. Here, a generative AI model is used to replace the input offensive language with polite language according to the prompt. The output is the corrected language, replacing the original sentence. 【0209】 Step 5: 【0210】 Grammar analysis is performed as part of natural language processing. The server automatically corrects typos and grammatical errors in the received text, providing smoother and more readable text. The input is the user's text, and the output is a corrected, structured text. 【0211】 Step 6: 【0212】 The server selects the most appropriate language based on the recipient information. It analyzes the specified recipient information and adjusts the sentence style appropriately. At this stage, the input is the corrected sentence and recipient information, and the output is the sentence adjusted to suit the recipient. 【0213】 Step 7: 【0214】 Finally, the corrected information is sent to the terminal and presented to the user. The user can review the output and make further corrections as needed. As a result, the completed information is ready for transmission. 【0215】 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. 【0216】 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. 【0217】 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. 【0218】 [Second Embodiment] 【0219】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0220】 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. 【0221】 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). 【0222】 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. 【0223】 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. 【0224】 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). 【0225】 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. 【0226】 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. 【0227】 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. 【0228】 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. 【0229】 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. 【0230】 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". 【0231】 This invention relates to a system that analyzes user-generated messages and automatically modifies them as needed. This system is implemented by a server, a terminal, and the user. 【0232】 First, the user enters the message using their device and prepares to send it. When the user presses the send button, the entered message is sent to the server. The server analyzes the received message, performs sentiment analysis using a specific method, and detects offensive language. 【0233】 The server utilizes a database to convert aggressive expressions into more positive and polite ones. This database contains common aggressive expressions and their corresponding polite equivalents. For example, the expression "What are you doing?" is converted to "Could you tell me what the current situation is?" 【0234】 Next, the server detects typographical errors in the communication. It evaluates the entire text using contextual analysis techniques and identifies the appropriate word by referring to a dictionary database. Once the typographical errors are corrected, a corrected version is generated while maintaining the consistency of the original communication. 【0235】 Furthermore, the server verifies the recipient information and evaluates whether the content of the message is appropriate for the recipient. By applying appropriate honorifics and language according to the recipient, communication is facilitated. 【0236】 Ultimately, the terminal receives the revised message from the server. The user can review the revisions and make further corrections as needed. This entire process ensures that the user can send reliable and polite messages. 【0237】 This system is useful not only for business purposes but also for individual email communication. The invention reduces the burden on the user and minimizes the possibility of misunderstanding, thereby enabling efficient communication. 【0238】 The following describes the processing flow. 【0239】 Step 1: 【0240】 The user enters the message on the terminal and specifies the required recipient. Once ready to send, the user presses the send button to send the message to the server. 【0241】 Step 2: 【0242】 The server analyzes the communication received from the user. It uses natural language processing techniques to deepen its understanding of the context and performs syntactic analysis to evaluate the entire text. 【0243】 Step 3: 【0244】 The server uses the analysis results to detect offensive expressions in the communication. It then compares them with a dedicated database and converts the detected expressions into appropriate, polite phrasing. 【0245】 Step 4: 【0246】 The server continues grammatical analysis, identifying typographical errors and grammatical mistakes in the communication. Based on the dictionary database, it automatically corrects typographical errors with words appropriate to the context. 【0247】 Step 5: 【0248】 The server checks the specified destination information and inserts or adjusts appropriate honorifics and language in the message according to the destination. 【0249】 Step 6: 【0250】 The terminal receives the revised communication from the server. The user reviews the revisions and makes any further corrections if necessary. 【0251】 Step 7: 【0252】 Once the user confirms that there are no problems with the revised message, they perform an approval operation, and the final transmission takes place. 【0253】 In this way, the system pays attention to the quality of the message and how the recipient receives it, supporting smooth communication. 【0254】 (Example 1) 【0255】 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." 【0256】 In modern communication, inappropriate expressions of emotion in messages can lead to misunderstandings and offense. Furthermore, typographical errors and inappropriate language use can hinder effective communication. Additionally, using appropriate honorifics for different recipients can be burdensome for users. The challenge lies in resolving these issues and achieving efficient and polite dialogue. 【0257】 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. 【0258】 In this invention, the server includes means for analyzing input information and converting aggressive expressions into polite expressions, means for performing syntactic analysis and automatically correcting typographical errors and omissions based on context, and means for adjusting the expression to an appropriate one based on the recipient information. This enables users to send communications that are emotionally neutral, accurate, and respectful. 【0259】 "Inputted information" refers to the text and data that the user sends to the server via the system. 【0260】 "Aggressive language" refers to linguistic expressions that may cause discomfort or rejection in others. 【0261】 "Polite language" refers to courteous expressions used to show respect to the other person and to promote good communication. 【0262】 Syntactic analysis is a technique that analyzes the structure of a text and clarifies the relationships between words and phrases. 【0263】 "Typographical errors" refer to spelling mistakes or missing characters in the entered information. 【0264】 "Automatic correction" refers to a process in which a system corrects typographical errors and grammatical mistakes to an appropriate form based on the context. 【0265】 "Recipient information" refers to information about the destination of a message, and is data used to identify the recipient at the destination. 【0266】 "Sentiment analysis" is a technique that analyzes linguistic expressions in a text and evaluates their emotional tone and nuances. 【0267】 A "generative model" is an artificial intelligence model that learns from large amounts of data to generate or transform text. 【0268】 This invention is a system that analyzes information entered by a user using a generation terminal and modifies it into appropriate expressions. Upon receiving this information, the server first performs sentiment analysis using a generation AI model. If aggressive expressions are detected, the server consults a database for converting them into polite expressions and modifies the expressions appropriately. The software used includes a natural language processing library and a dictionary database. 【0269】 Next, the server performs syntactic analysis of the communication and automatically corrects typos and grammatical errors based on context. This process utilizes advanced natural language processing techniques to select the correct words while maintaining the overall coherence of the sentence. 【0270】 Furthermore, the system verifies recipient information and applies appropriate language based on the user's specified recipient. This ensures that respectful expressions are used, facilitating smoother communication. 【0271】 Finally, the server sends the corrected information to the terminal for the user to review. The user can make further corrections as needed. This system can be used with various communication tools, such as email and messaging applications. 【0272】 For example, if a user enters the sentence "What are you doing?", the server will correct it to "Could you tell me what the current situation is?". An example of a prompt from the generating AI model is "Please make this more polite: 'What are you doing?'". In this way, users can send information using polite language and avoid misunderstandings. 【0273】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0274】 Step 1: 【0275】 The user enters the message using the terminal. The entered data is temporarily stored on the terminal and sent to the server when the communication button is pressed. The input is passed to the server as text data. 【0276】 Step 2: 【0277】 The server processes the received message using a data analysis module and initiates sentiment analysis. In this step, a generative AI model is used to assign a sentiment score to each word in the message. The output is data with each word assigned a sentiment score. 【0278】 Step 3: 【0279】 The server identifies offensive language based on sentiment scores and converts it to polite language as needed. Here, the server consults a conversion database, finds offensive language, and replaces it with registered polite language. The output is the corrected text. 【0280】 Step 4: 【0281】 The server processes the corrected message through its syntactic analysis engine, correcting typos and grammatical errors based on the context. The entire sentence is analyzed, and errors are corrected with appropriate words from the existing dictionary. The output is a grammatically correct sentence. 【0282】 Step 5: 【0283】 The server analyzes the destination information and applies appropriate diction according to the attributes of the recipient. In this process, honorific expressions and greetings based on the destination information are reflected in the communication text. The output is a text appropriately customized for the recipient. 【0284】 Step 6: 【0285】 The server sends the modified communication text to the terminal and prompts the user to confirm the content. The user checks the modified content on the terminal and manually makes further modifications if necessary. The final output is the communication text confirmed or further modified by the user. 【0286】 (Application Example 1) 【0287】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0288】 In electronic communication, it is an issue to prevent misunderstandings and troubles caused by aggression that may occur between individuals, and to perform important responses in financial transactions politely. Also, it is required to ensure the accuracy of information and smooth communication by automatically correcting typos and adopting appropriate expressions according to the destination. 【0289】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0290】 In this invention, the server includes means for analyzing the input information, detecting aggressive expressions, and converting them into polite expressions; means for performing syntactic analysis and automatically correcting typos based on the context; means for adjusting to appropriate diction based on the destination information; and means for correctly converting the communication with the counterpart in financial transactions. Thereby, it becomes possible to smoothly and politely conduct communication between individuals. 【0291】 "Inputted information" refers to communication data that a user sends to the system using their device. 【0292】 "Aggressive language" refers to words or phrases that may cause offense or hostility in the recipient. 【0293】 "Polite expression" refers to a method of expression that shows respect to the recipient and facilitates smooth communication. 【0294】 "Syntactic analysis" refers to the technique of analyzing grammatical structure and performing accurate semantic interpretation. 【0295】 "Typographical errors" refer to spelling mistakes or omissions that occur when a user enters data. 【0296】 "Context-based automatic correction" refers to a process that performs optimal proofreading based on the context and meaning of the input content. 【0297】 "Recipient information" refers to data about the individual or group to whom the communication is being sent. 【0298】 "Counterparty in financial transactions" refers to the party involved in electronic payments, fund transfers, and other financial transactions. 【0299】 "To politely rephrase" refers to changing aggressive or inappropriate language into milder and more appropriate language. 【0300】 This invention is realized by having a server analyze and modify communication messages entered by a user using a communication terminal. Upon receiving a communication message, the server first performs linguistic analysis to detect offensive expressions. The detected expressions are converted to appropriate expressions by referring to a pre-prepared database of polite expressions. This process utilizes sentiment analysis software such as TextBlob and EmotionAnalyzer, which are natural language processing libraries. 