System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to upload a draft of an article; means for a server to receive and store the uploaded draft; means for the server to invoke a AI engine to perform grammar checking, detect grammar errors, and generate revision suggestions; means for the server to analyze the structure of the article and generate revision suggestions; means for the server to verify the accuracy and format of citations and generate revision suggestions; and means for the user to review and apply the received revision suggestions.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Academic researchers, graduate students, undergraduate students, and educators face significant challenges in the complexities of formatting and citation rules in academic papers, as well as maintaining consistency in writing style. This proofreading work can be a distraction from research activities, reducing the time researchers have to focus on the content of their papers. The present invention aims to address these challenges and significantly reduce the time and effort required for the proofreading process, allowing researchers to focus more on their research. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system comprising the following means: a means for a user to upload a paper draft from a terminal; a means for a server to receive and store the uploaded draft; a means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; a means for the server to analyze the paper structure and generate improvement suggestions; a means for the server to check the accuracy and format of citations and generate correction suggestions; a means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; and a means for the user to review and apply the improvement suggestions. The system also includes a means for the server to proofread a paper based on the format of a specific academic journal and generate suggestions, and a means for the server to send improvement suggestions to an email address associated with the user's account. This improves the quality of paper proofreading, allowing researchers to focus on their own research.

[0006] A "means" is a device, apparatus, method, or part of a system used to accomplish a particular purpose.

[0007] A "user" is an entity that utilizes the system to upload drafts of papers and receives, reviews, and applies improvement suggestions.

[0008] A "terminal" is an electronic device such as a computer, smartphone, or tablet that is used by a user to upload a draft of a paper or review improvement proposals.

[0009] The "server" is a device that receives and stores uploaded drafts, and uses an AI engine to perform grammar checks, structure checks, and citation checks, and also has the function of generating and sending improvement suggestions to the user.

[0010] A "draft" is an incomplete manuscript of a paper that a user creates and uploads to the system.

[0011] An "AI engine" is software or a system that uses artificial intelligence technology to check the grammar, structure, and citations of a paper and generate suggested revisions.

[0012] "Grammar errors" are grammatical errors present in the text of a paper and are detected by the AI ​​engine.

[0013] "Structure" refers to the arrangement and order of headings, paragraphs, sections, etc. within a paper, and affects the overall coherence and readability of the paper.

[0014] Citations are sections of a paper that refer to other documents or materials, and their accuracy and format are important.

[0015] "Format" refers to the particular form or rules that the citations and overall style of a paper must follow, for example, following the guidelines of a particular academic journal.

[0016] "Improvement Suggestions" are suggested corrections and advice on grammar, structure, and citations generated by the AI ​​engine, providing guidance for users to improve their drafts.

[0017] "Review" is the process in which the user checks and evaluates the improvement suggestions from the AI ​​engine.

[0018] "Application" refers to the process in which the user modifies the draft of the paper based on the improvement suggestions. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a 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.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0033] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention provides a system that allows a user to upload a draft of a paper, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the user. Specific embodiments for implementing the present invention are described in detail below.

[0041] System configuration

[0042] The system consists of three main components: users, devices, and a server. Users use their devices to upload drafts of their papers, receive suggestions for improvement, and review and revise them. The server receives and stores the uploaded drafts, checks grammar, structure, and citations using an AI engine, and generates suggestions for improvement and sends them to the users' devices.

[0043] Explanation of program processing

[0044] 1. User uploads a draft

[0045] Users log in to the system from their own devices, access the screen for uploading a paper draft, select a file, and click the upload button to send the draft to the server.

[0046] 2. The server receives the draft

[0047] The server receives the draft uploaded by the user, saves it in the specified directory, and checks the integrity of the file for proper processing.

[0048] 3. Grammar check by AI engine

[0049] The AI ​​engine in the server will then analyze the draft for grammatical errors, generating suggestions to correct, for example, the mistake "He go to the library." to "He goes to the library."

[0050] 4. Structure check using AI engine

[0051] The server's AI engine analyzes the structure of a paper (headings, paragraphs, sections, etc.) and checks the consistency of the entire paper. For example, if the introduction is too short, it will make suggestions such as, "The introduction is too short. We recommend adding more details."

[0052] 5. Citation check using AI engine

[0053] The server's AI engine inspects citations in a paper to ensure they comply with a specific citation style. For example, if a citation does not follow APA style, it will suggest, "Your citation format should be revised to APA style."

[0054] 6. Generate and submit improvement suggestions

[0055] The server generates improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's device. The improvement suggestions are sent to the email address associated with the user's account or displayed on the user's dashboard when they log in to the system.

[0056] 7. Review and apply user improvement suggestions

[0057] The user reviews the improvement suggestions sent by the server, revises the draft as necessary, and re-edits the paper based on the reviewed suggestions to complete the final version.

[0058] Specific examples

[0059] For example, suppose a user uploads a draft of a research paper to the system. The draft contains grammatical errors, inconsistent structure, and incomplete citations. The server first checks for these issues using an AI engine, correcting "He go to the library" to "He goes to the library," noting that the introduction is too short, and generating suggestions for correcting citations that do not conform to APA style. These suggestions are then sent to the user, who can review and apply them to improve the quality of their paper.

[0060] As described above, the system of the present invention automatically proofreads papers, allowing researchers time to concentrate on their research and is extremely useful in improving the quality of papers.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] A user uploads a draft of a paper using a terminal. The user opens a file selection screen, selects the draft file, and clicks the "Upload" button. This operation sends the draft file to the server.

[0064] Step 2:

[0065] The server saves the draft file received from the user in the specified directory, and checks the integrity of the file. After confirming that the file has been saved correctly, the server proceeds to the next processing step.

[0066] Step 3:

[0067] The server launches the AI ​​engine for grammar check. The server passes the saved draft file to the AI ​​engine, which analyzes it for grammatical errors. For example, it finds the sentence "He go to the library." and generates a suggestion to correct it to "He goes to the library."

[0068] Step 4:

[0069] The server uses an AI engine to check the structure of the paper. It analyzes the arrangement of headings, paragraphs, and sections in the draft to ensure consistency. For example, if the introduction is too short, it generates a suggestion that the introduction should be longer.

[0070] Step 5:

[0071] The server checks citations using an AI engine. It analyzes the citation format in the draft and checks whether it conforms to a specific citation style (e.g., APA style). If there are any deficiencies, it generates a suggestion to "revise the citation format to APA style."

[0072] Step 6:

[0073] The server generates improvement suggestions based on the results of the grammar, structure, and citation checks. Each suggestion is summarized in an easy-to-read report. The server prepares this report and moves on to the next step.

[0074] Step 7:

[0075] The server sends the generated improvement suggestions and reports to the user's device, either to the email address associated with the user's account or displayed on the dashboard when the user accesses the system.

[0076] Step 8:

[0077] The user reviews the improvement suggestions on their device. The user checks the received suggestions and modifies the draft as necessary. For example, they fix the problematic parts and add new content. Once the modifications are complete, the user saves the final version of the paper and, if necessary, uploads it back to the system.

[0078] The above is a specific processing flow in the system of the present invention.

[0079] Example 1

[0080] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0081] Conventional paper proofreading systems have the drawback of being time-consuming and labor-intensive, as they require manual checks of grammar, structure, and citations. Furthermore, they often fail to guarantee that proofreading conforms to a specific citation style or secure data transmission. Furthermore, the formats of improvement suggestions received by users are not standardized, making reviewing and applying them difficult.

[0082] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0083] In this invention, the server includes: a means for a user to upload a document draft from a terminal; a means for the server to receive and store the uploaded draft; a means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; a means for the server to analyze the document structure and generate improvement suggestions; a means for the server to check the accuracy and format of citations and generate correction suggestions; a means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; a means for the server to review and apply the improvement suggestions received by the user; a means for the server to use a hash function to verify integrity when receiving files; a means for the server to generate suggestions from the AI ​​engine in JSON format; a means for the server to securely transmit and receive data using the HTTPS protocol; and a means for the terminal to use editor software to review and apply the improvement suggestions. This enables automated and efficient paper proofreading, secure data transmission and reception, and the provision of unified improvement suggestions.

[0084] A "user" is a person who uploads draft documents from a terminal and has the role of reviewing and applying suggestions.

[0085] "Terminal" means an electronic device used by a User to access the System, upload document drafts, and receive and review improvement suggestions.

[0086] The "server" is a device that has the function of storing drafts received from users, checking grammar, structure, and citations, generating improvement suggestions, and sending them to the user's terminal.

[0087] A "document draft" is an incomplete document that a user uploads to the system and that is checked for grammar, structure, and citations.

[0088] "Grammar checking" is the process of detecting grammar errors in a document and generating appropriate correction suggestions.

[0089] "AI Engine" refers to the artificial intelligence models and algorithms used to review documents and generate suggestions.

[0090] "Document structure" refers to the hierarchical and logical arrangement of the document as a whole, including headings, paragraphs, sections, etc.

[0091] "Accuracy of citations" means that citations within a document are based on appropriate sources and are expressed accurately.

[0092] "Citation formatting" refers to the proper citations in a document following a particular formatting style (e.g., APA style).

[0093] "Improvement suggestions" are recommendations for correcting and improving a document, generated based on the results of checks on grammar, structure, citations, etc.

[0094] A "hash function" is an algorithm used to verify the integrity of a file, generating a fixed-length output value (hash value) from input data.

[0095] "JSON" is a lightweight data interchange format for representing data in text form and is used to generate and transmit proposals.

[0096] The "HTTPS protocol" is a protocol used to send and receive data securely over the Internet, and provides data encryption.

[0097] "Editor software" means application software that enables a user to create, edit, or modify documents.

[0098] The present invention relates to a system that allows users to upload drafts of their papers, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the users. Specific embodiments of the system are described below.

[0099] System configuration

[0100] The system consists of three main components: users, devices, and a server. Users use their devices to upload drafts of their papers, receive suggestions for improvement, and review and revise them. The server receives and stores the uploaded drafts, checks grammar, structure, and citations using an AI engine, and generates suggestions for improvement and sends them to the users' devices.

[0101] Hardware and software used

[0102] This system uses the following hardware and software:

[0103] Terminal: Electronic device (PC, tablet, smartphone, etc.) through which a user accesses the system

[0104] Server: The central computer that processes the data, stores the drafts, runs the AI ​​engine, and generates and sends proposals.

[0105] Software: The following software is used:

[0106] Web Browser: Used by users to access the system and upload drafts.

[0107] AI engine: Natural language processing libraries (e.g., spaCy or Grammarly API) and pre-trained models (e.g., BERT model)

[0108] Data transfer protocol: HTTPS protocol is used to encrypt and securely transmit data.

[0109] Data format: Improvement suggestions are generated in JSON format and sent to the user's device.

[0110] Detailed explanation of the process

[0111] First, a user logs in to the system using a web browser on their device and uploads a draft of their paper. The server receives the draft and saves it in a specified directory. At this time, the server verifies the integrity of the file using a hash function to confirm that the file has been received correctly.

[0112] The server then launches an AI engine to check the document's grammar. The AI ​​engine uses natural language processing libraries to detect grammatical errors and generate correction suggestions. Similarly, the AI ​​engine analyzes the document's structure, evaluating the consistency of headings, paragraphs, sections, etc., and generates improvement suggestions. In addition, the AI ​​engine checks the citation format to ensure it conforms to a specific citation style (e.g., APA style).

[0113] Finally, the server compiles improvement suggestions based on the results of these checks and sends them to the user's device. The user reviews the improvement suggestions and revise the draft using dedicated editor software. Finally, the user improves the document based on the suggestions and finalizes it.

[0114] Specific examples

[0115] For example, if a user uploads a draft of a research paper containing the grammatical error "He go to the library," the server will use an AI engine to generate suggestions to correct this sentence to "He goes to the library." Furthermore, if the introduction is too short, the server will suggest, "The introduction is short, so we recommend adding more details," and if the citations do not conform to APA style, the server will suggest, "The citation format should be corrected to APA style." These suggestions are sent to the user in JSON format, who can review and revise the draft.

[0116] Specific prompt examples:

[0117] 1. Grammar error: 'He go to the library.' should be 'He goes to the library.'

[0118] 2. Inconsistent structure: The introduction is short, so the suggestion is, "The introduction is short, so we recommend adding more details."

[0119] 3. Incorrect citation: The citation format does not conform to APA style, so the suggestion is that "the citation format should be corrected to APA style."

[0120] As described above, the system of the present invention automatically proofreads papers, allowing researchers time to concentrate on their research and is extremely useful in improving the quality of papers.

[0121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0122] Step 1:

[0123] A user uploads a draft of a paper

[0124] Input: The user uses the device's web browser to select a draft file of the paper (e.g., research paper.docx).

[0125] How it works: A user logs into the system, accesses the upload screen, selects a draft file, and clicks the upload button.

[0126] Output: The draft file is sent to the server.

[0127] Step 2:

[0128] The server receives and saves the draft

[0129] Input: Draft file submitted by user.

[0130] How it works: The server saves the received draft file in a specific directory, using a hash function to verify the integrity of the file.

[0131] Output: Draft files saved in a directory and their consistency check results.

[0132] Step 3:

[0133] The server checks the grammar using an AI engine

[0134] Input: Saved draft file.

[0135] How it works: The AI ​​engine on the server analyzes the document using natural language processing libraries (e.g., spaCy or Grammarly API). It detects grammatical errors in the draft and generates correction suggestions. For example, it generates a suggestion to change "He go to the library." to "He goes to the library."

