system

Abstract

We provide the system. [Solution] A server means for receiving text data entered by a user, An analysis module means for analyzing the grammar and style of received text data, A generation engine means for correcting and improving grammar and style based on analyzed text data, A transmission module means for sending corrected and improved text data to the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes 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] Conventionally, appropriately correcting grammar and style in article writing requires a lot of time and specialized knowledge, and it has been a problem that especially writers, students, and professionals have difficulty in creating high-quality articles in a short time.

Means for Solving the Problems

[0005] The present invention is a system characterized by receiving text data input from a user, including an analysis module for analyzing the grammar and style of the text data, and using a generation engine for correcting and improving grammar and style based on the analysis result, and providing the generated correction result to the user.

[0006] A "user" is the entity that operates the system and provides and verifies input data.

[0007] "Text data" refers to digital character information, including sentences and phrases.

[0008] A "server" is a central processing unit that receives data from users and performs analysis and generation.

[0009] A "parsing module" is a software component that analyzes input text data and verifies its grammar and style.

[0010] A "generative engine" is a software function that suggests grammatical and stylistic corrections and improvements based on analyzed data.

[0011] A "transmission module" is a communication function that provides users with corrected and improved data.

[0012] "Profile data" refers to data that includes individual settings and historical information related to a user. [Brief explanation of the drawing]

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

Embodiments for Carrying out the Invention

[0014] 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.

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

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

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

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

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

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is a system for automatically correcting and improving the grammar and style of text data, and in its embodiment, it consists of three elements: a server, a terminal, and a user. This system operates as follows:

[0035] The user inputs text data via a terminal. The input data is sent to the server. The server is equipped with an analysis module, which performs grammatical and stylistic analysis. As a result of the analysis, grammatical errors and areas for stylistic improvement within the text are identified.

[0036] The server's built-in generation engine generates optimal revision suggestions based on the analysis results. These suggestions are customized based on the user's profile data, resulting in improvements tailored to each individual user. This allows for revisions that match the user's writing style.

[0037] The revised text data is sent back to the terminal via the transmission module. The user can review the revision suggestions on the terminal and ultimately choose which one to adopt. At this point, the user can quickly complete a high-quality document based on the provided revisions.

[0038] As a concrete example, consider a case where a user inputs the incomplete sentence "Poverty is increasing a lot." The server first recognizes the grammatical error "a lot." The generation engine then suggests a corrected version, such as "Poverty is increasing significantly," and the user can review the correction on their device and adopt it as the optimal sentence.

[0039] In this way, the present invention helps users create faster and more refined documents. The entire system automatically suggests grammatical and stylistic corrections, improving the user's writing ability and significantly reducing working time.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user enters text on the device and presses the send button. This action sends the entered text data to the server.

[0043] Step 2:

[0044] The server receives text data sent from the terminal. It passes the received text to the parsing module, which then begins parsing the grammar and style.

[0045] Step 3:

[0046] The analysis module on the server identifies grammatical errors and stylistic inconsistencies based on the input text. This analysis process evaluates sentence structure, punctuation, and vocabulary appropriateness.

[0047] Step 4:

[0048] Based on the analysis results, the server uses a generation engine to identify points that need correction and improvement, and then generates the most suitable correction proposals. At this time, it references the user's profile data to customize the suggestions.

[0049] Step 5:

[0050] The generated revision proposals are aggregated on the server and prepared to be sent back to the terminal via the transmission module. The revision proposals are formatted in a user-friendly format.

[0051] Step 6:

[0052] The terminal displays the proposed corrections received from the server. The user reviews these and evaluates whether each correction aligns with their intent. If necessary, they adopt or further refine the proposed corrections.

[0053] Step 7:

[0054] The user ultimately adopts the proposed revisions, finishes editing, and completes the document. At this stage, high-quality text is generated in a short amount of time.

[0055] (Example 1)

[0056] 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."

[0057] There is a need for technology that can edit information accurately and quickly. Conventional methods require finding and manually correcting grammatical errors and style inconsistencies, making efficiency difficult. Furthermore, there is a lack of customization features that can accommodate individual user styles and preferences, resulting in wasted time and effort in the editing process. Therefore, the present invention aims to automate grammatical and style correction more effectively and realize high-quality information processing that meets the needs of each user.

[0058] 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.

[0059] In this invention, the server includes an information processing device means for receiving information input by a user, an analysis structure means for analyzing the grammar and expression style of the received information, and a generation structure means for modifying and improving the grammar and expression style based on the analyzed information. This enables automatic and highly accurate modification of information, and allows for the rapid provision of optimal information that suits the user's style.

[0060] An "information processing device" is a device that receives information input from a user and has the function of managing and controlling that data.

[0061] An "analysis structure" is a mechanism for analyzing received information and identifying errors and areas for improvement in grammar and expression.

[0062] A "generative structure" is a mechanism for modifying grammar and expression patterns based on analyzed information to generate optimal information.

[0063] A "communication structure" is a structure that provides the means of communication necessary to transmit corrected and improved information to the user.

[0064] "Attribute data" refers to data that includes user characteristics, past activity history, preferences, etc., and is used to enable the provision of information tailored to each individual user.

[0065] A "revision option" is a selection of revisions generated by the generative structure that presents the option deemed optimal for the user.

[0066] An "information input device" is a device used by users to input information and to verify corrected information.

[0067] This invention provides a system that allows users to process information more efficiently and automatically receive modifications tailored to their individual style. Users input information using a terminal. For example, consider a scenario where a user inputs information such as, "I want to check my meeting schedule, but I've forgotten the time."

[0068] The terminal transmits the input information to the server via a data network. The server, equipped with an information processing device, receives the information. The received information is analyzed using an analysis structure to identify grammatical and expression errors and areas for improvement. Generative AI models are utilized in the analysis to precisely understand and process the information.

[0069] The analysis results are generated as suggested revisions using a generation structure. These revisions are customized to the optimal form based on the user's attribute data, allowing for precise modifications tailored to the user's preferences and style. Specifically, the server might generate a suggestion such as, "Please check the meeting start time. You need to reset the time."

[0070] The proposed revisions are then sent back to the terminal via the communication structure. The user can review the proposed revisions on the terminal and obtain the information in the most suitable format. This entire process allows the user to process information quickly and efficiently and obtain customized revisions.

[0071] For example, a user might input a prompt such as, "I've finished writing tomorrow's report, but I'd like to see improvements to the grammar and style." The system can then automatically make the necessary corrections and provide optimized suggestions. This invention significantly reduces the time and effort users spend creating information.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The user uses a terminal to input text data. The input data is a sentence written by the user, such as "I want to complete a review about the new product." The terminal prepares to send the input text data directly to the server.

[0075] Step 2:

[0076] The server receives text data input through an information processing device. The received data is passed to an analysis structure for analyzing grammar and expression. This analysis structure uses a generative AI model to identify grammatical errors and areas for improvement in expression within the input data. For example, it searches for appropriate grammar and areas for improvement in the phrase "I want to complete the review."

[0077] Step 3:

[0078] The server's generation structure generates suggested revisions based on the analyzed data. In this step, data processing is performed based on the analysis results, generating suggested revisions with grammatically correct and consistent expressions. A generation AI model assists in this process, creating suggested revisions such as "We would like to complete the new product review."

[0079] Step 4:

[0080] The server customizes the generated revision proposals based on the user's attribute data. Here, data processing is performed to create revision proposals that are more suitable for each user, taking into account their past editing history and style. This results in an optimized revised version.

[0081] Step 5:

[0082] The server sends the proposed corrections to the terminal via the communication structure. This output process involves secure data communication, and the customized corrections are delivered to the user's terminal.

[0083] Step 6:

[0084] The user reviews the proposed revisions received from the server on their device. At this point, the user is presented with multiple revision options and can select the best one. Based on the user's selection, the final text that aligns with the intended meaning is finalized. This allows the user to complete high-quality documents quickly and efficiently.

[0085] (Application Example 1)

[0086] 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."

[0087] This project aims to address the problem of grammatical errors and unclear stylistic choices often found in text data such as product reviews and inquiry messages, which hinder the effective communication of information to other users.

[0088] 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.

[0089] In this invention, the server includes an information processing device means for receiving character data entered by a user, an analysis means for analyzing the grammar and format of the received character data, and a generation mechanism means for modifying and improving the grammar and format based on the analyzed character data. This enables the provision of more accurate and readable product reviews and inquiry messages to users in real time, and facilitates the transmission of useful information to other users.

[0090] An "information processing device that receives character data entered by a user" refers to hardware or software that receives and processes character data entered by a user via a network.

[0091] "Analysis means for analyzing the grammar and format of received character data" refers to an algorithm or process for detecting and analyzing grammatical errors and formal defects contained in character data.

[0092] A "generative mechanism for correcting and improving grammar and form based on parsed character data" is an engine or model that generates optimal correction proposals based on the analysis results and provides them to the user.

[0093] A "communication method" is a system that transmits corrected and improved text data to the user's terminal and enables two-way communication with the user.

[0094] A "tool that enables real-time revision suggestions for text data as product reviews" is a function that provides immediate grammar and style suggestions to users when they write product reviews, thereby improving the quality of the reviews.

[0095] "Generating optimized correction suggestions based on user profile information" is a process that adjusts suggested corrections according to each user's preferences and past input history to provide more appropriate suggestions.

[0096] "Presented on a display device in a user-editable format" means that the proposed revisions are displayed on the user's device screen, allowing the user to select and edit them themselves.

[0097] A system for carrying out this invention consists of an information processing device, an analysis means, a generation mechanism, a communication means, and a modification suggestion tool.

[0098] The server receives character data entered by the user via an information processing device. The received character data is then analyzed grammatically and formally using an analysis tool. Specifically, the analysis tool utilizes natural language processing algorithms to identify grammatical errors and areas for formal improvement in the character data. Based on these analysis results, the generation mechanism generates revised versions using a generative AI model. This generation process also takes user profile information into consideration, resulting in the generation of sentences in a style appropriate for the user.

[0099] Next, the corrected text data is sent to the user's terminal via communication. The correction suggestion tool displays grammatical and stylistic correction items to the user in real time, which the user can review and select.

[0100] As a concrete example, suppose a user enters a product review on a smartphone app and writes the sentence, "The product is very good, but it's complicated to use." The server analyzes the redundancy of "but, however," and the generation engine suggests a revised version: "The product is very good, but it's complicated to use." This revised version is adjusted to take the user's preferences into account and displayed on the device. In this way, users can easily post more refined product reviews based on the suggested revisions.

[0101] An example of a prompt message is: "Please grammatically check the following text and suggest corrections: {user's text} User profile: Style preferences - {style preferences}".

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The user inputs character data via a terminal and sends that data to the information processing device. The input data is sent as text from the terminal to the server. The server receives this input and sends it to the next parsing step.

[0105] Step 2:

[0106] The server processes the received text data through a parsing system. The input here is the user's raw text data, and the parsing system uses natural language processing algorithms to identify grammatical errors and areas for stylistic improvement. The output is a list of the parsed information and identified errors.

[0107] Step 3:

[0108] The server passes the analyzed data to the generation mechanism. The input consists of an identified error list and a user profile, and the generation mechanism uses a generative AI model to perform data calculations to generate the optimal correction. The output is a correction tailored to the user's profile.

[0109] Step 4:

[0110] The server receives the proposed corrections from the generation mechanism and transmits them to the user's terminal via communication. The input is the proposed correction data, and the output is the correction suggestion displayed on the user's terminal.

[0111] Step 5:

[0112] The user reviews the suggested revisions presented on their device and selects which revision to ultimately adopt. The input for this step is the suggested revision, and the output is the final text data selected by the user. This selection allows the user to submit accurate and readable product reviews.