【0301】 Next, the server detects typos and missing characters in the communication text and performs automatic correction based on the context. TextBlob is also utilized in this process. Further, based on the destination information, the content is adjusted so that the most appropriate diction is applied to the user. For this reason, expression conversion rules for each destination are registered in the database. 【0302】 Furthermore, in communication texts related to financial transactions, the server performs special processing to convert the expression in a polite manner so as not to cause misunderstanding to the counterpart. As a result, the user can proceed with the transaction with confidence. 【0303】 Finally, the corrected communication text is sent back to the terminal, and the user can check it and make further edits if necessary. As a specific example, when the user attempts to send an expression like "Hurry up and refund!" this system converts it to "Could you please refund?" to mitigate the impact on the recipient. 【0304】 An example of a prompt text is as follows. 【0305】 "Please implement a program to carefully correct the message that the user sends to the counterpart in a financial transaction. Aggressive expressions are converted politely." 【0306】 The flow of the specific processing in Application Example 1 will be described using FIG. 12. 【0307】 Step 1: 【0308】 The server receives the communication text sent from the user. As input, it acquires the communication text input by the user from the terminal. In this step, the content of the communication text itself is the main data. 【0309】 Step 2: 【0310】 The server performs syntactic analysis on the received communication text using the TextBlob natural language processing library. The communication text received in step 1 is used as input, and its grammatical structure is analyzed. As a result, typos and omissions are detected, and a text with appropriate spelling corrections is output. 【0311】 Step 3: 【0312】 The server uses EmotionAnalyzer to perform sentiment analysis on the communication text. Here, the modified text from step 2 is input, and data processing is performed to assign a sentiment score to each word. As a result, aggressive expressions throughout the text are identified. 【0313】 Step 4: 【0314】 The server refers to a pre-configured database of polite expressions and performs a conversion process for aggressive language. Using the analysis results obtained in step 3 as input, it performs data conversion to replace aggressive language with polite language, and outputs the converted polite communication message. 【0315】 Step 5: 【0316】 The server compares the converted message with the destination information and adjusts the wording to suit the recipient. The input is the corrected message, which is the output of step 4, and appropriate corrections based on the destination are applied. The output is the final version of the message. 【0317】 Step 6: 【0318】 The server checks whether the language is polite, especially in the case of financial transactions, and makes any necessary corrections. The input is the communication obtained in step 5, and the output is the communication corrected to be appropriate for the other party. 【0319】 Step 7: 【0320】 The server then returns the final, corrected communication to the user's terminal. The user can review it and make further edits as needed. The output from step 6 is used as input and is presented to the user as a confirmation screen. 【0321】 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. 【0322】 This invention is a system that analyzes user-transmitted messages, incorporates an emotion engine, and automatically corrects the messages while recognizing the user's emotions. This system is particularly useful in today's world where online interactions are prevalent, as it facilitates smoother communication. The system is implemented via a server, terminal, and user. 【0323】 First, the user inputs a message using the device, and the emotion engine monitors the user's emotional state. The emotion engine recognizes emotions by analyzing the user's facial expressions, voice tone, input speed, etc., through the camera and microphone. Based on this analysis, it identifies the user's emotional state, and a corresponding correction process is then carried out. 【0324】 When a message is entered, the terminal sends the message and user sentiment information to the server. The server uses natural language processing technology to analyze the message, detect offensive language, and convert it into appropriate, polite language. It also corrects typos and adjusts the wording to be appropriate based on the recipient information. 【0325】 Furthermore, based on the emotion engine's evaluation, the tone and emphasis of the message are adjusted to match the user's emotions. For example, if the user is feeling anxious or irritated, the message is transformed into a calmer, more friendly tone to prevent misunderstandings. This process generates the final message. 【0326】 Finally, the terminal receives the revised message from the server and presents its contents to the user. The user reviews the revisions, makes any necessary additional corrections, and if there are no problems, sends the message for the final time. 【0327】 This system allows users to send precise messages while minimizing the influence of their own emotions. It contributes to more efficient business communication and the elimination of misunderstandings. 【0328】 The following describes the processing flow. 【0329】 Step 1: 【0330】 The user activates the emotion engine on their device while typing their message. The emotion engine analyzes the user's facial expressions and voice tone in real time through the camera and microphone, and determines their emotional state in conjunction with their typing speed. 【0331】 Step 2: 【0332】 The terminal sends the user's input message and emotional state data to the server. Emotional states include categories such as joy, anger, and sadness. 【0333】 Step 3: 【0334】 The server analyzes the received communication using natural language processing technology. It identifies aggressive expressions in the communication based on sentiment data and converts them into more polite expressions. 【0335】 Step 4: 【0336】 The server identifies typographical errors and grammatical mistakes in the communication using a dictionary database and independently corrects them with appropriate candidates based on the context. 【0337】 Step 5: 【0338】 The server adjusts the tone of its communication based on the user's emotional state. For example, if the user is irritated, it will change the language of the message to a more relaxed tone. 【0339】 Step 6: 【0340】 Based on the recipient information, the server incorporates appropriate honorifics and language into the message. If there are multiple recipients, adjustments are made individually to suit each recipient. 【0341】 Step 7: 【0342】 The terminal receives the modified communication message from the server. The user can review its contents and make further manual corrections if necessary. 【0343】 Step 8: 【0344】 After the user has made final confirmation of the revisions, they perform the send operation. The message is then sent to the specified recipient via the terminal. 【0345】 These steps make it easier for users to communicate their intended message accurately, without being influenced by their emotions. 【0346】 (Example 2) 【0347】 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". 【0348】 In modern digital communication, misunderstandings and inappropriate expressions influenced by emotions often occur, hindering smooth communication. This problem is particularly pronounced in email and chat communications, where the sender's emotional state can influence the tone and expression of the message. Therefore, there is a need for a system that automatically corrects emotionally-based misunderstandings and inappropriate expressions to ensure smooth and appropriate communication. 【0349】 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. 【0350】 In this invention, the server includes means for analyzing the input electronic message and converting aggressive expressions into polite language; means for automatically correcting typographical errors based on context using a natural language processing engine; means for adjusting the writing style to an appropriate style based on recipient information; means for identifying the sender's emotional state using facial recognition technology and voice analysis technology and adjusting the tone of the electronic message based on that emotion; and means for presenting the corrected electronic message and enabling the user to review and make further corrections to its content. This enables smooth and accurate messaging that is not influenced by the sender's emotions. 【0351】 "Electronic message" refers to text-based communication content transmitted via digital media. 【0352】 "Aggressive language" refers to words or phrases that may cause offense or hostility in the recipient. 【0353】 "Polite language" refers to expressions that are easy for the recipient to understand and are polite. 【0354】 A "natural language processing engine" is a system that utilizes technology to allow computer programs to analyze and understand human language. 【0355】 "Context-based automatic correction" refers to the process of analyzing the context of the input language data and correcting typos, grammatical errors, and other mistakes. 【0356】 "Recipient information" refers to information about the recipient of an electronic message, and an appropriate writing style is selected based on this information. 【0357】 "Facial recognition technology" refers to the technology that analyzes an individual's facial image to identify specific emotional states or characteristics. 【0358】 "Voice analysis technology" refers to the technology that analyzes voice data and detects the emotions and voice characteristics contained within it. 【0359】 "Emotional state" refers to a category that reflects the mental state an individual is experiencing in a particular situation. 【0360】 "Adjusting the tone" refers to the act of changing the tone or atmosphere of an electronic message to make it more appropriate for the recipient. 【0361】 "Additional modifications" refers to the process by which a user further edits the presented electronic message, adjusting it to best reflect their intended meaning. 【0362】 This system is a platform for facilitating digital communication. Specifically, it's a mechanism where terminals collect electronic messages entered by users, and servers process them. This process utilizes multiple hardware and software technologies. 【0363】 First, the user enters an electronic message using a terminal. This terminal is equipped with a camera and microphone for facial recognition and voice analysis. General image processing software (e.g., computer vision library) is used for facial recognition, and a voice analysis library (e.g., speech recognition engine) is used for voice analysis. This allows the user's emotional state to be captured in real time. 【0364】 Next, the device sends the acquired sentiment data and electronic message to the server. On the server, a natural language processing engine (e.g., a generative AI model) runs to analyze the message content. In this process, offensive language is detected and converted, the writing style is adjusted to an appropriate level based on the recipient information, and typographical errors are corrected. Furthermore, the tone and expression of the message are adjusted based on the acquired sentiment data. 【0365】 This allows the server to modify the message in a way that is not influenced by emotions and send it to the terminal. The terminal then presents the modified message from the server to the user, who can review it and make further modifications as needed. The message, once finally approved by the user, is sent to the specified recipient. 【0366】 For example, if a user reports being late for work and frantically types "I'm late! I'll be right there!", this system will convert it to "I'm sorry, I'm late. I'll be right on my way." An example of a prompt would be, "Please correct the message in the work report to a calm and polite tone." By using this prompt, the generative AI model helps construct an appropriate message. 【0367】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0368】 Step 1: 【0369】 The user enters electronic messages using the terminal. This input utilizes a text editor or messaging application. Simultaneously, the terminal's camera and microphone activate, capturing the user's facial expressions and voice in real time. This acquires facial expression and voice data. This input data is then used by facial recognition and voice analysis technologies to identify the user's emotional state. 【0370】 Step 2: 【0371】 The terminal sends the input electronic message and acquired emotional data (facial expressions and voice) to the server. This data is structured in a format such as JSON. The server uses a natural language processing engine to analyze the content of the received electronic message. It performs data processing such as grammatical analysis and keyword extraction on the text data received as input to detect aggressive expressions and typographical errors. 