[0136] Output: Grammar check results and suggested corrections.

[0137] Step 4:

[0138] The server checks the structure using an AI engine

[0139] Input: Saved draft file.

[0140] How it works: The server's AI engine uses trained models such as the BERT model to analyze the document structure (headings, paragraphs, sections, etc.) and check for consistency. For example, if the introduction is too short, it generates a suggestion such as "The introduction is short. We recommend adding more details."

[0141] Output: Results of the structure check and suggestions for improvement.

[0142] Step 5:

[0143] The server performs quote checking using an AI engine

[0144] Input: Saved draft file.

[0145] How it works: The server's AI engine uses rule-based NLP models and reference management software APIs (e.g., Zotero API) to check the accuracy of citation formatting. It checks whether the citation conforms to a specific citation style, such as APA style. For example, it generates a suggestion such as, "Your citation formatting should be corrected to APA style."

[0146] Output: Citation check results and suggested fixes.

[0147] Step 6:

[0148] The server generates and sends improvement suggestions

[0149] Input: Results of grammar checks, structure checks, and citation checks.

[0150] How it works: The server generates comprehensive improvement suggestions in JSON format based on the results of each check. The suggestions are sent to the user's device via HTTPS. When the user logs in to the system, the suggestions are displayed on the dashboard.

[0151] Output: Improvement suggestions sent to the user's device.

[0152] Step 7:

[0153] Users review and apply improvement suggestions

[0154] Input: Improvement suggestions sent by the server.

[0155] How it works: The user reviews the suggestions they receive and uses specialized editor software to revise the draft, for example by applying the provided grammar correction suggestions to revise the document.

[0156] Output: The modified draft file.

[0157] (Application example 1)

[0158] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0159] When content providers try to quickly generate high-quality documents, they face the problem of having to check grammar, structure, and citation formatting, which is time-consuming and laborious. It is also not easy to proofread documents to fit specific distribution formats. Therefore, there is a need for a method to efficiently proofread documents while maintaining the quality of the content.

[0160] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0161] In this invention, the server includes means for a user to upload a content draft from a terminal, means for the server to receive and store the uploaded draft, means for the server to call an AI engine for grammar check, detect grammatical errors, and generate correction suggestions, means for the server to analyze the structure of the content and generate improvement suggestions, means for the server to check the accuracy and format of citations and generate correction suggestions, means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal, and means for the user to review and apply the improvement suggestions received, thereby enabling content providers to efficiently create and distribute high-quality content.

[0162] Definitions of important words

[0163] "User" refers to the person who uploads draft content and receives suggested improvements for review and revision.

[0164] "Terminal" refers to a device used by a user to upload a content draft, and includes a smartphone, tablet, PC, etc.

[0165] "Server" means a central processing unit that receives and stores drafts of uploaded Content and performs grammar checks, structural analysis, and citation checks.

[0166] "AI engine" refers to a software system that uses artificial intelligence to detect grammatical errors and generate correction suggestions.

[0167] "Grammar checking" refers to the process of detecting grammatical errors in a content draft and making suggestions to fix them.

[0168] "Structural analysis" refers to the process of evaluating the logical organization of paragraphs, headings, sections, etc. throughout a content draft and making suggestions for improvement.

[0169] "Citation checking" refers to the process of reviewing citations in content for accuracy and formatting, and suggesting any necessary corrections.

[0170] "Improvement Suggestion" refers to a suggested revision of content that the server generates based on the results of grammar, structure, and citation checks and provides to the user.

[0171] "Distribution format" refers to the format or style required for a particular distribution channel or platform.

[0172] MODE FOR CARRYING OUT THE INVENTION

[0173] The present invention provides a system that allows users to upload drafts of content from devices such as smartphones, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the user. Specific embodiments for implementing the present invention are described in detail below.

[0174] System configuration

[0175] The system includes the following components:

[0176] 1. User Device

[0177] A device used by a user, such as a smartphone, tablet, or PC, that is used to upload drafts and review improvement suggestions.

[0178] 2. Server

[0179] The server is a central processing unit that receives and stores uploaded drafts and checks them for grammar, structure, and citations using an AI engine. The server runs using Python and natural language processing libraries (e.g., NLTK, TensorFlow).

[0180] 3. AI Engine

[0181] The AI ​​engine is a software system for grammar error detection, structural analysis, and citation checking, which generates suggestions for correcting grammatical errors and improving structure and citations.

[0182] Explanation of program processing

[0183] 1. User uploads draft content

[0184] Users log in to the system from their own devices, access the screen for uploading draft content, select a file, and click the upload button to send the draft to the server.

[0185] 2. The server receives the draft

[0186] The server receives the draft uploaded by the user, saves it in the specified directory, and checks the integrity of the file for proper processing.

[0187] 3. Grammar, structure, and citation checks using an AI engine

[0188] The AI ​​engine on the server starts up and first performs grammatical analysis. Then it analyzes the overall structure of the content (paragraphs, headings, etc.), and finally checks the citation style. For example, it generates a suggestion to correct the mistake "He go to the library" to "He goes to the library." In terms of structure, if the introduction is short, it will suggest "We recommend adding more detail to the introduction." Also, if the citation does not follow a specific style, it will point out that "the citation format needs to be corrected."

[0189] 4. Generate and submit improvement suggestions

[0190] The server generates improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's device. The improvement suggestions are sent to the contact information associated with the user's account or displayed on the user's dashboard when they log in to the system.

[0191] Specific examples

[0192] Suppose a user uploads a draft of a blog post to the system. The draft contains grammatical errors, inconsistent structure, and incomplete citations. The server first checks for these problems using an AI engine. Specifically, it generates suggestions to correct "He go to the library." to "He goes to the library.", suggests adding more detail to the short introduction, and further suggests correcting parts of the citation that do not comply with the syndication format. These suggestions are then sent to the user, who can review and apply them to improve the quality of the content.

[0193] Prompt Sentence Examples

[0194] Check the grammar, structure, and citations of blog posts uploaded by users and generate improvement suggestions as follows:

[0195] Grammar error: Change "He go to the library." to "He goes to the library."

[0196] Poor structure: "The introduction is short, so I suggest adding more details."

[0197] Incorrect citation: "Please correct your citation format."

[0198] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0199] Program processing flow

[0200] Step 1:

[0201] The user uploads a draft of content from the terminal. The input is the draft file specified by the user, and the output is the terminal sending the draft file to the server. When the user clicks the upload button, the draft file is sent from the terminal to the server.

[0202] Step 2:

[0203] The server receives the uploaded draft and saves it in the specified directory. The input is the draft file sent by the user, and the output is the draft file to be saved. The server first verifies the integrity of the draft file and saves it in the appropriate directory.

[0204] Step 3:

[0205] The server invokes the AI ​​engine to perform grammatical analysis of the draft. The input is the saved draft file, and the output is the results of grammatical error detection. The server inputs the saved draft file into the AI ​​engine and detects grammatical errors using a natural language processing library (NLTK). It generates a suggestion to correct the mistake "He go to the library." to "He goes to the library."

[0206] Step 4:

[0207] The server uses an AI engine to analyze the structure of the draft. The input is the saved draft file, and the output is structural improvement suggestions. The server evaluates the structure of the draft, including paragraphs, headings, and sections, to ensure consistency. For example, if the introduction is short, the server will make a suggestion such as, "We recommend adding more detail to the introduction."

[0208] Step 5:

[0209] The server uses an AI engine to check the citations in the draft. The input is the saved draft file, and the output is suggestions for correcting the citations and formatting. The server inspects the citations in the draft to ensure they conform to a specific style (e.g., APA style). If the citations do not follow the style, it suggests, "Your citation format needs to be revised."

[0210] Step 6:

[0211] The server generates improvement suggestions based on the results of each grammar, structure, and citation check and sends them to the user's device. The input is the check results from the AI ​​engine, and the output is the generated improvement suggestions. The server integrates the results of each check and generates improvement suggestions. These suggestions are then sent to the user's device and displayed on the dashboard or sent to the corresponding contact.

[0212] Step 7:

[0213] The user reviews and applies the improvement suggestions received. The input is the improvement suggestions sent from the server, and the output is the revised draft. The user checks the improvement suggestions on the terminal, adds necessary corrections to the draft, and re-edits it.

[0214] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0215] The present invention combines an emotion engine with a system for automatically proofreading a paper draft. This allows the system to recognize the user's emotional state and adjust the interface and the method of presenting improvement suggestions based on that state. Specific embodiments for implementing the present invention are described below.

[0216] System configuration

[0217] The system consists of four main components: the user, the device, the server, and the emotion engine. Users upload drafts of their papers via their devices, and the emotion engine recognizes their emotional state in real time. The server stores the received drafts and uses an AI engine to check grammar, structure, and citations, generating improvement suggestions. The emotion engine adjusts the interface and generates feedback messages based on the user's emotional data.

[0218] Explanation of program processing

[0219] 1. User uploads a draft

[0220] Using the terminal, the user selects the draft file from the file selection screen and clicks the upload button, which sends the file to the server.

[0221] During this process, the emotion engine analyzes the user's facial expressions and voice to recognize their current emotional state in real time.

[0222] 2. The server receives the draft

[0223] The server stores the uploaded draft and verifies the integrity of the file.

[0224] The emotion engine transmits the acquired emotion data to the server, which then stores the data.

[0225] 3. Grammar check by AI engine

[0226] The server's AI engine analyzes the draft for grammatical errors and generates correction suggestions.

[0227] The emotion engine adjusts the way suggestions are worded based on the user's emotional state, for example, using gentler language if the user is stressed.

[0228] 4. Structure check using AI engine

[0229] The server uses an AI engine to analyze the structure of the paper and generate suggestions regarding consistency and logic.

[0230] If the emotion engine determines that the user is tired, it will provide a concise summary of suggestions.

[0231] 5. Citation check using AI engine

[0232] The server's AI engine checks the citation format and generates appropriate correction suggestions.

[0233] The system adjusts which correction suggestions are given priority depending on the user's emotional state.

[0234] 6. Generate and submit improvement suggestions

[0235] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks, adjusting the wording and order of the suggestions taking into account data from the sentiment engine.

[0236] The final improvement proposals are sent to the user's device via the method selected by the user (email or dashboard display).

[0237] 7. Review and apply user improvement suggestions

[0238] The user receives and reviews the improvement suggestions via their device, while the emotion engine continues to monitor the user's emotional state and displays support messages as needed.

[0239] The user applies the suggested corrections and re-edits the draft, and the emotion engine supports the user in completing the final version while reducing stress.

[0240] Specific examples

[0241] Suppose a user uploads a draft of a research paper to the system. If the emotion engine detects that the user is nervous, it displays the message, "Relax and proceed. We'll help you." The server receives the draft and checks its grammar, structure, and citations. The engine finds an error in the sentence, "He go to the library." It generates a suggestion to correct it to, "He goes to the library." If the user is feeling even more fatigued, the suggestion is simplified and a simple suggestion such as, "The introduction is short, please add more details."

[0242] In this way, the system of the present invention automatically proofreads papers while taking into account the user's emotional state and provides optimal suggestions for improvement, helping researchers to write higher quality papers without feeling stressed.

[0243] The processing flow will be explained below.

[0244] Step 1:

[0245] The user uploads a draft of their paper using their device. They open a file selection screen and select the draft file. Then, by clicking the upload button, the selected file is sent to the server. At the same time, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their current emotional state.

[0246] Step 2:

[0247] The server saves the draft file received from the user in the specified directory and verifies the integrity of the file. After the file is saved correctly, the server saves the emotion data and proceeds to the next processing step.

[0248] Step 3:

[0249] The server launches the AI ​​engine to check grammar. The AI ​​engine reads the saved draft file and analyzes grammatical errors. For example, it finds the mistake "He go to the library." and generates a suggestion to correct it to "He goes to the library." If the emotion engine detects the user's stress, the AI ​​engine's output will use gentler expressions.

[0250] Step 4:

[0251] The server uses an AI engine to analyze the structure of the paper. It analyzes the arrangement of headings, paragraphs, and sections in the saved draft and checks for consistency. For example, it generates suggestions such as, "The introduction is short, so we recommend adding more details." If the emotion engine determines that the user is tired, it will display a concise summary of the suggestions.

[0252] Step 5:

[0253] The server uses an AI engine to check the accuracy and format of citations. It analyzes the citation format in the draft and checks whether it conforms to a specific citation style (e.g., APA style). If there are any deficiencies, it generates suggestions such as "Please revise the citation format to APA style." It prioritizes important revision suggestions based on the emotional state of the author.

[0254] Step 6:

[0255] The server generates improvement suggestions based on the results of grammar, structure, and citation checks. Each suggestion is summarized in an easy-to-read report. The wording and order of suggestions are adjusted taking into account data from the sentiment engine. If a user expressed negative sentiment during upload, subsequent suggestions may include encouraging content.

[0256] Step 7:

[0257] The server sends the generated improvement proposals and reports to the user's device either via email address associated with the user's account or displayed on the user's dashboard when they log in to the system. The tone of the proposals and the content of the message are adapted based on the emotional data.

[0258] Step 8:

[0259] The user reviews the improvement suggestions on their device. They confirm the suggestions and revise the draft based on them. The emotion engine monitors the user's emotional state during the review and displays encouraging or supportive messages as needed. For example, if the user is confused, the engine displays a message such as, "Don't worry, we'll provide advice as needed."

[0260] The above is a specific processing flow in the system of the present invention.