[0113] 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.

[0114] This invention relates to a system that optimizes text by analyzing the grammar and style of text data input by a user, and by recognizing the user's emotions. This system comprises a server, a terminal, and an emotion engine.

[0115] First, the user inputs text based on their emotions and intentions via their device and sends it to the server. Upon receiving the text data from the device, the server first passes it to a parsing module for grammatical and stylistic analysis. The parsing module analyzes the text data grammatically, points out errors, and identifies areas for stylistic improvement.

[0116] Next, the emotion engine on the server analyzes the text data and evaluates the user's emotions. This emotion engine infers the user's emotional state from the input words, phrases, and writing style, and passes the analysis results to the generation engine.

[0117] The generation engine creates suggested revisions by combining grammatical and stylistic corrections with sentiment information obtained from the sentiment engine. These suggested revisions are optimized to include a style and vocabulary appropriate to the user's emotions. This results in more personalized suggestions that reflect those emotions.

[0118] The modified text data is sent back to the terminal via the transmission module and presented to the user. The user reviews the proposed revisions, evaluates whether they align with their emotions and intentions, and then makes final edits. For example, if a user experiencing sadness enters the sentence "I'm sad today," the emotion engine will recognize this emotion. The generation engine can then suggest a revised sentence that reflects this emotion, such as "I'm feeling a bit down today, but I believe tomorrow will be better."

[0119] By incorporating an emotion engine in this way, it becomes possible to effectively generate text that reflects the emotions intended by the user, thereby supporting the creation of more appropriate and professional writing.

[0120] The following describes the processing flow.

[0121] Step 1:

[0122] The user initiates processing by typing text on their device and sending it to the server.

[0123] Step 2:

[0124] The server receives text data from the terminal and first passes it to the parsing module for grammatical and stylistic analysis. The parsing module identifies errors and stylistic inconsistencies in the text.

[0125] Step 3:

[0126] The server passes the analyzed data to the emotion engine, which analyzes the user's emotions based on the wording and context within the text. The emotion engine quantifies the emotions hidden in the input data and identifies what kind of emotions are being expressed.

[0127] Step 4:

[0128] Based on the analysis results and sentiment data, the server's generation engine generates optimal suggestions for correction and improvement. These suggestions include grammatical corrections as well as expressions appropriate to the user's emotional state.

[0129] Step 5:

[0130] The generated suggestions are sent to the terminal via the transmission module. On the terminal, the proposed revisions are presented to the user and displayed in a visually easy-to-understand format.

[0131] Step 6:

[0132] The user reviews the suggested revisions on their device and evaluates whether they align with their feelings and intentions. The user then makes final adjustments as needed to create the completed text.

[0133] (Example 2)

[0134] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0135] In modern communication, it is becoming increasingly important to accurately reflect the sender's emotions and intentions in written expression, in addition to grammatical and stylistic correctness. However, it is not easy for users to create text that appropriately reflects their own emotions and intentions. Therefore, there is a growing need for a system that can automatically generate text that reflects the user's emotions while simultaneously correcting grammar and style.

[0136] 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.

[0137] In this invention, the server includes an information processing device means for receiving character data entered by a user, an emotion analysis device means for evaluating the emotional state of the character data, and a data generation device means for creating correction candidates suitable for the user's emotions using the emotion information obtained from the emotion analysis device. This makes it possible to modify grammar and style while taking the user's emotions into consideration.

[0138] A "user" refers to a person who inputs text data into an information processing system to convey their emotions and intentions.

[0139] "Character data" refers to text-based information that is entered by the user and received and analyzed by the server.

[0140] An "information processing device" refers to a computing device that handles character data received from a user and operates as the foundation for subsequent analysis and generation processes.

[0141] An "analytical device" refers to software or hardware that has the function of syntactically and stylistically evaluating character data and detecting the need for correction or improvement.

[0142] A "data generation device" refers to a device that generates newly modified text data based on the analysis results and information obtained from sentiment analysis.

[0143] A "sentiment analysis device" refers to a device that analyzes the user's emotional state from input text data and uses that information to modify or generate text.

[0144] An "information transmission device" refers to a device that outputs corrected and improved character data for presentation to the user again.

[0145] This invention is a system for receiving text data entered by a user and optimizing that text based on emotion. The system includes an information processing device, an analysis device, an emotion analysis device, a data generation device, and an information transmission device.

[0146] Users input text data that reflects their emotions and intentions through a terminal. This data is sent from the terminal to a server, which is an information processing device. The server analyzes the received data using an analysis device. Specifically, it uses a syntactic analysis tool (e.g., Grammarly or ProWritingAid) to check the syntax and format of the input data and identify errors.

[0147] Subsequently, an emotion analysis device on the server analyzes the input text data to evaluate the user's emotions. Natural language processing techniques are used for emotion analysis, particularly emotion analysis libraries (e.g., VADER and TextBlob). This device infers the user's emotions from words, phrases, and the tone of sentences.

[0148] Based on the results of the sentiment analysis, the data generation device uses the sentiment information and the information obtained from the analysis device to generate optimized revision candidates. In this process, the text is modified to include a writing style and vocabulary appropriate to the user's emotions.

[0149] Finally, the information transmission device sends the revised data back to the terminal and presents it to the user. The user reviews this proposal, determines whether it aligns with their intentions, and makes further edits as needed.

[0150] As a concrete example, consider a case where a user inputs the text data "I am very happy today." The emotion analysis device identifies the word "happy," which indicates a positive emotion. Based on this, the data generation device generates a suggested sentence such as "Today was a truly wonderful day, and I feel great."

[0151] Another example of a prompt to input into the generation AI model is, "Please show me how to adjust the tone of the text based on the emotions entered." In this way, it becomes possible to generate text that takes the user's emotions into consideration.

[0152] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0153] Step 1:

[0154] The user inputs text data via a terminal. This input data is text that expresses the user's intentions and emotions. Because this text includes emotional expressions, its syntax and style may not be consistent. The input data is then sent to the server.

[0155] Step 2:

[0156] The server, acting as an information processing device, passes the received text data to the parser. The parser analyzes the text data using a syntactic analysis tool to identify grammatical errors and areas for stylistic improvement. The output of the analysis generates syntactic problems and suggested improvements.

[0157] Step 3:

[0158] The emotion analysis device on the server analyzes the received text data in parallel with the analysis results and evaluates the user's emotions. Based on natural language processing technology, it quantifies emotional states such as positive and negative. The output is emotional information inferred from the text data.

[0159] Step 4:

[0160] The server passes the results from the sentiment analysis device to the data generation device, which, combined with the information from the analysis device, generates optimized revision suggestions. In addition to improving grammar and style, the data generation device revises the text to suit the user's writing style based on the sentiment information. The output is revised text with a unified style appropriate to the sentiment.

[0161] Step 5:

[0162] The revised text data is returned to the terminal via the information transmission device and presented to the user. The user reviews this revised version and confirms that it matches their intentions. The user can make further edits as needed. The output is the final text after user review and final editing.

[0163] (Application Example 2)

[0164] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0165] In today's information society, users are exposed to vast amounts of information daily, and there is an increasing demand for information tailored to their individual emotions and intentions. However, conventional information delivery systems are unable to adequately provide personalized content based on users' emotions, making it difficult to achieve deeper user engagement.

[0166] 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.

[0167] In this invention, the server includes a device means for receiving data entered by a user, an analysis unit means for analyzing the grammar and style of the received text, a generation mechanism means for modifying and improving the grammar and style based on the analyzed text, and a transmission unit means for sending personalized text information generated based on emotion to the user. This makes it possible to provide optimal content according to the user's emotions and to quickly convey information that meets individual needs.

[0168] A "user" is a person who uses a system to input information and receives feedback from it.

[0169] "Data" refers to text and other information entered by users, which forms the basis for analysis and processing within the system.

[0170] "Device" refers to a part of a system that includes hardware and software for receiving and processing data from a user.

[0171] The "analysis unit" is a means of analyzing the grammar and style of the received text to identify errors and areas for improvement.

[0172] A "generation mechanism" is a system component that uses analyzed text to correct grammar and style, and then generates improved content.

[0173] An "emotion engine" is a processing mechanism that estimates emotions from the content of the user's input text and performs optimizations that reflect that information.

[0174] The "transmission unit" is a means for sending the text information, which has been improved by the generation mechanism, to the user's terminal.

[0175] Personalization is the act of individually optimizing and delivering content based on each user's emotions and characteristics.

[0176] To implement this invention, a terminal on which users can input emotion-based information and a server that performs text analysis and generation are required. Users input text related to their emotions and intentions using a smartphone or computer.

[0177] Data entered from the terminal is received by a "device that receives user-entered data" on the server. The received data is then sent to an "analysis unit" where its grammar and style are analyzed. This analysis unit identifies and reports grammatical errors and stylistic problems within the data.

[0178] The analyzed data is modified grammatically and stylistically by a "generative mechanism," resulting in improved content. This generative mechanism includes a process of adjusting and improving the text data based on the analysis results.

[0179] Furthermore, an "emotion engine" within the server estimates the user's emotions from the analyzed text, and a generation mechanism creates optimized text based on this. This optimization process generates personalized content that aligns with the user's emotions.

[0180] The "transmission unit" returns the generated optimized text to the user's device and presents it to the user. This allows the user to receive content that matches their own emotions.

[0181] For example, if a user enters the text "I'm tired today" to express fatigue, the emotion engine recognizes this emotion, and the generation mechanism generates and sends relaxing text such as "Take a break and relax." An example of a prompt might be in the form of "Please enter words to express your current mood."

[0182] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0183] Step 1:

[0184] The user's device inputs text data related to emotions and intentions and sends it to the server. At this stage, the user uses a smartphone or computer to provide information to the system. The server accurately receives the text data and prepares it for the next analysis process.

[0185] Step 2:

[0186] The analysis unit on the server analyzes the grammar and style of the received text data. The input to the analysis unit is text data sent by the user, and it identifies grammatical errors and style issues based on this data. The analyzed data includes detailed comments on grammar and style, serving as a roadmap for correction. This process allows for a thorough examination of grammatical and style errors, clearly outlining the path to improvement.

[0187] Step 3:

[0188] The server passes the analyzed data to the generation mechanism for grammatical and stylistic corrections. The analysis results are provided as input, and the generation mechanism uses this data to generate proposed corrections. These corrections specifically reflect the improvements in grammar and style, resulting in the output of improved text data. This transforms the user's input into a more refined form.

[0189] Step 4:

[0190] The server's sentiment engine estimates the user's emotions from the analyzed text data, and based on this, the generation mechanism creates personalized content optimized for that emotion. The sentiment engine's input is the modified text data, and through sentiment analysis, it evaluates how the text relates to the user's emotions. Optimization is then performed based on the sentiment information, adjusting the content to suit the user.

[0191] Step 5:

[0192] The server sends the text data, improved by the generation mechanism, from the "transmitter" to the user's terminal. The input to the transmitter is optimized text, and the user receives this output. The user evaluates the content to see if it fits their emotions and makes further edits as needed. This completes a series of cycles, including a user guide prompt that includes an example of a prompt: "Please enter words to express how you are feeling right now."

[0193] 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.

[0194] 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.

[0195] 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.

[0196] [Second Embodiment]

[0197] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0198] 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.

[0199] 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).

[0200] 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.

[0201] 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.

[0202] 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).

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] 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".