【0372】 Step 3: 【0373】 The server translates aggressive language into polite language based on data analyzed by a natural language processing engine. It also adjusts the style based on the recipient information. Furthermore, based on sentiment data, a generative AI model generates prompts to adjust the tone of the message. For example, if the user is expressing frustration, the message is rewritten to a calmer tone. The output is a modified and adjusted electronic message. 【0374】 Step 4: 【0375】 The server sends the revised electronic message to the terminal. The terminal displays the received message on its screen, allowing the user to review its contents. The user can make further revisions as needed. This interface includes visual elements such as drag-and-drop and click operations. 【0376】 Step 5: 【0377】 Finally, once the user approves the revisions, the device sends the finalized electronic message to the designated recipient. The output is the appropriately revised message delivered to the recipient. This ensures that communication accurately reflects the sender's intent. 【0378】 (Application Example 2) 【0379】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0380】 Modern online communication frequently leads to misunderstandings and unnecessary conflicts. This problem is particularly pronounced when information is transmitted while emotions are heightened. Inappropriate expressions and aggressive language based on emotions can hinder communication and cause serious problems in business and personal relationships. To solve these problems, there is a need for technology that accurately analyzes users' emotions and generates information that appropriately reflects them. 【0381】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0382】 In this invention, the server includes means for analyzing input information and converting aggressive expressions into polite expressions, means for performing grammatical analysis and automatically correcting typographical errors and omissions based on context, means for adjusting the language to be appropriate based on the information to be received, and means for identifying the user's emotional state and changing the expression according to the emotion based on a predetermined expression style. As a result, the information entered by the user can be converted into appropriate and refined content so as not to cause misunderstandings. 【0383】 "Inputted information" refers to strings of characters or sentences of data provided by the user to the information processing device. 【0384】 "Aggressive language" refers to language that may cause offense or hostility in the recipient. 【0385】 "Polite expression" refers to an expression that has been adjusted to be received respectfully and favorably by the recipient. 【0386】 "Grammar analysis" is the process of analyzing the linguistic structure of input information and organizing it into a normalized format. 【0387】 "Typographical errors" refer to incorrect or missing characters included in information. 【0388】 "Recipient information" refers to data about a specific individual or organization to which the information is being sent. 【0389】 "Emotional state" refers to the psychological state of a user, as judged from their facial expressions, tone of voice, and other factors. 【0390】 "Expressive style" refers to a set of methods of expression that include the tone and intonation of information. 【0391】 A description of the embodiment for carrying out the invention will be provided. 【0392】 This system begins with the user entering information into a terminal. The entered information is immediately sent to a server where it is processed. The server first uses a camera and microphone to collect the user's facial expressions and voice tone in order to analyze the emotions contained in the input information. This emotion data is processed using OpenCV and TensorFlow technologies. Once the emotion analysis is complete, natural language processing technology is used to detect aggressive expressions in the input information and convert them into polite expressions. Grammatical analysis is also performed at this time, and typos and omissions are automatically corrected. In this way, the information is adjusted so that it uses language appropriate for the recipient. 【0393】 It is also the server's role to change the style of information presentation based on the user's emotions. If the user is feeling anxious or frustrated, the server will transform the content into a calm and friendly tone to prevent those emotions from being misunderstood. The final information is sent from the server to the terminal and presented to the user. The user reviews the revised information and, if satisfied, can finally submit it. This process enables users to submit accurate and courteous information that is not influenced by emotions. 【0394】 As a concrete example, consider comments on a video streaming service. If a user tries to send a message like, "I don't understand why they did this!", this system detects that emotion and transforms it into a friendly and constructive tone such as, "I'd like to know more about this part. Could you tell me?" 【0395】 An example of a prompt to input into a generative AI model is: "Please suggest how to edit a comment entered by a user in an angry state to avoid misunderstandings, transforming it into a friendly and constructive tone." 【0396】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0397】 Step 1: 【0398】 The user enters information into the terminal. The entered strings and sentences are sent to the server as basic data for subsequent processing. At this stage, the data is structured according to a specific format and protocol, and prepared for the server to receive. 【0399】 Step 2: 【0400】 The server first collects user emotion data in order to analyze the received information. It captures the user's facial expressions and voice information using the device's camera and microphone, and processes this data using TensorFlow or OpenCV. The input is audio and video data, and the output is an evaluation value indicating the user's emotional state. 【0401】 Step 3: 【0402】 The server performs natural language processing on the input string based on sentiment evaluation. The input is data that combines the user's string information with sentiment evaluation, and the output is the result of identifying offensive expressions. It uses Python and the NLTK library to detect offensive words and phrases. 【0403】 Step 4: 【0404】 If offensive language is detected, the server converts it into polite language. Here, a generative AI model is used to replace the input offensive language with polite language according to the prompt. The output is the corrected language, replacing the original sentence. 【0405】 Step 5: 【0406】 Grammar analysis is performed as part of natural language processing. The server automatically corrects typos and grammatical errors in the received text, providing smoother and more readable text. The input is the user's text, and the output is a corrected, structured text. 【0407】 Step 6: 【0408】 The server selects the most appropriate language based on the recipient information. It analyzes the specified recipient information and adjusts the sentence style appropriately. At this stage, the input is the corrected sentence and recipient information, and the output is the sentence adjusted to suit the recipient. 【0409】 Step 7: 【0410】 Finally, the corrected information is sent to the terminal and presented to the user. The user can review the output and make further corrections as needed. As a result, the completed information is ready for transmission. 【0411】 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. 【0412】 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. 【0413】 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. 【0414】 [Third Embodiment] 【0415】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0416】 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. 【0417】 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). 【0418】 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. 【0419】 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. 【0420】 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). 【0421】 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. 【0422】 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. 【0423】 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. 【0424】 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. 【0425】 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. 【0426】 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". 【0427】 This invention relates to a system that analyzes user-generated messages and automatically modifies them as needed. This system is implemented by a server, a terminal, and the user. 【0428】 First, the user enters the message using their device and prepares to send it. When the user presses the send button, the entered message is sent to the server. The server analyzes the received message, performs sentiment analysis using a specific method, and detects offensive language. 【0429】 The server utilizes a database to convert aggressive expressions into more positive and polite ones. This database contains common aggressive expressions and their corresponding polite equivalents. For example, the expression "What are you doing?" is converted to "Could you tell me what the current situation is?" 【0430】 Next, the server detects typographical errors in the communication. It evaluates the entire text using contextual analysis techniques and identifies the appropriate word by referring to a dictionary database. Once the typographical errors are corrected, a corrected version is generated while maintaining the consistency of the original communication. 【0431】 Furthermore, the server verifies the recipient information and evaluates whether the content of the message is appropriate for the recipient. By applying appropriate honorifics and language according to the recipient, communication is facilitated. 【0432】 Ultimately, the terminal receives the revised message from the server. The user can review the revisions and make further corrections as needed. This entire process ensures that the user can send reliable and polite messages. 【0433】 This system is useful not only for business purposes but also for individual email communication. The invention reduces the burden on the user and minimizes the possibility of misunderstanding, thereby enabling efficient communication. 【0434】 The following describes the processing flow. 【0435】 Step 1: 【0436】 The user enters the message on the terminal and specifies the required recipient. Once ready to send, the user presses the send button to send the message to the server. 【0437】 Step 2: 【0438】 The server analyzes the communication received from the user. It uses natural language processing techniques to deepen its understanding of the context and performs syntactic analysis to evaluate the entire text. 【0439】 Step 3: 【0440】 The server uses the analysis results to detect offensive expressions in the communication. It then compares them with a dedicated database and converts the detected expressions into appropriate, polite phrasing. 【0441】 Step 4: 【0442】 The server continues grammatical analysis, identifying typographical errors and grammatical mistakes in the communication. Based on the dictionary database, it automatically corrects typographical errors with words appropriate to the context. 【0443】 Step 5: 【0444】 The server checks the specified destination information and inserts or adjusts appropriate honorifics and language in the message according to the destination. 【0445】 Step 6: 【0446】 The terminal receives the revised communication from the server. The user reviews the revisions and makes any further corrections if necessary. 【0447】 Step 7: 【0448】 Once the user confirms that there are no problems with the revised message, they perform an approval operation, and the final transmission takes place. 【0449】 In this way, the system pays attention to the quality of the message and how the recipient receives it, supporting smooth communication. 【0450】 (Example 1) 【0451】 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." 【0452】 In modern communication, inappropriate expressions of emotion in messages can lead to misunderstandings and offense. Furthermore, typographical errors and inappropriate language use can hinder effective communication. Additionally, using appropriate honorifics for different recipients can be burdensome for users. The challenge lies in resolving these issues and achieving efficient and polite dialogue. 【0453】 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. 【0454】 In this invention, the server includes means for analyzing input information and converting aggressive expressions into polite expressions, means for performing syntactic analysis and automatically correcting typographical errors and omissions based on context, and means for adjusting the expression to an appropriate one based on the recipient information. This enables users to send communications that are emotionally neutral, accurate, and respectful. 【0455】 "Inputted information" refers to the text and data that the user sends to the server via the system. 【0456】 "Aggressive language" refers to linguistic expressions that may cause discomfort or rejection in others. 【0457】 "Polite language" refers to courteous expressions used to show respect to the other person and to promote good communication. 【0458】 Syntactic analysis is a technique that analyzes the structure of a text and clarifies the relationships between words and phrases. 【0459】 "Typographical errors" refer to spelling mistakes or missing characters in the entered information. 【0460】 "Automatic correction" refers to a process in which a system corrects typographical errors and grammatical mistakes to an appropriate form based on the context. 