system

Abstract

We provide the system. [Solution] A means for receiving electronic messages sent by a user, A means for analyzing received electronic messages and detecting typographical errors and omissions, A means for generating correction suggestions based on detected typographical errors and omissions, A means for sending the generated correction suggestions to the user's terminal and enabling the user to make corrections, A means to perform a final check of the revised electronic message and prepare it for transmission, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the creation and transmission of electronic messages, there are problems that reliability is reduced due to typos, incompleteness of content, and policy violations, and the quality of communication is impaired. Also, human errors caused by a large amount of email sending work may waste labor and time. Means for solving such problems are required.

Means for Solving the Problems

[0005] This invention provides a system that receives electronic messages, automatically analyzes their content to detect typographical errors and omissions, and provides users with appropriate correction suggestions. Furthermore, by scrutinizing message content and generating correction suggestions that align with tone and policy, it can improve communication quality. In addition, by including security checks, it supports proper information management and prevention of accidental transmission. This results in savings of time and effort, enabling efficient management of electronic messages.

[0006] A "user" is an individual or legal entity that uses the system to create, send, and modify electronic messages.

[0007] "Electronic messaging" refers to communication such as email that is sent and received over a computer network.

[0008] "Means of receiving" refers to the functions and methods by which a server retrieves electronic messages sent by a user.

[0009] "Means of analysis" refers to functions and methods that use language processing technology to check for typographical errors and content in received electronic messages.

[0010] "Means for detecting typographical errors and omissions" refers to functions or methods for identifying errors in characters and words contained in electronic messages.

[0011] "Means for generating correction suggestions" refers to functions or methods for presenting improvement suggestions to users based on detected typos, grammatical errors, and other content inaccuracies.

[0012] A "user terminal" refers to a device used by a user, such as a computer or smartphone.

[0013] "Means of preparing for transmission" refers to functions and methods that perform the necessary processing to correctly send an electronic message after the user has made a final confirmation.

[0014] "Means for scrutinizing content" refers to functions and methods for thoroughly checking the information and wording of received electronic messages and determining whether revisions are necessary to align with the policies of a company or organization.

[0015] "Means of conducting security checks" refer to functions and methods for verifying that electronic messages do not contain confidential information or are addressed to the wrong recipient, and for ensuring proper information management. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

[0019] In the following embodiments, a processor with a reference numeral (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.

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

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

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention is a system that improves the quality and efficiency of electronic message transmission, and provides an automated email proofreading and review function using generation AI. Detailed embodiments of the invention will be described below.

[0038] The server receives email data from users who have finished composing their electronic messages. To analyze the received email data, the server uses natural language processing (NLP) techniques to analyze the text and identify typos and omissions. This involves using dictionary databases and language models to detect unnatural words and phrases within the email.

[0039] The server also automatically generates correction suggestions. Specifically, it proposes corrections for detected typos and omissions, and performs content review based on tone and policy, pointing out areas for improvement in expression and writing style. For example, in the case of business emails, it might suggest avoiding imperative forms to show consideration for the recipient.

[0040] The suggested corrections are sent to the user's device, where the user reviews them. The user can accept the suggestions and correct the electronic message, or make other corrections at their own discretion. Once the corrections are complete, the user sends the corrected message back to the server.

[0041] The server performs a security check as a final verification. This verifies that the message does not contain confidential information or incorrectly configured recipients. After the message is ready to send and the user approves, the electronic message is sent to the specified recipient.

[0042] For example, if a user creates an email saying, "Please be sure to attend tomorrow's meeting," the server will change "absolutely" to "definitely" and suggest softer phrasing such as "We would appreciate your attendance." In this way, the system provides an environment where users can efficiently send high-quality, error-free electronic messages.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user composes an electronic message and sends it to the server when it is ready to be sent. At this point, the email data is received by the server.

[0046] Step 2:

[0047] The server passes the received email data to the language processing unit, which analyzes the text using natural language processing techniques. This initiates the detection of typos and grammatical errors. The server refers to dictionary databases and language models to identify errors in word form and grammatical structure.

[0048] Step 3:

[0049] The server generates correction suggestions based on the detected typos and grammatical errors. These suggestions include replacing incorrect words with correct ones, as well as revising the wording based on the tone and content of the business email. For example, it might suggest changing "Please be sure to come" to "We would appreciate your attendance."

[0050] Step 4:

[0051] The server sends the generated revision suggestions to the user's terminal. The user reviews the suggestions and selects and adopts the revisions based on their own judgment. At this point, the user can either accept all the automated suggestions or make partial revisions.

[0052] Step 5:

[0053] Once the user has completed the corrections, they perform a final check on their device and send the corrected email back to the server. The server then checks the content again.

[0054] Step 6:

[0055] The server performs a final security check to ensure that the email does not contain any confidential information or incorrect recipient information. If necessary, it undergoes additional approval processes before being ready to send.

[0056] Step 7:

[0057] After all checks are complete, and based on user approval, the server sends an electronic message to the specified recipient. Upon successful transmission, the result is notified to the user's terminal.

[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] Conventional electronic message transmission systems suffer from problems such as reduced information quality due to typographical errors, omissions, and inappropriate expressions. Furthermore, messages may not conform to the intended tone or policy, potentially leading to misunderstandings. Security challenges, such as the leakage of confidential information and sending messages to the wrong recipients, cannot be ignored. A system is needed that efficiently solves these problems, allowing users to send high-quality electronic messages with peace of mind.

[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 receiving information transmitted by a user, means for analyzing the received information and detecting text errors, means for generating improvement suggestions based on the detected errors, means for transmitting the generated improvement suggestions to an information processing device so that they can be corrected by the user, and means for performing security checks to confirm that confidential information or incorrect recipients are not included. This enables the user to send high-quality and secure electronic messages.

[0063] "User" refers to the entity that performs the operation of sending an electronic message.

[0064] "Information" refers to text and data that are transmitted or received electronically.

[0065] "Receiving means" refers to a function for acquiring and storing information transmitted by the user.

[0066] "Analysis means" refers to a function that analyzes received information and processes it to detect errors or inappropriate expressions.

[0067] The term "improvement suggestion generation means" refers to a function that automatically creates corrective suggestions for detected errors.

[0068] An "information processing device" refers to a device that enables users to view and modify information.

[0069] "Correction mechanism" refers to a function that allows users to modify information based on improvement suggestions.

[0070] "Security verification means" refers to a function that performs processing to ensure that information is transmitted to the appropriate recipient and that the leakage of confidential information is prevented.

[0071] This invention provides a system for users to send electronic messages with high quality and security. This system is primarily realized through communication between a server, a terminal, and a user.

[0072] A server is a computer device that receives information sent from users. Upon receiving this information, the server performs analysis using natural language processing techniques. During the analysis process, software tools such as dictionary databases and language models are used to detect typographical errors, omissions, and inappropriate expressions within the information.

[0073] In response to detected deficiencies, the server generates improvement suggestions. A generation AI model supports this process, adjusting the user's message to match the intended tone and policy. Specific examples include suggestions to change imperative sentences to polite language or to simplify redundant expressions.

[0074] The user's terminal is a device for receiving and displaying improvement suggestions sent from the server. Through the terminal's interface, the user can review the suggestions and easily implement the corrections. An example of a prompt message to support this process would be: "Requesting improvements to the tone of your email. Current message: 'You must attend tomorrow's meeting.' Please provide improvement suggestions."

[0075] Furthermore, the server receives the modified message and performs a security check. This check evaluates whether it contains confidential information and whether it is being sent to the wrong recipient. Through this series of processes, users can ensure that they send accurate and high-quality information.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The server receives information sent by the user. The input is an electronic message created by the user, and the output is the digital data of that message. This data is retrieved using a secure communication protocol.

[0079] Step 2:

[0080] The server analyzes the received digital data. This process involves text analysis using natural language processing techniques. The input data is the email body, from which words and sentence structures are extracted. The output is a list of typos, omissions, and unnatural expressions.

[0081] Step 3:

[0082] The server generates improvement suggestions based on the analysis results. In this step, it utilizes a generative AI model to generate appropriate corrections based on the error list as input. The output is a specific correction suggestion, such as applying honorific language or simplifying redundant expressions.

[0083] Step 4:

[0084] The server sends the generated improvement suggestions to the user's terminal. The list of improvement suggestions serves as input, and the output is displayed on the user's screen. This allows the user to review the suggested modifications.

[0085] Step 5:

[0086] The user reviews the suggestions on their device and either accepts or modifies them. The user's actions are the input, and the output is a message indicating the modifications. Specifically, the process involves clicking on a suggestion to apply the changes.

[0087] Step 6:

[0088] The user sends the corrected message to the server. The input is the corrected message, and the output is the digital data that the server receives again. Data transmission is rapid.

[0089] Step 7:

[0090] The server performs a security check on the modified message. The input is the modified message data, and the output is the message after security has been confirmed. This process evaluates whether confidential information is present and whether an incorrect recipient has been detected.

[0091] Step 8:

[0092] The server sends the message, once all confirmations are complete, to the designated recipient. The input is the confirmed message, and the output is the accurate delivery to the recipient. The server performs this process only after final approval from the user.

[0093] (Application Example 1)

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

[0095] Inaccurate or inappropriate information can lead to misunderstandings and undermine credibility. Such problems are particularly serious in electronic transactions and important notices. Furthermore, there is a need for methods that automatically apply corrections before information is sent and, even after user confirmation, ensure the rapid transmission of reliable information. This necessitates improved information quality and efficient management.

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

[0097] In this invention, the server includes a device for receiving information transmitted from a user, a device for analyzing the received information and detecting errors, and a device for generating correction suggestions based on the detected errors. This enables automatic correction of information and final confirmation before transmission.

[0098] A "user" is an entity that uses a system or device to send and receive information.

[0099] "Information" refers to messages and data transmitted electronically, including text and other forms of digital content.

[0100] "Device" refers to a hardware or software component designed to perform a specific function.

[0101] "Analysis" is the process of understanding the content of information and identifying errors or areas for improvement.

[0102] An "error" refers to a mistake in information that includes misspellings, omissions, or grammatical or stylistic inappropriateness.

[0103] A "correction suggestion" refers to providing more appropriate wording or content for errors or areas that need improvement.

[0104] "Transmission" refers to the act of moving information from the source to a designated destination.

[0105] "Protection assessment" is a process that verifies the security of information and examines its confidentiality and the possibility of accidental transmission.

[0106] This invention is a system that improves the quality of information by automatically analyzing information transmitted by users, detecting errors, and correcting them. The system is implemented in the following way.

[0107] The server receives information sent from the user's terminal and analyzes it. Natural language processing techniques are used for the analysis, and dictionary databases and language models are used to identify errors in the received information. Through this process, typographical errors, omissions, and unnatural words and phrases are identified.

[0108] Next, the server uses a generative AI model to generate correction suggestions based on these errors. The generated correction suggestions are sent to the user's terminal, where the user can review the suggestions and decide whether to adopt them.

[0109] Subsequently, the corrected information is finalized by the server and a protection assessment is performed. This assessment includes checks to prevent the leakage of confidential information and the setting of inappropriate destinations.

[0110] As a concrete example, consider a scenario where the AI ​​generator, in response to the instruction "Create a payment confirmation email for tomorrow," provides a revised version of the email, correcting it to a more formal tone. This allows users to manage and send information quickly and with high quality.

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] The server receives information transmitted from the user's terminal. The input is an electronic message created by the user, and processing begins when the server receives it. The output is primary data to be used in subsequent analysis processes.

[0114] Step 2:

[0115] The server analyzes the received information using natural language processing (NLP) technology. The input is the previously received electronic message; the server uses an NLP engine to perform grammar and spell checks, detecting errors and omissions. The output is information with typos, omissions, and unnatural expressions highlighted.

[0116] Step 3:

[0117] The server generates correction suggestions using a generative AI model. The input is information in which errors have been identified, and based on this, the AI ​​generates suggestions including appropriate corrections and stylistic improvements. The output is presented to the user as a document incorporating the specific correction suggestions.

[0118] Step 4:

[0119] The terminal displays correction suggestions sent from the server to the user. The input is data containing suggestions from the server, which the terminal reads and displays on the interface so the user can review the corrections. The output is visualized information to assist the user in making decisions and selecting corrections.

[0120] Step 5:

[0121] Users review the proposed revisions and either adopt them or make their own modifications. User actions serve as input, and the output is the final, revised information. This allows for user-driven creation of high-quality information.

[0122] Step 6:

[0123] The server finally verifies the information modified by the user and performs a security assessment. The input is information confirmed by the user, and the server performs security checks on the data. The output is information that is guaranteed to prevent confidential information and accidental transmission, and if there are no problems, it is ready to be sent.