[0261] Example 2

[0262] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0263] While conventional paper proofreading systems can check grammar and structure, they have a problem in that they cannot make suggestions that take into account the user's emotional state. This causes problems such as users feeling stressed during the proofreading process and not being able to effectively utilize the suggestions for improvement.

[0264] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0265] In this invention, the server includes means for an emotion engine to recognize a user's emotion in real time and transmit that data to the server, means for the emotion engine to adjust the expression method and order of improvement suggestions based on the user's emotion data, and means for the server to generate comprehensive improvement suggestions based on the results of grammar, structure, and citation checks and transmit them to the user's terminal. This makes it possible to provide optimal improvement suggestions that take the user's emotional state into consideration.

[0266] "User" means any person or entity that uses the System to upload drafts of papers and receive suggestions for improvement.

[0267] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet.

[0268] "Server" means a remote computer that receives and stores uploaded drafts, performs various checks, and generates and submits improvement suggestions.

[0269] An "emotion engine" is software or hardware that analyzes a user's facial expressions and voice in real time to recognize their emotional state.

[0270] An "AI engine" is an artificial intelligence program that checks grammar, structure, and citations and generates suggestions for improvement.

[0271] "Grammar check" refers to the process of detecting grammatical errors in an uploaded draft and making correction suggestions.

[0272] A "structural check" is a process of analyzing the overall structure and logic of a paper and making suggestions for improvement regarding consistency and points of argument.

[0273] "Citation checking" is the process of verifying that citations in a paper are accurate and follow proper formatting, and making suggested revisions.

[0274] "Improvement Suggestions" are suggestions for improving the quality of a user's draft, generated based on the results of grammar, structure, and citation checks.

[0275] An "email address" is one of the communication methods associated with a user's account, and is an address used to receive information such as improvement suggestions.

[0276] The present invention is a system that allows users to upload a draft of a paper and receive optimal improvement suggestions using automatic proofreading and an emotion engine. Specific embodiments will be described step by step below.

[0277] Hardware and software used

[0278] User devices: computers, smartphones, tablets, etc. Through these devices, users upload drafts and view improvement suggestions.

[0279] Server: A remote computer that stores drafts, analyzes them, and generates improvement suggestions.

[0280] Emotion engine: Software or hardware that analyzes a user's facial expressions and voice in real time to recognize their emotional state. Examples include facial recognition technology and voice analysis technology.

[0281] AI Engine: An artificial intelligence program that checks grammar, structure, and citations. Examples include grammar analysis tools (e.g., Grammarly API) and machine learning models (e.g., BERT, GPT-3).

[0282] Data processing and calculation

[0283] User uploads draft

[0284] The user selects a draft of the paper from the device and uploads it to the server, which then transmits the data to the server using HTTP or HTTPS protocols.

[0285] The server receives and saves the draft

[0286] The server receives and stores the uploaded drafts, checking the integrity of the files and saving them in the appropriate folders.

[0287] Emotion recognition by emotion engine

[0288] The emotion engine analyzes the user's facial expressions and voice in real time to generate emotion data, which is then sent to a server via a REST API or similar and stored.

[0289] Grammar check by AI engine

[0290] The server passes the saved draft to an AI engine that analyzes it for grammatical errors. It uses grammar analysis tools to list the mistakes and suggest corrections.

[0291] Structural check using AI engine

[0292] The AI ​​engine analyzes the structure of a paper and generates suggestions for consistency and logic. For example, if a paragraph is unnaturally connected, it will suggest, "Merge this paragraph with the previous one."

[0293] Citation check by AI engine

[0294] The server uses an AI engine to check whether the citation format is correct and generate suggestions for corrections, such as "Please correct the citation according to APA style."

[0295] Generate comprehensive improvement suggestions

[0296] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks. It adjusts the wording and order of the suggestions based on data from the emotion engine. For example, it uses gentler wording when the user is feeling stressed.

[0297] Submit an improvement suggestion

[0298] The server sends the generated improvement suggestions to the user's device, either via email or as a dashboard display.

[0299] Review and apply user improvement suggestions

[0300] The user can review the improvement suggestions received through their device and apply any necessary corrections. The emotion engine also monitors the user's emotional state and displays supportive messages such as "Please stay calm and proceed."

[0301] Specific examples

[0302] A user uploads a draft of a research paper to the system. If the emotion engine detects that the user is nervous, it may display the message, "Relax and proceed. We'll help you." The server receives the draft and checks it for grammar, structure, and citations. The engine finds the error, "He go to the library." It generates a suggestion to correct it to, "He goes to the library." Furthermore, if the user is feeling fatigued, the suggestion may be simplified, with a simple suggestion such as, "The introduction is short; please add more detail."

[0303] Prompt Sentence Examples

[0304] "Generate timely emotional support messages for stressed users who upload their paper drafts."

[0305] "Write a concise suggestion for improving the paper structure for a user who is experiencing fatigue."

[0306] In this way, this system automatically proofreads papers while taking into account the user's emotional state and provides optimal improvement suggestions, thereby improving the quality of papers while reducing user stress.

[0307] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0308] Step 1:

[0309] User uploads draft

[0310] Input: The user selects the paper draft (e.g., a text file) on the file selection screen of the terminal and clicks the upload button.

[0311] Processing: The terminal sends the user's selected draft file to the server using HTTP or HTTPS protocol.

[0312] Output: A draft file is sent to the server.

[0313] Step 2:

[0314] The server receives and saves the draft

[0315] Input: The server receives the draft file sent from the terminal.

[0316] Processing: Saving the received file in a specific folder and checking the file integrity, for example, whether the file is corrupted and whether it was transferred completely.

[0317] Output: The draft file is saved on the server.

[0318] Step 3:

[0319] The emotion engine recognizes the user's emotions in real time and sends them to the server.

[0320] Input: Facial and voice data when users upload their drafts.

[0321] Processing: The emotion engine uses facial expression recognition software and voice analysis tools to analyze the user's emotional state in real time. The analysis results are converted into data and sent to a server using a REST API or similar.

[0322] Output: The user's emotional data (e.g., tension, stress, fatigue, etc.) is sent to the server.

[0323] Step 4:

[0324] The server's AI engine starts grammar checking

[0325] Input: Draft file saved on the server.

[0326] Processing: The server calls a grammar analysis tool (e.g., Grammarly API) to analyze the draft for grammar errors. It detects grammar errors and generates correction suggestions for each one.

[0327] Output: A list of grammar errors and suggested fixes for them.

[0328] Step 5:

[0329] The server's AI engine begins structure checks

[0330] Input: Draft file saved on the server.

[0331] Processing: The AI ​​engine analyzes the overall structure of the draft and generates suggestions for improvement regarding consistency and logic. For example, if a paragraph is not connected properly, it will suggest, "Merge this paragraph with the previous one."

[0332] Output: A list of structural errors and suggestions for improving them.

[0333] Step 6:

[0334] The server's AI engine starts checking quotes

[0335] Input: Draft file saved on the server.

[0336] Processing: The AI ​​engine analyzes the citations in the draft, checking whether they follow the proper formatting and generating correction suggestions if there are any deficiencies.

[0337] Output: A list of citation errors and suggested fixes.

[0338] Step 7:

[0339] Generate comprehensive improvement suggestions

[0340] Input: The results of grammar, structure, and citation checks, as well as user sentiment data sent from the sentiment engine.

[0341] Processing: The server integrates the results of each check and adjusts the wording and order of the improvement suggestions based on the emotional data. For example, if the user is feeling stressed, the suggestions will be presented in a gentler way and in an order that will reduce the burden.

[0342] Output: Comprehensive improvement suggestions.

[0343] Step 8:

[0344] The server sends improvement suggestions to the user's device

[0345] Input: Overall improvement suggestions.

[0346] Processing: The server sends the generated improvement suggestions to the user's email address or dashboard.

[0347] Output: Improvement suggestions that can be viewed on the user's device.

[0348] Step 9:

[0349] Review and apply user improvement suggestions

[0350] Input: Improvement suggestions received from the server.

[0351] Processing: The user reviews the received improvement suggestions and applies them to the draft if necessary. The emotion engine continues to monitor the user's emotional state and displays supportive messages such as "Keep calm and proceed."

[0352] Output: A draft with the corrections applied.

[0353] (Application example 2)

[0354] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0355] In production sites such as factories, employees are required to work efficiently while avoiding excessive stress and fatigue. However, current technology makes it difficult to monitor employees' emotional states in real time and provide appropriate feedback and improvement suggestions accordingly. In addition, there is a lack of means to adjust work suggestions based on employees' emotional states, making it difficult to improve work efficiency while managing employee stress.

[0356] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0357] In this invention, the server includes: means for a user to upload a draft of a paper from a terminal; means for the server to receive and store the uploaded draft; means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; means for the server to analyze the structure of the paper and generate improvement suggestions; means for the server to check the accuracy and format of citations and generate correction suggestions; means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; means for the user to review and apply the improvement suggestions received; means for recognizing the user's emotional state using an emotion engine and adjusting the interface and the expression method of the suggestions based on that state; means for monitoring work progress in real time and generating feedback messages based on the emotion engine; and means for adjusting the priority and expression method of the improvement suggestions based on the emotional state. This makes it possible to provide appropriate feedback and improvement suggestions in real time that take into account the emotional state of employees, thereby improving work efficiency and managing stress at the same time.

[0358] "User" refers to a person who uses the system to upload a draft paper and receive suggestions for improvement.

[0359] "Terminal" refers to the device used by a User to upload a draft of their paper.

[0360] "Server" refers to a centralized computer system that receives and stores drafts uploaded by users and performs various analyses.

[0361] "AI Engine" refers to an artificial intelligence system installed on a server that detects grammatical errors and generates correction suggestions.

[0362] An "emotion engine" is a system that recognizes a user's emotional state in real time and adjusts the interface and presentation of suggestions based on that data.

[0363] "Grammar check" refers to the AI ​​engine's process of analyzing the sentence structure in the draft, detecting grammatical errors, and suggesting corrections.

[0364] "Structure" refers to the organization, arrangement, and development of paragraphs of an entire paper or document.

[0365] "Citations" refer to references within a paper to other studies or sources.

[0366] "Interface" refers to the operation screen and display method that allows users to interact with the system.

[0367] "Feedback message" refers to a message that the emotion engine generates based on the user's emotional state to support the progress of work and mood.

[0368] "Real-time monitoring" refers to instantly monitoring the progress of work and the user's emotional state, and responding immediately if necessary.

[0369] "Improvement suggestions" refer to corrections and suggestions regarding grammar, structure, citations, etc. that the AI ​​engine generates based on the analysis results.

[0370] This invention relates to a system that improves the work efficiency and mental health of employees in factory production. The system consists of four main components: smart glasses worn by the user, a server, an AI engine, and an emotion engine.

[0371] System configuration

[0372] 1. Users

[0373] The user is a factory worker who wears smart glasses to perform his / her work. The smart glasses are equipped with a camera, a display, and a network module.

[0374] 2. Smart Glasses

[0375] The smart glasses are equipped with a camera that captures the user's facial expressions and work status in real time. The emotion engine analyzes the user's emotional state and sends the results to the server. Feedback messages and improvement suggestions from the server are displayed on the display.

[0376] 3. Server

[0377] The server is the main hub for the following operations:

[0378] Receive and store data uploaded by users.

[0379] An AI engine is used to perform grammar checks, structural analysis, and citation verification.

[0380] Use data from the emotion engine to tailor the wording of feedback messages and improvement suggestions.

[0381] The server is expected to be built on a general cloud computing environment (for example, AWS or Google Cloud Platform).

[0382] 4. AI Engine

[0383] The AI ​​engine is equipped with the technology to perform the following processes:

[0384] Grammar Check: Uses NLP (Natural Language Processing) techniques to detect grammatical errors and generate correction suggestions.

[0385] Structural analysis: Analyze the organization of an entire paper or document and generate improvement suggestions.

[0386] Citation Check: Checks the accuracy and format of citations in your paper and generates suggested revisions.

[0387] The AI ​​engine is developed using technologies such as TensorFlow and OpenCV.

[0388] 5. Emotion Engine

[0389] The emotion engine recognizes the user's emotional state and adjusts the presentation of the interface and suggestions based on that state.

[0390] Emotion analysis: Analyzes the user's facial expression data captured from the smart glasses camera to assess their emotional state.

[0391] Feedback generation: Generate appropriate feedback messages for users based on emotion data.

[0392] The emotion engine is built using, for example, the Affdex SDK.

[0393] Specific examples

[0394] Suppose an employee is performing assembly work. If the emotion engine recognizes the employee's fatigue, the smart glasses will display a message saying, "Please take a short break." If the AI ​​engine detects a mistake in the work, the smart glasses will display a suggestion saying, "The screws appear to be loose. Please check them again." In this way, the system of the present invention can provide appropriate feedback and improvement suggestions in real time, taking into account the employee's emotional state.

[0395] Prompt Sentence Examples

[0396] Desired function: Support for assembly work in factories

[0397] Main features: Real-time monitoring of work content, recognition of emotional state, and provision of improvement suggestions

[0398] Technologies used: Sentiment analysis with Affdex SDK, working analysis with TensorFlow and OpenCV

[0399] Input data: facial expression data of employees, video data of their work

[0400] Output data: Feedback messages, improvement suggestions

[0401] Targeted effects: Improved work efficiency and quality, reduced employee stress

[0402] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0403] Step 1: User puts on smart glasses

[0404] A user puts on smart glasses to start work in the factory. The camera in the smart glasses captures the user's facial expressions and work status in real time. The input is the user's facial expression data and work video data, and the output is that these data are sent to the server.