【0461】 "Recipient information" refers to information about the destination of a message, and is data used to identify the recipient at the destination. 【0462】 "Sentiment analysis" is a technique that analyzes linguistic expressions in a text and evaluates their emotional tone and nuances. 【0463】 A "generative model" is an artificial intelligence model that learns from large amounts of data to generate or transform text. 【0464】 This invention is a system that analyzes information entered by a user using a generation terminal and modifies it into appropriate expressions. Upon receiving this information, the server first performs sentiment analysis using a generation AI model. If aggressive expressions are detected, the server consults a database for converting them into polite expressions and modifies the expressions appropriately. The software used includes a natural language processing library and a dictionary database. 【0465】 Next, the server performs syntactic analysis of the communication and automatically corrects typos and grammatical errors based on context. This process utilizes advanced natural language processing techniques to select the correct words while maintaining the overall coherence of the sentence. 【0466】 Furthermore, the system verifies recipient information and applies appropriate language based on the user's specified recipient. This ensures that respectful expressions are used, facilitating smoother communication. 【0467】 Finally, the server sends the corrected information to the terminal for the user to review. The user can make further corrections as needed. This system can be used with various communication tools, such as email and messaging applications. 【0468】 For example, if a user enters the sentence "What are you doing?", the server will correct it to "Could you tell me what the current situation is?". An example of a prompt from the generating AI model is "Please make this more polite: 'What are you doing?'". In this way, users can send information using polite language and avoid misunderstandings. 【0469】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0470】 Step 1: 【0471】 The user enters the message using the terminal. The entered data is temporarily stored on the terminal and sent to the server when the communication button is pressed. The input is passed to the server as text data. 【0472】 Step 2: 【0473】 The server processes the received message using a data analysis module and initiates sentiment analysis. In this step, a generative AI model is used to assign a sentiment score to each word in the message. The output is data with each word assigned a sentiment score. 【0474】 Step 3: 【0475】 The server identifies offensive language based on sentiment scores and converts it to polite language as needed. Here, the server consults a conversion database, finds offensive language, and replaces it with registered polite language. The output is the corrected text. 【0476】 Step 4: 【0477】 The server processes the corrected message through its syntactic analysis engine, correcting typos and grammatical errors based on the context. The entire sentence is analyzed, and errors are corrected with appropriate words from the existing dictionary. The output is a grammatically correct sentence. 【0478】 Step 5: 【0479】 The server analyzes the recipient information and applies appropriate language based on the recipient's attributes. During this process, polite expressions and greetings based on the recipient information are reflected in the message. The output is a message appropriately customized for the recipient. 【0480】 Step 6: 【0481】 The server sends the revised communication to the terminal and prompts the user to confirm its contents. The user reviews the revisions on the terminal and makes further manual corrections if necessary. The final output is the communication as reviewed or further modified by the user. 【0482】 (Application Example 1) 【0483】 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." 【0484】 In electronic communication, preventing misunderstandings and aggression that can occur between individuals, and ensuring courteous communication, especially in important financial transactions, are crucial challenges. Furthermore, it is necessary to guarantee accuracy and smooth exchange of information through automatic correction of typographical errors and the adoption of appropriate expressions tailored to the recipient. 【0485】 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. 【0486】 In this invention, the server includes means for analyzing input information, detecting offensive expressions and converting them into polite expressions; means for performing syntactic analysis and automatically correcting typographical errors and omissions based on context; means for adjusting the language to be appropriate based on recipient information; and means for politely translating communications with counterparties in financial transactions. This makes it possible to conduct smooth and polite communication between individuals. 【0487】 "Inputted information" refers to communication data that a user sends to the system using their device. 【0488】 "Aggressive language" refers to words or phrases that may cause offense or hostility in the recipient. 【0489】 "Polite expression" refers to a method of expression that shows respect to the recipient and facilitates smooth communication. 【0490】 "Syntactic analysis" refers to the technique of analyzing grammatical structure and performing accurate semantic interpretation. 【0491】 "Typographical errors" refer to spelling mistakes or omissions that occur when a user enters data. 【0492】 "Context-based automatic correction" refers to a process that performs optimal proofreading based on the context and meaning of the input content. 【0493】 "Recipient information" refers to data about the individual or group to whom the communication is being sent. 【0494】 "Counterparty in financial transactions" refers to the party involved in electronic payments, fund transfers, and other financial transactions. 【0495】 "To politely rephrase" refers to changing aggressive or inappropriate language into milder and more appropriate language. 【0496】 This invention is realized by having a server analyze and modify communication messages entered by a user using a communication terminal. Upon receiving a communication message, the server first performs linguistic analysis to detect offensive expressions. The detected expressions are converted to appropriate expressions by referring to a pre-prepared database of polite expressions. This process utilizes sentiment analysis software such as TextBlob and EmotionAnalyzer, which are natural language processing libraries. 【0497】 Next, the server detects typos and omissions in the communication and automatically corrects them based on the context. TextBlob is also utilized in this process. Furthermore, the content is adjusted to apply the most appropriate language to the user based on the recipient information. For this reason, expression conversion rules for each recipient are registered in the database. 【0498】 Furthermore, the server performs special processing on communications related to financial transactions, transforming the language into polite expressions to prevent misunderstandings with the other party. This allows users to proceed with transactions with peace of mind. 【0499】 Finally, the revised message is sent back to the terminal, where the user can review it and make further edits if necessary. For example, if a user tries to send the phrase "Give me a refund immediately!", this system will convert it to "Could I request a refund?", mitigating the impact on the recipient. 【0500】 An example of a prompt message is as follows: 【0501】 "Please implement a program that politely modifies messages sent by users in financial transactions. It will transform aggressive language into courteous expressions." 【0502】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0503】 Step 1: 【0504】 The server receives the communication message sent by the user. It obtains the communication message entered by the user from the terminal as input. In this step, the content of the communication message itself is the main data. 【0505】 Step 2: 【0506】 The server performs syntactic analysis on the received communication text using the TextBlob natural language processing library. The communication text received in step 1 is used as input, and its grammatical structure is analyzed. As a result, typos and omissions are detected, and a text with appropriate spelling corrections is output. 【0507】 Step 3: 【0508】 The server uses EmotionAnalyzer to perform sentiment analysis on the communication text. Here, the modified text from step 2 is input, and data processing is performed to assign a sentiment score to each word. As a result, aggressive expressions throughout the text are identified. 【0509】 Step 4: 【0510】 The server refers to a pre-configured database of polite expressions and performs a conversion process for aggressive language. Using the analysis results obtained in step 3 as input, it performs data conversion to replace aggressive language with polite language, and outputs the converted polite communication message. 【0511】 Step 5: 【0512】 The server compares the converted message with the destination information and adjusts the wording to suit the recipient. The input is the corrected message, which is the output of step 4, and appropriate corrections based on the destination are applied. The output is the final version of the message. 【0513】 Step 6: 【0514】 The server checks whether the language is polite, especially in the case of financial transactions, and makes any necessary corrections. The input is the communication obtained in step 5, and the output is the communication corrected to be appropriate for the other party. 【0515】 Step 7: 【0516】 The server then returns the final, corrected communication to the user's terminal. The user can review it and make further edits as needed. The output from step 6 is used as input and is presented to the user as a confirmation screen. 【0517】 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. 【0518】 This invention is a system that analyzes user-transmitted messages, incorporates an emotion engine, and automatically corrects the messages while recognizing the user's emotions. This system is particularly useful in today's world where online interactions are prevalent, as it facilitates smoother communication. The system is implemented via a server, terminal, and user. 【0519】 First, the user inputs a message using the device, and the emotion engine monitors the user's emotional state. The emotion engine recognizes emotions by analyzing the user's facial expressions, voice tone, input speed, etc., through the camera and microphone. Based on this analysis, it identifies the user's emotional state, and a corresponding correction process is then carried out. 【0520】 When a message is entered, the terminal sends the message and user sentiment information to the server. The server uses natural language processing technology to analyze the message, detect offensive language, and convert it into appropriate, polite language. It also corrects typos and adjusts the wording to be appropriate based on the recipient information. 【0521】 Furthermore, based on the emotion engine's evaluation, the tone and emphasis of the message are adjusted to match the user's emotions. For example, if the user is feeling anxious or irritated, the message is transformed into a calmer, more friendly tone to prevent misunderstandings. This process generates the final message. 【0522】 Finally, the terminal receives the revised message from the server and presents its contents to the user. The user reviews the revisions, makes any necessary additional corrections, and if there are no problems, sends the message for the final time. 【0523】 This system allows users to send precise messages while minimizing the influence of their own emotions. It contributes to more efficient business communication and the elimination of misunderstandings. 【0524】 The following describes the processing flow. 【0525】 Step 1: 【0526】 The user activates the emotion engine on their device while typing their message. The emotion engine analyzes the user's facial expressions and voice tone in real time through the camera and microphone, and determines their emotional state in conjunction with their typing speed. 【0527】 Step 2: 【0528】 The terminal sends the user's input message and emotional state data to the server. Emotional states include categories such as joy, anger, and sadness. 【0529】 Step 3: 【0530】 The server analyzes the received communication using natural language processing technology. It identifies aggressive expressions in the communication based on sentiment data and converts them into more polite expressions. 【0531】 Step 4: 【0532】 The server identifies typographical errors and grammatical mistakes in the communication using a dictionary database and independently corrects them with appropriate candidates based on the context. 【0533】 Step 5: 【0534】 The server adjusts the tone of its communication based on the user's emotional state. For example, if the user is irritated, it will change the language of the message to a more relaxed tone. 【0535】 Step 6: 【0536】 Based on the recipient information, the server incorporates appropriate honorifics and language into the message. If there are multiple recipients, adjustments are made individually to suit each recipient. 【0537】 Step 7: 【0538】 The terminal receives the modified communication message from the server. The user can review its contents and make further manual corrections if necessary. 【0539】 Step 8: 【0540】 After the user has made final confirmation of the revisions, they perform the send operation. The message is then sent to the specified recipient via the terminal. 