[0209] This invention is a system for automatically correcting and improving the grammar and style of text data, and in its embodiment, it consists of three elements: a server, a terminal, and a user. This system operates as follows:

[0210] The user inputs text data via a terminal. The input data is sent to the server. The server is equipped with an analysis module, which performs grammatical and stylistic analysis. As a result of the analysis, grammatical errors and areas for stylistic improvement within the text are identified.

[0211] The server's built-in generation engine generates optimal revision suggestions based on the analysis results. These suggestions are customized based on the user's profile data, resulting in improvements tailored to each individual user. This allows for revisions that match the user's writing style.

[0212] The revised text data is sent back to the terminal via the transmission module. The user can review the revision suggestions on the terminal and ultimately choose which one to adopt. At this point, the user can quickly complete a high-quality document based on the provided revisions.

[0213] As a concrete example, consider a case where a user inputs the incomplete sentence "Poverty is increasing a lot." The server first recognizes the grammatical error "a lot." The generation engine then suggests a corrected version, such as "Poverty is increasing significantly," and the user can review the correction on their device and adopt it as the optimal sentence.

[0214] In this way, the present invention helps users create faster and more refined documents. The entire system automatically suggests grammatical and stylistic corrections, improving the user's writing ability and significantly reducing working time.

[0215] The following describes the processing flow.

[0216] Step 1:

[0217] The user enters text on the device and presses the send button. This action sends the entered text data to the server.

[0218] Step 2:

[0219] The server receives text data sent from the terminal. It passes the received text to the parsing module, which then begins parsing the grammar and style.

[0220] Step 3:

[0221] The analysis module on the server identifies grammatical errors and stylistic inconsistencies based on the input text. This analysis process evaluates sentence structure, punctuation, and vocabulary appropriateness.

[0222] Step 4:

[0223] Based on the analysis results, the server uses a generation engine to identify points that need correction and improvement, and then generates the most suitable correction proposals. At this time, it references the user's profile data to customize the suggestions.

[0224] Step 5:

[0225] The generated revision proposals are aggregated on the server and prepared to be sent back to the terminal via the transmission module. The revision proposals are formatted in a user-friendly format.

[0226] Step 6:

[0227] The terminal displays the proposed corrections received from the server. The user reviews these and evaluates whether each correction aligns with their intent. If necessary, they adopt or further refine the proposed corrections.

[0228] Step 7:

[0229] The user ultimately adopts the proposed revisions, finishes editing, and completes the document. At this stage, high-quality text is generated in a short amount of time.

[0230] (Example 1)

[0231] 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."

[0232] There is a need for technology that can edit information accurately and quickly. Conventional methods require finding and manually correcting grammatical errors and style inconsistencies, making efficiency difficult. Furthermore, there is a lack of customization features that can accommodate individual user styles and preferences, resulting in wasted time and effort in the editing process. Therefore, the present invention aims to automate grammatical and style correction more effectively and realize high-quality information processing that meets the needs of each user.

[0233] 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.

[0234] In this invention, the server includes an information processing device means for receiving information input by a user, an analysis structure means for analyzing the grammar and expression style of the received information, and a generation structure means for modifying and improving the grammar and expression style based on the analyzed information. This enables automatic and highly accurate modification of information, and allows for the rapid provision of optimal information that suits the user's style.

[0235] An "information processing device" is a device that receives information input from a user and has the function of managing and controlling that data.

[0236] An "analysis structure" is a mechanism for analyzing received information and identifying errors and areas for improvement in grammar and expression.

[0237] A "generative structure" is a mechanism for modifying grammar and expression patterns based on analyzed information to generate optimal information.

[0238] A "communication structure" is a structure that provides the means of communication necessary to transmit corrected and improved information to the user.

[0239] "Attribute data" refers to data that includes user characteristics, past activity history, preferences, etc., and is used to enable the provision of information tailored to each individual user.

[0240] A "revision option" is a selection of revisions generated by the generative structure that presents the option deemed optimal for the user.

[0241] An "information input device" is a device used by users to input information and to verify corrected information.

[0242] This invention provides a system that allows users to process information more efficiently and automatically receive modifications tailored to their individual style. Users input information using a terminal. For example, consider a scenario where a user inputs information such as, "I want to check my meeting schedule, but I've forgotten the time."

[0243] The terminal transmits the input information to the server via a data network. The server, equipped with an information processing device, receives the information. The received information is analyzed using an analysis structure to identify grammatical and expression errors and areas for improvement. Generative AI models are utilized in the analysis to precisely understand and process the information.

[0244] The analysis results are generated as suggested revisions using a generation structure. These revisions are customized to the optimal form based on the user's attribute data, allowing for precise modifications tailored to the user's preferences and style. Specifically, the server might generate a suggestion such as, "Please check the meeting start time. You need to reset the time."

[0245] The proposed revisions are then sent back to the terminal via the communication structure. The user can review the proposed revisions on the terminal and obtain the information in the most suitable format. This entire process allows the user to process information quickly and efficiently and obtain customized revisions.

[0246] For example, a user might input a prompt such as, "I've finished writing tomorrow's report, but I'd like to see improvements to the grammar and style." The system can then automatically make the necessary corrections and provide optimized suggestions. This invention significantly reduces the time and effort users spend creating information.

[0247] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0248] Step 1:

[0249] The user uses a terminal to input text data. The input data is a sentence written by the user, such as "I want to complete a review about the new product." The terminal prepares to send the input text data directly to the server.

[0250] Step 2:

[0251] The server receives text data input through an information processing device. The received data is passed to an analysis structure for analyzing grammar and expression. This analysis structure uses a generative AI model to identify grammatical errors and areas for improvement in expression within the input data. For example, it searches for appropriate grammar and areas for improvement in the phrase "I want to complete the review."

[0252] Step 3:

[0253] The server's generation structure generates suggested revisions based on the analyzed data. In this step, data processing is performed based on the analysis results, generating suggested revisions with grammatically correct and consistent expressions. A generation AI model assists in this process, creating suggested revisions such as "We would like to complete the new product review."

[0254] Step 4:

[0255] The server customizes the generated revision proposals based on the user's attribute data. Here, data processing is performed to create revision proposals that are more suitable for each user, taking into account their past editing history and style. This results in an optimized revised version.

[0256] Step 5:

[0257] The server sends the proposed corrections to the terminal via the communication structure. This output process involves secure data communication, and the customized corrections are delivered to the user's terminal.

[0258] Step 6:

[0259] The user reviews the proposed revisions received from the server on their device. At this point, the user is presented with multiple revision options and can select the best one. Based on the user's selection, the final text that aligns with the intended meaning is finalized. This allows the user to complete high-quality documents quickly and efficiently.

[0260] (Application Example 1)

[0261] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0262] This project aims to address the problem of grammatical errors and unclear stylistic choices often found in text data such as product reviews and inquiry messages, which hinder the effective communication of information to other users.

[0263] 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.

[0264] In this invention, the server includes an information processing device means for receiving character data entered by a user, an analysis means for analyzing the grammar and format of the received character data, and a generation mechanism means for modifying and improving the grammar and format based on the analyzed character data. This enables the provision of more accurate and readable product reviews and inquiry messages to users in real time, and facilitates the transmission of useful information to other users.

[0265] An "information processing device that receives character data entered by a user" refers to hardware or software that receives and processes character data entered by a user via a network.

[0266] "Analysis means for analyzing the grammar and format of received character data" refers to an algorithm or process for detecting and analyzing grammatical errors and formal defects contained in character data.

[0267] A "generative mechanism for correcting and improving grammar and form based on parsed character data" is an engine or model that generates optimal correction proposals based on the analysis results and provides them to the user.

[0268] A "communication method" is a system that transmits corrected and improved text data to the user's terminal and enables two-way communication with the user.

[0269] A "tool that enables real-time revision suggestions for text data as product reviews" is a function that provides immediate grammar and style suggestions to users when they write product reviews, thereby improving the quality of the reviews.

[0270] "Generating optimized correction suggestions based on user profile information" is a process that adjusts suggested corrections according to each user's preferences and past input history to provide more appropriate suggestions.

[0271] "Presented on a display device in a user-editable format" means that the proposed revisions are displayed on the user's device screen, allowing the user to select and edit them themselves.

[0272] A system for carrying out this invention consists of an information processing device, an analysis means, a generation mechanism, a communication means, and a modification suggestion tool.

[0273] The server receives character data entered by the user via an information processing device. The received character data is then analyzed grammatically and formally using an analysis tool. Specifically, the analysis tool utilizes natural language processing algorithms to identify grammatical errors and areas for formal improvement in the character data. Based on these analysis results, the generation mechanism generates revised versions using a generative AI model. This generation process also takes user profile information into consideration, resulting in the generation of sentences in a style appropriate for the user.

[0274] Next, the corrected text data is sent to the user's terminal via communication. The correction suggestion tool displays grammatical and stylistic correction items to the user in real time, which the user can review and select.

[0275] As a concrete example, suppose a user enters a product review on a smartphone app and writes the sentence, "The product is very good, but it's complicated to use." The server analyzes the redundancy of "but, however," and the generation engine suggests a revised version: "The product is very good, but it's complicated to use." This revised version is adjusted to take the user's preferences into account and displayed on the device. In this way, users can easily post more refined product reviews based on the suggested revisions.

[0276] An example of a prompt message is: "Please grammatically check the following text and suggest corrections: {user's text} User profile: Style preferences - {style preferences}".

[0277] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0278] Step 1:

[0279] The user inputs character data via the terminal and transmits the data to the information processing device. The input data is an input transmitted from the terminal to the server as text. The server receives this input and sends it to the next analysis step.

[0280] Step 2:

[0281] The server applies the received character data to the analysis means. The input here is the raw character data of the user, and the analysis means performs data processing to identify grammatical errors and style improvement points using natural language processing algorithms. The output is a list of the analyzed information and the identified errors.

[0282] Step 3:

[0283] The server passes the analyzed data to the generation mechanism. The inputs are the identified error list and the user profile, and the generation mechanism performs data operations to generate an optimal amendment using a generation AI model. The output is an amendment that conforms to the user's profile.

[0284] Step 4:

[0285] The server receives the amendment from the generation mechanism and transmits it to the user's terminal via the communication means. The input is the amendment data, and the output is a correction proposal displayed on the user's terminal.

[0286] Step 5:

[0287] The user checks the correction proposals presented on the terminal and selects which proposal to finally adopt. The input for this step is the correction proposal, and the output is the final character data selected by the user. With this selection, the user can post an accurate and easy-to-read product review.

[0288] 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.

[0289] This invention relates to a system that optimizes text by analyzing the grammar and style of text data input by a user, and by recognizing the user's emotions. This system comprises a server, a terminal, and an emotion engine.

[0290] First, the user inputs text based on their emotions and intentions via their device and sends it to the server. Upon receiving the text data from the device, the server first passes it to a parsing module for grammatical and stylistic analysis. The parsing module analyzes the text data grammatically, points out errors, and identifies areas for stylistic improvement.

[0291] Next, the emotion engine on the server analyzes the text data and evaluates the user's emotions. This emotion engine infers the user's emotional state from the input words, phrases, and writing style, and passes the analysis results to the generation engine.

[0292] The generation engine creates suggested revisions by combining grammatical and stylistic corrections with sentiment information obtained from the sentiment engine. These suggested revisions are optimized to include a style and vocabulary appropriate to the user's emotions. This results in more personalized suggestions that reflect those emotions.

[0293] The modified text data is sent back to the terminal via the transmission module and presented to the user. The user reviews the proposed revisions, evaluates whether they align with their emotions and intentions, and then makes final edits. For example, if a user experiencing sadness enters the sentence "I'm sad today," the emotion engine will recognize this emotion. The generation engine can then suggest a revised sentence that reflects this emotion, such as "I'm feeling a bit down today, but I believe tomorrow will be better."