[0124] 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.

[0125] This invention incorporates an emotion engine that recognizes user emotions, in addition to an automated email proofreading and review function using generation AI, in order to improve the quality and efficiency related to the creation and transmission of electronic messages. This makes it possible to provide more appropriate revision suggestions.

[0126] The server receives electronic messages created by users and analyzes their content. During the analysis process, the server first uses language processing technology to detect typos and grammatical errors and generates necessary correction suggestions. Simultaneously, an emotion engine identifies the emotions expressed in the user's writing and suggests revisions to the tone and content accordingly.

[0127] This allows the emotion engine to recognize, for example, anger in a user's mind, and suggest more neutral and appropriate expressions. For instance, if a user types, "Please deal with this immediately! I'm really angry," the emotion engine will sense the user's anger and suggest a calmer expression such as, "Please take swift action."

[0128] The generated correction suggestions are sent to the user's device for review. The user can consider the suggestions and revise the message as needed. Once the revisions are complete, the user sends the revised message back to the server.

[0129] The server performs a final review of the modified message. This final review includes security checks, and the message is then ready for transmission. Once the message is approved, it is sent according to the user's instructions. This makes it possible to efficiently send high-quality electronic messages that have been edited to reflect the user's emotions.

[0130] The following describes the processing flow.

[0131] Step 1:

[0132] The user composes an electronic message on their device and prepares it for sending. They then perform the necessary steps to send the completed message to the server.

[0133] Step 2:

[0134] The server prepares to process the electronic message received from the user, and first starts text analysis in the language processing unit. This analysis checks for words and grammatical structures and identifies typos and omissions.

[0135] Step 3:

[0136] The server generates correction suggestions based on the detected typos and grammatical errors. It refers to a dictionary database and suggests replacing incorrect words with correct ones.

[0137] Step 4:

[0138] Simultaneously, the server uses an emotion engine to identify the user's emotions from the content of the electronic message. The emotion engine analyzes the emotions in the text and identifies various emotion categories (e.g., anger, joy, anxiety).

[0139] Step 5:

[0140] Based on the perceived emotions, the server generates additional revised suggestions with adjusted tones to avoid misunderstandings. For example, if overly strong language is used, it will suggest softer phrasing.

[0141] Step 6:

[0142] The server sends all generated correction suggestions to the user's terminal. The user reviews these suggestions on their terminal and makes the necessary corrections to the electronic message. The user can accept the suggestions or make their own corrections.

[0143] Step 7:

[0144] After completing the corrections, the user resends the electronic message to the server. As a final check, the server verifies the content and security to ensure that the message does not contain any confidential information or be addressed to the wrong recipient.

[0145] Step 8:

[0146] Once the server is ready to send, it will send the electronic message to the specified recipient after the user's final approval. After the transmission is complete, the server will notify the user's device of the result.

[0147] (Example 2)

[0148] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0149] In creating electronic communications, challenges exist not only in preventing typos and omissions, but also in generating appropriate expressions that resonate with the user's emotions. Furthermore, creating communications that match the tone and policy of the content can be time-consuming. Additionally, there is a growing need for security checks before transmission to ensure that confidential information and incorrect recipients are not included. Technologies that can efficiently and effectively address these challenges are needed.

[0150] 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.

[0151] In this invention, the server includes means for receiving electronic communications transmitted by a user, means for analyzing the received electronic communications and detecting grammatical errors and input errors, and means for analyzing the user's emotions and generating emotion-based correction suggestions. This makes it possible to generate appropriate correction suggestions that are sensitive to the user's emotions and to correct electronic communications to be of higher quality and more to the user's tone. It also facilitates the transmission of secure communications that do not contain confidential information or incorrect destinations.

[0152] "Electronic communication" refers to digital messages created by a user and sent to other users or systems.

[0153] A "grammatical error" refers to a grammatical inaccuracy or flaw in the content of electronic communications.

[0154] "Input errors" refer to spelling mistakes or typos that occur when users create electronic communications.

[0155] A "correction suggestion" is a proposal to recommend more appropriate expressions or structures to the user based on detected grammatical errors, input mistakes, or the results of sentiment analysis.

[0156] "Sentiment analysis" is the process of identifying and analyzing a user's psychological and emotional state from the content of their electronic communications.

[0157] "Security verification" is the process of checking for the presence of confidential information and the accuracy of the destination before electronic communications are transmitted, in order to ensure security.

[0158] This invention is a system that utilizes natural language processing technology and emotion recognition technology to improve the quality of electronic communications.

[0159] The server receives electronic communications sent by users from their terminals and analyzes their content. The hardware used here includes general server equipment, and the software includes a generative AI model suitable for text analysis. Specifically, the generative AI model used is a language model equipped with natural language processing technology.

[0160] During the analysis process, the server detects typographical errors and grammatical mistakes in electronic communications and generates appropriate correction suggestions based on these. Furthermore, the server uses emotion recognition technology to analyze the user's emotional state and suggests modifications to expressions and tone that correspond to those emotions.

[0161] Once a revision suggestion is generated, the server sends it to the user's terminal. The user can review the suggestion and revise their message if necessary. This interaction enables high-quality electronic communication that is sensitive to emotions.

[0162] For example, if a user enters "Please deal with this immediately! I'm really angry," the server will perform sentiment analysis and suggest a calmer expression such as "Please take prompt action." An example of the prompt used in this case would be: "User input: Please deal with this immediately! I'm really angry. Generating AI prompt: Identify expressions that convey anger in this message and generate a revised suggestion in a more neutral tone."

[0163] Thus, the present invention helps users create electronic communications with well-organized content for efficient communication.

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] The server receives electronic communications from the user's terminal. It receives the user message as text data as input and stores it in a database. As a preprocessing step, it normalizes the text, removing unnecessary symbols and spaces. The output at this step is clean text data ready for analysis.

[0167] Step 2:

[0168] The server analyzes the received clean text data using natural language processing techniques. The input is the clean text obtained in step 1, and a generative AI model is used here. Specifically, it detects grammatical errors and typos and generates correction suggestions. The output is a list of errors and correction suggestions. This brings the user's message closer to grammatically correct form.

[0169] Step 3:

[0170] The server analyzes the user's emotions contained in the text data. The input is the text data processed in step 2, and the generating AI model performs emotion analysis. Specifically, it uses an emotion engine to identify the user's emotional state and generates suggestions to modify the tone and expression to suit that emotion. The output is the emotion-based modification suggestions.

[0171] Step 4:

[0172] The server sends the generated correction suggestions to the user's terminal. The input for this step is the correction suggestions generated in steps 2 and 3. The server formats each correction suggestion in an easily understandable format and transfers it to the user's terminal. The output is correction suggestion data that the user can review.

[0173] Step 5:

[0174] The user reviews the suggested revisions on their device and decides whether to revise the message content. The input is the suggested revision data sent from the server. The user accepts the suggestions or makes manual revisions to determine the final version of the message. The output is the revised message data. Specifically, the user confirms the revised version and sends it to the server.

[0175] Step 6:

[0176] The server receives the final version of the message from the user and performs a final check. The input for this step is the message data modified by the user. The server performs a security check to ensure that it does not contain confidential information or misdirected recipients. The output is an electronic communication ready for transmission. This ensures secure and high-quality electronic communication.

[0177] (Application Example 2)

[0178] 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".

[0179] Modern communication often takes place via electronic messages, requiring not only the detection of typos and grammatical errors, but also the ability to appropriately understand the sender's emotions and revise messages to match the appropriate tone. However, conventional systems often fail to offer emotion-based revision suggestions, potentially leading to emotional misunderstandings. Furthermore, security checks are necessary to ensure the content is safe and appropriate before transmission. Technologies are needed to address these challenges.

[0180] 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.

[0181] In this invention, the server includes means for recognizing the user's emotions and generating tone correction suggestions based on those emotions; means for transmitting the generated correction suggestions to the user's terminal and enabling the user to make corrections; and means for final confirmation of the corrected electronic message and preparing it for transmission. This makes it possible to efficiently transmit high-quality electronic messages that appropriately take the user's emotions into consideration.

[0182] An "electronic message" is a digital message transmitted using a computer or mobile device, and can include text, images, and files.

[0183] "Typographical errors and omissions" refer to errors or omissions in the use of language within electronic messages and are one of the factors that hinder accurate communication.

[0184] "Correction suggestions" are recommended sentences or expressions generated by the system to correct typos and omissions, and are intended to improve the accuracy of electronic messages.

[0185] "Emotional recognition" is the process of analyzing and understanding a user's emotional state from the content of electronic messages, and is necessary to improve the quality of communication.

[0186] A "tone correction suggestion" is a proposal to change the emotional tone of an electronic message to an appropriate one, providing language that will not mislead the recipient.

[0187] A "user terminal" is a hardware device used by a user to perform operations such as creating, sending, and receiving electronic messages, and includes smartphones and personal computers.

[0188] "Final confirmation" is the process of verifying that the content and recipient of an electronic message are correct before sending it, in order to prevent accidental sending or miscommunication.

[0189] "Preparing to send" refers to completing the necessary processes to actually send an electronic message after it has been confirmed to be accurate and secure.

[0190] This invention provides a system for improving the quality of electronic messages. This system is built using a server, a user terminal, and necessary AI software.

[0191] The server has the capability to receive electronic messages sent by users. These messages are stored in a database and kept until the analysis program is run. Next, the server performs natural language processing and uses a generative AI model to detect typos and grammatical errors in the messages. SpaCy, an open-source natural language processing tool, is commonly used.

[0192] Furthermore, the server uses an emotion recognition engine to analyze the emotional tone of the message. This process utilizes a PyTorch model for emotion analysis to generate expressions that more accurately reflect the user's intent. This engine can correct expressions that the user unintentionally uses to mislead others.

[0193] The user terminal receives correction suggestions sent from the server and has the capability for the user to accept the suggestions or make further corrections. This allows the user to review the final corrected message and make further edits if necessary.

[0194] As a concrete example, consider a scenario where a user is creating a customer support email. Suppose the user uses the phrase, "I am disappointed with this product; please address this." An example of a prompt might be, "Perform a sentiment analysis on the following email and revise it to a more positive expression. Original: 'I am disappointed with this product; please address this.'" This prompt allows the system to suggest a more polite expression, improving the impression the email recipient has.

[0195] This system improves the quality and accuracy of emails, enabling communication that avoids misunderstandings.

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

[0197] Step 1:

[0198] The user composes an electronic message and presses the send button.

[0199] In this step, the user's device is prepared to send message data to the server. The input is the electronic message created by the user, and the output is the data to be sent to the server.

[0200] Step 2:

[0201] The server receives an electronic message.

[0202] The server receives messages sent from the user terminal and prepares to parse them. The input is the message received from the user terminal, and the output is the message data for proceeding to the next parsing step.

[0203] Step 3:

[0204] The server detects typos and omissions in messages.

[0205] The server performs natural language processing using spaCy to identify typos and omissions in messages. The input is the message data to be analyzed, and the output is the message data with the typos and omissions identified.

[0206] Step 4:

[0207] The server uses an emotion engine to analyze the message.

[0208] The server uses PyTorch to perform sentiment recognition and evaluate the emotional tone of messages. The input is message data including typographical errors, and the output is message data with sentiment scores assigned to it.

[0209] Step 5:

[0210] The server generates correction suggestions.

[0211] The server uses a generative AI model to create correction suggestions based on detected typos and grammatical errors, as well as the assessed sentiment. The input is message data with sentiment scores, and the output is data with correction suggestions attached.

[0212] Step 6:

[0213] The server sends the suggested corrections to the user's terminal.

[0214] The server forwards the generated correction suggestions to the user's terminal, making them available for review and correction. The input is message data with correction suggestions, and the output is notification data received by the user's terminal.

[0215] Step 7:

[0216] The user reviews the suggested corrections and modifies the message as needed.

[0217] Based on the correction suggestions received on the user's terminal, the user reviews the message content and makes corrections. The input is the correction suggestion and the original message, and the output is the message corrected by the user.

[0218] Step 8:

[0219] The user sends the corrected message to the server.

[0220] The user terminal resends the modified message data to the server and prepares for final confirmation. The input is the message modified by the user, and the output is the data sent to the server.

[0221] Step 9:

[0222] The server performs final verification and security checks.

[0223] The server performs a final content review and security check on the modified message and completes the preparation for transmission. The input is the final version of the message data, and the output is the message data ready for transmission.

[0224] Step 10:

[0225] The server sends the final electronic message to the designated recipient.