[0405] Step 2: Emotional state analysis by the emotion engine

[0406] The server receives the facial expression data sent from the smart glasses. The emotion engine then analyzes it and evaluates the user's emotional state (e.g., fatigue, stress, or relaxation). The input is the facial expression data, and the output is the evaluation result of the emotional state. The emotion engine uses the Affdex SDK to analyze the facial expression data.

[0407] Step 3: Real-time operation monitoring

[0408] The server receives video data of the work sent from the smart glasses. The AI ​​engine analyzes the video data to check the progress of the work and detect errors and areas for improvement. The input is the video data, and the output is the work status and error detection results. The AI ​​engine performs analysis using TensorFlow and OpenCV.

[0409] Step 4: Generate feedback and improvement suggestions

[0410] The server integrates the emotional state evaluation results from the emotion engine and the work situation analysis results from the AI ​​engine. Then, based on the emotional state, it generates appropriate feedback messages and improvement suggestions for the user. The inputs are the emotional state evaluation results and the work situation analysis results, and the output is the feedback messages and improvement suggestions.

[0411] Step 5: Viewing feedback messages

[0412] The server sends the generated feedback messages and improvement suggestions to the smart glasses display. The user receives this feedback in real time and improves their work. The input is the feedback messages and improvement suggestions, and the output is the feedback displayed on the smart glasses display.

[0413] Step 6: User improvement and data feedback

[0414] The user improves their work based on the feedback from the smart glasses. The improved work data is again captured by the smart glasses' camera and sent to the server. The input is the improved work data, and the output is the data sent to the server. This feedback loop ensures that the latest data is always analyzed, leading to continuous work improvement.

[0415] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0416] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0417] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0418] [Second embodiment]

[0419] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0420] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0421] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0422] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0423] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0424] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0425] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0426] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0427] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0428] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0429] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0430] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0431] The present invention provides a system that allows a user to upload a draft of a paper, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the user. Specific embodiments for implementing the present invention are described in detail below.

[0432] System configuration

[0433] The system consists of three main components: users, devices, and a server. Users use their devices to upload drafts of their papers, receive suggestions for improvement, and review and revise them. The server receives and stores the uploaded drafts, checks grammar, structure, and citations using an AI engine, and generates suggestions for improvement and sends them to the users' devices.

[0434] Explanation of program processing

[0435] 1. User uploads a draft

[0436] Users log in to the system from their own devices, access the screen for uploading a paper draft, select a file, and click the upload button to send the draft to the server.

[0437] 2. The server receives the draft

[0438] The server receives the draft uploaded by the user, saves it in the specified directory, and checks the integrity of the file for proper processing.

[0439] 3. Grammar check by AI engine

[0440] The AI ​​engine in the server will then analyze the draft for grammatical errors, generating suggestions to correct, for example, the mistake "He go to the library." to "He goes to the library."

[0441] 4. Structure check using AI engine

[0442] The server's AI engine analyzes the structure of a paper (headings, paragraphs, sections, etc.) and checks the consistency of the entire paper. For example, if the introduction is too short, it will make suggestions such as, "The introduction is too short. We recommend adding more details."

[0443] 5. Citation check using AI engine

[0444] The server's AI engine inspects citations in a paper to ensure they comply with a specific citation style. For example, if a citation does not follow APA style, it will suggest, "Your citation format should be revised to APA style."

[0445] 6. Generate and submit improvement suggestions

[0446] The server generates improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's device. The improvement suggestions are sent to the email address associated with the user's account or displayed on the user's dashboard when they log in to the system.

[0447] 7. Review and apply user improvement suggestions

[0448] The user reviews the improvement suggestions sent by the server, revises the draft as necessary, and re-edits the paper based on the reviewed suggestions to complete the final version.

[0449] Specific examples

[0450] For example, suppose a user uploads a draft of a research paper to the system. The draft contains grammatical errors, inconsistent structure, and incomplete citations. The server first checks for these issues using an AI engine, correcting "He go to the library" to "He goes to the library," noting that the introduction is too short, and generating suggestions for correcting citations that do not conform to APA style. These suggestions are then sent to the user, who can review and apply them to improve the quality of their paper.

[0451] As described above, the system of the present invention automatically proofreads papers, allowing researchers time to concentrate on their research and is extremely useful in improving the quality of papers.

[0452] The processing flow will be explained below.

[0453] Step 1:

[0454] A user uploads a draft of a paper using a terminal. The user opens a file selection screen, selects the draft file, and clicks the "Upload" button. This operation sends the draft file to the server.

[0455] Step 2:

[0456] The server saves the draft file received from the user in the specified directory, and checks the integrity of the file. After confirming that the file has been saved correctly, the server proceeds to the next processing step.

[0457] Step 3:

[0458] The server launches the AI ​​engine for grammar check. The server passes the saved draft file to the AI ​​engine, which analyzes it for grammatical errors. For example, it finds the sentence "He go to the library." and generates a suggestion to correct it to "He goes to the library."

[0459] Step 4:

[0460] The server uses an AI engine to check the structure of the paper. It analyzes the arrangement of headings, paragraphs, and sections in the draft to ensure consistency. For example, if the introduction is too short, it generates a suggestion that the introduction should be longer.

[0461] Step 5:

[0462] The server checks citations using an AI engine. It analyzes the citation format in the draft and checks whether it conforms to a specific citation style (e.g., APA style). If there are any deficiencies, it generates a suggestion to "revise the citation format to APA style."

[0463] Step 6:

[0464] The server generates improvement suggestions based on the results of the grammar, structure, and citation checks. Each suggestion is summarized in an easy-to-read report. The server prepares this report and moves on to the next step.

[0465] Step 7:

[0466] The server sends the generated improvement suggestions and reports to the user's device, either to the email address associated with the user's account or displayed on the dashboard when the user accesses the system.

[0467] Step 8:

[0468] The user reviews the improvement suggestions on their device. The user checks the received suggestions and modifies the draft as necessary. For example, they fix the problematic parts and add new content. Once the modifications are complete, the user saves the final version of the paper and, if necessary, uploads it back to the system.

[0469] The above is a specific processing flow in the system of the present invention.

[0470] Example 1

[0471] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0472] Conventional paper proofreading systems have the drawback of being time-consuming and labor-intensive, as they require manual checks of grammar, structure, and citations. Furthermore, they often fail to guarantee that proofreading conforms to a specific citation style or secure data transmission. Furthermore, the formats of improvement suggestions received by users are not standardized, making reviewing and applying them difficult.

[0473] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0474] In this invention, the server includes: a means for a user to upload a document draft from a terminal; a means for the server to receive and store the uploaded draft; a means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; a means for the server to analyze the document structure and generate improvement suggestions; a means for the server to check the accuracy and format of citations and generate correction suggestions; a means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; a means for the server to review and apply the improvement suggestions received by the user; a means for the server to use a hash function to verify integrity when receiving files; a means for the server to generate suggestions from the AI ​​engine in JSON format; a means for the server to securely transmit and receive data using the HTTPS protocol; and a means for the terminal to use editor software to review and apply the improvement suggestions. This enables automated and efficient paper proofreading, secure data transmission and reception, and the provision of unified improvement suggestions.

[0475] A "user" is a person who uploads draft documents from a terminal and has the role of reviewing and applying suggestions.

[0476] "Terminal" means an electronic device used by a User to access the System, upload document drafts, and receive and review improvement suggestions.

[0477] The "server" is a device that has the function of storing drafts received from users, checking grammar, structure, and citations, generating improvement suggestions, and sending them to the user's terminal.

[0478] A "document draft" is an incomplete document that a user uploads to the system and that is checked for grammar, structure, and citations.

[0479] "Grammar checking" is the process of detecting grammar errors in a document and generating appropriate correction suggestions.

[0480] "AI Engine" refers to the artificial intelligence models and algorithms used to review documents and generate suggestions.

[0481] "Document structure" refers to the hierarchical and logical arrangement of the document as a whole, including headings, paragraphs, sections, etc.

[0482] "Accuracy of citations" means that citations within a document are based on appropriate sources and are expressed accurately.

[0483] "Citation formatting" refers to the proper citations in a document following a particular formatting style (e.g., APA style).

[0484] "Improvement suggestions" are recommendations for correcting and improving a document, generated based on the results of checks on grammar, structure, citations, etc.

[0485] A "hash function" is an algorithm used to verify the integrity of a file, generating a fixed-length output value (hash value) from input data.

[0486] "JSON" is a lightweight data interchange format for representing data in text form and is used to generate and transmit proposals.

[0487] The "HTTPS protocol" is a protocol used to send and receive data securely over the Internet, and provides data encryption.

[0488] "Editor software" means application software that enables a user to create, edit, or modify documents.

[0489] The present invention relates to a system that allows users to upload drafts of their papers, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the users. Specific embodiments of the system are described below.

[0490] System configuration

[0491] The system consists of three main components: users, devices, and a server. Users use their devices to upload drafts of their papers, receive suggestions for improvement, and review and revise them. The server receives and stores the uploaded drafts, checks grammar, structure, and citations using an AI engine, and generates suggestions for improvement and sends them to the users' devices.

[0492] Hardware and software used

[0493] This system uses the following hardware and software:

[0494] Terminal: Electronic device (PC, tablet, smartphone, etc.) through which a user accesses the system

[0495] Server: The central computer that processes the data, stores the drafts, runs the AI ​​engine, and generates and sends proposals.

[0496] Software: The following software is used:

[0497] Web Browser: Used by users to access the system and upload drafts.

[0498] AI engine: Natural language processing libraries (e.g., spaCy or Grammarly API) and pre-trained models (e.g., BERT model)

[0499] Data transfer protocol: HTTPS protocol is used to encrypt and securely transmit data.

[0500] Data format: Improvement suggestions are generated in JSON format and sent to the user's device.

[0501] Detailed explanation of the process

[0502] First, a user logs in to the system using a web browser on their device and uploads a draft of their paper. The server receives the draft and saves it in a specified directory. At this time, the server verifies the integrity of the file using a hash function to confirm that the file has been received correctly.

[0503] The server then launches an AI engine to check the document's grammar. The AI ​​engine uses natural language processing libraries to detect grammatical errors and generate correction suggestions. Similarly, the AI ​​engine analyzes the document's structure, evaluating the consistency of headings, paragraphs, sections, etc., and generates improvement suggestions. In addition, the AI ​​engine checks the citation format to ensure it conforms to a specific citation style (e.g., APA style).

[0504] Finally, the server compiles improvement suggestions based on the results of these checks and sends them to the user's device. The user reviews the improvement suggestions and revise the draft using dedicated editor software. Finally, the user improves the document based on the suggestions and finalizes it.

[0505] Specific examples

[0506] For example, if a user uploads a draft of a research paper containing the grammatical error "He go to the library," the server will use an AI engine to generate suggestions to correct this sentence to "He goes to the library." Furthermore, if the introduction is too short, the server will suggest, "The introduction is short, so we recommend adding more details," and if the citations do not conform to APA style, the server will suggest, "The citation format should be corrected to APA style." These suggestions are sent to the user in JSON format, who can review and revise the draft.

[0507] Specific prompt examples:

[0508] 1. Grammar error: 'He go to the library.' should be 'He goes to the library.'

[0509] 2. Inconsistent structure: The introduction is short, so the suggestion is, "The introduction is short, so we recommend adding more details."

[0510] 3. Incorrect citation: The citation format does not conform to APA style, so the suggestion is that "the citation format should be corrected to APA style."

[0511] As described above, the system of the present invention automatically proofreads papers, allowing researchers time to concentrate on their research and is extremely useful in improving the quality of papers.

[0512] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0513] Step 1:

[0514] A user uploads a draft of a paper

[0515] Input: The user uses the device's web browser to select a draft file of the paper (e.g., research paper.docx).

[0516] How it works: A user logs into the system, accesses the upload screen, selects a draft file, and clicks the upload button.

[0517] Output: The draft file is sent to the server.

[0518] Step 2:

[0519] The server receives and saves the draft

[0520] Input: Draft file submitted by user.

[0521] How it works: The server saves the received draft file in a specific directory, using a hash function to verify the integrity of the file.

[0522] Output: Draft files saved in a directory and their consistency check results.

[0523] Step 3:

[0524] The server checks the grammar using an AI engine

[0525] Input: Saved draft file.

[0526] How it works: The AI ​​engine on the server analyzes the document using natural language processing libraries (e.g., spaCy or Grammarly API). It detects grammatical errors in the draft and generates correction suggestions. For example, it generates a suggestion to change "He go to the library." to "He goes to the library."

[0527] Output: Grammar check results and suggested corrections.

[0528] Step 4:

[0529] The server checks the structure using an AI engine

[0530] Input: Saved draft file.

[0531] How it works: The server's AI engine uses trained models such as the BERT model to analyze the document structure (headings, paragraphs, sections, etc.) and check for consistency. For example, if the introduction is too short, it generates a suggestion such as "The introduction is short. We recommend adding more details."

[0532] Output: Results of the structure check and suggestions for improvement.

[0533] Step 5:

[0534] The server performs quote checking using an AI engine

[0535] Input: Saved draft file.

[0536] How it works: The server's AI engine uses rule-based NLP models and reference management software APIs (e.g., Zotero API) to check the accuracy of citation formatting. It checks whether the citation conforms to a specific citation style, such as APA style. For example, it generates a suggestion such as, "Your citation formatting should be corrected to APA style."