[0294] By incorporating an emotion engine in this way, it becomes possible to effectively generate text that reflects the emotions intended by the user, thereby supporting the creation of more appropriate and professional writing.

[0295] The following describes the processing flow.

[0296] Step 1:

[0297] The user initiates processing by typing text on their device and sending it to the server.

[0298] Step 2:

[0299] The server receives text data from the terminal and first passes it to the parsing module for grammatical and stylistic analysis. The parsing module identifies errors and stylistic inconsistencies in the text.

[0300] Step 3:

[0301] The server passes the analyzed data to the emotion engine, which analyzes the user's emotions based on the wording and context within the text. The emotion engine quantifies the emotions hidden in the input data and identifies what kind of emotions are being expressed.

[0302] Step 4:

[0303] Based on the analysis results and emotion data, the generation engine in the server generates optimal proposals for modification and improvement. In addition to grammatical corrections, these proposals include expressions suitable for the user's emotional state.

[0304] Step 5:

[0305] The generated proposals are sent to the terminal through the transmission module. On the terminal, the amended version is presented to the user and displayed in a visually understandable form.

[0306] Step 6:

[0307] The user checks the proposed amendments on the terminal and evaluates whether they match their emotions and intentions. The user makes final adjustments as needed to create the completed text.

[0308] (Example 2)

[0309] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0310] In modern communication, in text expression, it is becoming increasingly important not only to ensure the appropriateness of grammar and style but also to accurately reflect the emotions and intentions of the sender. However, it is not easy for users to create texts that appropriately reflect their emotions and intentions. Therefore, there is a growing need for a system that can automatically generate texts that reflect the user's emotions while correcting grammar and style.

[0311] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0312] In this invention, the server includes an information processing device means for receiving character data entered by a user, an emotion analysis device means for evaluating the emotional state of the character data, and a data generation device means for creating correction candidates suitable for the user's emotions using the emotion information obtained from the emotion analysis device. This makes it possible to modify grammar and style while taking the user's emotions into consideration.

[0313] A "user" refers to a person who inputs text data into an information processing system to convey their emotions and intentions.

[0314] "Character data" refers to text-based information that is entered by the user and received and analyzed by the server.

[0315] An "information processing device" refers to a computing device that handles character data received from a user and operates as the foundation for subsequent analysis and generation processes.

[0316] An "analytical device" refers to software or hardware that has the function of syntactically and stylistically evaluating character data and detecting the need for correction or improvement.

[0317] A "data generation device" refers to a device that generates newly modified text data based on the analysis results and information obtained from sentiment analysis.

[0318] A "sentiment analysis device" refers to a device that analyzes the user's emotional state from input text data and uses that information to modify or generate text.

[0319] An "information transmission device" refers to a device that outputs corrected and improved character data for presentation to the user again.

[0320] This invention is a system for receiving text data entered by a user and optimizing that text based on emotion. The system includes an information processing device, an analysis device, an emotion analysis device, a data generation device, and an information transmission device.

[0321] Users input text data that reflects their emotions and intentions through a terminal. This data is sent from the terminal to a server, which is an information processing device. The server analyzes the received data using an analysis device. Specifically, it uses a syntactic analysis tool (e.g., Grammarly or ProWritingAid) to check the syntax and format of the input data and identify errors.

[0322] Subsequently, an emotion analysis device on the server analyzes the input text data to evaluate the user's emotions. Natural language processing techniques are used for emotion analysis, particularly emotion analysis libraries (e.g., VADER and TextBlob). This device infers the user's emotions from words, phrases, and the tone of sentences.

[0323] Based on the results of the sentiment analysis, the data generation device uses the sentiment information and the information obtained from the analysis device to generate optimized revision candidates. In this process, the text is modified to include a writing style and vocabulary appropriate to the user's emotions.

[0324] Finally, the information transmission device sends the revised data back to the terminal and presents it to the user. The user reviews this proposal, determines whether it aligns with their intentions, and makes further edits as needed.

[0325] As a concrete example, consider a case where a user inputs the text data "I am very happy today." The emotion analysis device identifies the word "happy," which indicates a positive emotion. Based on this, the data generation device generates a suggested sentence such as "Today was a truly wonderful day, and I feel great."

[0326] Another example of a prompt to input into the generation AI model is, "Please show me how to adjust the tone of the text based on the emotions entered." In this way, it becomes possible to generate text that takes the user's emotions into consideration.

[0327] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0328] Step 1:

[0329] The user inputs text data via a terminal. This input data is text that expresses the user's intentions and emotions. Because this text includes emotional expressions, its syntax and style may not be consistent. The input data is then sent to the server.

[0330] Step 2:

[0331] The server, acting as an information processing device, passes the received text data to the parser. The parser analyzes the text data using a syntactic analysis tool to identify grammatical errors and areas for stylistic improvement. The output of the analysis generates syntactic problems and suggested improvements.

[0332] Step 3:

[0333] The emotion analysis device on the server analyzes the received text data in parallel with the analysis results and evaluates the user's emotions. Based on natural language processing technology, it quantifies emotional states such as positive and negative. The output is emotional information inferred from the text data.

[0334] Step 4:

[0335] The server passes the results from the sentiment analysis device to the data generation device, which, combined with the information from the analysis device, generates optimized revision suggestions. In addition to improving grammar and style, the data generation device revises the text to suit the user's writing style based on the sentiment information. The output is revised text with a unified style appropriate to the sentiment.

[0336] Step 5:

[0337] The revised text data is returned to the terminal via the information transmission device and presented to the user. The user reviews this revised version and confirms that it matches their intentions. The user can make further edits as needed. The output is the final text after user review and final editing.

[0338] (Application Example 2)

[0339] 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."

[0340] In today's information society, users are exposed to vast amounts of information daily, and there is an increasing demand for information tailored to their individual emotions and intentions. However, conventional information delivery systems are unable to adequately provide personalized content based on users' emotions, making it difficult to achieve deeper user engagement.

[0341] 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.

[0342] In this invention, the server includes a device means for receiving data entered by a user, an analysis unit means for analyzing the grammar and style of the received text, a generation mechanism means for modifying and improving the grammar and style based on the analyzed text, and a transmission unit means for sending personalized text information generated based on emotion to the user. This makes it possible to provide optimal content according to the user's emotions and to quickly convey information that meets individual needs.

[0343] A "user" is a person who uses a system to input information and receives feedback from it.

[0344] "Data" refers to text and other information entered by users, which forms the basis for analysis and processing within the system.

[0345] "Device" refers to a part of a system that includes hardware and software for receiving and processing data from a user.

[0346] The "analysis unit" is a means of analyzing the grammar and style of the received text to identify errors and areas for improvement.

[0347] A "generation mechanism" is a system component that uses analyzed text to correct grammar and style, and then generates improved content.

[0348] An "emotion engine" is a processing mechanism that estimates emotions from the content of the user's input text and performs optimizations that reflect that information.

[0349] The "transmission unit" is a means for sending the text information, which has been improved by the generation mechanism, to the user's terminal.

[0350] Personalization is the act of individually optimizing and delivering content based on each user's emotions and characteristics.

[0351] To implement this invention, a terminal on which users can input emotion-based information and a server that performs text analysis and generation are required. Users input text related to their emotions and intentions using a smartphone or computer.

[0352] Data entered from the terminal is received by a "device that receives user-entered data" on the server. The received data is then sent to an "analysis unit" where its grammar and style are analyzed. This analysis unit identifies and reports grammatical errors and stylistic problems within the data.

[0353] The analyzed data is modified grammatically and stylistically by a "generative mechanism," resulting in improved content. This generative mechanism includes a process of adjusting and improving the text data based on the analysis results.

[0354] Furthermore, an "emotion engine" within the server estimates the user's emotions from the analyzed text, and a generation mechanism creates optimized text based on this. This optimization process generates personalized content that aligns with the user's emotions.

[0355] The "transmission unit" returns the generated optimized text to the user's device and presents it to the user. This allows the user to receive content that matches their own emotions.

[0356] For example, if a user enters the text "I'm tired today" to express fatigue, the emotion engine recognizes this emotion, and the generation mechanism generates and sends relaxing text such as "Take a break and relax." An example of a prompt might be in the form of "Please enter words to express your current mood."

[0357] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0358] Step 1:

[0359] The user's device inputs text data related to emotions and intentions and sends it to the server. At this stage, the user uses a smartphone or computer to provide information to the system. The server accurately receives the text data and prepares it for the next analysis process.

[0360] Step 2:

[0361] The analysis unit on the server analyzes the grammar and style of the received text data. The input to the analysis unit is text data sent by the user, and it identifies grammatical errors and style issues based on this data. The analyzed data includes detailed comments on grammar and style, serving as a roadmap for correction. This process allows for a thorough examination of grammatical and style errors, clearly outlining the path to improvement.

[0362] Step 3:

[0363] The server passes the analyzed data to the generation mechanism for grammatical and stylistic corrections. The analysis results are provided as input, and the generation mechanism uses this data to generate proposed corrections. These corrections specifically reflect the improvements in grammar and style, resulting in the output of improved text data. This transforms the user's input into a more refined form.

[0364] Step 4:

[0365] The server's sentiment engine estimates the user's emotions from the analyzed text data, and based on this, the generation mechanism creates personalized content optimized for that emotion. The sentiment engine's input is the modified text data, and through sentiment analysis, it evaluates how the text relates to the user's emotions. Optimization is then performed based on the sentiment information, adjusting the content to suit the user.

[0366] Step 5:

[0367] The server sends the text data, improved by the generation mechanism, from the "transmitter" to the user's terminal. The input to the transmitter is optimized text, and the user receives this output. The user evaluates the content to see if it fits their emotions and makes further edits as needed. This completes a series of cycles, including a user guide prompt that includes an example of a prompt: "Please enter words to express how you are feeling right now."

[0368] 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.

[0369] 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.

[0370] 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.

[0371] [Third Embodiment]

[0372] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0373] 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.

[0374] 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).

[0375] 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.

[0376] 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.

[0377] 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).

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] 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".

[0384] This invention is a system for automatically correcting and improving the grammar and style of text data, and in its embodiment, it consists of three elements: a server, a terminal, and a user. This system operates as follows:

[0385] The user inputs text data via a terminal. The input data is sent to the server. The server is equipped with an analysis module, which performs grammatical and stylistic analysis. As a result of the analysis, grammatical errors and areas for stylistic improvement within the text are identified.

[0386] The server's built-in generation engine generates optimal revision suggestions based on the analysis results. These suggestions are customized based on the user's profile data, resulting in improvements tailored to each individual user. This allows for revisions that match the user's writing style.

[0387] The revised text data is sent back to the terminal via the transmission module. The user can review the revision suggestions on the terminal and ultimately choose which one to adopt. At this point, the user can quickly complete a high-quality document based on the provided revisions.

[0388] As a concrete example, consider a case where a user inputs the incomplete sentence "Poverty is increasing a lot." The server first recognizes the grammatical error "a lot." The generation engine then suggests a corrected version, such as "Poverty is increasing significantly," and the user can review the correction on their device and adopt it as the optimal sentence.

[0389] In this way, the present invention helps users create faster and more refined documents. The entire system automatically suggests grammatical and stylistic corrections, improving the user's writing ability and significantly reducing working time.

[0390] The following describes the processing flow.

[0391] Step 1:

[0392] The user enters text on the device and presses the send button. This action sends the entered text data to the server.

[0393] Step 2:

[0394] The server receives text data sent from the terminal. It passes the received text to the parsing module, which then begins parsing the grammar and style.