[0226] The server completes the process by delivering the message, after all checks have been completed, to the recipient. The input is the message data ready to send, and the output is the message that arrives at the recipient, confirming that the message has been sent.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] [Second Embodiment]

[0231] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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).

[0237] 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.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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".

[0243] This invention is a system that improves the quality and efficiency of electronic message transmission, and provides an automated email proofreading and review function using generation AI. Detailed embodiments of the invention will be described below.

[0244] The server receives email data from users who have finished composing their electronic messages. To analyze the received email data, the server uses natural language processing (NLP) techniques to analyze the text and identify typos and omissions. This involves using dictionary databases and language models to detect unnatural words and phrases within the email.

[0245] The server also automatically generates correction suggestions. Specifically, it proposes corrections for detected typos and omissions, and performs content review based on tone and policy, pointing out areas for improvement in expression and writing style. For example, in the case of business emails, it might suggest avoiding imperative forms to show consideration for the recipient.

[0246] The suggested corrections are sent to the user's device, where the user reviews them. The user can accept the suggestions and correct the electronic message, or make other corrections at their own discretion. Once the corrections are complete, the user sends the corrected message back to the server.

[0247] The server performs a security check as a final verification. This verifies that the message does not contain confidential information or incorrectly configured recipients. After the message is ready to send and the user approves, the electronic message is sent to the specified recipient.

[0248] For example, if a user creates an email saying, "Please be sure to attend tomorrow's meeting," the server will change "absolutely" to "definitely" and suggest softer phrasing such as "We would appreciate your attendance." In this way, the system provides an environment where users can efficiently send high-quality, error-free electronic messages.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] The user composes an electronic message and sends it to the server when it is ready to be sent. At this point, the email data is received by the server.

[0252] Step 2:

[0253] The server passes the received email data to the language processing unit, which analyzes the text using natural language processing techniques. This initiates the detection of typos and grammatical errors. The server refers to dictionary databases and language models to identify errors in word form and grammatical structure.

[0254] Step 3:

[0255] The server generates correction suggestions based on the detected typos and grammatical errors. These suggestions include replacing incorrect words with correct ones, as well as revising the wording based on the tone and content of the business email. For example, it might suggest changing "Please be sure to come" to "We would appreciate your attendance."

[0256] Step 4:

[0257] The server sends the generated revision suggestions to the user's terminal. The user reviews the suggestions and selects and adopts the revisions based on their own judgment. At this point, the user can either accept all the automated suggestions or make partial revisions.

[0258] Step 5:

[0259] Once the user has completed the corrections, they perform a final check on their device and send the corrected email back to the server. The server then checks the content again.

[0260] Step 6:

[0261] The server performs a final security check to ensure that the email does not contain any confidential information or incorrect recipient information. If necessary, it undergoes additional approval processes before being ready to send.

[0262] Step 7:

[0263] After all checks are complete, and based on user approval, the server sends an electronic message to the specified recipient. Upon successful transmission, the result is notified to the user's terminal.

[0264] (Example 1)

[0265] 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."

[0266] Conventional electronic message transmission systems suffer from problems such as reduced information quality due to typographical errors, omissions, and inappropriate expressions. Furthermore, messages may not conform to the intended tone or policy, potentially leading to misunderstandings. Security challenges, such as the leakage of confidential information and sending messages to the wrong recipients, cannot be ignored. A system is needed that efficiently solves these problems, allowing users to send high-quality electronic messages with peace of mind.

[0267] 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.

[0268] In this invention, the server includes means for receiving information transmitted by a user, means for analyzing the received information and detecting text errors, means for generating improvement suggestions based on the detected errors, means for transmitting the generated improvement suggestions to an information processing device so that they can be corrected by the user, and means for performing security checks to confirm that confidential information or incorrect recipients are not included. This enables the user to send high-quality and secure electronic messages.

[0269] "User" refers to the entity that performs the operation of sending an electronic message.

[0270] "Information" refers to text and data that are transmitted or received electronically.

[0271] "Receiving means" refers to a function for acquiring and storing information transmitted by the user.

[0272] "Analysis means" refers to a function that analyzes received information and processes it to detect errors or inappropriate expressions.

[0273] The term "improvement suggestion generation means" refers to a function that automatically creates corrective suggestions for detected errors.

[0274] An "information processing device" refers to a device that enables users to view and modify information.

[0275] "Correction mechanism" refers to a function that allows users to modify information based on improvement suggestions.

[0276] "Security verification means" refers to a function that performs processing to ensure that information is transmitted to the appropriate recipient and that the leakage of confidential information is prevented.

[0277] This invention provides a system for users to send electronic messages with high quality and security. This system is primarily realized through communication between a server, a terminal, and a user.

[0278] A server is a computer device that receives information sent from users. Upon receiving this information, the server performs analysis using natural language processing techniques. During the analysis process, software tools such as dictionary databases and language models are used to detect typographical errors, omissions, and inappropriate expressions within the information.

[0279] In response to detected deficiencies, the server generates improvement suggestions. A generation AI model supports this process, adjusting the user's message to match the intended tone and policy. Specific examples include suggestions to change imperative sentences to polite language or to simplify redundant expressions.

[0280] The user's terminal is a device for receiving and displaying improvement proposals sent from the server. Through the terminal interface, the user can view the proposals and easily reflect the modifications. As an example of a prompt sentence to support this process, a format like "Request for improvement in the tone of an email. Current message: 'Please definitely attend tomorrow's meeting.' Provide improvement suggestions." can be considered.

[0281] Furthermore, the server receives the modified message and conducts a security check. In this check, aspects such as whether there is no confidential information and whether it is not sent to the wrong recipient are evaluated. Through such a series of processes, the user can achieve the transmission of accurate and high-quality information.

[0282] The flow of specific processing in Example 1 will be described using FIG. 11.

[0283] Step 1:

[0284] The server receives the information sent from the user. The input is an electronic message created by the user, and the output is the digital data of that message. This data is obtained using a secure communication protocol.

[0285] Step 2:

[0286] The server analyzes the received digital data. In this process, text analysis using natural language processing technology is performed. The input data is the email body, from which the words and sentence structures are extracted. The output is a list of spelling mistakes, omissions, and unnatural expressions.

[0287] Step 3:

[0288] The server generates improvement proposals based on the analysis results. In this step, the generative AI model is utilized to generate appropriate amendments based on the error list as input. The output is specific modification proposals, such as the application of honorifics or the simplification of redundant expressions.

[0289] Step 4:

[0290] The server sends the generated improvement suggestions to the user's terminal. The list of improvement suggestions serves as input, and the output is displayed on the user's screen. This allows the user to review the suggested modifications.

[0291] Step 5:

[0292] The user reviews the suggestions on their device and either accepts or modifies them. The user's actions are the input, and the output is a message indicating the modifications. Specifically, the process involves clicking on a suggestion to apply the changes.

[0293] Step 6:

[0294] The user sends the corrected message to the server. The input is the corrected message, and the output is the digital data that the server receives again. Data transmission is rapid.

[0295] Step 7:

[0296] The server performs a security check on the modified message. The input is the modified message data, and the output is the message after security has been confirmed. This process evaluates whether confidential information is present and whether an incorrect recipient has been detected.

[0297] Step 8:

[0298] The server sends the message, once all confirmations are complete, to the designated recipient. The input is the confirmed message, and the output is the accurate delivery to the recipient. The server performs this process only after final approval from the user.

[0299] (Application Example 1)

[0300] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0301] Inaccuracy or inappropriate expression of information causes misunderstandings and impairs reliability. Such problems are particularly serious in electronic transactions and important notifications. Furthermore, there is a need for a method that can quickly transmit reliable information by automatically applying corrections before information is transmitted and after user confirmation. This requires improving the quality of information and efficient management.

[0302] 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.

[0303] In this invention, the server includes a device that receives information transmitted from a user, a device that analyzes the received information and detects errors, and a device that generates a correction proposal based on the detected errors. This enables automatic correction of information and final confirmation before transmission.

[0304] A "user" is a subject that transmits and receives information using a system or device.

[0305] "Information" refers to electronically transmitted messages and data, including text and other forms of digital content.

[0306] "Device" refers to a hardware or software component designed to perform a specific function.

[0307] "Analysis" is a process performed to understand the content of information and identify errors and improvement points.

[0308] "Error" refers to a mistake including typographical errors, omissions, or grammatical or stylistic inappropriateness in information.

[0309] A "correction suggestion" refers to providing more appropriate wording or content for errors or areas that need improvement.

[0310] "Transmission" refers to the act of moving information from the source to a designated destination.

[0311] "Protection assessment" is a process that verifies the security of information and examines its confidentiality and the possibility of accidental transmission.

[0312] This invention is a system that improves the quality of information by automatically analyzing information transmitted by users, detecting errors, and correcting them. The system is implemented in the following way.

[0313] The server receives information sent from the user's terminal and analyzes it. Natural language processing techniques are used for the analysis, and dictionary databases and language models are used to identify errors in the received information. Through this process, typographical errors, omissions, and unnatural words and phrases are identified.

[0314] Next, the server uses a generative AI model to generate correction suggestions based on these errors. The generated correction suggestions are sent to the user's terminal, where the user can review the suggestions and decide whether to adopt them.

[0315] Subsequently, the corrected information is finalized by the server and a protection assessment is performed. This assessment includes checks to prevent the leakage of confidential information and the setting of inappropriate destinations.

[0316] As a concrete example, consider a scenario where the AI ​​generator, in response to the instruction "Create a payment confirmation email for tomorrow," provides a revised version of the email, correcting it to a more formal tone. This allows users to manage and send information quickly and with high quality.

[0317] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0318] Step 1:

[0319] The server receives information transmitted from the user's terminal. The input is an electronic message created by the user, and processing begins when the server receives it. The output is primary data to be used in subsequent analysis processes.

[0320] Step 2:

[0321] The server analyzes the received information using natural language processing (NLP) technology. The input is the previously received electronic message; the server uses an NLP engine to perform grammar and spell checks, detecting errors and omissions. The output is information with typos, omissions, and unnatural expressions highlighted.

[0322] Step 3:

[0323] The server generates correction suggestions using a generative AI model. The input is information in which errors have been identified, and based on this, the AI ​​generates suggestions including appropriate corrections and stylistic improvements. The output is presented to the user as a document incorporating the specific correction suggestions.

[0324] Step 4:

[0325] The terminal displays correction suggestions sent from the server to the user. The input is data containing suggestions from the server, which the terminal reads and displays on the interface so the user can review the corrections. The output is visualized information to assist the user in making decisions and selecting corrections.

[0326] Step 5:

[0327] Users review the proposed revisions and either adopt them or make their own modifications. User actions serve as input, and the output is the final, revised information. This allows for user-driven creation of high-quality information.

[0328] Step 6:

[0329] The server finally verifies the information modified by the user and performs a security assessment. The input is information confirmed by the user, and the server performs security checks on the data. The output is information that is guaranteed to prevent confidential information and accidental transmission, and if there are no problems, it is ready to be sent.

[0330] 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.

[0331] This invention incorporates an emotion engine that recognizes user emotions, in addition to an automated email proofreading and review function using generation AI, in order to improve the quality and efficiency related to the creation and transmission of electronic messages. This makes it possible to provide more appropriate revision suggestions.

[0332] The server receives electronic messages created by users and analyzes their content. During the analysis process, the server first uses language processing technology to detect typos and grammatical errors and generates necessary correction suggestions. Simultaneously, an emotion engine identifies the emotions expressed in the user's writing and suggests revisions to the tone and content accordingly.

[0333] This allows the emotion engine to recognize, for example, anger in a user's mind, and suggest more neutral and appropriate expressions. For instance, if a user types, "Please deal with this immediately! I'm really angry," the emotion engine will sense the user's anger and suggest a calmer expression such as, "Please take swift action."

[0334] The generated correction suggestions are sent to the user's device for review. The user can consider the suggestions and revise the message as needed. Once the revisions are complete, the user sends the revised message back to the server.

[0335] The server performs a final review of the modified message. This final review includes security checks, and the message is then ready for transmission. Once the message is approved, it is sent according to the user's instructions. This makes it possible to efficiently send high-quality electronic messages that have been edited to reflect the user's emotions.

[0336] The following describes the processing flow.

[0337] Step 1:

[0338] The user composes an electronic message on their device and prepares it for sending. They then perform the necessary steps to send the completed message to the server.

[0339] Step 2:

[0340] The server prepares to process the electronic message received from the user, and first starts text analysis in the language processing unit. This analysis checks for words and grammatical structures and identifies typos and omissions.