[0537] Output: Citation check results and suggested fixes.

[0538] Step 6:

[0539] The server generates and sends improvement suggestions

[0540] Input: Results of grammar checks, structure checks, and citation checks.

[0541] How it works: The server generates comprehensive improvement suggestions in JSON format based on the results of each check. The suggestions are sent to the user's device via HTTPS. When the user logs in to the system, the suggestions are displayed on the dashboard.

[0542] Output: Improvement suggestions sent to the user's device.

[0543] Step 7:

[0544] Users review and apply improvement suggestions

[0545] Input: Improvement suggestions sent by the server.

[0546] How it works: The user reviews the suggestions they receive and uses specialized editor software to revise the draft, for example by applying the provided grammar correction suggestions to revise the document.

[0547] Output: The modified draft file.

[0548] (Application example 1)

[0549] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0550] When content providers try to quickly generate high-quality documents, they face the problem of having to check grammar, structure, and citation formatting, which is time-consuming and laborious. It is also not easy to proofread documents to fit specific distribution formats. Therefore, there is a need for a method to efficiently proofread documents while maintaining the quality of the content.

[0551] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0552] In this invention, the server includes means for a user to upload a content draft from a terminal, means for the server to receive and store the uploaded draft, means for the server to call an AI engine for grammar check, detect grammatical errors, and generate correction suggestions, means for the server to analyze the structure of the content and generate improvement suggestions, means for the server to check the accuracy and format of citations and generate correction suggestions, means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal, and means for the user to review and apply the improvement suggestions received, thereby enabling content providers to efficiently create and distribute high-quality content.

[0553] Definitions of important words

[0554] "User" refers to the person who uploads draft content and receives suggested improvements for review and revision.

[0555] "Terminal" refers to a device used by a user to upload a content draft, and includes a smartphone, tablet, PC, etc.

[0556] "Server" means a central processing unit that receives and stores drafts of uploaded Content and performs grammar checks, structural analysis, and citation checks.

[0557] "AI engine" refers to a software system that uses artificial intelligence to detect grammatical errors and generate correction suggestions.

[0558] "Grammar checking" refers to the process of detecting grammatical errors in a content draft and making suggestions to fix them.

[0559] "Structural analysis" refers to the process of evaluating the logical organization of paragraphs, headings, sections, etc. throughout a content draft and making suggestions for improvement.

[0560] "Citation checking" refers to the process of reviewing citations in content for accuracy and formatting, and suggesting any necessary corrections.

[0561] "Improvement Suggestion" refers to a suggested revision of content that the server generates based on the results of grammar, structure, and citation checks and provides to the user.

[0562] "Distribution format" refers to the format or style required for a particular distribution channel or platform.

[0563] MODE FOR CARRYING OUT THE INVENTION

[0564] The present invention provides a system that allows users to upload drafts of content from devices such as smartphones, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the user. Specific embodiments for implementing the present invention are described in detail below.

[0565] System configuration

[0566] The system includes the following components:

[0567] 1. User Device

[0568] A device used by a user, such as a smartphone, tablet, or PC, that is used to upload drafts and review improvement suggestions.

[0569] 2. Server

[0570] The server is a central processing unit that receives and stores uploaded drafts and checks them for grammar, structure, and citations using an AI engine. The server runs using Python and natural language processing libraries (e.g., NLTK, TensorFlow).

[0571] 3. AI Engine

[0572] The AI ​​engine is a software system for grammar error detection, structural analysis, and citation checking, which generates suggestions for correcting grammatical errors and improving structure and citations.

[0573] Explanation of program processing

[0574] 1. User uploads draft content

[0575] Users log in to the system from their own devices, access the screen for uploading draft content, select a file, and click the upload button to send the draft to the server.

[0576] 2. The server receives the draft

[0577] The server receives the draft uploaded by the user, saves it in the specified directory, and checks the integrity of the file for proper processing.

[0578] 3. Grammar, structure, and citation checks using an AI engine

[0579] The AI ​​engine on the server starts up and first performs grammatical analysis. Then it analyzes the overall structure of the content (paragraphs, headings, etc.), and finally checks the citation style. For example, it generates a suggestion to correct the mistake "He go to the library" to "He goes to the library." In terms of structure, if the introduction is short, it will suggest "We recommend adding more detail to the introduction." Also, if the citation does not follow a specific style, it will point out that "the citation format needs to be corrected."

[0580] 4. Generate and submit improvement suggestions

[0581] The server generates improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's device. The improvement suggestions are sent to the contact information associated with the user's account or displayed on the user's dashboard when they log in to the system.

[0582] Specific examples

[0583] Suppose a user uploads a draft of a blog post to the system. The draft contains grammatical errors, inconsistent structure, and incomplete citations. The server first checks for these problems using an AI engine. Specifically, it generates suggestions to correct "He go to the library." to "He goes to the library.", suggests adding more detail to the short introduction, and further suggests correcting parts of the citation that do not comply with the syndication format. These suggestions are then sent to the user, who can review and apply them to improve the quality of the content.

[0584] Prompt Sentence Examples

[0585] Check the grammar, structure, and citations of blog posts uploaded by users and generate improvement suggestions as follows:

[0586] Grammar error: Change "He go to the library." to "He goes to the library."

[0587] Poor structure: "The introduction is short, so I suggest adding more details."

[0588] Incorrect citation: "Please correct your citation format."

[0589] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0590] Program processing flow

[0591] Step 1:

[0592] The user uploads a draft of content from the terminal. The input is the draft file specified by the user, and the output is the terminal sending the draft file to the server. When the user clicks the upload button, the draft file is sent from the terminal to the server.

[0593] Step 2:

[0594] The server receives the uploaded draft and saves it in the specified directory. The input is the draft file sent by the user, and the output is the draft file to be saved. The server first verifies the integrity of the draft file and saves it in the appropriate directory.

[0595] Step 3:

[0596] The server invokes the AI ​​engine to perform grammatical analysis of the draft. The input is the saved draft file, and the output is the results of grammatical error detection. The server inputs the saved draft file into the AI ​​engine and detects grammatical errors using a natural language processing library (NLTK). It generates a suggestion to correct the mistake "He go to the library." to "He goes to the library."

[0597] Step 4:

[0598] The server uses an AI engine to analyze the structure of the draft. The input is the saved draft file, and the output is structural improvement suggestions. The server evaluates the structure of the draft, including paragraphs, headings, and sections, to ensure consistency. For example, if the introduction is short, the server will make a suggestion such as, "We recommend adding more detail to the introduction."

[0599] Step 5:

[0600] The server uses an AI engine to check the citations in the draft. The input is the saved draft file, and the output is suggestions for correcting the citations and formatting. The server inspects the citations in the draft to ensure they conform to a specific style (e.g., APA style). If the citations do not follow the style, it suggests, "Your citation format needs to be revised."

[0601] Step 6:

[0602] The server generates improvement suggestions based on the results of each grammar, structure, and citation check and sends them to the user's device. The input is the check results from the AI ​​engine, and the output is the generated improvement suggestions. The server integrates the results of each check and generates improvement suggestions. These suggestions are then sent to the user's device and displayed on the dashboard or sent to the corresponding contact.

[0603] Step 7:

[0604] The user reviews and applies the improvement suggestions received. The input is the improvement suggestions sent from the server, and the output is the revised draft. The user checks the improvement suggestions on the terminal, adds necessary corrections to the draft, and re-edits it.

[0605] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0606] The present invention combines an emotion engine with a system for automatically proofreading a paper draft. This allows the system to recognize the user's emotional state and adjust the interface and the method of presenting improvement suggestions based on that state. Specific embodiments for implementing the present invention are described below.

[0607] System configuration

[0608] The system consists of four main components: the user, the device, the server, and the emotion engine. Users upload drafts of their papers via their devices, and the emotion engine recognizes their emotional state in real time. The server stores the received drafts and uses an AI engine to check grammar, structure, and citations, generating improvement suggestions. The emotion engine adjusts the interface and generates feedback messages based on the user's emotional data.

[0609] Explanation of program processing

[0610] 1. User uploads a draft

[0611] Using the terminal, the user selects the draft file from the file selection screen and clicks the upload button, which sends the file to the server.

[0612] During this process, the emotion engine analyzes the user's facial expressions and voice to recognize their current emotional state in real time.

[0613] 2. The server receives the draft

[0614] The server stores the uploaded draft and verifies the integrity of the file.

[0615] The emotion engine transmits the acquired emotion data to the server, which then stores the data.

[0616] 3. Grammar check by AI engine

[0617] The server's AI engine analyzes the draft for grammatical errors and generates correction suggestions.

[0618] The emotion engine adjusts the way suggestions are worded based on the user's emotional state, for example, using gentler language if the user is stressed.

[0619] 4. Structure check using AI engine

[0620] The server uses an AI engine to analyze the structure of the paper and generate suggestions regarding consistency and logic.

[0621] If the emotion engine determines that the user is tired, it will provide a concise summary of suggestions.

[0622] 5. Citation check using AI engine

[0623] The server's AI engine checks the citation format and generates appropriate correction suggestions.

[0624] The system adjusts which correction suggestions are given priority depending on the user's emotional state.

[0625] 6. Generate and submit improvement suggestions

[0626] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks, adjusting the wording and order of the suggestions taking into account data from the sentiment engine.

[0627] The final improvement proposals are sent to the user's device via the method selected by the user (email or dashboard display).

[0628] 7. Review and apply user improvement suggestions

[0629] The user receives and reviews the improvement suggestions via their device, while the emotion engine continues to monitor the user's emotional state and displays support messages as needed.

[0630] The user applies the suggested corrections and re-edits the draft, and the emotion engine supports the user in completing the final version while reducing stress.

[0631] Specific examples

[0632] Suppose a user uploads a draft of a research paper to the system. If the emotion engine detects that the user is nervous, it displays the message, "Relax and proceed. We'll help you." The server receives the draft and checks its grammar, structure, and citations. The engine finds an error in the sentence, "He go to the library." It generates a suggestion to correct it to, "He goes to the library." If the user is feeling even more fatigued, the suggestion is simplified and a simple suggestion such as, "The introduction is short, please add more details."

[0633] In this way, the system of the present invention automatically proofreads papers while taking into account the user's emotional state and provides optimal suggestions for improvement, helping researchers to write higher quality papers without feeling stressed.

[0634] The processing flow will be explained below.

[0635] Step 1:

[0636] The user uploads a draft of their paper using their device. They open a file selection screen and select the draft file. Then, by clicking the upload button, the selected file is sent to the server. At the same time, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their current emotional state.

[0637] Step 2:

[0638] The server saves the draft file received from the user in the specified directory and verifies the integrity of the file. After the file is saved correctly, the server saves the emotion data and proceeds to the next processing step.

[0639] Step 3:

[0640] The server launches the AI ​​engine to check grammar. The AI ​​engine reads the saved draft file and analyzes grammatical errors. For example, it finds the mistake "He go to the library." and generates a suggestion to correct it to "He goes to the library." If the emotion engine detects the user's stress, the AI ​​engine's output will use gentler expressions.

[0641] Step 4:

[0642] The server uses an AI engine to analyze the structure of the paper. It analyzes the arrangement of headings, paragraphs, and sections in the saved draft and checks for consistency. For example, it generates suggestions such as, "The introduction is short, so we recommend adding more details." If the emotion engine determines that the user is tired, it will display a concise summary of the suggestions.

[0643] Step 5:

[0644] The server uses an AI engine to check the accuracy and format of citations. It analyzes the citation format in the draft and checks whether it conforms to a specific citation style (e.g., APA style). If there are any deficiencies, it generates suggestions such as "Please revise the citation format to APA style." It prioritizes important revision suggestions based on the emotional state of the author.

[0645] Step 6:

[0646] The server generates improvement suggestions based on the results of grammar, structure, and citation checks. Each suggestion is summarized in an easy-to-read report. The wording and order of suggestions are adjusted taking into account data from the sentiment engine. If a user expressed negative sentiment during upload, subsequent suggestions may include encouraging content.

[0647] Step 7:

[0648] The server sends the generated improvement proposals and reports to the user's device either via email address associated with the user's account or displayed on the user's dashboard when they log in to the system. The tone of the proposals and the content of the message are adapted based on the emotional data.

[0649] Step 8:

[0650] The user reviews the improvement suggestions on their device. They confirm the suggestions and revise the draft based on them. The emotion engine monitors the user's emotional state during the review and displays encouraging or supportive messages as needed. For example, if the user is confused, the engine displays a message such as, "Don't worry, we'll provide advice as needed."

[0651] The above is a specific processing flow in the system of the present invention.

[0652] Example 2

[0653] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0654] While conventional paper proofreading systems can check grammar and structure, they have a problem in that they cannot make suggestions that take into account the user's emotional state. This causes problems such as users feeling stressed during the proofreading process and not being able to effectively utilize the suggestions for improvement.

[0655] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0656] In this invention, the server includes means for an emotion engine to recognize a user's emotion in real time and transmit that data to the server, means for the emotion engine to adjust the expression method and order of improvement suggestions based on the user's emotion data, and means for the server to generate comprehensive improvement suggestions based on the results of grammar, structure, and citation checks and transmit them to the user's terminal. This makes it possible to provide optimal improvement suggestions that take the user's emotional state into consideration.

[0657] "User" means any person or entity that uses the System to upload drafts of papers and receive suggestions for improvement.

[0658] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet.