[0395] Step 3:

[0396] The analysis module on the server identifies grammatical errors and stylistic inconsistencies based on the input text. This analysis process evaluates sentence structure, punctuation, and vocabulary appropriateness.

[0397] Step 4:

[0398] Based on the analysis results, the server uses a generation engine to identify points that need correction and improvement, and then generates the most suitable correction proposals. At this time, it references the user's profile data to customize the suggestions.

[0399] Step 5:

[0400] The generated revision proposals are aggregated on the server and prepared to be sent back to the terminal via the transmission module. The revision proposals are formatted in a user-friendly format.

[0401] Step 6:

[0402] The terminal displays the proposed corrections received from the server. The user reviews these and evaluates whether each correction aligns with their intent. If necessary, they adopt or further refine the proposed corrections.

[0403] Step 7:

[0404] The user ultimately adopts the proposed revisions, finishes editing, and completes the document. At this stage, high-quality text is generated in a short amount of time.

[0405] (Example 1)

[0406] 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."

[0407] There is a need for technology that can edit information accurately and quickly. Conventional methods require finding and manually correcting grammatical errors and style inconsistencies, making efficiency difficult. Furthermore, there is a lack of customization features that can accommodate individual user styles and preferences, resulting in wasted time and effort in the editing process. Therefore, the present invention aims to automate grammatical and style correction more effectively and realize high-quality information processing that meets the needs of each user.

[0408] 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.

[0409] In this invention, the server includes an information processing device means for receiving information input by a user, an analysis structure means for analyzing the grammar and expression style of the received information, and a generation structure means for modifying and improving the grammar and expression style based on the analyzed information. This enables automatic and highly accurate modification of information, and allows for the rapid provision of optimal information that suits the user's style.

[0410] An "information processing device" is a device that receives information input from a user and has the function of managing and controlling that data.

[0411] An "analysis structure" is a mechanism for analyzing received information and identifying errors and areas for improvement in grammar and expression.

[0412] A "generative structure" is a mechanism for modifying grammar and expression patterns based on analyzed information to generate optimal information.

[0413] A "communication structure" is a structure that provides the means of communication necessary to transmit corrected and improved information to the user.

[0414] "Attribute data" refers to data that includes user characteristics, past activity history, preferences, etc., and is used to enable the provision of information tailored to each individual user.

[0415] A "revision option" is a selection of revisions generated by the generative structure that presents the option deemed optimal for the user.

[0416] An "information input device" is a device used by users to input information and to verify corrected information.

[0417] This invention provides a system that allows users to process information more efficiently and automatically receive modifications tailored to their individual style. Users input information using a terminal. For example, consider a scenario where a user inputs information such as, "I want to check my meeting schedule, but I've forgotten the time."

[0418] The terminal transmits the input information to the server via a data network. The server, equipped with an information processing device, receives the information. The received information is analyzed using an analysis structure to identify grammatical and expression errors and areas for improvement. Generative AI models are utilized in the analysis to precisely understand and process the information.

[0419] The analysis results are generated as suggested revisions using a generation structure. These revisions are customized to the optimal form based on the user's attribute data, allowing for precise modifications tailored to the user's preferences and style. Specifically, the server might generate a suggestion such as, "Please check the meeting start time. You need to reset the time."

[0420] The proposed revisions are then sent back to the terminal via the communication structure. The user can review the proposed revisions on the terminal and obtain the information in the most suitable format. This entire process allows the user to process information quickly and efficiently and obtain customized revisions.

[0421] For example, a user might input a prompt such as, "I've finished writing tomorrow's report, but I'd like to see improvements to the grammar and style." The system can then automatically make the necessary corrections and provide optimized suggestions. This invention significantly reduces the time and effort users spend creating information.

[0422] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0423] Step 1:

[0424] The user uses a terminal to input text data. The input data is a sentence written by the user, such as "I want to complete a review about the new product." The terminal prepares to send the input text data directly to the server.

[0425] Step 2:

[0426] The server receives text data input through an information processing device. The received data is passed to an analysis structure for analyzing grammar and expression. This analysis structure uses a generative AI model to identify grammatical errors and areas for improvement in expression within the input data. For example, it searches for appropriate grammar and areas for improvement in the phrase "I want to complete the review."

[0427] Step 3:

[0428] The server's generation structure generates suggested revisions based on the analyzed data. In this step, data processing is performed based on the analysis results, generating suggested revisions with grammatically correct and consistent expressions. A generation AI model assists in this process, creating suggested revisions such as "We would like to complete the new product review."

[0429] Step 4:

[0430] The server customizes the generated revision proposals based on the user's attribute data. Here, data processing is performed to create revision proposals that are more suitable for each user, taking into account their past editing history and style. This results in an optimized revised version.

[0431] Step 5:

[0432] The server sends the proposed corrections to the terminal via the communication structure. This output process involves secure data communication, and the customized corrections are delivered to the user's terminal.

[0433] Step 6:

[0434] The user reviews the proposed revisions received from the server on their device. At this point, the user is presented with multiple revision options and can select the best one. Based on the user's selection, the final text that aligns with the intended meaning is finalized. This allows the user to complete high-quality documents quickly and efficiently.

[0435] (Application Example 1)

[0436] 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."

[0437] This project aims to address the problem of grammatical errors and unclear stylistic choices often found in text data such as product reviews and inquiry messages, which hinder the effective communication of information to other users.

[0438] 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.

[0439] In this invention, the server includes an information processing device means for receiving character data entered by a user, an analysis means for analyzing the grammar and format of the received character data, and a generation mechanism means for modifying and improving the grammar and format based on the analyzed character data. This enables the provision of more accurate and readable product reviews and inquiry messages to users in real time, and facilitates the transmission of useful information to other users.

[0440] An "information processing device that receives character data entered by a user" refers to hardware or software that receives and processes character data entered by a user via a network.

[0441] "Analysis means for analyzing the grammar and format of received character data" refers to an algorithm or process for detecting and analyzing grammatical errors and formal defects contained in character data.

[0442] A "generative mechanism for correcting and improving grammar and form based on parsed character data" is an engine or model that generates optimal correction proposals based on the analysis results and provides them to the user.

[0443] A "communication method" is a system that transmits corrected and improved text data to the user's terminal and enables two-way communication with the user.

[0444] A "tool that enables real-time revision suggestions for text data as product reviews" is a function that provides immediate grammar and style suggestions to users when they write product reviews, thereby improving the quality of the reviews.

[0445] "Generating optimized correction suggestions based on user profile information" is a process that adjusts suggested corrections according to each user's preferences and past input history to provide more appropriate suggestions.

[0446] "Presented on a display device in a user-editable format" means that the proposed revisions are displayed on the user's device screen, allowing the user to select and edit them themselves.

[0447] A system for carrying out this invention consists of an information processing device, an analysis means, a generation mechanism, a communication means, and a modification suggestion tool.

[0448] The server receives character data entered by the user via an information processing device. The received character data is then analyzed grammatically and formally using an analysis tool. Specifically, the analysis tool utilizes natural language processing algorithms to identify grammatical errors and areas for formal improvement in the character data. Based on these analysis results, the generation mechanism generates revised versions using a generative AI model. This generation process also takes user profile information into consideration, resulting in the generation of sentences in a style appropriate for the user.

[0449] Next, the corrected text data is sent to the user's terminal via communication. The correction suggestion tool displays grammatical and stylistic correction items to the user in real time, which the user can review and select.

[0450] As a concrete example, suppose a user enters a product review on a smartphone app and writes the sentence, "The product is very good, but it's complicated to use." The server analyzes the redundancy of "but, however," and the generation engine suggests a revised version: "The product is very good, but it's complicated to use." This revised version is adjusted to take the user's preferences into account and displayed on the device. In this way, users can easily post more refined product reviews based on the suggested revisions.

[0451] An example of a prompt message is: "Please grammatically check the following text and suggest corrections: {user's text} User profile: Style preferences - {style preferences}".

[0452] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0453] Step 1:

[0454] The user inputs character data via a terminal and sends that data to the information processing device. The input data is sent as text from the terminal to the server. The server receives this input and sends it to the next parsing step.

[0455] Step 2:

[0456] The server processes the received text data through a parsing system. The input here is the user's raw text data, and the parsing system uses natural language processing algorithms to identify grammatical errors and areas for stylistic improvement. The output is a list of the parsed information and identified errors.

[0457] Step 3:

[0458] The server passes the analyzed data to the generation mechanism. The input consists of an identified error list and a user profile, and the generation mechanism uses a generative AI model to perform data calculations to generate the optimal correction. The output is a correction tailored to the user's profile.

[0459] Step 4:

[0460] The server receives the proposed corrections from the generation mechanism and transmits them to the user's terminal via communication. The input is the proposed correction data, and the output is the correction suggestion displayed on the user's terminal.

[0461] Step 5:

[0462] The user reviews the suggested revisions presented on their device and selects which revision to ultimately adopt. The input for this step is the suggested revision, and the output is the final text data selected by the user. This selection allows the user to submit accurate and readable product reviews.

[0463] 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.

[0464] This invention relates to a system that optimizes text by analyzing the grammar and style of text data input by a user, and by recognizing the user's emotions. This system comprises a server, a terminal, and an emotion engine.

[0465] First, the user inputs text based on their emotions and intentions via their device and sends it to the server. Upon receiving the text data from the device, the server first passes it to a parsing module for grammatical and stylistic analysis. The parsing module analyzes the text data grammatically, points out errors, and identifies areas for stylistic improvement.

[0466] Next, the emotion engine on the server analyzes the text data and evaluates the user's emotions. This emotion engine infers the user's emotional state from the input words, phrases, and writing style, and passes the analysis results to the generation engine.

[0467] The generation engine creates suggested revisions by combining grammatical and stylistic corrections with sentiment information obtained from the sentiment engine. These suggested revisions are optimized to include a style and vocabulary appropriate to the user's emotions. This results in more personalized suggestions that reflect those emotions.

[0468] The modified text data is sent back to the terminal via the transmission module and presented to the user. The user reviews the proposed revisions, evaluates whether they align with their emotions and intentions, and then makes final edits. For example, if a user experiencing sadness enters the sentence "I'm sad today," the emotion engine will recognize this emotion. The generation engine can then suggest a revised sentence that reflects this emotion, such as "I'm feeling a bit down today, but I believe tomorrow will be better."

[0469] By incorporating an emotion engine in this way, it becomes possible to effectively generate text that reflects the emotions intended by the user, thereby supporting the creation of more appropriate and professional writing.

[0470] The following describes the processing flow.

[0471] Step 1:

[0472] The user initiates processing by typing text on their device and sending it to the server.

[0473] Step 2:

[0474] The server receives text data from the terminal and first passes it to the parsing module for grammatical and stylistic analysis. The parsing module identifies errors and stylistic inconsistencies in the text.

[0475] Step 3:

[0476] The server passes the analyzed data to the emotion engine, which analyzes the user's emotions based on the wording and context within the text. The emotion engine quantifies the emotions hidden in the input data and identifies what kind of emotions are being expressed.

[0477] Step 4:

[0478] Based on the analysis results and sentiment data, the server's generation engine generates optimal suggestions for correction and improvement. These suggestions include grammatical corrections as well as expressions appropriate to the user's emotional state.

[0479] Step 5:

[0480] The generated suggestions are sent to the terminal via the transmission module. On the terminal, the proposed revisions are presented to the user and displayed in a visually easy-to-understand format.

[0481] Step 6:

[0482] The user reviews the suggested revisions on their device and evaluates whether they align with their feelings and intentions. The user then makes final adjustments as needed to create the completed text.