[0341] Step 3:

[0342] The server generates correction suggestions based on the detected typos and grammatical errors. It refers to a dictionary database and suggests replacing incorrect words with correct ones.

[0343] Step 4:

[0344] Simultaneously, the server uses an emotion engine to identify the user's emotions from the content of the electronic message. The emotion engine analyzes the emotions in the text and identifies various emotion categories (e.g., anger, joy, anxiety).

[0345] Step 5:

[0346] Based on the perceived emotions, the server generates additional revised suggestions with adjusted tones to avoid misunderstandings. For example, if overly strong language is used, it will suggest softer phrasing.

[0347] Step 6:

[0348] The server sends all generated correction suggestions to the user's terminal. The user reviews these suggestions on their terminal and makes the necessary corrections to the electronic message. The user can accept the suggestions or make their own corrections.

[0349] Step 7:

[0350] After completing the corrections, the user resends the electronic message to the server. As a final check, the server verifies the content and security to ensure that the message does not contain any confidential information or be addressed to the wrong recipient.

[0351] Step 8:

[0352] Once the server is ready to send, it will send the electronic message to the specified recipient after the user's final approval. After the transmission is complete, the server will notify the user's device of the result.

[0353] (Example 2)

[0354] 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".

[0355] In creating electronic communications, challenges exist not only in preventing typos and omissions, but also in generating appropriate expressions that resonate with the user's emotions. Furthermore, creating communications that match the tone and policy of the content can be time-consuming. Additionally, there is a growing need for security checks before transmission to ensure that confidential information and incorrect recipients are not included. Technologies that can efficiently and effectively address these challenges are needed.

[0356] 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.

[0357] In this invention, the server includes means for receiving electronic communications transmitted by a user, means for analyzing the received electronic communications and detecting grammatical errors and input errors, and means for analyzing the user's emotions and generating emotion-based correction suggestions. This makes it possible to generate appropriate correction suggestions that are sensitive to the user's emotions and to correct electronic communications to be of higher quality and more to the user's tone. It also facilitates the transmission of secure communications that do not contain confidential information or incorrect destinations.

[0358] "Electronic communication" refers to digital messages created by a user and sent to other users or systems.

[0359] A "grammatical error" refers to a grammatical inaccuracy or flaw in the content of electronic communications.

[0360] "Input errors" refer to spelling mistakes or typos that occur when users create electronic communications.

[0361] A "correction suggestion" is a proposal to recommend more appropriate expressions or structures to the user based on detected grammatical errors, input mistakes, or the results of sentiment analysis.

[0362] "Sentiment analysis" is the process of identifying and analyzing a user's psychological and emotional state from the content of their electronic communications.

[0363] "Security verification" is the process of checking for the presence of confidential information and the accuracy of the destination before electronic communications are transmitted, in order to ensure security.

[0364] This invention is a system that utilizes natural language processing technology and emotion recognition technology to improve the quality of electronic communications.

[0365] The server receives electronic communications sent by users from their terminals and analyzes their content. The hardware used here includes general server equipment, and the software includes a generative AI model suitable for text analysis. Specifically, the generative AI model used is a language model equipped with natural language processing technology.

[0366] During the analysis process, the server detects typographical errors and grammatical mistakes in electronic communications and generates appropriate correction suggestions based on these. Furthermore, the server uses emotion recognition technology to analyze the user's emotional state and suggests modifications to expressions and tone that correspond to those emotions.

[0367] Once a revision suggestion is generated, the server sends it to the user's terminal. The user can review the suggestion and revise their message if necessary. This interaction enables high-quality electronic communication that is sensitive to emotions.

[0368] For example, if a user enters "Please deal with this immediately! I'm really angry," the server will perform sentiment analysis and suggest a calmer expression such as "Please take prompt action." An example of the prompt used in this case would be: "User input: Please deal with this immediately! I'm really angry. Generating AI prompt: Identify expressions that convey anger in this message and generate a revised suggestion in a more neutral tone."

[0369] Thus, the present invention helps users create electronic communications with well-organized content for efficient communication.

[0370] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0371] Step 1:

[0372] The server receives electronic communications from the user's terminal. It receives the user message as text data as input and stores it in a database. As a preprocessing step, it normalizes the text, removing unnecessary symbols and spaces. The output at this step is clean text data ready for analysis.

[0373] Step 2:

[0374] The server analyzes the received clean text data using natural language processing techniques. The input is the clean text obtained in step 1, and a generative AI model is used here. Specifically, it detects grammatical errors and typos and generates correction suggestions. The output is a list of errors and correction suggestions. This brings the user's message closer to grammatically correct form.

[0375] Step 3:

[0376] The server analyzes the user's emotions contained in the text data. The input is the text data processed in step 2, and the generating AI model performs emotion analysis. Specifically, it uses an emotion engine to identify the user's emotional state and generates suggestions to modify the tone and expression to suit that emotion. The output is the emotion-based modification suggestions.

[0377] Step 4:

[0378] The server sends the generated correction suggestions to the user's terminal. The input for this step is the correction suggestions generated in steps 2 and 3. The server formats each correction suggestion in an easily understandable format and transfers it to the user's terminal. The output is correction suggestion data that the user can review.

[0379] Step 5:

[0380] The user reviews the suggested revisions on their device and decides whether to revise the message content. The input is the suggested revision data sent from the server. The user accepts the suggestions or makes manual revisions to determine the final version of the message. The output is the revised message data. Specifically, the user confirms the revised version and sends it to the server.

[0381] Step 6:

[0382] The server receives the final version of the message from the user and performs a final check. The input for this step is the message data modified by the user. The server performs a security check to ensure that it does not contain confidential information or misdirected recipients. The output is an electronic communication ready for transmission. This ensures secure and high-quality electronic communication.

[0383] (Application Example 2)

[0384] 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."

[0385] Modern communication often takes place via electronic messages, requiring not only the detection of typos and grammatical errors, but also the ability to appropriately understand the sender's emotions and revise messages to match the appropriate tone. However, conventional systems often fail to offer emotion-based revision suggestions, potentially leading to emotional misunderstandings. Furthermore, security checks are necessary to ensure the content is safe and appropriate before transmission. Technologies are needed to address these challenges.

[0386] 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.

[0387] In this invention, the server includes means for recognizing the user's emotions and generating tone correction suggestions based on those emotions; means for transmitting the generated correction suggestions to the user's terminal and enabling the user to make corrections; and means for final confirmation of the corrected electronic message and preparing it for transmission. This makes it possible to efficiently transmit high-quality electronic messages that appropriately take the user's emotions into consideration.

[0388] An "electronic message" is a digital message transmitted using a computer or mobile device, and can include text, images, and files.

[0389] "Typographical errors and omissions" refer to errors or omissions in the use of language within electronic messages and are one of the factors that hinder accurate communication.

[0390] "Correction suggestions" are recommended sentences or expressions generated by the system to correct typos and omissions, and are intended to improve the accuracy of electronic messages.

[0391] "Emotional recognition" is the process of analyzing and understanding a user's emotional state from the content of electronic messages, and is necessary to improve the quality of communication.

[0392] A "tone correction suggestion" is a proposal to change the emotional tone of an electronic message to an appropriate one, providing language that will not mislead the recipient.

[0393] A "user terminal" is a hardware device used by a user to perform operations such as creating, sending, and receiving electronic messages, and includes smartphones and personal computers.

[0394] "Final confirmation" is the process of verifying that the content and recipient of an electronic message are correct before sending it, in order to prevent accidental sending or miscommunication.

[0395] "Preparing to send" refers to completing the necessary processes to actually send an electronic message after it has been confirmed to be accurate and secure.

[0396] This invention provides a system for improving the quality of electronic messages. This system is built using a server, a user terminal, and necessary AI software.

[0397] The server has the capability to receive electronic messages sent by users. These messages are stored in a database and kept until the analysis program is run. Next, the server performs natural language processing and uses a generative AI model to detect typos and grammatical errors in the messages. SpaCy, an open-source natural language processing tool, is commonly used.

[0398] Furthermore, the server uses an emotion recognition engine to analyze the emotional tone of the message. This process utilizes a PyTorch model for emotion analysis to generate expressions that more accurately reflect the user's intent. This engine can correct expressions that the user unintentionally uses to mislead others.

[0399] The user terminal receives correction suggestions sent from the server and has the capability for the user to accept the suggestions or make further corrections. This allows the user to review the final corrected message and make further edits if necessary.

[0400] As a concrete example, consider a scenario where a user is creating a customer support email. Suppose the user uses the phrase, "I am disappointed with this product; please address this." An example of a prompt might be, "Perform a sentiment analysis on the following email and revise it to a more positive expression. Original: 'I am disappointed with this product; please address this.'" This prompt allows the system to suggest a more polite expression, improving the impression the email recipient has.

[0401] This system improves the quality and accuracy of emails, enabling communication that avoids misunderstandings.

[0402] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0403] Step 1:

[0404] The user composes an electronic message and presses the send button.

[0405] In this step, the user's device is prepared to send message data to the server. The input is the electronic message created by the user, and the output is the data to be sent to the server.

[0406] Step 2:

[0407] The server receives an electronic message.

[0408] The server receives messages sent from the user terminal and prepares to parse them. The input is the message received from the user terminal, and the output is the message data for proceeding to the next parsing step.

[0409] Step 3:

[0410] The server detects typos and omissions in messages.

[0411] The server performs natural language processing using spaCy to identify typos and omissions in messages. The input is the message data to be analyzed, and the output is the message data with the typos and omissions identified.

[0412] Step 4:

[0413] The server uses an emotion engine to analyze the message.

[0414] The server uses PyTorch to perform sentiment recognition and evaluate the emotional tone of messages. The input is message data including typographical errors, and the output is message data with sentiment scores assigned to it.

[0415] Step 5:

[0416] The server generates correction suggestions.

[0417] The server uses a generative AI model to create correction suggestions based on detected typos and grammatical errors, as well as the assessed sentiment. The input is message data with sentiment scores, and the output is data with correction suggestions attached.

[0418] Step 6:

[0419] The server sends the suggested corrections to the user's terminal.

[0420] The server forwards the generated correction suggestions to the user's terminal, making them available for review and correction. The input is message data with correction suggestions, and the output is notification data received by the user's terminal.

[0421] Step 7:

[0422] The user reviews the suggested corrections and modifies the message as needed.

[0423] Based on the correction suggestions received on the user's terminal, the user reviews the message content and makes corrections. The input is the correction suggestion and the original message, and the output is the message corrected by the user.

[0424] Step 8:

[0425] The user sends the corrected message to the server.

[0426] The user terminal resends the modified message data to the server and prepares for final confirmation. The input is the message modified by the user, and the output is the data sent to the server.

[0427] Step 9:

[0428] The server performs final verification and security checks.

[0429] The server performs a final content review and security check on the modified message and completes the preparation for transmission. The input is the final version of the message data, and the output is the message data ready for transmission.

[0430] Step 10:

[0431] The server sends the final electronic message to the designated recipient.

[0432] The server completes the process by delivering the message, after all checks have been completed, to the recipient. The input is the message data ready to send, and the output is the message that arrives at the recipient, confirming that the message has been sent.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] [Third Embodiment]

[0437] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0438] 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.

[0439] 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).

[0440] 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.

[0441] 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.

[0442] 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).

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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".

[0449] This invention is a system that improves the quality and efficiency of electronic message transmission, and provides an automated email proofreading and review function using generation AI. Detailed embodiments of the invention will be described below.

[0450] The server receives email data from users who have finished composing their electronic messages. To analyze the received email data, the server uses natural language processing (NLP) techniques to analyze the text and identify typos and omissions. This involves using dictionary databases and language models to detect unnatural words and phrases within the email.

[0451] The server also automatically generates correction suggestions. Specifically, it proposes corrections for detected typos and omissions, and performs content review based on tone and policy, pointing out areas for improvement in expression and writing style. For example, in the case of business emails, it might suggest avoiding imperative forms to show consideration for the recipient.

[0452] The suggested corrections are sent to the user's device, where the user reviews them. The user can accept the suggestions and correct the electronic message, or make other corrections at their own discretion. Once the corrections are complete, the user sends the corrected message back to the server.

[0453] The server performs a security check as a final verification. This verifies that the message does not contain confidential information or incorrectly configured recipients. After the message is ready to send and the user approves, the electronic message is sent to the specified recipient.

[0454] For example, if a user creates an email saying, "Please be sure to attend tomorrow's meeting," the server will change "absolutely" to "definitely" and suggest softer phrasing such as "We would appreciate your attendance." In this way, the system provides an environment where users can efficiently send high-quality, error-free electronic messages.

[0455] The following describes the processing flow.