【0541】 These steps make it easier for users to communicate their intended message accurately, without being influenced by their emotions. 【0542】 (Example 2) 【0543】 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." 【0544】 In modern digital communication, misunderstandings and inappropriate expressions influenced by emotions often occur, hindering smooth communication. This problem is particularly pronounced in email and chat communications, where the sender's emotional state can influence the tone and expression of the message. Therefore, there is a need for a system that automatically corrects emotionally-based misunderstandings and inappropriate expressions to ensure smooth and appropriate communication. 【0545】 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. 【0546】 In this invention, the server includes means for analyzing the input electronic message and converting aggressive expressions into polite language; means for automatically correcting typographical errors based on context using a natural language processing engine; means for adjusting the writing style to an appropriate style based on recipient information; means for identifying the sender's emotional state using facial recognition technology and voice analysis technology and adjusting the tone of the electronic message based on that emotion; and means for presenting the corrected electronic message and enabling the user to review and make further corrections to its content. This enables smooth and accurate messaging that is not influenced by the sender's emotions. 【0547】 "Electronic message" refers to text-based communication content transmitted via digital media. 【0548】 "Aggressive language" refers to words or phrases that may cause offense or hostility in the recipient. 【0549】 "Polite language" refers to expressions that are easy for the recipient to understand and are polite. 【0550】 A "natural language processing engine" is a system that utilizes technology to allow computer programs to analyze and understand human language. 【0551】 "Context-based automatic correction" refers to the process of analyzing the context of the input language data and correcting typos, grammatical errors, and other mistakes. 【0552】 "Recipient information" refers to information about the recipient of an electronic message, and an appropriate writing style is selected based on this information. 【0553】 "Facial recognition technology" refers to the technology that analyzes an individual's facial image to identify specific emotional states or characteristics. 【0554】 "Voice analysis technology" refers to the technology that analyzes voice data and detects the emotions and voice characteristics contained within it. 【0555】 "Emotional state" refers to a category that reflects the mental state an individual is experiencing in a particular situation. 【0556】 "Adjusting the tone" refers to the act of changing the tone or atmosphere of an electronic message to make it more appropriate for the recipient. 【0557】 "Additional modifications" refers to the process by which a user further edits the presented electronic message, adjusting it to best reflect their intended meaning. 【0558】 This system is a platform for facilitating digital communication. Specifically, it's a mechanism where terminals collect electronic messages entered by users, and servers process them. This process utilizes multiple hardware and software technologies. 【0559】 First, the user enters an electronic message using a terminal. This terminal is equipped with a camera and microphone for facial recognition and voice analysis. General image processing software (e.g., computer vision library) is used for facial recognition, and a voice analysis library (e.g., speech recognition engine) is used for voice analysis. This allows the user's emotional state to be captured in real time. 【0560】 Next, the device sends the acquired sentiment data and electronic message to the server. On the server, a natural language processing engine (e.g., a generative AI model) runs to analyze the message content. In this process, offensive language is detected and converted, the writing style is adjusted to an appropriate level based on the recipient information, and typographical errors are corrected. Furthermore, the tone and expression of the message are adjusted based on the acquired sentiment data. 【0561】 This allows the server to modify the message in a way that is not influenced by emotions and send it to the terminal. The terminal then presents the modified message from the server to the user, who can review it and make further modifications as needed. The message, once finally approved by the user, is sent to the specified recipient. 【0562】 For example, if a user reports being late for work and frantically types "I'm late! I'll be right there!", this system will convert it to "I'm sorry, I'm late. I'll be right on my way." An example of a prompt would be, "Please correct the message in the work report to a calm and polite tone." By using this prompt, the generative AI model helps construct an appropriate message. 【0563】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0564】 Step 1: 【0565】 The user enters electronic messages using the terminal. This input utilizes a text editor or messaging application. Simultaneously, the terminal's camera and microphone activate, capturing the user's facial expressions and voice in real time. This acquires facial expression and voice data. This input data is then used by facial recognition and voice analysis technologies to identify the user's emotional state. 【0566】 Step 2: 【0567】 The terminal sends the input electronic message and acquired emotional data (facial expressions and voice) to the server. This data is structured in a format such as JSON. The server uses a natural language processing engine to analyze the content of the received electronic message. It performs data processing such as grammatical analysis and keyword extraction on the text data received as input to detect aggressive expressions and typographical errors. 【0568】 Step 3: 【0569】 The server translates aggressive language into polite language based on data analyzed by a natural language processing engine. It also adjusts the style based on the recipient information. Furthermore, based on sentiment data, a generative AI model generates prompts to adjust the tone of the message. For example, if the user is expressing frustration, the message is rewritten to a calmer tone. The output is a modified and adjusted electronic message. 【0570】 Step 4: 【0571】 The server sends the revised electronic message to the terminal. The terminal displays the received message on its screen, allowing the user to review its contents. The user can make further revisions as needed. This interface includes visual elements such as drag-and-drop and click operations. 【0572】 Step 5: 【0573】 Finally, once the user approves the revisions, the device sends the finalized electronic message to the designated recipient. The output is the appropriately revised message delivered to the recipient. This ensures that communication accurately reflects the sender's intent. 【0574】 (Application Example 2) 【0575】 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." 【0576】 Modern online communication frequently leads to misunderstandings and unnecessary conflicts. This problem is particularly pronounced when information is transmitted while emotions are heightened. Inappropriate expressions and aggressive language based on emotions can hinder communication and cause serious problems in business and personal relationships. To solve these problems, there is a need for technology that accurately analyzes users' emotions and generates information that appropriately reflects them. 【0577】 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. 【0578】 In this invention, the server includes means for analyzing input information and converting aggressive expressions into polite expressions, means for performing grammatical analysis and automatically correcting typographical errors and omissions based on context, means for adjusting the language to be appropriate based on the information to be received, and means for identifying the user's emotional state and changing the expression according to the emotion based on a predetermined expression style. As a result, the information entered by the user can be converted into appropriate and refined content so as not to cause misunderstandings. 【0579】 "Inputted information" refers to strings of characters or sentences of data provided by the user to the information processing device. 【0580】 "Aggressive language" refers to language that may cause offense or hostility in the recipient. 【0581】 "Polite expression" refers to an expression that has been adjusted to be received respectfully and favorably by the recipient. 【0582】 "Grammar analysis" is the process of analyzing the linguistic structure of input information and organizing it into a normalized format. 【0583】 "Typographical errors" refer to incorrect or missing characters included in information. 【0584】 "Recipient information" refers to data about a specific individual or organization to which the information is being sent. 【0585】 "Emotional state" refers to the psychological state of a user, as judged from their facial expressions, tone of voice, and other factors. 【0586】 "Expressive style" refers to a set of methods of expression that include the tone and intonation of information. 【0587】 A description of the embodiment for carrying out the invention will be provided. 【0588】 This system begins with the user entering information into a terminal. The entered information is immediately sent to a server where it is processed. The server first uses a camera and microphone to collect the user's facial expressions and voice tone in order to analyze the emotions contained in the input information. This emotion data is processed using OpenCV and TensorFlow technologies. Once the emotion analysis is complete, natural language processing technology is used to detect aggressive expressions in the input information and convert them into polite expressions. Grammatical analysis is also performed at this time, and typos and omissions are automatically corrected. In this way, the information is adjusted so that it uses language appropriate for the recipient. 【0589】 It is also the server's role to change the style of information presentation based on the user's emotions. If the user is feeling anxious or frustrated, the server will transform the content into a calm and friendly tone to prevent those emotions from being misunderstood. The final information is sent from the server to the terminal and presented to the user. The user reviews the revised information and, if satisfied, can finally submit it. This process enables users to submit accurate and courteous information that is not influenced by emotions. 【0590】 As a concrete example, consider comments on a video streaming service. If a user tries to send a message like, "I don't understand why they did this!", this system detects that emotion and transforms it into a friendly and constructive tone such as, "I'd like to know more about this part. Could you tell me?" 【0591】 An example of a prompt to input into a generative AI model is: "Please suggest how to edit a comment entered by a user in an angry state to avoid misunderstandings, transforming it into a friendly and constructive tone." 【0592】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0593】 Step 1: 【0594】 The user enters information into the terminal. The entered strings and sentences are sent to the server as basic data for subsequent processing. At this stage, the data is structured according to a specific format and protocol, and prepared for the server to receive. 【0595】 Step 2: 【0596】 The server first collects user emotion data in order to analyze the received information. It captures the user's facial expressions and voice information using the device's camera and microphone, and processes this data using TensorFlow or OpenCV. The input is audio and video data, and the output is an evaluation value indicating the user's emotional state. 【0597】 Step 3: 【0598】 The server performs natural language processing on the input string based on sentiment evaluation. The input is data that combines the user's string information with sentiment evaluation, and the output is the result of identifying offensive expressions. It uses Python and the NLTK library to detect offensive words and phrases. 【0599】 Step 4: 【0600】 If offensive language is detected, the server converts it into polite language. Here, a generative AI model is used to replace the input offensive language with polite language according to the prompt. The output is the corrected language, replacing the original sentence. 【0601】 Step 5: 【0602】 Grammar analysis is performed as part of natural language processing. The server automatically corrects typos and grammatical errors in the received text, providing smoother and more readable text. The input is the user's text, and the output is a corrected, structured text. 【0603】 Step 6: 【0604】 The server selects the most appropriate language based on the recipient information. It analyzes the specified recipient information and adjusts the sentence style appropriately. At this stage, the input is the corrected sentence and recipient information, and the output is the sentence adjusted to suit the recipient. 【0605】 Step 7: 【0606】 Finally, the corrected information is sent to the terminal and presented to the user. The user can review the output and make further corrections as needed. As a result, the completed information is ready for transmission. 