[0483] (Example 2)

[0484] 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."

[0485] In modern communication, it is becoming increasingly important to accurately reflect the sender's emotions and intentions in written expression, in addition to grammatical and stylistic correctness. However, it is not easy for users to create text that appropriately reflects their own emotions and intentions. Therefore, there is a growing need for a system that can automatically generate text that reflects the user's emotions while simultaneously correcting grammar and style.

[0486] 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.

[0487] In this invention, the server includes an information processing device means for receiving character data entered by a user, an emotion analysis device means for evaluating the emotional state of the character data, and a data generation device means for creating correction candidates suitable for the user's emotions using the emotion information obtained from the emotion analysis device. This makes it possible to modify grammar and style while taking the user's emotions into consideration.

[0488] A "user" refers to a person who inputs text data into an information processing system to convey their emotions and intentions.

[0489] "Character data" refers to text-based information that is entered by the user and received and analyzed by the server.

[0490] An "information processing device" refers to a computing device that handles character data received from a user and operates as the foundation for subsequent analysis and generation processes.

[0491] An "analytical device" refers to software or hardware that has the function of syntactically and stylistically evaluating character data and detecting the need for correction or improvement.

[0492] A "data generation device" refers to a device that generates newly modified text data based on the analysis results and information obtained from sentiment analysis.

[0493] A "sentiment analysis device" refers to a device that analyzes the user's emotional state from input text data and uses that information to modify or generate text.

[0494] An "information transmission device" refers to a device that outputs corrected and improved character data for presentation to the user again.

[0495] This invention is a system for receiving text data entered by a user and optimizing that text based on emotion. The system includes an information processing device, an analysis device, an emotion analysis device, a data generation device, and an information transmission device.

[0496] Users input text data that reflects their emotions and intentions through a terminal. This data is sent from the terminal to a server, which is an information processing device. The server analyzes the received data using an analysis device. Specifically, it uses a syntactic analysis tool (e.g., Grammarly or ProWritingAid) to check the syntax and format of the input data and identify errors.

[0497] Subsequently, an emotion analysis device on the server analyzes the input text data to evaluate the user's emotions. Natural language processing techniques are used for emotion analysis, particularly emotion analysis libraries (e.g., VADER and TextBlob). This device infers the user's emotions from words, phrases, and the tone of sentences.

[0498] Based on the results of the sentiment analysis, the data generation device uses the sentiment information and the information obtained from the analysis device to generate optimized revision candidates. In this process, the text is modified to include a writing style and vocabulary appropriate to the user's emotions.

[0499] Finally, the information transmission device sends the revised data back to the terminal and presents it to the user. The user reviews this proposal, determines whether it aligns with their intentions, and makes further edits as needed.

[0500] As a concrete example, consider a case where a user inputs the text data "I am very happy today." The emotion analysis device identifies the word "happy," which indicates a positive emotion. Based on this, the data generation device generates a suggested sentence such as "Today was a truly wonderful day, and I feel great."

[0501] Another example of a prompt to input into the generation AI model is, "Please show me how to adjust the tone of the text based on the emotions entered." In this way, it becomes possible to generate text that takes the user's emotions into consideration.

[0502] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0503] Step 1:

[0504] The user inputs text data via a terminal. This input data is text that expresses the user's intentions and emotions. Because this text includes emotional expressions, its syntax and style may not be consistent. The input data is then sent to the server.

[0505] Step 2:

[0506] The server, acting as an information processing device, passes the received text data to the parser. The parser analyzes the text data using a syntactic analysis tool to identify grammatical errors and areas for stylistic improvement. The output of the analysis generates syntactic problems and suggested improvements.

[0507] Step 3:

[0508] The emotion analysis device on the server analyzes the received text data in parallel with the analysis results and evaluates the user's emotions. Based on natural language processing technology, it quantifies emotional states such as positive and negative. The output is emotional information inferred from the text data.

[0509] Step 4:

[0510] The server passes the results from the sentiment analysis device to the data generation device, which, combined with the information from the analysis device, generates optimized revision suggestions. In addition to improving grammar and style, the data generation device revises the text to suit the user's writing style based on the sentiment information. The output is revised text with a unified style appropriate to the sentiment.

[0511] Step 5:

[0512] The revised text data is returned to the terminal via the information transmission device and presented to the user. The user reviews this revised version and confirms that it matches their intentions. The user can make further edits as needed. The output is the final text after user review and final editing.

[0513] (Application Example 2)

[0514] 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."

[0515] In today's information society, users are exposed to vast amounts of information daily, and there is an increasing demand for information tailored to their individual emotions and intentions. However, conventional information delivery systems are unable to adequately provide personalized content based on users' emotions, making it difficult to achieve deeper user engagement.

[0516] 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.

[0517] In this invention, the server includes a device means for receiving data entered by a user, an analysis unit means for analyzing the grammar and style of the received text, a generation mechanism means for modifying and improving the grammar and style based on the analyzed text, and a transmission unit means for sending personalized text information generated based on emotion to the user. This makes it possible to provide optimal content according to the user's emotions and to quickly convey information that meets individual needs.

[0518] A "user" is a person who uses a system to input information and receives feedback from it.

[0519] "Data" refers to text and other information entered by users, which forms the basis for analysis and processing within the system.

[0520] "Device" refers to a part of a system that includes hardware and software for receiving and processing data from a user.

[0521] The "analysis unit" is a means of analyzing the grammar and style of the received text to identify errors and areas for improvement.

[0522] A "generation mechanism" is a system component that uses analyzed text to correct grammar and style, and then generates improved content.

[0523] An "emotion engine" is a processing mechanism that estimates emotions from the content of the user's input text and performs optimizations that reflect that information.

[0524] The "transmission unit" is a means for sending the text information, which has been improved by the generation mechanism, to the user's terminal.

[0525] Personalization is the act of individually optimizing and delivering content based on each user's emotions and characteristics.

[0526] To implement this invention, a terminal on which users can input emotion-based information and a server that performs text analysis and generation are required. Users input text related to their emotions and intentions using a smartphone or computer.

[0527] Data entered from the terminal is received by a "device that receives user-entered data" on the server. The received data is then sent to an "analysis unit" where its grammar and style are analyzed. This analysis unit identifies and reports grammatical errors and stylistic problems within the data.

[0528] The analyzed data is modified grammatically and stylistically by a "generative mechanism," resulting in improved content. This generative mechanism includes a process of adjusting and improving the text data based on the analysis results.

[0529] Furthermore, an "emotion engine" within the server estimates the user's emotions from the analyzed text, and a generation mechanism creates optimized text based on this. This optimization process generates personalized content that aligns with the user's emotions.

[0530] The "transmission unit" returns the generated optimized text to the user's device and presents it to the user. This allows the user to receive content that matches their own emotions.

[0531] For example, if a user enters the text "I'm tired today" to express fatigue, the emotion engine recognizes this emotion, and the generation mechanism generates and sends relaxing text such as "Take a break and relax." An example of a prompt might be in the form of "Please enter words to express your current mood."

[0532] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0533] Step 1:

[0534] The user's device inputs text data related to emotions and intentions and sends it to the server. At this stage, the user uses a smartphone or computer to provide information to the system. The server accurately receives the text data and prepares it for the next analysis process.

[0535] Step 2:

[0536] The analysis unit on the server analyzes the grammar and style of the received text data. The input to the analysis unit is text data sent by the user, and it identifies grammatical errors and style issues based on this data. The analyzed data includes detailed comments on grammar and style, serving as a roadmap for correction. This process allows for a thorough examination of grammatical and style errors, clearly outlining the path to improvement.

[0537] Step 3:

[0538] The server passes the analyzed data to the generation mechanism for grammatical and stylistic corrections. The analysis results are provided as input, and the generation mechanism uses this data to generate proposed corrections. These corrections specifically reflect the improvements in grammar and style, resulting in the output of improved text data. This transforms the user's input into a more refined form.

[0539] Step 4:

[0540] The server's sentiment engine estimates the user's emotions from the analyzed text data, and based on this, the generation mechanism creates personalized content optimized for that emotion. The sentiment engine's input is the modified text data, and through sentiment analysis, it evaluates how the text relates to the user's emotions. Optimization is then performed based on the sentiment information, adjusting the content to suit the user.

[0541] Step 5:

[0542] The server sends the text data, improved by the generation mechanism, from the "transmitter" to the user's terminal. The input to the transmitter is optimized text, and the user receives this output. The user evaluates the content to see if it fits their emotions and makes further edits as needed. This completes a series of cycles, including a user guide prompt that includes an example of a prompt: "Please enter words to express how you are feeling right now."

[0543] 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.

[0544] 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.

[0545] 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.

[0546] [Fourth Embodiment]

[0547] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0548] 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.

[0549] 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).

[0550] 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.

[0551] 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.

[0552] 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).

[0553] 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.

[0554] 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.

[0555] 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.

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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".

[0560] This invention is a system for automatically correcting and improving the grammar and style of text data, and in its embodiment, it consists of three elements: a server, a terminal, and a user. This system operates as follows:

[0561] The user inputs text data via a terminal. The input data is sent to the server. The server is equipped with an analysis module, which performs grammatical and stylistic analysis. As a result of the analysis, grammatical errors and areas for stylistic improvement within the text are identified.

[0562] The server's built-in generation engine generates optimal revision suggestions based on the analysis results. These suggestions are customized based on the user's profile data, resulting in improvements tailored to each individual user. This allows for revisions that match the user's writing style.

[0563] The revised text data is sent back to the terminal via the transmission module. The user can review the revision suggestions on the terminal and ultimately choose which one to adopt. At this point, the user can quickly complete a high-quality document based on the provided revisions.

[0564] As a concrete example, consider a case where a user inputs the incomplete sentence "Poverty is increasing a lot." The server first recognizes the grammatical error "a lot." The generation engine then suggests a corrected version, such as "Poverty is increasing significantly," and the user can review the correction on their device and adopt it as the optimal sentence.

[0565] In this way, the present invention helps users create faster and more refined documents. The entire system automatically suggests grammatical and stylistic corrections, improving the user's writing ability and significantly reducing working time.

[0566] The following describes the processing flow.

[0567] Step 1:

[0568] The user enters text on the device and presses the send button. This action sends the entered text data to the server.

[0569] Step 2:

[0570] The server receives text data sent from the terminal. It passes the received text to the parsing module, which then begins parsing the grammar and style.

[0571] Step 3:

[0572] The analysis module on the server identifies grammatical errors and stylistic inconsistencies based on the input text. This analysis process evaluates sentence structure, punctuation, and vocabulary appropriateness.

[0573] Step 4:

[0574] Based on the analysis results, the server uses a generation engine to identify points that need correction and improvement, and then generates the most suitable correction proposals. At this time, it references the user's profile data to customize the suggestions.

[0575] Step 5:

[0576] The generated revision proposals are aggregated on the server and prepared to be sent back to the terminal via the transmission module. The revision proposals are formatted in a user-friendly format.

[0577] Step 6:

[0578] The terminal displays the proposed corrections received from the server. The user reviews these and evaluates whether each correction aligns with their intent. If necessary, they adopt or further refine the proposed corrections.

[0579] Step 7:

[0580] The user ultimately adopts the proposed revisions, finishes editing, and completes the document. At this stage, high-quality text is generated in a short amount of time.

[0581] (Example 1)

[0582] 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".

[0583] There is a need for technology that can edit information accurately and quickly. Conventional methods require finding and manually correcting grammatical errors and style inconsistencies, making efficiency difficult. Furthermore, there is a lack of customization features that can accommodate individual user styles and preferences, resulting in wasted time and effort in the editing process. Therefore, the present invention aims to automate grammatical and style correction more effectively and realize high-quality information processing that meets the needs of each user.