[0456] Step 1:

[0457] The user composes an electronic message and sends it to the server when it is ready to be sent. At this point, the email data is received by the server.

[0458] Step 2:

[0459] The server passes the received email data to the language processing unit, which analyzes the text using natural language processing techniques. This initiates the detection of typos and grammatical errors. The server refers to dictionary databases and language models to identify errors in word form and grammatical structure.

[0460] Step 3:

[0461] The server generates correction suggestions based on the detected typos and grammatical errors. These suggestions include replacing incorrect words with correct ones, as well as revising the wording based on the tone and content of the business email. For example, it might suggest changing "Please be sure to come" to "We would appreciate your attendance."

[0462] Step 4:

[0463] The server sends the generated revision suggestions to the user's terminal. The user reviews the suggestions and selects and adopts the revisions based on their own judgment. At this point, the user can either accept all the automated suggestions or make partial revisions.

[0464] Step 5:

[0465] Once the user has completed the corrections, they perform a final check on their device and send the corrected email back to the server. The server then checks the content again.

[0466] Step 6:

[0467] The server performs a final security check to ensure that the email does not contain any confidential information or incorrect recipient information. If necessary, it undergoes additional approval processes before being ready to send.

[0468] Step 7:

[0469] After all checks are complete, and based on user approval, the server sends an electronic message to the specified recipient. Upon successful transmission, the result is notified to the user's terminal.

[0470] (Example 1)

[0471] 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."

[0472] Conventional electronic message transmission systems suffer from problems such as reduced information quality due to typographical errors, omissions, and inappropriate expressions. Furthermore, messages may not conform to the intended tone or policy, potentially leading to misunderstandings. Security challenges, such as the leakage of confidential information and sending messages to the wrong recipients, cannot be ignored. A system is needed that efficiently solves these problems, allowing users to send high-quality electronic messages with peace of mind.

[0473] 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.

[0474] In this invention, the server includes means for receiving information transmitted by a user, means for analyzing the received information and detecting text errors, means for generating improvement suggestions based on the detected errors, means for transmitting the generated improvement suggestions to an information processing device so that they can be corrected by the user, and means for performing security checks to confirm that confidential information or incorrect recipients are not included. This enables the user to send high-quality and secure electronic messages.

[0475] "User" refers to the entity that performs the operation of sending an electronic message.

[0476] "Information" refers to text and data that are transmitted or received electronically.

[0477] "Receiving means" refers to a function for acquiring and storing information transmitted by the user.

[0478] "Analysis means" refers to a function that analyzes received information and processes it to detect errors or inappropriate expressions.

[0479] The term "improvement suggestion generation means" refers to a function that automatically creates corrective suggestions for detected errors.

[0480] An "information processing device" refers to a device that enables users to view and modify information.

[0481] "Correction mechanism" refers to a function that allows users to modify information based on improvement suggestions.

[0482] "Security verification means" refers to a function that performs processing to ensure that information is transmitted to the appropriate recipient and that the leakage of confidential information is prevented.

[0483] This invention provides a system for users to send electronic messages with high quality and security. This system is primarily realized through communication between a server, a terminal, and a user.

[0484] A server is a computer device that receives information sent from users. Upon receiving this information, the server performs analysis using natural language processing techniques. During the analysis process, software tools such as dictionary databases and language models are used to detect typographical errors, omissions, and inappropriate expressions within the information.

[0485] In response to detected deficiencies, the server generates improvement suggestions. A generation AI model supports this process, adjusting the user's message to match the intended tone and policy. Specific examples include suggestions to change imperative sentences to polite language or to simplify redundant expressions.

[0486] The user's terminal is a device for receiving and displaying improvement suggestions sent from the server. Through the terminal's interface, the user can review the suggestions and easily implement the corrections. An example of a prompt message to support this process would be: "Requesting improvements to the tone of your email. Current message: 'You must attend tomorrow's meeting.' Please provide improvement suggestions."

[0487] Furthermore, the server receives the modified message and performs a security check. This check evaluates whether it contains confidential information and whether it is being sent to the wrong recipient. Through this series of processes, users can ensure that they send accurate and high-quality information.

[0488] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0489] Step 1:

[0490] The server receives information sent by the user. The input is an electronic message created by the user, and the output is the digital data of that message. This data is retrieved using a secure communication protocol.

[0491] Step 2:

[0492] The server analyzes the received digital data. This process involves text analysis using natural language processing techniques. The input data is the email body, from which words and sentence structures are extracted. The output is a list of typos, omissions, and unnatural expressions.

[0493] Step 3:

[0494] The server generates improvement suggestions based on the analysis results. In this step, it utilizes a generative AI model to generate appropriate corrections based on the error list as input. The output is a specific correction suggestion, such as applying honorific language or simplifying redundant expressions.

[0495] Step 4:

[0496] The server sends the generated improvement suggestions to the user's terminal. The list of improvement suggestions serves as input, and the output is displayed on the user's screen. This allows the user to review the suggested modifications.

[0497] Step 5:

[0498] The user reviews the suggestions on their device and either accepts or modifies them. The user's actions are the input, and the output is a message indicating the modifications. Specifically, the process involves clicking on a suggestion to apply the changes.

[0499] Step 6:

[0500] The user sends the corrected message to the server. The input is the corrected message, and the output is the digital data that the server receives again. Data transmission is rapid.

[0501] Step 7:

[0502] The server performs a security check on the modified message. The input is the modified message data, and the output is the message after security has been confirmed. This process evaluates whether confidential information is present and whether an incorrect recipient has been detected.

[0503] Step 8:

[0504] The server sends the message, once all confirmations are complete, to the designated recipient. The input is the confirmed message, and the output is the accurate delivery to the recipient. The server performs this process only after final approval from the user.

[0505] (Application Example 1)

[0506] 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."

[0507] Inaccurate or inappropriate information can lead to misunderstandings and undermine credibility. Such problems are particularly serious in electronic transactions and important notices. Furthermore, there is a need for methods that automatically apply corrections before information is sent and, even after user confirmation, ensure the rapid transmission of reliable information. This necessitates improved information quality and efficient management.

[0508] 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.

[0509] In this invention, the server includes a device for receiving information transmitted from a user, a device for analyzing the received information and detecting errors, and a device for generating correction suggestions based on the detected errors. This enables automatic correction of information and final confirmation before transmission.

[0510] A "user" is an entity that uses a system or device to send and receive information.

[0511] "Information" refers to messages and data transmitted electronically, including text and other forms of digital content.

[0512] "Device" refers to a hardware or software component designed to perform a specific function.

[0513] "Analysis" is the process of understanding the content of information and identifying errors or areas for improvement.

[0514] An "error" refers to a mistake in information that includes misspellings, omissions, or grammatical or stylistic inappropriateness.

[0515] A "correction suggestion" refers to providing more appropriate wording or content for errors or areas that need improvement.

[0516] "Transmission" refers to the act of moving information from the source to a designated destination.

[0517] "Protection assessment" is a process that verifies the security of information and examines its confidentiality and the possibility of accidental transmission.

[0518] This invention is a system that improves the quality of information by automatically analyzing information transmitted by users, detecting errors, and correcting them. The system is implemented in the following way.

[0519] The server receives information sent from the user's terminal and analyzes it. Natural language processing techniques are used for the analysis, and dictionary databases and language models are used to identify errors in the received information. Through this process, typographical errors, omissions, and unnatural words and phrases are identified.

[0520] Next, the server uses a generative AI model to generate correction suggestions based on these errors. The generated correction suggestions are sent to the user's terminal, where the user can review the suggestions and decide whether to adopt them.

[0521] Subsequently, the corrected information is finalized by the server and a protection assessment is performed. This assessment includes checks to prevent the leakage of confidential information and the setting of inappropriate destinations.

[0522] As a concrete example, consider a scenario where the AI ​​generator, in response to the instruction "Create a payment confirmation email for tomorrow," provides a revised version of the email, correcting it to a more formal tone. This allows users to manage and send information quickly and with high quality.

[0523] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0524] Step 1:

[0525] The server receives information transmitted from the user's terminal. The input is an electronic message created by the user, and processing begins when the server receives it. The output is primary data to be used in subsequent analysis processes.

[0526] Step 2:

[0527] The server analyzes the received information using natural language processing (NLP) technology. The input is the previously received electronic message; the server uses an NLP engine to perform grammar and spell checks, detecting errors and omissions. The output is information with typos, omissions, and unnatural expressions highlighted.

[0528] Step 3:

[0529] The server generates correction suggestions using a generative AI model. The input is information in which errors have been identified, and based on this, the AI ​​generates suggestions including appropriate corrections and stylistic improvements. The output is presented to the user as a document incorporating the specific correction suggestions.

[0530] Step 4:

[0531] The terminal displays correction suggestions sent from the server to the user. The input is data containing suggestions from the server, which the terminal reads and displays on the interface so the user can review the corrections. The output is visualized information to assist the user in making decisions and selecting corrections.

[0532] Step 5:

[0533] Users review the proposed revisions and either adopt them or make their own modifications. User actions serve as input, and the output is the final, revised information. This allows for user-driven creation of high-quality information.

[0534] Step 6:

[0535] The server finally verifies the information modified by the user and performs a security assessment. The input is information confirmed by the user, and the server performs security checks on the data. The output is information that is guaranteed to prevent confidential information and accidental transmission, and if there are no problems, it is ready to be sent.

[0536] 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.

[0537] This invention incorporates an emotion engine that recognizes user emotions, in addition to an automated email proofreading and review function using generation AI, in order to improve the quality and efficiency related to the creation and transmission of electronic messages. This makes it possible to provide more appropriate revision suggestions.

[0538] The server receives electronic messages created by users and analyzes their content. During the analysis process, the server first uses language processing technology to detect typos and grammatical errors and generates necessary correction suggestions. Simultaneously, an emotion engine identifies the emotions expressed in the user's writing and suggests revisions to the tone and content accordingly.

[0539] This allows the emotion engine to recognize, for example, anger in a user's mind, and suggest more neutral and appropriate expressions. For instance, if a user types, "Please deal with this immediately! I'm really angry," the emotion engine will sense the user's anger and suggest a calmer expression such as, "Please take swift action."

[0540] The generated correction suggestions are sent to the user's device for review. The user can consider the suggestions and revise the message as needed. Once the revisions are complete, the user sends the revised message back to the server.

[0541] The server performs a final review of the modified message. This final review includes security checks, and the message is then ready for transmission. Once the message is approved, it is sent according to the user's instructions. This makes it possible to efficiently send high-quality electronic messages that have been edited to reflect the user's emotions.

[0542] The following describes the processing flow.

[0543] Step 1:

[0544] The user composes an electronic message on their device and prepares it for sending. They then perform the necessary steps to send the completed message to the server.

[0545] Step 2:

[0546] The server prepares to process the electronic message received from the user, and first starts text analysis in the language processing unit. This analysis checks for words and grammatical structures and identifies typos and omissions.

[0547] Step 3:

[0548] The server generates correction suggestions based on the detected typos and grammatical errors. It refers to a dictionary database and suggests replacing incorrect words with correct ones.

[0549] Step 4:

[0550] Simultaneously, the server uses an emotion engine to identify the user's emotions from the content of the electronic message. The emotion engine analyzes the emotions in the text and identifies various emotion categories (e.g., anger, joy, anxiety).

[0551] Step 5:

[0552] Based on the perceived emotions, the server generates additional revised suggestions with adjusted tones to avoid misunderstandings. For example, if overly strong language is used, it will suggest softer phrasing.

[0553] Step 6:

[0554] The server sends all generated correction suggestions to the user's terminal. The user reviews these suggestions on their terminal and makes the necessary corrections to the electronic message. The user can accept the suggestions or make their own corrections.

[0555] Step 7:

[0556] After completing the corrections, the user resends the electronic message to the server. As a final check, the server verifies the content and security to ensure that the message does not contain any confidential information or be addressed to the wrong recipient.

[0557] Step 8:

[0558] Once the server is ready to send, it will send the electronic message to the specified recipient after the user's final approval. After the transmission is complete, the server will notify the user's device of the result.

[0559] (Example 2)

[0560] 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."

[0561] In creating electronic communications, challenges exist not only in preventing typos and omissions, but also in generating appropriate expressions that resonate with the user's emotions. Furthermore, creating communications that match the tone and policy of the content can be time-consuming. Additionally, there is a growing need for security checks before transmission to ensure that confidential information and incorrect recipients are not included. Technologies that can efficiently and effectively address these challenges are needed.

[0562] 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.