【0607】 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. 【0608】 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. 【0609】 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. 【0610】 [Fourth Embodiment] 【0611】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0612】 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. 【0613】 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). 【0614】 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. 【0615】 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. 【0616】 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). 【0617】 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. 【0618】 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. 【0619】 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. 【0620】 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. 【0621】 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. 【0622】 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. 【0623】 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". 【0624】 This invention relates to a system that analyzes user-generated messages and automatically modifies them as needed. This system is implemented by a server, a terminal, and the user. 【0625】 First, the user enters the message using their device and prepares to send it. When the user presses the send button, the entered message is sent to the server. The server analyzes the received message, performs sentiment analysis using a specific method, and detects offensive language. 【0626】 The server utilizes a database to convert aggressive expressions into more positive and polite ones. This database contains common aggressive expressions and their corresponding polite equivalents. For example, the expression "What are you doing?" is converted to "Could you tell me what the current situation is?" 【0627】 Next, the server detects typographical errors in the communication. It evaluates the entire text using contextual analysis techniques and identifies the appropriate word by referring to a dictionary database. Once the typographical errors are corrected, a corrected version is generated while maintaining the consistency of the original communication. 【0628】 Furthermore, the server verifies the recipient information and evaluates whether the content of the message is appropriate for the recipient. By applying appropriate honorifics and language according to the recipient, communication is facilitated. 【0629】 Ultimately, the terminal receives the revised message from the server. The user can review the revisions and make further corrections as needed. This entire process ensures that the user can send reliable and polite messages. 【0630】 This system is useful not only for business purposes but also for individual email communication. The invention reduces the burden on the user and minimizes the possibility of misunderstanding, thereby enabling efficient communication. 【0631】 The following describes the processing flow. 【0632】 Step 1: 【0633】 The user enters the message on the terminal and specifies the required recipient. Once ready to send, the user presses the send button to send the message to the server. 【0634】 Step 2: 【0635】 The server analyzes the communication received from the user. It uses natural language processing techniques to deepen its understanding of the context and performs syntactic analysis to evaluate the entire text. 【0636】 Step 3: 【0637】 The server uses the analysis results to detect offensive expressions in the communication. It then compares them with a dedicated database and converts the detected expressions into appropriate, polite phrasing. 【0638】 Step 4: 【0639】 The server continues grammatical analysis, identifying typographical errors and grammatical mistakes in the communication. Based on the dictionary database, it automatically corrects typographical errors with words appropriate to the context. 【0640】 Step 5: 【0641】 The server checks the specified destination information and inserts or adjusts appropriate honorifics and language in the message according to the destination. 【0642】 Step 6: 【0643】 The terminal receives the revised communication from the server. The user reviews the revisions and makes any further corrections if necessary. 【0644】 Step 7: 【0645】 Once the user confirms that there are no problems with the revised message, they perform an approval operation, and the final transmission takes place. 【0646】 In this way, the system pays attention to the quality of the message and how the recipient receives it, supporting smooth communication. 【0647】 (Example 1) 【0648】 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". 【0649】 In modern communication, inappropriate expressions of emotion in messages can lead to misunderstandings and offense. Furthermore, typographical errors and inappropriate language use can hinder effective communication. Additionally, using appropriate honorifics for different recipients can be burdensome for users. The challenge lies in resolving these issues and achieving efficient and polite dialogue. 【0650】 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. 【0651】 In this invention, the server includes means for analyzing input information and converting aggressive expressions into polite expressions, means for performing syntactic analysis and automatically correcting typographical errors and omissions based on context, and means for adjusting the expression to an appropriate one based on the recipient information. This enables users to send communications that are emotionally neutral, accurate, and respectful. 【0652】 "Inputted information" refers to the text and data that the user sends to the server via the system. 【0653】 "Aggressive language" refers to linguistic expressions that may cause discomfort or rejection in others. 【0654】 "Polite language" refers to courteous expressions used to show respect to the other person and to promote good communication. 【0655】 Syntactic analysis is a technique that analyzes the structure of a text and clarifies the relationships between words and phrases. 【0656】 "Typographical errors" refer to spelling mistakes or missing characters in the entered information. 【0657】 "Automatic correction" refers to a process in which a system corrects typographical errors and grammatical mistakes to an appropriate form based on the context. 【0658】 "Recipient information" refers to information about the destination of a message, and is data used to identify the recipient at the destination. 【0659】 "Sentiment analysis" is a technique that analyzes linguistic expressions in a text and evaluates their emotional tone and nuances. 【0660】 A "generative model" is an artificial intelligence model that learns from large amounts of data to generate or transform text. 【0661】 This invention is a system that analyzes information entered by a user using a generation terminal and modifies it into appropriate expressions. Upon receiving this information, the server first performs sentiment analysis using a generation AI model. If aggressive expressions are detected, the server consults a database for converting them into polite expressions and modifies the expressions appropriately. The software used includes a natural language processing library and a dictionary database. 【0662】 Next, the server performs syntactic analysis of the communication and automatically corrects typos and grammatical errors based on context. This process utilizes advanced natural language processing techniques to select the correct words while maintaining the overall coherence of the sentence. 【0663】 Furthermore, the system verifies recipient information and applies appropriate language based on the user's specified recipient. This ensures that respectful expressions are used, facilitating smoother communication. 【0664】 Finally, the server sends the corrected information to the terminal for the user to review. The user can make further corrections as needed. This system can be used with various communication tools, such as email and messaging applications. 【0665】 For example, if a user enters the sentence "What are you doing?", the server will correct it to "Could you tell me what the current situation is?". An example of a prompt from the generating AI model is "Please make this more polite: 'What are you doing?'". In this way, users can send information using polite language and avoid misunderstandings. 【0666】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0667】 Step 1: 【0668】 The user enters the message using the terminal. The entered data is temporarily stored on the terminal and sent to the server when the communication button is pressed. The input is passed to the server as text data. 【0669】 Step 2: 【0670】 The server processes the received message using a data analysis module and initiates sentiment analysis. In this step, a generative AI model is used to assign a sentiment score to each word in the message. The output is data with each word assigned a sentiment score. 【0671】 Step 3: 【0672】 The server identifies offensive language based on sentiment scores and converts it to polite language as needed. Here, the server consults a conversion database, finds offensive language, and replaces it with registered polite language. The output is the corrected text. 【0673】 Step 4: 【0674】 The server processes the corrected message through its syntactic analysis engine, correcting typos and grammatical errors based on the context. The entire sentence is analyzed, and errors are corrected with appropriate words from the existing dictionary. The output is a grammatically correct sentence. 【0675】 Step 5: 【0676】 The server analyzes the recipient information and applies appropriate language based on the recipient's attributes. During this process, polite expressions and greetings based on the recipient information are reflected in the message. The output is a message appropriately customized for the recipient. 【0677】 Step 6: 【0678】 The server sends the revised communication to the terminal and prompts the user to confirm its contents. The user reviews the revisions on the terminal and makes further manual corrections if necessary. The final output is the communication as reviewed or further modified by the user. 【0679】 (Application Example 1) 【0680】 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". 【0681】 In electronic communication, preventing misunderstandings and aggression that can occur between individuals, and ensuring courteous communication, especially in important financial transactions, are crucial challenges. Furthermore, it is necessary to guarantee accuracy and smooth exchange of information through automatic correction of typographical errors and the adoption of appropriate expressions tailored to the recipient. 【0682】 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. 【0683】 In this invention, the server includes means for analyzing input information, detecting offensive expressions and converting them into polite expressions; means for performing syntactic analysis and automatically correcting typographical errors and omissions based on context; means for adjusting the language to be appropriate based on recipient information; and means for politely translating communications with counterparties in financial transactions. This makes it possible to conduct smooth and polite communication between individuals. 【0684】 "Inputted information" refers to communication data that a user sends to the system using their device. 【0685】 "Aggressive language" refers to words or phrases that may cause offense or hostility in the recipient. 【0686】 "Polite expression" refers to a method of expression that shows respect to the recipient and facilitates smooth communication. 【0687】 "Syntactic analysis" refers to the technique of analyzing grammatical structure and performing accurate semantic interpretation. 【0688】 "Typographical errors" refer to spelling mistakes or omissions that occur when a user enters data. 【0689】 "Context-based automatic correction" refers to a process that performs optimal proofreading based on the context and meaning of the input content. 【0690】 "Recipient information" refers to data about the individual or group to whom the communication is being sent. 【0691】 "Counterparty in financial transactions" refers to the party involved in electronic payments, fund transfers, and other financial transactions. 【0692】 "To politely rephrase" refers to changing aggressive or inappropriate language into milder and more appropriate language. 【0693】 This invention is realized by having a server analyze and modify communication messages entered by a user using a communication terminal. Upon receiving a communication message, the server first performs linguistic analysis to detect offensive expressions. The detected expressions are converted to appropriate expressions by referring to a pre-prepared database of polite expressions. This process utilizes sentiment analysis software such as TextBlob and EmotionAnalyzer, which are natural language processing libraries. 【0694】 Next, the server detects typos and omissions in the communication and automatically corrects them based on the context. TextBlob is also utilized in this process. Furthermore, the content is adjusted to apply the most appropriate language to the user based on the recipient information. For this reason, expression conversion rules for each recipient are registered in the database. 【0695】 Furthermore, the server performs special processing on communications related to financial transactions, transforming the language into polite expressions to prevent misunderstandings with the other party. This allows users to proceed with transactions with peace of mind. 