[0659] "Server" means a remote computer that receives and stores uploaded drafts, performs various checks, and generates and submits improvement suggestions.

[0660] An "emotion engine" is software or hardware that analyzes a user's facial expressions and voice in real time to recognize their emotional state.

[0661] An "AI engine" is an artificial intelligence program that checks grammar, structure, and citations and generates suggestions for improvement.

[0662] "Grammar check" refers to the process of detecting grammatical errors in an uploaded draft and making correction suggestions.

[0663] A "structural check" is a process of analyzing the overall structure and logic of a paper and making suggestions for improvement regarding consistency and points of argument.

[0664] "Citation checking" is the process of verifying that citations in a paper are accurate and follow proper formatting, and making suggested revisions.

[0665] "Improvement Suggestions" are suggestions for improving the quality of a user's draft, generated based on the results of grammar, structure, and citation checks.

[0666] An "email address" is one of the means of communication associated with a user's account, and is an address used to receive information such as improvement suggestions.

[0667] The present invention is a system that allows users to upload a draft of a paper and receive optimal improvement suggestions using automatic proofreading and an emotion engine. Specific embodiments will be described step by step below.

[0668] Hardware and software used

[0669] User devices: computers, smartphones, tablets, etc. Through these devices, users upload drafts and view improvement suggestions.

[0670] Server: A remote computer that stores drafts, analyzes them, and generates improvement suggestions.

[0671] Emotion engine: Software or hardware that analyzes a user's facial expressions and voice in real time to recognize their emotional state. Examples include facial recognition technology and voice analysis technology.

[0672] AI Engine: An artificial intelligence program that checks grammar, structure, and citations. Examples include grammar analysis tools (e.g., Grammarly API) and machine learning models (e.g., BERT, GPT-3).

[0673] Data processing and calculation

[0674] User uploads draft

[0675] The user selects a draft of the paper from the device and uploads it to the server, which then transmits the data to the server using HTTP or HTTPS protocols.

[0676] The server receives and saves the draft

[0677] The server receives and stores the uploaded drafts, checking the integrity of the files and saving them in the appropriate folders.

[0678] Emotion recognition by emotion engine

[0679] The emotion engine analyzes the user's facial expressions and voice in real time to generate emotion data, which is then sent to a server via a REST API or similar and stored.

[0680] Grammar check by AI engine

[0681] The server passes the saved draft to an AI engine that analyzes it for grammatical errors. It uses grammar analysis tools to list the mistakes and suggest corrections.

[0682] Structural check using AI engine

[0683] The AI ​​engine analyzes the structure of a paper and generates suggestions for consistency and logic. For example, if a paragraph is unnaturally connected, it will suggest, "Merge this paragraph with the previous one."

[0684] Citation check by AI engine

[0685] The server uses an AI engine to check whether the citation format is correct and generate suggestions for corrections, such as "Please correct the citation according to APA style."

[0686] Generate comprehensive improvement suggestions

[0687] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks. It adjusts the wording and order of the suggestions based on data from the emotion engine. For example, it uses gentler wording when the user is feeling stressed.

[0688] Submit an improvement suggestion

[0689] The server sends the generated improvement suggestions to the user's device, either via email or as a dashboard display.

[0690] Review and apply user improvement suggestions

[0691] The user can review the improvement suggestions received through their device and apply any necessary corrections. The emotion engine also monitors the user's emotional state and displays supportive messages such as "Please stay calm and proceed."

[0692] Specific examples

[0693] A user uploads a draft of a research paper to the system. If the emotion engine detects that the user is nervous, it may display the message, "Relax and proceed. We'll help you." The server receives the draft and checks it for grammar, structure, and citations. The engine finds the error, "He go to the library." It generates a suggestion to correct it to, "He goes to the library." Furthermore, if the user is feeling fatigued, the suggestion may be simplified, with a simple suggestion such as, "The introduction is short; please add more detail."

[0694] Prompt Sentence Examples

[0695] "Generate timely emotional support messages for stressed users who upload their paper drafts."

[0696] "Write a concise suggestion for improving the paper structure for a user who is experiencing fatigue."

[0697] In this way, this system automatically proofreads papers while taking into account the user's emotional state and provides optimal improvement suggestions, thereby improving the quality of papers while reducing user stress.

[0698] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0699] Step 1:

[0700] User uploads draft

[0701] Input: The user selects the paper draft (e.g., a text file) on the file selection screen of the terminal and clicks the upload button.

[0702] Processing: The terminal sends the user's selected draft file to the server using HTTP or HTTPS protocol.

[0703] Output: A draft file is sent to the server.

[0704] Step 2:

[0705] The server receives and saves the draft

[0706] Input: The server receives the draft file sent from the terminal.

[0707] Processing: Saving the received file in a specific folder and checking the file integrity, for example, whether the file is corrupted and whether it was transferred completely.

[0708] Output: The draft file is saved on the server.

[0709] Step 3:

[0710] The emotion engine recognizes the user's emotions in real time and sends them to the server.

[0711] Input: Facial and voice data when users upload their drafts.

[0712] Processing: The emotion engine uses facial expression recognition software and voice analysis tools to analyze the user's emotional state in real time. The analysis results are converted into data and sent to a server using a REST API or similar.

[0713] Output: The user's emotional data (e.g., tension, stress, fatigue, etc.) is sent to the server.

[0714] Step 4:

[0715] The server's AI engine starts grammar checking

[0716] Input: Draft file saved on the server.

[0717] Processing: The server calls a grammar analysis tool (e.g., Grammarly API) to analyze the draft for grammar errors. It detects grammar errors and generates correction suggestions for each one.

[0718] Output: A list of grammar errors and suggested fixes for them.

[0719] Step 5:

[0720] The server's AI engine begins structure checks

[0721] Input: Draft file saved on the server.

[0722] Processing: The AI ​​engine analyzes the overall structure of the draft and generates suggestions for improvement regarding consistency and logic. For example, if a paragraph is not connected properly, it will suggest, "Merge this paragraph with the previous one."

[0723] Output: A list of structural errors and suggestions for improving them.

[0724] Step 6:

[0725] The server's AI engine starts checking quotes

[0726] Input: Draft file saved on the server.

[0727] Processing: The AI ​​engine analyzes the citations in the draft, checking whether they follow the proper formatting and generating correction suggestions if there are any deficiencies.

[0728] Output: A list of citation errors and suggested fixes.

[0729] Step 7:

[0730] Generate comprehensive improvement suggestions

[0731] Input: The results of grammar, structure, and citation checks, as well as user sentiment data sent from the sentiment engine.

[0732] Processing: The server integrates the results of each check and adjusts the wording and order of the improvement suggestions based on the emotional data. For example, if the user is feeling stressed, the suggestions will be presented in a gentler way and in an order that will reduce the burden.

[0733] Output: Comprehensive improvement suggestions.

[0734] Step 8:

[0735] The server sends improvement suggestions to the user's device

[0736] Input: Overall improvement suggestions.

[0737] Processing: The server sends the generated improvement suggestions to the user's email address or dashboard.

[0738] Output: Improvement suggestions that can be viewed on the user's device.

[0739] Step 9:

[0740] Review and apply user improvement suggestions

[0741] Input: Improvement suggestions received from the server.

[0742] Processing: The user reviews the received improvement suggestions and applies them to the draft if necessary. The emotion engine continues to monitor the user's emotional state and displays supportive messages such as "Keep calm and proceed."

[0743] Output: A draft with the corrections applied.

[0744] (Application example 2)

[0745] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0746] In production sites such as factories, employees are required to work efficiently while avoiding excessive stress and fatigue. However, current technology makes it difficult to monitor employees' emotional states in real time and provide appropriate feedback and improvement suggestions accordingly. In addition, there is a lack of means to adjust work suggestions based on employees' emotional states, making it a challenge to improve work efficiency while managing employee stress.

[0747] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0748] In this invention, the server includes: means for a user to upload a draft of a paper from a terminal; means for the server to receive and store the uploaded draft; means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; means for the server to analyze the structure of the paper and generate improvement suggestions; means for the server to check the accuracy and format of citations and generate correction suggestions; means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; means for the user to review and apply the improvement suggestions received; means for recognizing the user's emotional state using an emotion engine and adjusting the interface and the expression method of the suggestions based on that state; means for monitoring work progress in real time and generating feedback messages based on the emotion engine; and means for adjusting the priority and expression method of the improvement suggestions based on the emotional state. This makes it possible to provide appropriate feedback and improvement suggestions in real time that take into account the emotional state of employees, thereby improving work efficiency and managing stress at the same time.

[0749] "User" refers to a person who uses the system to upload a draft paper and receive suggestions for improvement.

[0750] "Terminal" refers to the device used by a User to upload a draft of their paper.

[0751] "Server" refers to a centralized computer system that receives and stores drafts uploaded by users and performs various analyses.

[0752] "AI Engine" refers to an artificial intelligence system installed on a server that detects grammatical errors and generates correction suggestions.

[0753] An "emotion engine" is a system that recognizes a user's emotional state in real time and adjusts the interface and presentation of suggestions based on that data.

[0754] "Grammar check" refers to the AI ​​engine's process of analyzing the sentence structure in the draft, detecting grammatical errors, and suggesting corrections.

[0755] "Structure" refers to the organization, arrangement, and development of paragraphs of an entire paper or document.

[0756] "Citations" refer to references within a paper to other studies or sources.

[0757] "Interface" refers to the operation screen and display method that allows users to interact with the system.

[0758] "Feedback message" refers to a message that is generated by the emotion engine based on the user's emotional state to support the progress of work and mood.

[0759] "Real-time monitoring" refers to instantly monitoring the progress of work and the user's emotional state, and responding immediately if necessary.

[0760] "Improvement suggestions" refer to corrections and suggestions regarding grammar, structure, citations, etc. that the AI ​​engine generates based on the analysis results.

[0761] This invention relates to a system that improves the work efficiency and mental health of employees in factory production. The system consists of four main components: smart glasses worn by the user, a server, an AI engine, and an emotion engine.

[0762] System configuration

[0763] 1. Users

[0764] The user is a factory worker who wears smart glasses to perform his / her work. The smart glasses are equipped with a camera, a display, and a network module.

[0765] 2. Smart Glasses

[0766] The smart glasses are equipped with a camera that captures the user's facial expressions and work status in real time. The emotion engine analyzes the user's emotional state and sends the results to the server. Feedback messages and improvement suggestions from the server are displayed on the display.

[0767] 3. Server

[0768] The server is the main hub for the following operations:

[0769] Receives and stores data uploaded by users.

[0770] An AI engine is used to perform grammar checks, structural analysis, and citation verification.

[0771] Use data from the emotion engine to tailor the wording of feedback messages and improvement suggestions.

[0772] The server is expected to be built on a general cloud computing environment (for example, AWS or Google Cloud Platform).

[0773] 4. AI Engine

[0774] The AI ​​engine is equipped with the technology to perform the following processes:

[0775] Grammar Check: Uses NLP (Natural Language Processing) techniques to detect grammatical errors and generate correction suggestions.

[0776] Structural analysis: Analyze the organization of an entire paper or document and generate improvement suggestions.

[0777] Citation Check: Checks the accuracy and format of citations in your paper and generates suggested revisions.

[0778] The AI ​​engine is developed using technologies such as TensorFlow and OpenCV.

[0779] 5. Emotion Engine

[0780] The emotion engine recognizes the user's emotional state and adjusts the presentation of the interface and suggestions based on that state.

[0781] Emotion analysis: Analyzes the user's facial expression data captured from the smart glasses camera to assess their emotional state.

[0782] Feedback generation: Generate appropriate feedback messages for users based on emotion data.

[0783] The emotion engine is built using, for example, the Affdex SDK.

[0784] Specific examples

[0785] Suppose an employee is performing assembly work. If the emotion engine recognizes the employee's fatigue, the smart glasses will display a message saying, "Please take a short break." If the AI ​​engine detects a mistake in the work, the smart glasses will display a suggestion saying, "The screws appear to be loose. Please check again." In this way, the system of the present invention can provide appropriate feedback and improvement suggestions in real time, taking into account the employee's emotional state.

[0786] Prompt Sentence Examples

[0787] Desired function: Support for assembly work in factories

[0788] Main features: Real-time monitoring of work content, recognition of emotional state, and provision of improvement suggestions

[0789] Technologies used: Sentiment analysis with Affdex SDK, working analysis with TensorFlow and OpenCV

[0790] Input data: facial expression data of employees, video data of their work

[0791] Output data: Feedback messages, improvement suggestions

[0792] Targeted effects: Improved work efficiency and quality, reduced employee stress

[0793] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0794] Step 1: User puts on smart glasses

[0795] A user puts on smart glasses to start work in the factory. The camera in the smart glasses captures the user's facial expressions and work status in real time. The input is the user's facial expression data and work video data, and the output is that these data are sent to the server.

[0796] Step 2: Emotional state analysis by the emotion engine

[0797] The server receives the facial expression data sent from the smart glasses. The emotion engine then analyzes it and evaluates the user's emotional state (e.g., fatigue, stress, or relaxation). The input is the facial expression data, and the output is the evaluation result of the emotional state. The emotion engine uses the Affdex SDK to analyze the facial expression data.

[0798] Step 3: Real-time operation monitoring

[0799] The server receives video data of the work sent from the smart glasses. The AI ​​engine analyzes the video data to check the progress of the work and detect errors and areas for improvement. The input is the video data, and the output is the work status and error detection results. The AI ​​engine performs analysis using TensorFlow and OpenCV.