[0563] In this invention, the server includes means for receiving electronic communications transmitted by a user, means for analyzing the received electronic communications and detecting grammatical errors and input errors, and means for analyzing the user's emotions and generating emotion-based correction suggestions. This makes it possible to generate appropriate correction suggestions that are sensitive to the user's emotions and to correct electronic communications to be of higher quality and more to the user's tone. It also facilitates the transmission of secure communications that do not contain confidential information or incorrect destinations.

[0564] "Electronic communication" refers to digital messages created by a user and sent to other users or systems.

[0565] A "grammatical error" refers to a grammatical inaccuracy or flaw in the content of electronic communications.

[0566] "Input errors" refer to spelling mistakes or typos that occur when users create electronic communications.

[0567] A "correction suggestion" is a proposal to recommend more appropriate expressions or structures to the user based on detected grammatical errors, input mistakes, or the results of sentiment analysis.

[0568] "Sentiment analysis" is the process of identifying and analyzing a user's psychological and emotional state from the content of their electronic communications.

[0569] "Security verification" is the process of checking for the presence of confidential information and the accuracy of the destination before electronic communications are transmitted, in order to ensure security.

[0570] This invention is a system that utilizes natural language processing technology and emotion recognition technology to improve the quality of electronic communications.

[0571] The server receives electronic communications sent by users from their terminals and analyzes their content. The hardware used here includes general server equipment, and the software includes a generative AI model suitable for text analysis. Specifically, the generative AI model used is a language model equipped with natural language processing technology.

[0572] During the analysis process, the server detects typographical errors and grammatical mistakes in electronic communications and generates appropriate correction suggestions based on these. Furthermore, the server uses emotion recognition technology to analyze the user's emotional state and suggests modifications to expressions and tone that correspond to those emotions.

[0573] Once a revision suggestion is generated, the server sends it to the user's terminal. The user can review the suggestion and revise their message if necessary. This interaction enables high-quality electronic communication that is sensitive to emotions.

[0574] For example, if a user enters "Please deal with this immediately! I'm really angry," the server will perform sentiment analysis and suggest a calmer expression such as "Please take prompt action." An example of the prompt used in this case would be: "User input: Please deal with this immediately! I'm really angry. Generating AI prompt: Identify expressions that convey anger in this message and generate a revised suggestion in a more neutral tone."

[0575] Thus, the present invention helps users create electronic communications with well-organized content for efficient communication.

[0576] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0577] Step 1:

[0578] The server receives electronic communications from the user's terminal. It receives the user message as text data as input and stores it in a database. As a preprocessing step, it normalizes the text, removing unnecessary symbols and spaces. The output at this step is clean text data ready for analysis.

[0579] Step 2:

[0580] The server analyzes the received clean text data using natural language processing techniques. The input is the clean text obtained in step 1, and a generative AI model is used here. Specifically, it detects grammatical errors and typos and generates correction suggestions. The output is a list of errors and correction suggestions. This brings the user's message closer to grammatically correct form.

[0581] Step 3:

[0582] The server analyzes the user's emotions contained in the text data. The input is the text data processed in step 2, and the generating AI model performs emotion analysis. Specifically, it uses an emotion engine to identify the user's emotional state and generates suggestions to modify the tone and expression to suit that emotion. The output is the emotion-based modification suggestions.

[0583] Step 4:

[0584] The server sends the generated correction suggestions to the user's terminal. The input for this step is the correction suggestions generated in steps 2 and 3. The server formats each correction suggestion in an easily understandable format and transfers it to the user's terminal. The output is correction suggestion data that the user can review.

[0585] Step 5:

[0586] The user reviews the suggested revisions on their device and decides whether to revise the message content. The input is the suggested revision data sent from the server. The user accepts the suggestions or makes manual revisions to determine the final version of the message. The output is the revised message data. Specifically, the user confirms the revised version and sends it to the server.

[0587] Step 6:

[0588] The server receives the final version of the message from the user and performs a final check. The input for this step is the message data modified by the user. The server performs a security check to ensure that it does not contain confidential information or misdirected recipients. The output is an electronic communication ready for transmission. This ensures secure and high-quality electronic communication.

[0589] (Application Example 2)

[0590] 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."

[0591] Modern communication often takes place via electronic messages, requiring not only the detection of typos and grammatical errors, but also the ability to appropriately understand the sender's emotions and revise messages to match the appropriate tone. However, conventional systems often fail to offer emotion-based revision suggestions, potentially leading to emotional misunderstandings. Furthermore, security checks are necessary to ensure the content is safe and appropriate before transmission. Technologies are needed to address these challenges.

[0592] 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.

[0593] In this invention, the server includes means for recognizing the user's emotions and generating tone correction suggestions based on those emotions; means for transmitting the generated correction suggestions to the user's terminal and enabling the user to make corrections; and means for final confirmation of the corrected electronic message and preparing it for transmission. This makes it possible to efficiently transmit high-quality electronic messages that appropriately take the user's emotions into consideration.

[0594] An "electronic message" is a digital message transmitted using a computer or mobile device, and can include text, images, and files.

[0595] "Typographical errors and omissions" refer to errors or omissions in the use of language within electronic messages and are one of the factors that hinder accurate communication.

[0596] "Correction suggestions" are recommended sentences or expressions generated by the system to correct typos and omissions, and are intended to improve the accuracy of electronic messages.

[0597] "Emotional recognition" is the process of analyzing and understanding a user's emotional state from the content of electronic messages, and is necessary to improve the quality of communication.

[0598] A "tone correction suggestion" is a proposal to change the emotional tone of an electronic message to an appropriate one, providing language that will not mislead the recipient.

[0599] A "user terminal" is a hardware device used by a user to perform operations such as creating, sending, and receiving electronic messages, and includes smartphones and personal computers.

[0600] "Final confirmation" is the process of verifying that the content and recipient of an electronic message are correct before sending it, in order to prevent accidental sending or miscommunication.

[0601] "Preparing to send" refers to completing the necessary processes to actually send an electronic message after it has been confirmed to be accurate and secure.

[0602] This invention provides a system for improving the quality of electronic messages. This system is built using a server, a user terminal, and necessary AI software.

[0603] The server has the capability to receive electronic messages sent by users. These messages are stored in a database and kept until the analysis program is run. Next, the server performs natural language processing and uses a generative AI model to detect typos and grammatical errors in the messages. SpaCy, an open-source natural language processing tool, is commonly used.

[0604] Furthermore, the server uses an emotion recognition engine to analyze the emotional tone of the message. This process utilizes a PyTorch model for emotion analysis to generate expressions that more accurately reflect the user's intent. This engine can correct expressions that the user unintentionally uses to mislead others.

[0605] The user terminal receives correction suggestions sent from the server and has the capability for the user to accept the suggestions or make further corrections. This allows the user to review the final corrected message and make further edits if necessary.

[0606] As a concrete example, consider a scenario where a user is creating a customer support email. Suppose the user uses the phrase, "I am disappointed with this product; please address this." An example of a prompt might be, "Perform a sentiment analysis on the following email and revise it to a more positive expression. Original: 'I am disappointed with this product; please address this.'" This prompt allows the system to suggest a more polite expression, improving the impression the email recipient has.

[0607] This system improves the quality and accuracy of emails, enabling communication that avoids misunderstandings.

[0608] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0609] Step 1:

[0610] The user composes an electronic message and presses the send button.

[0611] In this step, the user's device is prepared to send message data to the server. The input is the electronic message created by the user, and the output is the data to be sent to the server.

[0612] Step 2:

[0613] The server receives an electronic message.

[0614] The server receives messages sent from the user terminal and prepares to parse them. The input is the message received from the user terminal, and the output is the message data for proceeding to the next parsing step.

[0615] Step 3:

[0616] The server detects typos and omissions in messages.

[0617] The server performs natural language processing using spaCy to identify typos and omissions in messages. The input is the message data to be analyzed, and the output is the message data with the typos and omissions identified.

[0618] Step 4:

[0619] The server uses an emotion engine to analyze the message.

[0620] The server uses PyTorch to perform sentiment recognition and evaluate the emotional tone of messages. The input is message data including typographical errors, and the output is message data with sentiment scores assigned to it.

[0621] Step 5:

[0622] The server generates correction suggestions.

[0623] The server uses a generative AI model to create correction suggestions based on detected typos and grammatical errors, as well as the assessed sentiment. The input is message data with sentiment scores, and the output is data with correction suggestions attached.

[0624] Step 6:

[0625] The server sends the suggested corrections to the user's terminal.

[0626] The server forwards the generated correction suggestions to the user's terminal, making them available for review and correction. The input is message data with correction suggestions, and the output is notification data received by the user's terminal.

[0627] Step 7:

[0628] The user reviews the suggested corrections and modifies the message as needed.

[0629] Based on the correction suggestions received on the user's terminal, the user reviews the message content and makes corrections. The input is the correction suggestion and the original message, and the output is the message corrected by the user.

[0630] Step 8:

[0631] The user sends the corrected message to the server.

[0632] The user terminal resends the modified message data to the server and prepares for final confirmation. The input is the message modified by the user, and the output is the data sent to the server.

[0633] Step 9:

[0634] The server performs final verification and security checks.

[0635] The server performs a final content review and security check on the modified message and completes the preparation for transmission. The input is the final version of the message data, and the output is the message data ready for transmission.

[0636] Step 10:

[0637] The server sends the final electronic message to the designated recipient.

[0638] The server completes the process by delivering the message, after all checks have been completed, to the recipient. The input is the message data ready to send, and the output is the message that arrives at the recipient, confirming that the message has been sent.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] [Fourth Embodiment]

[0643] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0644] 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.

[0645] 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).

[0646] 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.

[0647] 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.

[0648] 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).

[0649] 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.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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".

[0656] This invention is a system that improves the quality and efficiency of electronic message transmission, and provides an automated email proofreading and review function using generation AI. Detailed embodiments of the invention will be described below.

[0657] The server receives email data from users who have finished composing their electronic messages. To analyze the received email data, the server uses natural language processing (NLP) techniques to analyze the text and identify typos and omissions. This involves using dictionary databases and language models to detect unnatural words and phrases within the email.

[0658] The server also automatically generates correction suggestions. Specifically, it proposes corrections for detected typos and omissions, and performs content review based on tone and policy, pointing out areas for improvement in expression and writing style. For example, in the case of business emails, it might suggest avoiding imperative forms to show consideration for the recipient.

[0659] The suggested corrections are sent to the user's device, where the user reviews them. The user can accept the suggestions and correct the electronic message, or make other corrections at their own discretion. Once the corrections are complete, the user sends the corrected message back to the server.

[0660] The server performs a security check as a final verification. This verifies that the message does not contain confidential information or incorrectly configured recipients. After the message is ready to send and the user approves, the electronic message is sent to the specified recipient.

[0661] For example, if a user creates an email saying, "Please be sure to attend tomorrow's meeting," the server will change "absolutely" to "definitely" and suggest softer phrasing such as "We would appreciate your attendance." In this way, the system provides an environment where users can efficiently send high-quality, error-free electronic messages.

[0662] The following describes the processing flow.

[0663] Step 1:

[0664] The user composes an electronic message and sends it to the server when it is ready to be sent. At this point, the email data is received by the server.

[0665] Step 2:

[0666] The server passes the received email data to the language processing unit, which analyzes the text using natural language processing techniques. This initiates the detection of typos and grammatical errors. The server refers to dictionary databases and language models to identify errors in word form and grammatical structure.

[0667] Step 3:

[0668] The server generates correction suggestions based on the detected typos and grammatical errors. These suggestions include replacing incorrect words with correct ones, as well as revising the wording based on the tone and content of the business email. For example, it might suggest changing "Please be sure to come" to "We would appreciate your attendance."

[0669] Step 4:

[0670] The server sends the generated revision suggestions to the user's terminal. The user reviews the suggestions and selects and adopts the revisions based on their own judgment. At this point, the user can either accept all the automated suggestions or make partial revisions.

[0671] Step 5:

[0672] Once the user has completed the corrections, they perform a final check on their device and send the corrected email back to the server. The server then checks the content again.

[0673] Step 6:

[0674] The server performs a final security check to ensure that the email does not contain any confidential information or incorrect recipient information. If necessary, it undergoes additional approval processes before being ready to send.

[0675] Step 7:

[0676] After all checks are complete, and based on user approval, the server sends an electronic message to the specified recipient. Upon successful transmission, the result is notified to the user's terminal.

[0677] (Example 1)

[0678] 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".

[0679] Conventional electronic message transmission systems suffer from problems such as reduced information quality due to typographical errors, omissions, and inappropriate expressions. Furthermore, messages may not conform to the intended tone or policy, potentially leading to misunderstandings. Security challenges, such as the leakage of confidential information and sending messages to the wrong recipients, cannot be ignored. A system is needed that efficiently solves these problems, allowing users to send high-quality electronic messages with peace of mind.