【0696】 Finally, the revised message is sent back to the terminal, where the user can review it and make further edits if necessary. For example, if a user tries to send the phrase "Give me a refund immediately!", this system will convert it to "Could I request a refund?", mitigating the impact on the recipient. 【0697】 An example of a prompt message is as follows: 【0698】 "Please implement a program that politely modifies messages sent by users in financial transactions. It will transform aggressive language into courteous expressions." 【0699】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0700】 Step 1: 【0701】 The server receives the communication message sent by the user. It obtains the communication message entered by the user from the terminal as input. In this step, the content of the communication message itself is the main data. 【0702】 Step 2: 【0703】 The server performs syntactic analysis on the received communication text using the TextBlob natural language processing library. The communication text received in step 1 is used as input, and its grammatical structure is analyzed. As a result, typos and omissions are detected, and a text with appropriate spelling corrections is output. 【0704】 Step 3: 【0705】 The server uses EmotionAnalyzer to perform sentiment analysis on the communication text. Here, the modified text from step 2 is input, and data processing is performed to assign a sentiment score to each word. As a result, aggressive expressions throughout the text are identified. 【0706】 Step 4: 【0707】 The server refers to a pre-configured database of polite expressions and performs a conversion process for aggressive language. Using the analysis results obtained in step 3 as input, it performs data conversion to replace aggressive language with polite language, and outputs the converted polite communication message. 【0708】 Step 5: 【0709】 The server compares the converted message with the destination information and adjusts the wording to suit the recipient. The input is the corrected message, which is the output of step 4, and appropriate corrections based on the destination are applied. The output is the final version of the message. 【0710】 Step 6: 【0711】 The server checks whether the language is polite, especially in the case of financial transactions, and makes any necessary corrections. The input is the communication obtained in step 5, and the output is the communication corrected to be appropriate for the other party. 【0712】 Step 7: 【0713】 The server then returns the final, corrected communication to the user's terminal. The user can review it and make further edits as needed. The output from step 6 is used as input and is presented to the user as a confirmation screen. 【0714】 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. 【0715】 This invention is a system that analyzes user-transmitted messages, incorporates an emotion engine, and automatically corrects the messages while recognizing the user's emotions. This system is particularly useful in today's world where online interactions are prevalent, as it facilitates smoother communication. The system is implemented via a server, terminal, and user. 【0716】 First, the user inputs a message using the device, and the emotion engine monitors the user's emotional state. The emotion engine recognizes emotions by analyzing the user's facial expressions, voice tone, input speed, etc., through the camera and microphone. Based on this analysis, it identifies the user's emotional state, and a corresponding correction process is then carried out. 【0717】 When a message is entered, the terminal sends the message and user sentiment information to the server. The server uses natural language processing technology to analyze the message, detect offensive language, and convert it into appropriate, polite language. It also corrects typos and adjusts the wording to be appropriate based on the recipient information. 【0718】 Furthermore, based on the emotion engine's evaluation, the tone and emphasis of the message are adjusted to match the user's emotions. For example, if the user is feeling anxious or irritated, the message is transformed into a calmer, more friendly tone to prevent misunderstandings. This process generates the final message. 【0719】 Finally, the terminal receives the revised message from the server and presents its contents to the user. The user reviews the revisions, makes any necessary additional corrections, and if there are no problems, sends the message for the final time. 【0720】 This system allows users to send precise messages while minimizing the influence of their own emotions. It contributes to more efficient business communication and the elimination of misunderstandings. 【0721】 The following describes the processing flow. 【0722】 Step 1: 【0723】 The user activates the emotion engine on their device while typing their message. The emotion engine analyzes the user's facial expressions and voice tone in real time through the camera and microphone, and determines their emotional state in conjunction with their typing speed. 【0724】 Step 2: 【0725】 The terminal sends the user's input message and emotional state data to the server. Emotional states include categories such as joy, anger, and sadness. 【0726】 Step 3: 【0727】 The server analyzes the received communication using natural language processing technology. It identifies aggressive expressions in the communication based on sentiment data and converts them into more polite expressions. 【0728】 Step 4: 【0729】 The server identifies typographical errors and grammatical mistakes in the communication using a dictionary database and independently corrects them with appropriate candidates based on the context. 【0730】 Step 5: 【0731】 The server adjusts the tone of its communication based on the user's emotional state. For example, if the user is irritated, it will change the language of the message to a more relaxed tone. 【0732】 Step 6: 【0733】 Based on the recipient information, the server incorporates appropriate honorifics and language into the message. If there are multiple recipients, adjustments are made individually to suit each recipient. 【0734】 Step 7: 【0735】 The terminal receives the modified communication message from the server. The user can review its contents and make further manual corrections if necessary. 【0736】 Step 8: 【0737】 After the user has made final confirmation of the revisions, they perform the send operation. The message is then sent to the specified recipient via the terminal. 【0738】 These steps make it easier for users to communicate their intended message accurately, without being influenced by their emotions. 【0739】 (Example 2) 【0740】 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". 【0741】 In modern digital communication, misunderstandings and inappropriate expressions influenced by emotions often occur, hindering smooth communication. This problem is particularly pronounced in email and chat communications, where the sender's emotional state can influence the tone and expression of the message. Therefore, there is a need for a system that automatically corrects emotionally-based misunderstandings and inappropriate expressions to ensure smooth and appropriate communication. 【0742】 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. 【0743】 In this invention, the server includes means for analyzing the input electronic message and converting aggressive expressions into polite language; means for automatically correcting typographical errors based on context using a natural language processing engine; means for adjusting the writing style to an appropriate style based on recipient information; means for identifying the sender's emotional state using facial recognition technology and voice analysis technology and adjusting the tone of the electronic message based on that emotion; and means for presenting the corrected electronic message and enabling the user to review and make further corrections to its content. This enables smooth and accurate messaging that is not influenced by the sender's emotions. 【0744】 "Electronic message" refers to text-based communication content transmitted via digital media. 【0745】 "Aggressive language" refers to words or phrases that may cause offense or hostility in the recipient. 【0746】 "Polite language" refers to expressions that are easy for the recipient to understand and are polite. 【0747】 A "natural language processing engine" is a system that utilizes technology to allow computer programs to analyze and understand human language. 【0748】 "Context-based automatic correction" refers to the process of analyzing the context of the input language data and correcting typos, grammatical errors, and other mistakes. 【0749】 "Recipient information" refers to information about the recipient of an electronic message, and an appropriate writing style is selected based on this information. 【0750】 "Facial recognition technology" refers to the technology that analyzes an individual's facial image to identify specific emotional states or characteristics. 【0751】 "Voice analysis technology" refers to the technology that analyzes voice data and detects the emotions and voice characteristics contained within it. 【0752】 "Emotional state" refers to a category that reflects the mental state an individual is experiencing in a particular situation. 【0753】 "Adjusting the tone" refers to the act of changing the tone or atmosphere of an electronic message to make it more appropriate for the recipient. 【0754】 "Additional modifications" refers to the process by which a user further edits the presented electronic message, adjusting it to best reflect their intended meaning. 【0755】 This system is a platform for facilitating digital communication. Specifically, it's a mechanism where terminals collect electronic messages entered by users, and servers process them. This process utilizes multiple hardware and software technologies. 【0756】 First, the user enters an electronic message using a terminal. This terminal is equipped with a camera and microphone for facial recognition and voice analysis. General image processing software (e.g., computer vision library) is used for facial recognition, and a voice analysis library (e.g., speech recognition engine) is used for voice analysis. This allows the user's emotional state to be captured in real time. 【0757】 Next, the device sends the acquired sentiment data and electronic message to the server. On the server, a natural language processing engine (e.g., a generative AI model) runs to analyze the message content. In this process, offensive language is detected and converted, the writing style is adjusted to an appropriate level based on the recipient information, and typographical errors are corrected. Furthermore, the tone and expression of the message are adjusted based on the acquired sentiment data. 【0758】 This allows the server to modify the message in a way that is not influenced by emotions and send it to the terminal. The terminal then presents the modified message from the server to the user, who can review it and make further modifications as needed. The message, once finally approved by the user, is sent to the specified recipient. 【0759】 For example, if a user reports being late for work and frantically types "I'm late! I'll be right there!", this system will convert it to "I'm sorry, I'm late. I'll be right on my way." An example of a prompt would be, "Please correct the message in the work report to a calm and polite tone." By using this prompt, the generative AI model helps construct an appropriate message. 【0760】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0761】 Step 1: 【0762】 The user enters electronic messages using the terminal. This input utilizes a text editor or messaging application. Simultaneously, the terminal's camera and microphone activate, capturing the user's facial expressions and voice in real time. This acquires facial expression and voice data. This input data is then used by facial recognition and voice analysis technologies to identify the user's emotional state. 【0763】 Step 2: 【0764】 The terminal sends the input electronic message and acquired emotional data (facial expressions and voice) to the server. This data is structured in a format such as JSON. The server uses a natural language processing engine to analyze the content of the received electronic message. It performs data processing such as grammatical analysis and keyword extraction on the text data received as input to detect aggressive expressions and typographical errors. 【0765】 Step 3: 【0766】 The server translates aggressive language into polite language based on data analyzed by a natural language processing engine. It also adjusts the style based on the recipient information. Furthermore, based on sentiment data, a generative AI model generates prompts to adjust the tone of the message. For example, if the user is expressing frustration, the message is rewritten to a calmer tone. The output is a modified and adjusted electronic message. 【0767】 Step 4: 【0768】 The server sends the revised electronic message to the terminal. The terminal displays the received message on its screen, allowing the user to review its contents. The user can make further revisions as needed. This interface includes visual elements such as drag-and-drop and click operations. 【0769】 Step 5: 【0770】 Finally, once the user approves the revisions, the device sends the finalized electronic message to the designated recipient. The output is the appropriately revised message delivered to the recipient. This ensures that communication accurately reflects the sender's intent. 【0771】 (Application Example 2) 【0772】 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". 