[0584] 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.

[0585] In this invention, the server includes an information processing device means for receiving information input by a user, an analysis structure means for analyzing the grammar and expression style of the received information, and a generation structure means for modifying and improving the grammar and expression style based on the analyzed information. This enables automatic and highly accurate modification of information, and allows for the rapid provision of optimal information that suits the user's style.

[0586] An "information processing device" is a device that receives information input from a user and has the function of managing and controlling that data.

[0587] An "analysis structure" is a mechanism for analyzing received information and identifying errors and areas for improvement in grammar and expression.

[0588] A "generative structure" is a mechanism for modifying grammar and expression patterns based on analyzed information to generate optimal information.

[0589] A "communication structure" is a structure that provides the means of communication necessary to transmit corrected and improved information to the user.

[0590] "Attribute data" refers to data that includes user characteristics, past activity history, preferences, etc., and is used to enable the provision of information tailored to each individual user.

[0591] A "revision option" is a selection of revisions generated by the generative structure that presents the option deemed optimal for the user.

[0592] An "information input device" is a device used by users to input information and to verify corrected information.

[0593] This invention provides a system that allows users to process information more efficiently and automatically receive modifications tailored to their individual style. Users input information using a terminal. For example, consider a scenario where a user inputs information such as, "I want to check my meeting schedule, but I've forgotten the time."

[0594] The terminal transmits the input information to the server via a data network. The server, equipped with an information processing device, receives the information. The received information is analyzed using an analysis structure to identify grammatical and expression errors and areas for improvement. Generative AI models are utilized in the analysis to precisely understand and process the information.

[0595] The analysis results are generated as suggested revisions using a generation structure. These revisions are customized to the optimal form based on the user's attribute data, allowing for precise modifications tailored to the user's preferences and style. Specifically, the server might generate a suggestion such as, "Please check the meeting start time. You need to reset the time."

[0596] The proposed revisions are then sent back to the terminal via the communication structure. The user can review the proposed revisions on the terminal and obtain the information in the most suitable format. This entire process allows the user to process information quickly and efficiently and obtain customized revisions.

[0597] For example, a user might input a prompt such as, "I've finished writing tomorrow's report, but I'd like to see improvements to the grammar and style." The system can then automatically make the necessary corrections and provide optimized suggestions. This invention significantly reduces the time and effort users spend creating information.

[0598] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0599] Step 1:

[0600] The user uses a terminal to input text data. The input data is a sentence written by the user, such as "I want to complete a review about the new product." The terminal prepares to send the input text data directly to the server.

[0601] Step 2:

[0602] The server receives text data input through an information processing device. The received data is passed to an analysis structure for analyzing grammar and expression. This analysis structure uses a generative AI model to identify grammatical errors and areas for improvement in expression within the input data. For example, it searches for appropriate grammar and areas for improvement in the phrase "I want to complete the review."

[0603] Step 3:

[0604] The server's generation structure generates suggested revisions based on the analyzed data. In this step, data processing is performed based on the analysis results, generating suggested revisions with grammatically correct and consistent expressions. A generation AI model assists in this process, creating suggested revisions such as "We would like to complete the new product review."

[0605] Step 4:

[0606] The server customizes the generated revision proposals based on the user's attribute data. Here, data processing is performed to create revision proposals that are more suitable for each user, taking into account their past editing history and style. This results in an optimized revised version.

[0607] Step 5:

[0608] The server sends the proposed corrections to the terminal via the communication structure. This output process involves secure data communication, and the customized corrections are delivered to the user's terminal.

[0609] Step 6:

[0610] The user reviews the proposed revisions received from the server on their device. At this point, the user is presented with multiple revision options and can select the best one. Based on the user's selection, the final text that aligns with the intended meaning is finalized. This allows the user to complete high-quality documents quickly and efficiently.

[0611] (Application Example 1)

[0612] 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".

[0613] This project aims to address the problem of grammatical errors and unclear stylistic choices often found in text data such as product reviews and inquiry messages, which hinder the effective communication of information to other users.

[0614] 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.

[0615] In this invention, the server includes an information processing device means for receiving character data entered by a user, an analysis means for analyzing the grammar and format of the received character data, and a generation mechanism means for modifying and improving the grammar and format based on the analyzed character data. This enables the provision of more accurate and readable product reviews and inquiry messages to users in real time, and facilitates the transmission of useful information to other users.

[0616] An "information processing device that receives character data entered by a user" refers to hardware or software that receives and processes character data entered by a user via a network.

[0617] "Analysis means for analyzing the grammar and format of received character data" refers to an algorithm or process for detecting and analyzing grammatical errors and formal defects contained in character data.

[0618] A "generative mechanism for correcting and improving grammar and form based on parsed character data" is an engine or model that generates optimal correction proposals based on the analysis results and provides them to the user.

[0619] A "communication method" is a system that transmits corrected and improved text data to the user's terminal and enables two-way communication with the user.

[0620] A "tool that enables real-time revision suggestions for text data as product reviews" is a function that provides immediate grammar and style suggestions to users when they write product reviews, thereby improving the quality of the reviews.

[0621] "Generating optimized correction suggestions based on user profile information" is a process that adjusts suggested corrections according to each user's preferences and past input history to provide more appropriate suggestions.

[0622] "Presented on a display device in a user-editable format" means that the proposed revisions are displayed on the user's device screen, allowing the user to select and edit them themselves.

[0623] A system for carrying out this invention consists of an information processing device, an analysis means, a generation mechanism, a communication means, and a modification suggestion tool.

[0624] The server receives character data entered by the user via an information processing device. The received character data is then analyzed grammatically and formally using an analysis tool. Specifically, the analysis tool utilizes natural language processing algorithms to identify grammatical errors and areas for formal improvement in the character data. Based on these analysis results, the generation mechanism generates revised versions using a generative AI model. This generation process also takes user profile information into consideration, resulting in the generation of sentences in a style appropriate for the user.

[0625] Next, the corrected text data is sent to the user's terminal via communication. The correction suggestion tool displays grammatical and stylistic correction items to the user in real time, which the user can review and select.

[0626] As a concrete example, suppose a user enters a product review on a smartphone app and writes the sentence, "The product is very good, but it's complicated to use." The server analyzes the redundancy of "but, however," and the generation engine suggests a revised version: "The product is very good, but it's complicated to use." This revised version is adjusted to take the user's preferences into account and displayed on the device. In this way, users can easily post more refined product reviews based on the suggested revisions.

[0627] An example of a prompt message is: "Please grammatically check the following text and suggest corrections: {user's text} User profile: Style preferences - {style preferences}".

[0628] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0629] Step 1:

[0630] The user inputs character data via a terminal and sends that data to the information processing device. The input data is sent as text from the terminal to the server. The server receives this input and sends it to the next parsing step.

[0631] Step 2:

[0632] The server processes the received text data through a parsing system. The input here is the user's raw text data, and the parsing system uses natural language processing algorithms to identify grammatical errors and areas for stylistic improvement. The output is a list of the parsed information and identified errors.

[0633] Step 3:

[0634] The server passes the analyzed data to the generation mechanism. The input consists of an identified error list and a user profile, and the generation mechanism uses a generative AI model to perform data calculations to generate the optimal correction. The output is a correction tailored to the user's profile.

[0635] Step 4:

[0636] The server receives the proposed corrections from the generation mechanism and transmits them to the user's terminal via communication. The input is the proposed correction data, and the output is the correction suggestion displayed on the user's terminal.

[0637] Step 5:

[0638] The user reviews the suggested revisions presented on their device and selects which revision to ultimately adopt. The input for this step is the suggested revision, and the output is the final text data selected by the user. This selection allows the user to submit accurate and readable product reviews.

[0639] 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.

[0640] This invention relates to a system that optimizes text by analyzing the grammar and style of text data input by a user, and by recognizing the user's emotions. This system comprises a server, a terminal, and an emotion engine.

[0641] First, the user inputs text based on their emotions and intentions via their device and sends it to the server. Upon receiving the text data from the device, the server first passes it to a parsing module for grammatical and stylistic analysis. The parsing module analyzes the text data grammatically, points out errors, and identifies areas for stylistic improvement.

[0642] Next, the emotion engine on the server analyzes the text data and evaluates the user's emotions. This emotion engine infers the user's emotional state from the input words, phrases, and writing style, and passes the analysis results to the generation engine.

[0643] The generation engine creates suggested revisions by combining grammatical and stylistic corrections with sentiment information obtained from the sentiment engine. These suggested revisions are optimized to include a style and vocabulary appropriate to the user's emotions. This results in more personalized suggestions that reflect those emotions.

[0644] The modified text data is sent back to the terminal via the transmission module and presented to the user. The user reviews the proposed revisions, evaluates whether they align with their emotions and intentions, and then makes final edits. For example, if a user experiencing sadness enters the sentence "I'm sad today," the emotion engine will recognize this emotion. The generation engine can then suggest a revised sentence that reflects this emotion, such as "I'm feeling a bit down today, but I believe tomorrow will be better."

[0645] By incorporating an emotion engine in this way, it becomes possible to effectively generate text that reflects the emotions intended by the user, thereby supporting the creation of more appropriate and professional writing.

[0646] The following describes the processing flow.

[0647] Step 1:

[0648] The user initiates processing by typing text on their device and sending it to the server.

[0649] Step 2:

[0650] The server receives text data from the terminal and first passes it to the parsing module for grammatical and stylistic analysis. The parsing module identifies errors and stylistic inconsistencies in the text.

[0651] Step 3:

[0652] The server passes the analyzed data to the emotion engine, which analyzes the user's emotions based on the wording and context within the text. The emotion engine quantifies the emotions hidden in the input data and identifies what kind of emotions are being expressed.

[0653] Step 4:

[0654] Based on the analysis results and sentiment data, the server's generation engine generates optimal suggestions for correction and improvement. These suggestions include grammatical corrections as well as expressions appropriate to the user's emotional state.

[0655] Step 5:

[0656] The generated suggestions are sent to the terminal via the transmission module. On the terminal, the proposed revisions are presented to the user and displayed in a visually easy-to-understand format.

[0657] Step 6:

[0658] The user reviews the suggested revisions on their device and evaluates whether they align with their feelings and intentions. The user then makes final adjustments as needed to create the completed text.

[0659] (Example 2)

[0660] 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".

[0661] In modern communication, it is becoming increasingly important to accurately reflect the sender's emotions and intentions in written expression, in addition to grammatical and stylistic correctness. However, it is not easy for users to create text that appropriately reflects their own emotions and intentions. Therefore, there is a growing need for a system that can automatically generate text that reflects the user's emotions while simultaneously correcting grammar and style.

[0662] 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.

[0663] In this invention, the server includes an information processing device means for receiving character data entered by a user, an emotion analysis device means for evaluating the emotional state of the character data, and a data generation device means for creating correction candidates suitable for the user's emotions using the emotion information obtained from the emotion analysis device. This makes it possible to modify grammar and style while taking the user's emotions into consideration.

[0664] A "user" refers to a person who inputs text data into an information processing system to convey their emotions and intentions.

[0665] "Character data" refers to text-based information that is entered by the user and received and analyzed by the server.

[0666] An "information processing device" refers to a computing device that handles character data received from a user and operates as the foundation for subsequent analysis and generation processes.

[0667] An "analytical device" refers to software or hardware that has the function of syntactically and stylistically evaluating character data and detecting the need for correction or improvement.

[0668] A "data generation device" refers to a device that generates newly modified text data based on the analysis results and information obtained from sentiment analysis.