[0680] 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.

[0681] In this invention, the server includes means for receiving information transmitted by a user, means for analyzing the received information and detecting text errors, means for generating improvement suggestions based on the detected errors, means for transmitting the generated improvement suggestions to an information processing device so that they can be corrected by the user, and means for performing security checks to confirm that confidential information or incorrect recipients are not included. This enables the user to send high-quality and secure electronic messages.

[0682] "User" refers to the entity that performs the operation of sending an electronic message.

[0683] "Information" refers to text and data that are transmitted or received electronically.

[0684] "Receiving means" refers to a function for acquiring and storing information transmitted by the user.

[0685] "Analysis means" refers to a function that analyzes received information and processes it to detect errors or inappropriate expressions.

[0686] The term "improvement suggestion generation means" refers to a function that automatically creates corrective suggestions for detected errors.

[0687] An "information processing device" refers to a device that enables users to view and modify information.

[0688] "Correction mechanism" refers to a function that allows users to modify information based on improvement suggestions.

[0689] "Security verification means" refers to a function that performs processing to ensure that information is transmitted to the appropriate recipient and that the leakage of confidential information is prevented.

[0690] This invention provides a system for users to send electronic messages with high quality and security. This system is primarily realized through communication between a server, a terminal, and a user.

[0691] A server is a computer device that receives information sent from users. Upon receiving this information, the server performs analysis using natural language processing techniques. During the analysis process, software tools such as dictionary databases and language models are used to detect typographical errors, omissions, and inappropriate expressions within the information.

[0692] In response to detected deficiencies, the server generates improvement suggestions. A generation AI model supports this process, adjusting the user's message to match the intended tone and policy. Specific examples include suggestions to change imperative sentences to polite language or to simplify redundant expressions.

[0693] The user's terminal is a device for receiving and displaying improvement suggestions sent from the server. Through the terminal's interface, the user can review the suggestions and easily implement the corrections. An example of a prompt message to support this process would be: "Requesting improvements to the tone of your email. Current message: 'You must attend tomorrow's meeting.' Please provide improvement suggestions."

[0694] Furthermore, the server receives the modified message and performs a security check. This check evaluates whether it contains confidential information and whether it is being sent to the wrong recipient. Through this series of processes, users can ensure that they send accurate and high-quality information.

[0695] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0696] Step 1:

[0697] The server receives information sent by the user. The input is an electronic message created by the user, and the output is the digital data of that message. This data is retrieved using a secure communication protocol.

[0698] Step 2:

[0699] The server analyzes the received digital data. This process involves text analysis using natural language processing techniques. The input data is the email body, from which words and sentence structures are extracted. The output is a list of typos, omissions, and unnatural expressions.

[0700] Step 3:

[0701] The server generates improvement suggestions based on the analysis results. In this step, it utilizes a generative AI model to generate appropriate corrections based on the error list as input. The output is a specific correction suggestion, such as applying honorific language or simplifying redundant expressions.

[0702] Step 4:

[0703] The server sends the generated improvement suggestions to the user's terminal. The list of improvement suggestions serves as input, and the output is displayed on the user's screen. This allows the user to review the suggested modifications.

[0704] Step 5:

[0705] The user reviews the suggestions on their device and either accepts or modifies them. The user's actions are the input, and the output is a message indicating the modifications. Specifically, the process involves clicking on a suggestion to apply the changes.

[0706] Step 6:

[0707] The user sends the corrected message to the server. The input is the corrected message, and the output is the digital data that the server receives again. Data transmission is rapid.

[0708] Step 7:

[0709] The server performs a security check on the modified message. The input is the modified message data, and the output is the message after security has been confirmed. This process evaluates whether confidential information is present and whether an incorrect recipient has been detected.

[0710] Step 8:

[0711] The server sends the message, once all confirmations are complete, to the designated recipient. The input is the confirmed message, and the output is the accurate delivery to the recipient. The server performs this process only after final approval from the user.

[0712] (Application Example 1)

[0713] 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".

[0714] Inaccurate or inappropriate information can lead to misunderstandings and undermine credibility. Such problems are particularly serious in electronic transactions and important notices. Furthermore, there is a need for methods that automatically apply corrections before information is sent and, even after user confirmation, ensure the rapid transmission of reliable information. This necessitates improved information quality and efficient management.

[0715] 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.

[0716] In this invention, the server includes a device for receiving information transmitted from a user, a device for analyzing the received information and detecting errors, and a device for generating correction suggestions based on the detected errors. This enables automatic correction of information and final confirmation before transmission.

[0717] A "user" is an entity that uses a system or device to send and receive information.

[0718] "Information" refers to messages and data transmitted electronically, including text and other forms of digital content.

[0719] "Device" refers to a hardware or software component designed to perform a specific function.

[0720] "Analysis" is the process of understanding the content of information and identifying errors or areas for improvement.

[0721] An "error" refers to a mistake in information that includes misspellings, omissions, or grammatical or stylistic inappropriateness.

[0722] A "correction suggestion" refers to providing more appropriate wording or content for errors or areas that need improvement.

[0723] "Transmission" refers to the act of moving information from the source to a designated destination.

[0724] "Protection assessment" is a process that verifies the security of information and examines its confidentiality and the possibility of accidental transmission.

[0725] This invention is a system that improves the quality of information by automatically analyzing information transmitted by users, detecting errors, and correcting them. The system is implemented in the following way.

[0726] The server receives information sent from the user's terminal and analyzes it. Natural language processing techniques are used for the analysis, and dictionary databases and language models are used to identify errors in the received information. Through this process, typographical errors, omissions, and unnatural words and phrases are identified.

[0727] Next, the server uses a generative AI model to generate correction suggestions based on these errors. The generated correction suggestions are sent to the user's terminal, where the user can review the suggestions and decide whether to adopt them.

[0728] Subsequently, the corrected information is finalized by the server and a protection assessment is performed. This assessment includes checks to prevent the leakage of confidential information and the setting of inappropriate destinations.

[0729] As a concrete example, consider a scenario where the AI ​​generator, in response to the instruction "Create a payment confirmation email for tomorrow," provides a revised version of the email, correcting it to a more formal tone. This allows users to manage and send information quickly and with high quality.

[0730] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0731] Step 1:

[0732] The server receives information transmitted from the user's terminal. The input is an electronic message created by the user, and processing begins when the server receives it. The output is primary data to be used in subsequent analysis processes.

[0733] Step 2:

[0734] The server analyzes the received information using natural language processing (NLP) technology. The input is the previously received electronic message; the server uses an NLP engine to perform grammar and spell checks, detecting errors and omissions. The output is information with typos, omissions, and unnatural expressions highlighted.

[0735] Step 3:

[0736] The server generates correction suggestions using a generative AI model. The input is information in which errors have been identified, and based on this, the AI ​​generates suggestions including appropriate corrections and stylistic improvements. The output is presented to the user as a document incorporating the specific correction suggestions.

[0737] Step 4:

[0738] The terminal displays correction suggestions sent from the server to the user. The input is data containing suggestions from the server, which the terminal reads and displays on the interface so the user can review the corrections. The output is visualized information to assist the user in making decisions and selecting corrections.

[0739] Step 5:

[0740] Users review the proposed revisions and either adopt them or make their own modifications. User actions serve as input, and the output is the final, revised information. This allows for user-driven creation of high-quality information.

[0741] Step 6:

[0742] The server finally verifies the information modified by the user and performs a security assessment. The input is information confirmed by the user, and the server performs security checks on the data. The output is information that is guaranteed to prevent confidential information and accidental transmission, and if there are no problems, it is ready to be sent.

[0743] 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.

[0744] This invention incorporates an emotion engine that recognizes user emotions, in addition to an automated email proofreading and review function using generation AI, in order to improve the quality and efficiency related to the creation and transmission of electronic messages. This makes it possible to provide more appropriate revision suggestions.

[0745] The server receives electronic messages created by users and analyzes their content. During the analysis process, the server first uses language processing technology to detect typos and grammatical errors and generates necessary correction suggestions. Simultaneously, an emotion engine identifies the emotions expressed in the user's writing and suggests revisions to the tone and content accordingly.

[0746] This allows the emotion engine to recognize, for example, anger in a user's mind, and suggest more neutral and appropriate expressions. For instance, if a user types, "Please deal with this immediately! I'm really angry," the emotion engine will sense the user's anger and suggest a calmer expression such as, "Please take swift action."

[0747] The generated correction suggestions are sent to the user's device for review. The user can consider the suggestions and revise the message as needed. Once the revisions are complete, the user sends the revised message back to the server.

[0748] The server performs a final review of the modified message. This final review includes security checks, and the message is then ready for transmission. Once the message is approved, it is sent according to the user's instructions. This makes it possible to efficiently send high-quality electronic messages that have been edited to reflect the user's emotions.

[0749] The following describes the processing flow.

[0750] Step 1:

[0751] The user composes an electronic message on their device and prepares it for sending. They then perform the necessary steps to send the completed message to the server.

[0752] Step 2:

[0753] The server prepares to process the electronic message received from the user, and first starts text analysis in the language processing unit. This analysis checks for words and grammatical structures and identifies typos and omissions.

[0754] Step 3:

[0755] The server generates correction suggestions based on the detected typos and grammatical errors. It refers to a dictionary database and suggests replacing incorrect words with correct ones.

[0756] Step 4:

[0757] Simultaneously, the server uses an emotion engine to identify the user's emotions from the content of the electronic message. The emotion engine analyzes the emotions in the text and identifies various emotion categories (e.g., anger, joy, anxiety).

[0758] Step 5:

[0759] Based on the perceived emotions, the server generates additional revised suggestions with adjusted tones to avoid misunderstandings. For example, if overly strong language is used, it will suggest softer phrasing.

[0760] Step 6:

[0761] The server sends all generated correction suggestions to the user's terminal. The user reviews these suggestions on their terminal and makes the necessary corrections to the electronic message. The user can accept the suggestions or make their own corrections.

[0762] Step 7:

[0763] After completing the corrections, the user resends the electronic message to the server. As a final check, the server verifies the content and security to ensure that the message does not contain any confidential information or be addressed to the wrong recipient.

[0764] Step 8:

[0765] Once the server is ready to send, it will send the electronic message to the specified recipient after the user's final approval. After the transmission is complete, the server will notify the user's device of the result.

[0766] (Example 2)

[0767] 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".

[0768] In creating electronic communications, challenges exist not only in preventing typos and omissions, but also in generating appropriate expressions that resonate with the user's emotions. Furthermore, creating communications that match the tone and policy of the content can be time-consuming. Additionally, there is a growing need for security checks before transmission to ensure that confidential information and incorrect recipients are not included. Technologies that can efficiently and effectively address these challenges are needed.

[0769] 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.

[0770] In this invention, the server includes means for receiving electronic communications transmitted by a user, means for analyzing the received electronic communications and detecting grammatical errors and input errors, and means for analyzing the user's emotions and generating emotion-based correction suggestions. This makes it possible to generate appropriate correction suggestions that are sensitive to the user's emotions and to correct electronic communications to be of higher quality and more to the user's tone. It also facilitates the transmission of secure communications that do not contain confidential information or incorrect destinations.

[0771] "Electronic communication" refers to digital messages created by a user and sent to other users or systems.

[0772] A "grammatical error" refers to a grammatical inaccuracy or flaw in the content of electronic communications.

[0773] "Input errors" refer to spelling mistakes or typos that occur when users create electronic communications.

[0774] A "correction suggestion" is a proposal to recommend more appropriate expressions or structures to the user based on detected grammatical errors, input mistakes, or the results of sentiment analysis.

[0775] "Sentiment analysis" is the process of identifying and analyzing a user's psychological and emotional state from the content of their electronic communications.

[0776] "Security verification" is the process of checking for the presence of confidential information and the accuracy of the destination before electronic communications are transmitted, in order to ensure security.

[0777] This invention is a system that utilizes natural language processing technology and emotion recognition technology to improve the quality of electronic communications.

[0778] The server receives electronic communications sent by users from their terminals and analyzes their content. The hardware used here includes general server equipment, and the software includes a generative AI model suitable for text analysis. Specifically, the generative AI model used is a language model equipped with natural language processing technology.

[0779] During the analysis process, the server detects typographical errors and grammatical mistakes in electronic communications and generates appropriate correction suggestions based on these. Furthermore, the server uses emotion recognition technology to analyze the user's emotional state and suggests modifications to expressions and tone that correspond to those emotions.