【0773】 Modern online communication frequently leads to misunderstandings and unnecessary conflicts. This problem is particularly pronounced when information is transmitted while emotions are heightened. Inappropriate expressions and aggressive language based on emotions can hinder communication and cause serious problems in business and personal relationships. To solve these problems, there is a need for technology that accurately analyzes users' emotions and generates information that appropriately reflects them. 【0774】 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. 【0775】 In this invention, the server includes means for analyzing input information and converting aggressive expressions into polite expressions, means for performing grammatical analysis and automatically correcting typographical errors and omissions based on context, means for adjusting the language to be appropriate based on the information to be received, and means for identifying the user's emotional state and changing the expression according to the emotion based on a predetermined expression style. As a result, the information entered by the user can be converted into appropriate and refined content so as not to cause misunderstandings. 【0776】 "Inputted information" refers to strings of characters or sentences of data provided by the user to the information processing device. 【0777】 "Aggressive language" refers to language that may cause offense or hostility in the recipient. 【0778】 "Polite expression" refers to an expression that has been adjusted to be received respectfully and favorably by the recipient. 【0779】 "Grammar analysis" is the process of analyzing the linguistic structure of input information and organizing it into a normalized format. 【0780】 "Typographical errors" refer to incorrect or missing characters included in information. 【0781】 "Recipient information" refers to data about a specific individual or organization to which the information is being sent. 【0782】 "Emotional state" refers to the psychological state of a user, as judged from their facial expressions, tone of voice, and other factors. 【0783】 "Expressive style" refers to a set of methods of expression that include the tone and intonation of information. 【0784】 A description of the embodiment for carrying out the invention will be provided. 【0785】 This system begins with the user entering information into a terminal. The entered information is immediately sent to a server where it is processed. The server first uses a camera and microphone to collect the user's facial expressions and voice tone in order to analyze the emotions contained in the input information. This emotion data is processed using OpenCV and TensorFlow technologies. Once the emotion analysis is complete, natural language processing technology is used to detect aggressive expressions in the input information and convert them into polite expressions. Grammatical analysis is also performed at this time, and typos and omissions are automatically corrected. In this way, the information is adjusted so that it uses language appropriate for the recipient. 【0786】 It is also the server's role to change the style of information presentation based on the user's emotions. If the user is feeling anxious or frustrated, the server will transform the content into a calm and friendly tone to prevent those emotions from being misunderstood. The final information is sent from the server to the terminal and presented to the user. The user reviews the revised information and, if satisfied, can finally submit it. This process enables users to submit accurate and courteous information that is not influenced by emotions. 【0787】 As a concrete example, consider comments on a video streaming service. If a user tries to send a message like, "I don't understand why they did this!", this system detects that emotion and transforms it into a friendly and constructive tone such as, "I'd like to know more about this part. Could you tell me?" 【0788】 An example of a prompt to input into a generative AI model is: "Please suggest how to edit a comment entered by a user in an angry state to avoid misunderstandings, transforming it into a friendly and constructive tone." 【0789】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0790】 Step 1: 【0791】 The user enters information into the terminal. The entered strings and sentences are sent to the server as basic data for subsequent processing. At this stage, the data is structured according to a specific format and protocol, and prepared for the server to receive. 【0792】 Step 2: 【0793】 The server first collects user emotion data in order to analyze the received information. It captures the user's facial expressions and voice information using the device's camera and microphone, and processes this data using TensorFlow or OpenCV. The input is audio and video data, and the output is an evaluation value indicating the user's emotional state. 【0794】 Step 3: 【0795】 The server performs natural language processing on the input string based on sentiment evaluation. The input is data that combines the user's string information with sentiment evaluation, and the output is the result of identifying offensive expressions. It uses Python and the NLTK library to detect offensive words and phrases. 【0796】 Step 4: 【0797】 If offensive language is detected, the server converts it into polite language. Here, a generative AI model is used to replace the input offensive language with polite language according to the prompt. The output is the corrected language, replacing the original sentence. 【0798】 Step 5: 【0799】 Grammar analysis is performed as part of natural language processing. The server automatically corrects typos and grammatical errors in the received text, providing smoother and more readable text. The input is the user's text, and the output is a corrected, structured text. 【0800】 Step 6: 【0801】 The server selects the most appropriate language based on the recipient information. It analyzes the specified recipient information and adjusts the sentence style appropriately. At this stage, the input is the corrected sentence and recipient information, and the output is the sentence adjusted to suit the recipient. 【0802】 Step 7: 【0803】 Finally, the corrected information is sent to the terminal and presented to the user. The user can review the output and make further corrections as needed. As a result, the completed information is ready for transmission. 【0804】 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. 【0805】 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. 【0806】 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. 【0807】 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. 【0808】 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. 【0809】 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. 【0810】 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. 【0811】 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. 【0812】 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." 【0813】 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. 【0814】 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. 【0815】 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. 【0816】 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. 【0817】 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. 【0818】 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. 【0819】 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. 【0820】 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. 【0821】 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. 【0822】 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. 【0823】 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. 【0824】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0825】 The following is further disclosed regarding the embodiments described above. 【0826】 (Claim 1) 【0827】 A means for analyzing input communication messages, detecting aggressive expressions, and converting them into polite expressions, 【0828】 A means of performing syntactic analysis and automatically correcting typographical errors and grammatical errors based on context, 【0829】 A means of adjusting the wording to be appropriate based on the recipient information, 【0830】 A means of presenting the corrected communication and enabling user verification, 【0831】 A system that includes this. 【0832】 (Claim 2) 【0833】 The system according to claim 1, which evaluates positive or negative expressions by assigning a sentiment score to each word in a communication received from a user. 【0834】 (Claim 3) 【0835】 The system according to claim 1, which dynamically applies appropriate language to multiple destinations specified by the user, for each user. 【0836】 "Example 1" 【0837】 (Claim 1) 【0838】 A means of analyzing input information, detecting offensive expressions, and converting them into polite expressions, 【0839】 A means of performing syntactic analysis and automatically correcting typographical errors and grammatical errors based on context, 【0840】 A means of adjusting the expression to an appropriate one based on the recipient information, 【0841】 A means to present the revised content and enable user verification, 【0842】 A means of performing sentiment analysis and evaluating and transforming expressions using generative models, 【0843】 A system that includes this. 【0844】 (Claim 2) 【0845】 The system according to claim 1, which evaluates positive or negative expressions by assigning a sentiment score to each word in the information received from the user. 【0846】 (Claim 3) 【0847】 The system according to claim 1, which dynamically applies expressions appropriate to the user to multiple destinations specified by the user. 【0848】 "Application Example 1" 【0849】 (Claim 1) 【0850】 A means of analyzing input information, detecting offensive expressions, and converting them into polite expressions, 【0851】 A means of performing syntactic analysis and automatically correcting typographical errors and grammatical errors based on context, 【0852】 A means of adjusting the wording to be appropriate based on the recipient information, 【0853】 A means to present corrected information and enable user verification, 【0854】 A means of politely transforming communication with counterparties in financial transactions, 【0855】 A system that includes this. 【0856】 (Claim 2) 【0857】 The system according to claim 1, which evaluates positive or negative expressions by assigning an emotion index to each word in the information received from the user. 【0858】 (Claim 3) 【0859】 The system according to claim 1, which dynamically applies appropriate language to multiple recipients specified by the user, for each recipient. 【0860】 "Example 2 of combining an emotion engine" 【0861】 (Claim 1) 【0862】 A means for analyzing input electronic messages, detecting aggressive expressions, and converting them into polite language, 【0863】 A means of automatically correcting typographical errors based on context using a natural language processing engine, 【0864】 A means of adjusting the writing style to an appropriate one based on the recipient information, 【0865】 A means for identifying the sender's emotional state using facial recognition technology and voice analysis technology, and adjusting the tone of an electronic message based on that emotion, 【0866】 A means of presenting a revised electronic message and enabling the user to review and make further modifications to its content, 【0867】 A system that includes this. 【0868】 (Claim 2) 【0869】 The system according to claim 1, which assigns an emotion index to each word in an electronic message received from a user, and uses a generative AI model to adaptively adjust and evaluate the expression. 【0870】 (Claim 3) 【0871】 The system according to claim 1, which dynamically applies an expression appropriate to each recipient to multiple recipients specified by the user. 【0872】 "Application example 2 when combining with an emotional engine" 【0873】 (Claim 1) 【0874】 A means of analyzing input information, detecting offensive expressions, and converting them into polite expressions, 【0875】 A means of performing grammatical analysis and automatically correcting typographical errors and omissions based on context, 【0876】 A means of adjusting the wording to be appropriate based on the information to be received, 【0877】 A means to present corrected information and enable user verification, 【0878】 A means for identifying the emotional state of a user and changing the expression according to that emotion based on a predetermined expression style, 【0879】 A system that includes this. 【0880】 (Claim 2) 【0881】 The system according to claim 1, which evaluates positive or negative expressions by assigning a sentiment value to each word in the information received from the user. 【0882】 (Claim 3) 【0883】 The system according to claim 1, which dynamically applies appropriate language to multiple recipients specified by the user. [Explanation of Symbols] 【0884】 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

[Claim 1] A means for analyzing input communication messages, detecting aggressive expressions, and converting them into polite expressions, A means of performing syntactic analysis and automatically correcting typographical errors and grammatical errors based on context, A means of adjusting the wording to be appropriate based on the recipient information, A means of presenting the corrected communication and enabling user verification, A system that includes this. [Claim 2] The system according to claim 1, which evaluates positive or negative expressions by assigning a sentiment score to each word in a communication received from a user. [Claim 3] The system according to claim 1, which dynamically applies appropriate language to multiple destinations specified by the user, for each destination.

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