[0800] Step 4: Generate feedback and improvement suggestions

[0801] The server integrates the emotional state evaluation results from the emotion engine and the work situation analysis results from the AI ​​engine. Then, based on the emotional state, it generates appropriate feedback messages and improvement suggestions for the user. The inputs are the emotional state evaluation results and the work situation analysis results, and the output is the feedback messages and improvement suggestions.

[0802] Step 5: Viewing feedback messages

[0803] The server sends the generated feedback messages and improvement suggestions to the smart glasses display. The user receives this feedback in real time and improves their work. The input is the feedback messages and improvement suggestions, and the output is the feedback displayed on the smart glasses display.

[0804] Step 6: User improvement and data feedback

[0805] The user improves their work based on the feedback from the smart glasses. The improved work data is again captured by the smart glasses' camera and sent to the server. The input is the improved work data, and the output is the data sent to the server. This feedback loop ensures that the latest data is always analyzed, leading to continuous work improvement.

[0806] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0807] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0808] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0809] [Third embodiment]

[0810] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0811] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0812] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0813] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0814] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0815] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0816] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0817] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0818] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0819] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0820] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0821] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0822] The present invention provides a system that allows a user to upload a draft of a paper, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the user. Specific embodiments for implementing the present invention are described in detail below.

[0823] System configuration

[0824] The system consists of three main components: users, devices, and a server. Users use their devices to upload drafts of their papers, receive suggestions for improvement, and review and revise them. The server receives and stores the uploaded drafts, checks grammar, structure, and citations using an AI engine, and generates suggestions for improvement and sends them to the users' devices.

[0825] Explanation of program processing

[0826] 1. User uploads a draft

[0827] Users log in to the system from their own devices, access the screen for uploading a paper draft, select a file, and click the upload button to send the draft to the server.

[0828] 2. The server receives the draft

[0829] The server receives the draft uploaded by the user, saves it in the specified directory, and checks the integrity of the file for proper processing.

[0830] 3. Grammar check by AI engine

[0831] The AI ​​engine in the server will then analyze the draft for grammatical errors, generating suggestions to correct, for example, the mistake "He go to the library." to "He goes to the library."

[0832] 4. Structure check using AI engine

[0833] The server's AI engine analyzes the structure of a paper (headings, paragraphs, sections, etc.) and checks the consistency of the entire paper. For example, if the introduction is too short, it will make suggestions such as, "The introduction is too short. We recommend adding more details."

[0834] 5. Citation check using AI engine

[0835] The server's AI engine inspects citations in a paper to ensure they comply with a specific citation style. For example, if a citation does not follow APA style, it will suggest, "Your citation format should be revised to APA style."

[0836] 6. Generate and submit improvement suggestions

[0837] The server generates improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's device. The improvement suggestions are sent to the email address associated with the user's account or displayed on the user's dashboard when they log in to the system.

[0838] 7. Review and apply user improvement suggestions

[0839] The user reviews the improvement suggestions sent by the server, revises the draft as necessary, and re-edits the paper based on the reviewed suggestions to complete the final version.

[0840] Specific examples

[0841] For example, suppose a user uploads a draft of a research paper to the system. The draft contains grammatical errors, inconsistent structure, and incomplete citations. The server first checks for these issues using an AI engine, correcting "He go to the library" to "He goes to the library," noting that the introduction is too short, and generating suggestions for correcting citations that do not conform to APA style. These suggestions are then sent to the user, who can review and apply them to improve the quality of their paper.

[0842] As described above, the system of the present invention automatically proofreads papers, allowing researchers time to concentrate on their research and is extremely useful in improving the quality of papers.

[0843] The processing flow will be explained below.

[0844] Step 1:

[0845] A user uploads a draft of a paper using a terminal. The user opens the file selection screen, selects the draft file, and clicks the "Upload" button. This operation sends the draft file to the server.

[0846] Step 2:

[0847] The server saves the draft file received from the user in the specified directory, and checks the integrity of the file. After confirming that the file has been saved correctly, the server proceeds to the next processing step.

[0848] Step 3:

[0849] The server launches the AI ​​engine for grammar check. The server passes the saved draft file to the AI ​​engine, which analyzes it for grammatical errors. For example, it finds the sentence "He go to the library." and generates a suggestion to correct it to "He goes to the library."

[0850] Step 4:

[0851] The server uses an AI engine to check the structure of the paper. It analyzes the arrangement of headings, paragraphs, and sections in the draft to ensure consistency. For example, if the introduction is too short, it generates a suggestion that the introduction should be longer.

[0852] Step 5:

[0853] The server checks citations using an AI engine. It analyzes the citation format in the draft and checks whether it conforms to a specific citation style (e.g., APA style). If there are any deficiencies, it generates a suggestion to "revise the citation format to APA style."

[0854] Step 6:

[0855] The server generates improvement suggestions based on the results of the grammar, structure, and citation checks. Each suggestion is summarized in an easy-to-read report. The server prepares this report and moves on to the next step.

[0856] Step 7:

[0857] The server sends the generated improvement suggestions and reports to the user's device, either to the email address associated with the user's account or displayed on the dashboard when the user accesses the system.

[0858] Step 8:

[0859] The user reviews the improvement suggestions on their device. The user checks the received suggestions and modifies the draft as necessary. For example, they fix the problematic parts and add new content. Once the modifications are complete, the user saves the final version of the paper and, if necessary, uploads it back to the system.

[0860] The above is a specific processing flow in the system of the present invention.

[0861] Example 1

[0862] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0863] Conventional paper proofreading systems have the drawback of being time-consuming and labor-intensive, as they require manual checks of grammar, structure, and citations. Furthermore, they often fail to guarantee that proofreading conforms to a specific citation style or secure data transmission. Furthermore, the formats of improvement suggestions received by users are not standardized, making reviewing and applying them difficult.

[0864] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0865] In this invention, the server includes: a means for a user to upload a document draft from a terminal; a means for the server to receive and store the uploaded draft; a means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; a means for the server to analyze the document structure and generate improvement suggestions; a means for the server to check the accuracy and format of citations and generate correction suggestions; a means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; a means for the server to review and apply the improvement suggestions received by the user; a means for the server to use a hash function to verify integrity when receiving files; a means for the server to generate suggestions from the AI ​​engine in JSON format; a means for the server to securely transmit and receive data using the HTTPS protocol; and a means for the terminal to use editor software to review and apply the improvement suggestions. This enables automated and efficient paper proofreading, secure data transmission and reception, and the provision of unified improvement suggestions.

[0866] A "user" is a person who uploads draft documents from a terminal and has the role of reviewing and applying suggestions.

[0867] "Terminal" means an electronic device that a User uses to access the System, upload draft documents, and receive and review improvement suggestions.

[0868] The "server" is a device that has the function of storing drafts received from users, checking grammar, structure, and citations, generating improvement suggestions, and sending them to the user's terminal.

[0869] A "document draft" is an incomplete document that a user uploads to the system and that is checked for grammar, structure, and citations.

[0870] "Grammar checking" is the process of detecting grammar errors in a document and generating appropriate correction suggestions.

[0871] "AI Engine" refers to the artificial intelligence models and algorithms used to review documents and generate suggestions.

[0872] "Document structure" refers to the hierarchical and logical arrangement of the document as a whole, including headings, paragraphs, sections, etc.

[0873] "Accuracy of citations" means that citations within a document are based on appropriate sources and are expressed accurately.

[0874] "Citation formatting" refers to the proper citations in a document following a particular formatting style (e.g., APA style).

[0875] "Improvement suggestions" are recommendations for correcting and improving a document, generated based on the results of checks on grammar, structure, citations, etc.

[0876] A "hash function" is an algorithm used to verify the integrity of a file, generating a fixed-length output value (hash value) from input data.

[0877] "JSON" is a lightweight data interchange format for representing data in text form and is used to generate and transmit proposals.

[0878] The "HTTPS protocol" is a protocol used to send and receive data securely over the Internet and provides data encryption.

[0879] "Editor software" means application software that enables a user to create, edit, or modify documents.

[0880] The present invention relates to a system that allows users to upload drafts of their papers, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the users. Specific embodiments of the system are described below.

[0881] System configuration

[0882] The system consists of three main components: users, devices, and a server. Users use their devices to upload drafts of their papers, receive suggestions for improvement, and review and revise them. The server receives and stores the uploaded drafts, checks grammar, structure, and citations using an AI engine, and generates suggestions for improvement and sends them to the users' devices.

[0883] Hardware and software used

[0884] This system uses the following hardware and software:

[0885] Terminal: Electronic device (PC, tablet, smartphone, etc.) through which a user accesses the system

[0886] Server: The central computer that processes the data, stores the drafts, runs the AI ​​engine, and generates and sends proposals.

[0887] Software: The following software is used:

[0888] Web Browser: Used by users to access the system and upload drafts.

[0889] AI engine: Natural language processing libraries (e.g., spaCy or Grammarly API) and pre-trained models (e.g., BERT model)

[0890] Data transfer protocol: HTTPS protocol is used to encrypt and securely transmit data.

[0891] Data format: Improvement suggestions are generated in JSON format and sent to the user's device.

[0892] Detailed explanation of the process

[0893] First, a user logs in to the system using a web browser on their device and uploads a draft of their paper. The server receives the draft and saves it in a specified directory. At this time, the server verifies the integrity of the file using a hash function to confirm that the file has been received correctly.

[0894] The server then launches an AI engine to check the document's grammar. The AI ​​engine uses natural language processing libraries to detect grammatical errors and generate correction suggestions. Similarly, the AI ​​engine analyzes the document's structure, evaluating the consistency of headings, paragraphs, sections, etc., and generates improvement suggestions. In addition, the AI ​​engine checks the citation format to ensure it conforms to a specific citation style (e.g., APA style).

[0895] Finally, the server compiles improvement suggestions based on the results of these checks and sends them to the user's device. The user reviews the improvement suggestions and revise the draft using dedicated editor software. Finally, the user improves the document based on the suggestions and finalizes it.

[0896] Specific examples

[0897] For example, if a user uploads a draft of a research paper containing the grammatical error "He go to the library," the server will use an AI engine to generate suggestions to correct this sentence to "He goes to the library." Furthermore, if the introduction is too short, the server will suggest, "The introduction is short, so we recommend adding more details," and if the citations do not conform to APA style, the server will suggest, "The citation format should be corrected to APA style." These suggestions are sent to the user in JSON format, who can review and revise the draft.

[0898] Specific prompt examples:

[0899] 1. Grammar error: 'He go to the library.' should be 'He goes to the library.'

[0900] 2. Inconsistent structure: The introduction is short, so the suggestion is, "The introduction is short, so we recommend adding more details."

[0901] 3. Incorrect citation: The citation format does not conform to APA style, so the suggestion is that "the citation format should be corrected to APA style."

[0902] As described above, the system of the present invention automatically proofreads papers, allowing researchers time to concentrate on their research and is extremely useful in improving the quality of papers.

[0903] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0904] Step 1:

[0905] A user uploads a draft of a paper

[0906] Input: The user uses the device's web browser to select a draft file of the paper (e.g., research paper.docx).

[0907] How it works: A user logs into the system, accesses the upload screen, selects a draft file, and clicks the upload button.

[0908] Output: The draft file is sent to the server.

[0909] Step 2:

[0910] The server receives and saves the draft

[0911] Input: Draft file submitted by user.

[0912] How it works: The server saves the received draft file in a specific directory, using a hash function to verify the integrity of the file.

[0913] Output: Draft files saved in a directory and their consistency check results.

[0914] Step 3:

[0915] The server checks the grammar using an AI engine

[0916] Input: Saved draft file.

[0917] How it works: The AI ​​engine on the server analyzes the document using natural language processing libraries (e.g., spaCy or Grammarly API). It detects grammatical errors in the draft and generates correction suggestions. For example, it generates a suggestion to change "He go to the library." to "He goes to the library."

[0918] Output: Grammar check results and suggested corrections.

[0919] Step 4:

[0920] The server checks the structure using an AI engine

[0921] Input: Saved draft file.

[0922] How it works: The server's AI engine uses trained models such as the BERT model to analyze the document structure (headings, paragraphs, sections, etc.) and check for consistency. For example, if the introduction is too short, it generates a suggestion such as "The introduction is short. We recommend adding more details."

[0923] Output: Results of the structure check and suggestions for improvement.

[0924] Step 5:

[0925] The server performs quote checking using an AI engine

[0926] Input: Saved draft file.

[0927] How it works: The server's AI engine uses rule-based NLP models and reference management software APIs (e.g., Zotero API) to check the accuracy of citation formatting. It checks whether the citation conforms to a specific citation style, such as APA style. For example, it generates a suggestion such as, "Your citation formatting should be corrected to APA style."

[0928] Output: Citation check results and suggested fixes.

[0929] Step 6:

[0930] The server generates and sends improvement suggestions

[0931] Input: Results of grammar checks, structure checks, and citation checks.

[0932] How it works: The server generates comprehensive improvement suggestions in JSON format based on the results of each check. The suggestions are sent to the user's device via HTTPS. When the user logs in to the system, the suggestions are displayed on the dashboard.

[0933] Output: Improvement suggestions sent to the user's device.

[0934] Step 7:

[0935] Users review and apply improvement suggestions

[0936] Input: Improvement suggestions sent by the server.

[0937] How it works: The user reviews the suggestions they receive and uses specialized editor software to revise the draft, for example by applying the provided grammar correction suggestions to revise the document.