[0669] A "sentiment analysis device" refers to a device that analyzes the user's emotional state from input text data and uses that information to modify or generate text.

[0670] An "information transmission device" refers to a device that outputs corrected and improved character data for presentation to the user again.

[0671] This invention is a system for receiving text data entered by a user and optimizing that text based on emotion. The system includes an information processing device, an analysis device, an emotion analysis device, a data generation device, and an information transmission device.

[0672] Users input text data that reflects their emotions and intentions through a terminal. This data is sent from the terminal to a server, which is an information processing device. The server analyzes the received data using an analysis device. Specifically, it uses a syntactic analysis tool (e.g., Grammarly or ProWritingAid) to check the syntax and format of the input data and identify errors.

[0673] Subsequently, an emotion analysis device on the server analyzes the input text data to evaluate the user's emotions. Natural language processing techniques are used for emotion analysis, particularly emotion analysis libraries (e.g., VADER and TextBlob). This device infers the user's emotions from words, phrases, and the tone of sentences.

[0674] Based on the results of the sentiment analysis, the data generation device uses the sentiment information and the information obtained from the analysis device to generate optimized revision candidates. In this process, the text is modified to include a writing style and vocabulary appropriate to the user's emotions.

[0675] Finally, the information transmission device sends the revised data back to the terminal and presents it to the user. The user reviews this proposal, determines whether it aligns with their intentions, and makes further edits as needed.

[0676] As a concrete example, consider a case where a user inputs the text data "I am very happy today." The emotion analysis device identifies the word "happy," which indicates a positive emotion. Based on this, the data generation device generates a suggested sentence such as "Today was a truly wonderful day, and I feel great."

[0677] Another example of a prompt to input into the generation AI model is, "Please show me how to adjust the tone of the text based on the emotions entered." In this way, it becomes possible to generate text that takes the user's emotions into consideration.

[0678] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0679] Step 1:

[0680] The user inputs text data via a terminal. This input data is text that expresses the user's intentions and emotions. Because this text includes emotional expressions, its syntax and style may not be consistent. The input data is then sent to the server.

[0681] Step 2:

[0682] The server, acting as an information processing device, passes the received text data to the parser. The parser analyzes the text data using a syntactic analysis tool to identify grammatical errors and areas for stylistic improvement. The output of the analysis generates syntactic problems and suggested improvements.

[0683] Step 3:

[0684] The emotion analysis device on the server analyzes the received text data in parallel with the analysis results and evaluates the user's emotions. Based on natural language processing technology, it quantifies emotional states such as positive and negative. The output is emotional information inferred from the text data.

[0685] Step 4:

[0686] The server passes the results from the sentiment analysis device to the data generation device, which, combined with the information from the analysis device, generates optimized revision suggestions. In addition to improving grammar and style, the data generation device revises the text to suit the user's writing style based on the sentiment information. The output is revised text with a unified style appropriate to the sentiment.

[0687] Step 5:

[0688] The revised text data is returned to the terminal via the information transmission device and presented to the user. The user reviews this revised version and confirms that it matches their intentions. The user can make further edits as needed. The output is the final text after user review and final editing.

[0689] (Application Example 2)

[0690] 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".

[0691] In today's information society, users are exposed to vast amounts of information daily, and there is an increasing demand for information tailored to their individual emotions and intentions. However, conventional information delivery systems are unable to adequately provide personalized content based on users' emotions, making it difficult to achieve deeper user engagement.

[0692] 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.

[0693] In this invention, the server includes a device means for receiving data entered by a user, an analysis unit means for analyzing the grammar and style of the received text, a generation mechanism means for modifying and improving the grammar and style based on the analyzed text, and a transmission unit means for sending personalized text information generated based on emotion to the user. This makes it possible to provide optimal content according to the user's emotions and to quickly convey information that meets individual needs.

[0694] A "user" is a person who uses a system to input information and receives feedback from it.

[0695] "Data" refers to text and other information entered by users, which forms the basis for analysis and processing within the system.

[0696] "Device" refers to a part of a system that includes hardware and software for receiving and processing data from a user.

[0697] The "analysis unit" is a means of analyzing the grammar and style of the received text to identify errors and areas for improvement.

[0698] A "generation mechanism" is a system component that uses analyzed text to correct grammar and style, and then generates improved content.

[0699] An "emotion engine" is a processing mechanism that estimates emotions from the content of the user's input text and performs optimizations that reflect that information.

[0700] The "transmission unit" is a means for sending the text information, which has been improved by the generation mechanism, to the user's terminal.

[0701] Personalization is the act of individually optimizing and delivering content based on each user's emotions and characteristics.

[0702] To implement this invention, a terminal on which users can input emotion-based information and a server that performs text analysis and generation are required. Users input text related to their emotions and intentions using a smartphone or computer.

[0703] Data entered from the terminal is received by a "device that receives user-entered data" on the server. The received data is then sent to an "analysis unit" where its grammar and style are analyzed. This analysis unit identifies and reports grammatical errors and stylistic problems within the data.

[0704] The analyzed data is modified grammatically and stylistically by a "generative mechanism," resulting in improved content. This generative mechanism includes a process of adjusting and improving the text data based on the analysis results.

[0705] Furthermore, an "emotion engine" within the server estimates the user's emotions from the analyzed text, and a generation mechanism creates optimized text based on this. This optimization process generates personalized content that aligns with the user's emotions.

[0706] The "transmission unit" returns the generated optimized text to the user's device and presents it to the user. This allows the user to receive content that matches their own emotions.

[0707] For example, if a user enters the text "I'm tired today" to express fatigue, the emotion engine recognizes this emotion, and the generation mechanism generates and sends relaxing text such as "Take a break and relax." An example of a prompt might be in the form of "Please enter words to express your current mood."

[0708] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0709] Step 1:

[0710] The user's device inputs text data related to emotions and intentions and sends it to the server. At this stage, the user uses a smartphone or computer to provide information to the system. The server accurately receives the text data and prepares it for the next analysis process.

[0711] Step 2:

[0712] The analysis unit on the server analyzes the grammar and style of the received text data. The input to the analysis unit is text data sent by the user, and it identifies grammatical errors and style issues based on this data. The analyzed data includes detailed comments on grammar and style, serving as a roadmap for correction. This process allows for a thorough examination of grammatical and style errors, clearly outlining the path to improvement.

[0713] Step 3:

[0714] The server passes the analyzed data to the generation mechanism for grammatical and stylistic corrections. The analysis results are provided as input, and the generation mechanism uses this data to generate proposed corrections. These corrections specifically reflect the improvements in grammar and style, resulting in the output of improved text data. This transforms the user's input into a more refined form.

[0715] Step 4:

[0716] The server's sentiment engine estimates the user's emotions from the analyzed text data, and based on this, the generation mechanism creates personalized content optimized for that emotion. The sentiment engine's input is the modified text data, and through sentiment analysis, it evaluates how the text relates to the user's emotions. Optimization is then performed based on the sentiment information, adjusting the content to suit the user.

[0717] Step 5:

[0718] The server sends the text data, improved by the generation mechanism, from the "transmitter" to the user's terminal. The input to the transmitter is optimized text, and the user receives this output. The user evaluates the content to see if it fits their emotions and makes further edits as needed. This completes a series of cycles, including a user guide prompt that includes an example of a prompt: "Please enter words to express how you are feeling right now."

[0719] 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.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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."

[0728] 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.

[0729] 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.

[0730] 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.

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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.

[0735] 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.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] The following is further disclosed regarding the embodiments described above.

[0741] (Claim 1)

[0742] A server means for receiving text data entered by a user,

[0743] An analysis module means for analyzing the grammar and style of received text data,

[0744] A generation engine means for correcting and improving grammar and style based on analyzed text data,

[0745] A transmission module means for sending corrected and improved text data to the user,

[0746] A system that includes this.

[0747] (Claim 2)

[0748] The system according to claim 1, wherein a generation engine that corrects grammar and style generates optimized correction candidates based on the user's profile data and presents them to the user.

[0749] (Claim 3)

[0750] The system according to claim 1, wherein the corrected and improved text data is presented to the terminal in a user-editable format.

[0751] "Example 1"

[0752] (Claim 1)

[0753] Information processing device means for receiving information entered by a user,

[0754] An analysis structure means for analyzing the grammar and expression style of received information,

[0755] Generative structure means for modifying and improving grammar and expression patterns based on analyzed information,

[0756] A communication structure means for sending corrected and improved information to the user,

[0757] A system that includes this.

[0758] (Claim 2)

[0759] The system according to claim 1, wherein a generative structure that modifies grammar and expression style generates optimized modification options based on the user's attribute data and presents them to the user.

[0760] (Claim 3)

[0761] The system according to claim 1, wherein the corrected and improved information is presented to the information input device in a user-editable format.

[0762] "Application Example 1"

[0763] (Claim 1)

[0764] Information processing device means for receiving character data entered by a user,

[0765] An analysis means for analyzing the grammar and format of received character data,

[0766] A generation mechanism means for correcting and improving grammar and form based on analyzed character data,

[0767] A communication means for sending corrected and improved character data to the user,

[0768] A tool that enables real-time correction suggestions for text data as product reviews,

[0769] A system that includes this.

[0770] (Claim 2)

[0771] The system according to claim 1, wherein a generation mechanism that corrects grammar and form generates optimized correction candidates based on the user's profile information and presents them to the user.

[0772] (Claim 3)

[0773] The system according to claim 1, wherein the corrected and improved character data is presented on a display device in a user-editable format.

[0774] "Example 2 of combining an emotion engine"

[0775] (Claim 1)

[0776] Information processing device means for receiving character data entered by a user,

[0777] An analysis device means for analyzing the syntax and format of received character data,

[0778] A data generation device means for modifying and improving syntax and style based on analyzed character data,

[0779] A sentiment analysis device means for evaluating the emotional state of text data,

[0780] A data generation device means that uses emotional information obtained from an emotion analysis device to create correction candidates suitable for the user's emotions,

[0781] Information transmission device means for sending corrected and improved character data to the user,

[0782] A system that includes this.

[0783] (Claim 2)

[0784] The system according to claim 1, wherein a data generation device that corrects syntax and style generates optimized correction candidates based on the user's emotional state and presents them to the user.

[0785] (Claim 3)

[0786] The system according to claim 1, wherein the corrected and improved character data is presented to an input / output device in a user-editable format.

[0787] "Application example 2 when combining with an emotional engine"

[0788] (Claim 1)

[0789] A device means for receiving data entered by a user,

[0790] An analysis unit means for analyzing the grammar and style of the received text,

[0791] Generative mechanism means for correcting and improving grammar and style based on analyzed text,

[0792] An emotion engine means that optimizes text content based on the user's emotions estimated by the analysis unit,

[0793] A transmission unit means that sends personalized text information generated based on emotions to the user,

[0794] A system that includes this.

[0795] (Claim 2)

[0796] The system according to claim 1, wherein a generation mechanism that corrects grammar and style generates optimized correction suggestions based on user characteristic data and presents them to the user.

[0797] (Claim 3)

[0798] The system according to claim 1, wherein corrected and improved text information is presented to the terminal in a user-editable format. [Explanation of symbols]

[0799] 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 server means for receiving text data entered by a user, An analysis module means for analyzing the grammar and style of received text data, A generation engine means for correcting and improving grammar and style based on analyzed text data, A transmission module means for sending corrected and improved text data to the user, A system that includes this.

2. The system according to claim 1, wherein a generation engine that corrects grammar and style generates optimized correction candidates based on the user's profile data and presents them to the user.

3. The system according to claim 1, wherein the corrected and improved text data is presented to the terminal in a user-editable format.

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