[0780] Once a revision suggestion is generated, the server sends it to the user's terminal. The user can review the suggestion and revise their message if necessary. This interaction enables high-quality electronic communication that is sensitive to emotions.

[0781] For example, if a user enters "Please deal with this immediately! I'm really angry," the server will perform sentiment analysis and suggest a calmer expression such as "Please take prompt action." An example of the prompt used in this case would be: "User input: Please deal with this immediately! I'm really angry. Generating AI prompt: Identify expressions that convey anger in this message and generate a revised suggestion in a more neutral tone."

[0782] Thus, the present invention helps users create electronic communications with well-organized content for efficient communication.

[0783] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0784] Step 1:

[0785] The server receives electronic communications from the user's terminal. It receives the user message as text data as input and stores it in a database. As a preprocessing step, it normalizes the text, removing unnecessary symbols and spaces. The output at this step is clean text data ready for analysis.

[0786] Step 2:

[0787] The server analyzes the received clean text data using natural language processing techniques. The input is the clean text obtained in step 1, and a generative AI model is used here. Specifically, it detects grammatical errors and typos and generates correction suggestions. The output is a list of errors and correction suggestions. This brings the user's message closer to grammatically correct form.

[0788] Step 3:

[0789] The server analyzes the user's emotions contained in the text data. The input is the text data processed in step 2, and the generating AI model performs emotion analysis. Specifically, it uses an emotion engine to identify the user's emotional state and generates suggestions to modify the tone and expression to suit that emotion. The output is the emotion-based modification suggestions.

[0790] Step 4:

[0791] The server sends the generated correction suggestions to the user's terminal. The input for this step is the correction suggestions generated in steps 2 and 3. The server formats each correction suggestion in an easily understandable format and transfers it to the user's terminal. The output is correction suggestion data that the user can review.

[0792] Step 5:

[0793] The user reviews the suggested revisions on their device and decides whether to revise the message content. The input is the suggested revision data sent from the server. The user accepts the suggestions or makes manual revisions to determine the final version of the message. The output is the revised message data. Specifically, the user confirms the revised version and sends it to the server.

[0794] Step 6:

[0795] The server receives the final version of the message from the user and performs a final check. The input for this step is the message data modified by the user. The server performs a security check to ensure that it does not contain confidential information or misdirected recipients. The output is an electronic communication ready for transmission. This ensures secure and high-quality electronic communication.

[0796] (Application Example 2)

[0797] 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".

[0798] Modern communication often takes place via electronic messages, requiring not only the detection of typos and grammatical errors, but also the ability to appropriately understand the sender's emotions and revise messages to match the appropriate tone. However, conventional systems often fail to offer emotion-based revision suggestions, potentially leading to emotional misunderstandings. Furthermore, security checks are necessary to ensure the content is safe and appropriate before transmission. Technologies are needed to address these challenges.

[0799] 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.

[0800] In this invention, the server includes means for recognizing the user's emotions and generating tone correction suggestions based on those emotions; means for transmitting the generated correction suggestions to the user's terminal and enabling the user to make corrections; and means for final confirmation of the corrected electronic message and preparing it for transmission. This makes it possible to efficiently transmit high-quality electronic messages that appropriately take the user's emotions into consideration.

[0801] An "electronic message" is a digital message transmitted using a computer or mobile device, and can include text, images, and files.

[0802] "Typographical errors and omissions" refer to errors or omissions in the use of language within electronic messages and are one of the factors that hinder accurate communication.

[0803] "Correction suggestions" are recommended sentences or expressions generated by the system to correct typos and omissions, and are intended to improve the accuracy of electronic messages.

[0804] "Emotional recognition" is the process of analyzing and understanding a user's emotional state from the content of electronic messages, and is necessary to improve the quality of communication.

[0805] A "tone correction suggestion" is a proposal to change the emotional tone of an electronic message to an appropriate one, providing language that will not mislead the recipient.

[0806] A "user terminal" is a hardware device used by a user to perform operations such as creating, sending, and receiving electronic messages, and includes smartphones and personal computers.

[0807] "Final confirmation" is the process of verifying that the content and recipient of an electronic message are correct before sending it, in order to prevent accidental sending or miscommunication.

[0808] "Preparing to send" refers to completing the necessary processes to actually send an electronic message after it has been confirmed to be accurate and secure.

[0809] This invention provides a system for improving the quality of electronic messages. This system is built using a server, a user terminal, and necessary AI software.

[0810] The server has the capability to receive electronic messages sent by users. These messages are stored in a database and kept until the analysis program is run. Next, the server performs natural language processing and uses a generative AI model to detect typos and grammatical errors in the messages. SpaCy, an open-source natural language processing tool, is commonly used.

[0811] Furthermore, the server uses an emotion recognition engine to analyze the emotional tone of the message. This process utilizes a PyTorch model for emotion analysis to generate expressions that more accurately reflect the user's intent. This engine can correct expressions that the user unintentionally uses to mislead others.

[0812] The user terminal receives correction suggestions sent from the server and has the capability for the user to accept the suggestions or make further corrections. This allows the user to review the final corrected message and make further edits if necessary.

[0813] As a concrete example, consider a scenario where a user is creating a customer support email. Suppose the user uses the phrase, "I am disappointed with this product; please address this." An example of a prompt might be, "Perform a sentiment analysis on the following email and revise it to a more positive expression. Original: 'I am disappointed with this product; please address this.'" This prompt allows the system to suggest a more polite expression, improving the impression the email recipient has.

[0814] This system improves the quality and accuracy of emails, enabling communication that avoids misunderstandings.

[0815] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0816] Step 1:

[0817] The user composes an electronic message and presses the send button.

[0818] In this step, the user's device is prepared to send message data to the server. The input is the electronic message created by the user, and the output is the data to be sent to the server.

[0819] Step 2:

[0820] The server receives an electronic message.

[0821] The server receives messages sent from the user terminal and prepares to parse them. The input is the message received from the user terminal, and the output is the message data for proceeding to the next parsing step.

[0822] Step 3:

[0823] The server detects typos and omissions in messages.

[0824] The server performs natural language processing using spaCy to identify typos and omissions in messages. The input is the message data to be analyzed, and the output is the message data with the typos and omissions identified.

[0825] Step 4:

[0826] The server uses an emotion engine to analyze the message.

[0827] The server uses PyTorch to perform sentiment recognition and evaluate the emotional tone of messages. The input is message data including typographical errors, and the output is message data with sentiment scores assigned to it.

[0828] Step 5:

[0829] The server generates correction suggestions.

[0830] The server uses a generative AI model to create correction suggestions based on detected typos and grammatical errors, as well as the assessed sentiment. The input is message data with sentiment scores, and the output is data with correction suggestions attached.

[0831] Step 6:

[0832] The server sends the suggested corrections to the user's terminal.

[0833] The server forwards the generated correction suggestions to the user's terminal, making them available for review and correction. The input is message data with correction suggestions, and the output is notification data received by the user's terminal.

[0834] Step 7:

[0835] The user reviews the suggested corrections and modifies the message as needed.

[0836] Based on the correction suggestions received on the user's terminal, the user reviews the message content and makes corrections. The input is the correction suggestion and the original message, and the output is the message corrected by the user.

[0837] Step 8:

[0838] The user sends the corrected message to the server.

[0839] The user terminal resends the modified message data to the server and prepares for final confirmation. The input is the message modified by the user, and the output is the data sent to the server.

[0840] Step 9:

[0841] The server performs final verification and security checks.

[0842] The server performs a final content review and security check on the modified message and completes the preparation for transmission. The input is the final version of the message data, and the output is the message data ready for transmission.

[0843] Step 10:

[0844] The server sends the final electronic message to the designated recipient.

[0845] The server completes the process by delivering the message, after all checks have been completed, to the recipient. The input is the message data ready to send, and the output is the message that arrives at the recipient, confirming that the message has been sent.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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."

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0867] The following is further disclosed regarding the embodiments described above.

[0868] (Claim 1)

[0869] A means for receiving electronic messages sent by a user,

[0870] A means for analyzing received electronic messages and detecting typographical errors and omissions,

[0871] A means for generating correction suggestions based on detected typographical errors and omissions,

[0872] A means for sending the generated correction suggestions to the user's terminal and enabling the user to make corrections,

[0873] A means to perform a final check of the revised electronic message and prepare it for transmission,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, further comprising means for scrutinizing the content of the analyzed electronic message, and characterized in that it generates revision suggestions that match the tone and policy of the electronic message.

[0877] (Claim 3)

[0878] The system according to claim 1, further comprising means for performing security checks to confirm that it does not contain confidential information or incorrect destinations.

[0879] "Example 1"

[0880] (Claim 1)

[0881] A means for receiving information sent from a user,

[0882] A means for analyzing received information and detecting errors in the text,

[0883] A means for generating improvement suggestions based on detected errors,

[0884] A means for transmitting the generated improvement suggestions to an information processing device and enabling them to be modified by the user,

[0885] A means to make final confirmation of the corrected information and prepare it for transmission,

[0886] A system that includes this.

[0887] (Claim 2)

[0888] The system according to claim 1, further comprising means for evaluating the content of the analyzed information, and characterized in that it generates improvement suggestions that are consistent with the tone and policy of the information.

[0889] (Claim 3)

[0890] The system according to claim 1, further comprising means for performing security checks and confirming that it does not contain confidential information or incorrect recipients.

[0891] "Application Example 1"

[0892] (Claim 1)

[0893] A device that receives information transmitted from a user,

[0894] A device that analyzes received information and detects errors,

[0895] A device that generates correction suggestions based on detected errors,

[0896] A device that sends the generated correction suggestions to the user's device, making them available for the user to correct,

[0897] A device that finally verifies the corrected information and prepares it for transmission,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, characterized in that it scrutinizes the content of the analyzed information and generates revised suggestions that are consistent with the nature of the information and the policy.

[0901] (Claim 3)

[0902] The system according to claim 1, characterized in that it performs a protection assessment and confirms that it does not contain confidential information or inappropriate recipients.

[0903] (Claim 4)

[0904] The system according to claim 1, further comprising a device for performing additional content improvements before transmitting the corrected information with the user's confirmation.

[0905] (Claim 5)

[0906] The system according to claim 1, characterized by including a function to automatically apply pre-prepared revised versions based on user instructions.

[0907] "Example 2 of combining an emotion engine"

[0908] (Claim 1)

[0909] A means for receiving electronic communications transmitted from a user,

[0910] A means for analyzing received electronic communications and detecting grammatical errors and input errors,

[0911] A means for generating correction suggestions based on detected grammatical errors and input mistakes,

[0912] A means of analyzing user emotions and generating emotion-based correction suggestions,

[0913] A means for sending the generated correction suggestions to the user device and enabling the user to make corrections,

[0914] A means of finalizing the corrected electronic communications and preparing them for transmission,

[0915] A system that includes this.

[0916] (Claim 2)

[0917] The system according to claim 1, further comprising means for scrutinizing the content of the analyzed electronic communications, and characterized in that it generates revision suggestions to match the tone and guidelines of the electronic communications.

[0918] (Claim 3)

[0919] The system according to claim 1, further comprising means for performing security checks and confirming that it does not contain confidential information or incorrect destinations.

[0920] "Application example 2 when combining with an emotional engine"

[0921] (Claim 1)

[0922] A means for receiving electronic messages sent by a user,

[0923] A means for analyzing received electronic messages and detecting typographical errors and omissions,

[0924] A means for generating correction suggestions based on detected typographical errors and omissions,

[0925] A means for recognizing user emotions and generating tone correction suggestions based on those emotions,

[0926] A means for sending the generated correction suggestions to the user's terminal and enabling the user to make corrections,

[0927] A means to perform a final check of the revised electronic message and prepare it for transmission,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, further comprising means for scrutinizing the content of the analyzed electronic message, and characterized in that it generates revision suggestions that match the tone and policy of the electronic message.

[0931] (Claim 3)

[0932] The system according to claim 1, further comprising means for performing security checks to confirm that it does not contain confidential information or incorrect destinations. [Explanation of symbols]

[0933] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving electronic messages sent by a user, A means for analyzing received electronic messages and detecting typographical errors and omissions, A means for generating correction suggestions based on detected typographical errors and omissions, A means for sending the generated correction suggestions to the user's terminal and enabling the user to make corrections, A means to perform a final check of the revised electronic message and prepare it for transmission, A system that includes this.

2. The system according to claim 1, further comprising means for scrutinizing the content of the analyzed electronic message, and characterized in that it generates revision suggestions that match the tone and policy of the electronic message.

3. The system according to claim 1, further comprising means for performing security checks to confirm that it does not contain confidential information or incorrect destinations.

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