[0938] Output: The modified draft file.

[0939] (Application example 1)

[0940] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0941] When content providers try to quickly generate high-quality documents, they face the problem of having to check grammar, structure, and citation formatting, which is time-consuming and laborious. It is also not easy to proofread documents to fit specific distribution formats. Therefore, there is a need for a method to efficiently proofread documents while maintaining the quality of the content.

[0942] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0943] In this invention, the server includes means for a user to upload a content draft from a terminal, means for the server to receive and store the uploaded draft, means for the server to call an AI engine for grammar check, detect grammatical errors, and generate correction suggestions, means for the server to analyze the structure of the content and generate improvement suggestions, means for the server to check the accuracy and format of citations and generate correction suggestions, means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal, and means for the user to review and apply the improvement suggestions received, thereby enabling content providers to efficiently create and distribute high-quality content.

[0944] Definitions of important words

[0945] "User" refers to the person who uploads draft content and receives suggested improvements for review and revision.

[0946] "Terminal" refers to a device used by a user to upload a content draft, and includes a smartphone, tablet, PC, etc.

[0947] "Server" means a central processing unit that receives and stores drafts of uploaded Content and performs grammar checks, structural analysis, and citation checks.

[0948] "AI engine" refers to a software system that uses artificial intelligence to detect grammatical errors and generate correction suggestions.

[0949] "Grammar checking" refers to the process of detecting grammatical errors in a content draft and making suggestions to fix them.

[0950] "Structural analysis" refers to the process of evaluating the logical organization of paragraphs, headings, sections, etc. throughout a content draft and making suggestions for improvement.

[0951] "Citation checking" refers to the process of reviewing citations in content for accuracy and formatting, and suggesting any necessary corrections.

[0952] "Improvement Suggestion" refers to a suggested revision of content that the server generates based on the results of grammar, structure, and citation checks and provides to the user.

[0953] "Distribution format" refers to the format or style required for a particular distribution channel or platform.

[0954] MODE FOR CARRYING OUT THE INVENTION

[0955] The present invention provides a system that allows users to upload drafts of content from devices such as smartphones, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the user. Specific embodiments for implementing the present invention are described in detail below.

[0956] System configuration

[0957] The system includes the following components:

[0958] 1. User Device

[0959] A device used by a user, such as a smartphone, tablet, or PC, that is used to upload drafts and review improvement suggestions.

[0960] 2. Server

[0961] The server is a central processing unit that receives and stores uploaded drafts and checks grammar, structure, and citations using an AI engine. The server runs using Python and natural language processing libraries (e.g., NLTK, TensorFlow).

[0962] 3. AI Engine

[0963] The AI ​​engine is a software system for grammar error detection, structural analysis, and citation checking, which generates suggestions for correcting grammatical errors and improving structure and citations.

[0964] Explanation of program processing

[0965] 1. User uploads draft content

[0966] Users log in to the system from their own devices, access the screen for uploading draft content, select a file, and click the upload button to send the draft to the server.

[0967] 2. The server receives the draft

[0968] The server receives the draft uploaded by the user, saves it in the specified directory, and checks the integrity of the file for proper processing.

[0969] 3. Grammar, structure, and citation checks using an AI engine

[0970] The AI ​​engine on the server starts up and first performs grammatical analysis. Then it analyzes the overall structure of the content (paragraphs, headings, etc.), and finally checks the citation style. For example, it generates a suggestion to correct the mistake "He go to the library" to "He goes to the library." In terms of structure, if the introduction is short, it will suggest "We recommend adding more detail to the introduction." Also, if the citation does not follow a specific style, it will point out that "the citation format needs to be corrected."

[0971] 4. Generate and submit improvement suggestions

[0972] The server generates improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's device. The improvement suggestions are sent to the contact information associated with the user's account or displayed on the user's dashboard when they log in to the system.

[0973] Specific examples

[0974] Suppose a user uploads a draft of a blog post to the system. The draft contains grammatical errors, inconsistent structure, and incomplete citations. The server first checks for these problems using an AI engine. Specifically, it generates suggestions to correct "He go to the library." to "He goes to the library.", suggests adding more detail to the short introduction, and further suggests correcting parts of the citation that do not comply with the syndication format. These suggestions are then sent to the user, who can review and apply them to improve the quality of the content.

[0975] Prompt Sentence Examples

[0976] Check the grammar, structure, and citations of blog posts uploaded by users and generate improvement suggestions as follows:

[0977] Grammar error: Change "He go to the library." to "He goes to the library."

[0978] Poor structure: "The introduction is short, so I suggest adding more details."

[0979] Incorrect citation: "Please correct your citation format."

[0980] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0981] Program processing flow

[0982] Step 1:

[0983] The user uploads a draft of content from the terminal. The input is the draft file specified by the user, and the output is the terminal sending the draft file to the server. When the user clicks the upload button, the draft file is sent from the terminal to the server.

[0984] Step 2:

[0985] The server receives the uploaded draft and saves it in the specified directory. The input is the draft file sent by the user, and the output is the draft file to be saved. The server first verifies the integrity of the draft file and saves it in the appropriate directory.

[0986] Step 3:

[0987] The server invokes the AI ​​engine to perform grammatical analysis of the draft. The input is the saved draft file, and the output is the results of grammatical error detection. The server inputs the saved draft file into the AI ​​engine and detects grammatical errors using a natural language processing library (NLTK). It generates a suggestion to correct the mistake "He go to the library." to "He goes to the library."

[0988] Step 4:

[0989] The server uses an AI engine to analyze the structure of the draft. The input is the saved draft file, and the output is structural improvement suggestions. The server evaluates the structure of the draft, including paragraphs, headings, and sections, to ensure consistency. For example, if the introduction is short, the server will make a suggestion such as, "We recommend adding more detail to the introduction."

[0990] Step 5:

[0991] The server uses an AI engine to check the citations in the draft. The input is the saved draft file, and the output is suggestions for correcting the citations and formatting. The server inspects the citations in the draft to ensure they conform to a specific style (e.g., APA style). If the citations do not follow the style, it suggests, "Your citation format needs to be revised."

[0992] Step 6:

[0993] The server generates improvement suggestions based on the results of each grammar, structure, and citation check and sends them to the user's device. The input is the check results from the AI ​​engine, and the output is the generated improvement suggestions. The server integrates the results of each check and generates improvement suggestions. These suggestions are then sent to the user's device and displayed on the dashboard or sent to the corresponding contact.

[0994] Step 7:

[0995] The user reviews and applies the improvement suggestions received. The input is the improvement suggestions sent from the server, and the output is the revised draft. The user checks the improvement suggestions on the terminal, adds necessary corrections to the draft, and re-edits it.

[0996] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0997] The present invention combines an emotion engine with a system for automatically proofreading a paper draft. This allows the system to recognize the user's emotional state and adjust the interface and the method of presenting improvement suggestions based on that state. Specific embodiments for implementing the present invention are described below.

[0998] System configuration

[0999] The system consists of four main components: the user, the device, the server, and the emotion engine. Users upload drafts of their papers via their devices, and the emotion engine recognizes their emotional state in real time. The server stores the received drafts and uses an AI engine to check grammar, structure, and citations, generating improvement suggestions. The emotion engine adjusts the interface and generates feedback messages based on the user's emotional data.

[1000] Explanation of program processing

[1001] 1. User uploads a draft

[1002] Using the terminal, the user selects the draft file from the file selection screen and clicks the upload button, which sends the file to the server.

[1003] During this process, the emotion engine analyzes the user's facial expressions and voice to recognize their current emotional state in real time.

[1004] 2. The server receives the draft

[1005] The server stores the uploaded draft and verifies the integrity of the file.

[1006] The emotion engine transmits the acquired emotion data to the server, which then stores the data.

[1007] 3. Grammar check by AI engine

[1008] The server's AI engine analyzes the draft for grammatical errors and generates correction suggestions.

[1009] The emotion engine adjusts the way suggestions are worded based on the user's emotional state, for example, using gentler language if the user is stressed.

[1010] 4. Structure check using AI engine

[1011] The server uses an AI engine to analyze the structure of the paper and generate suggestions regarding consistency and logic.

[1012] If the emotion engine determines that the user is tired, it will provide a concise summary of suggestions.

[1013] 5. Citation check using AI engine

[1014] The server's AI engine checks the citation format and generates appropriate correction suggestions.

[1015] The system adjusts which correction suggestions are given priority depending on the user's emotional state.

[1016] 6. Generate and submit improvement suggestions

[1017] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks, adjusting the wording and order of the suggestions taking into account data from the sentiment engine.

[1018] The final improvement proposals are sent to the user's device via the method selected by the user (email or dashboard display).

[1019] 7. Review and apply user improvement suggestions

[1020] The user receives and reviews the improvement suggestions via their device, while the emotion engine continues to monitor the user's emotional state and displays support messages as needed.

[1021] The user applies the suggested corrections and re-edits the draft, and the emotion engine supports the user in completing the final version while reducing stress.

[1022] Specific examples

[1023] Suppose a user uploads a draft of a research paper to the system. If the emotion engine detects that the user is nervous, it displays the message, "Relax and proceed. We'll help you." The server receives the draft and checks its grammar, structure, and citations. The engine finds an error in the sentence, "He go to the library." It generates a suggestion to correct it to, "He goes to the library." If the user is feeling even more fatigued, the suggestion is simplified and a simple suggestion such as, "The introduction is short, please add more details."

[1024] In this way, the system of the present invention automatically proofreads papers while taking into account the user's emotional state and provides optimal suggestions for improvement, helping researchers to write higher quality papers without feeling stressed.

[1025] The processing flow will be explained below.

[1026] Step 1:

[1027] The user uploads a draft of their paper using their device. They open a file selection screen and select the draft file. Then, by clicking the upload button, the selected file is sent to the server. At the same time, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their current emotional state.

[1028] Step 2:

[1029] The server saves the draft file received from the user in the specified directory and verifies the integrity of the file. After the file is saved correctly, the server saves the emotion data and proceeds to the next processing step.

[1030] Step 3:

[1031] The server launches the AI ​​engine to check grammar. The AI ​​engine reads the saved draft file and analyzes grammatical errors. For example, it finds the mistake "He go to the library." and generates a suggestion to correct it to "He goes to the library." If the emotion engine detects the user's stress, the AI ​​engine's output will use gentler expressions.

[1032] Step 4:

[1033] The server uses an AI engine to analyze the structure of the paper. It analyzes the arrangement of headings, paragraphs, and sections in the saved draft and checks for consistency. For example, it generates suggestions such as, "The introduction is short, so we recommend adding more details." If the emotion engine determines that the user is tired, it will display a concise summary of the suggestions.

[1034] Step 5:

[1035] The server uses an AI engine to check the accuracy and format of citations. It analyzes the citation format in the draft and checks whether it conforms to a specific citation style (e.g., APA style). If there are any deficiencies, it generates suggestions such as "Please revise the citation format to APA style." It prioritizes important revision suggestions based on the emotional state of the author.

[1036] Step 6:

[1037] The server generates improvement suggestions based on the results of grammar, structure, and citation checks. Each suggestion is summarized in an easy-to-read report. The wording and order of suggestions are adjusted taking into account data from the sentiment engine. If a user expressed negative sentiment during upload, subsequent suggestions may include encouraging content.

[1038] Step 7:

[1039] The server sends the generated improvement proposals and reports to the user's device either via email address associated with the user's account or displayed on the user's dashboard when they log in to the system. The tone of the proposals and the content of the message are adapted based on the emotional data.

[1040] Step 8:

[1041] The user reviews the improvement suggestions on their device. They confirm the suggestions and revise the draft based on them. The emotion engine monitors the user's emotional state during the review and displays encouraging or supportive messages as needed. For example, if the user is confused, the engine displays a message such as, "Don't worry, we'll provide advice as needed."

[1042] The above is a specific processing flow in the system of the present invention.

[1043] Example 2

[1044] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1045] While conventional paper proofreading systems can check grammar and structure, they have a problem in that they cannot make suggestions that take into account the user's emotional state. This causes problems such as users feeling stressed during the proofreading process and not being able to effectively utilize the suggestions for improvement.

[1046] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1047] In this invention, the server includes means for an emotion engine to recognize a user's emotion in real time and transmit that data to the server, means for the emotion engine to adjust the expression method and order of improvement suggestions based on the user's emotion data, and means for the server to generate comprehensive improvement suggestions based on the results of grammar, structure, and citation checks and transmit them to the user's terminal. This makes it possible to provide optimal improvement suggestions that take the user's emotional state into consideration.

[1048] "User" means any person or entity that uses the System to upload drafts of papers and receive suggestions for improvement.

[1049] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet.

[1050] "Server" means a remote computer that receives and stores uploaded drafts, performs various checks, and generates and submits improvement suggestions.

[1051] An "emotion engine" is software or hardware that analyzes a user's facial expressions and voice in real time to recognize their emotional state.

[1052] An "AI engine" is an artificial intelligence program that checks grammar, structure, and citations and generates suggestions for improvement.

[1053] "Grammar check" refers to the process of detecting grammatical errors in an uploaded draft and making correction suggestions.

[1054] A "structural check" is a process of analyzing the overall structure and logic of a paper and making suggestions for improvement regarding consistency and points of argument.

[1055] "Citation checking" is the process of verifying that citations in a paper are accurate and follow proper formatting, and making suggested revisions.

[1056] "Improvement Suggestions" are suggestions for improving the quality of a user's draft, generated based on the results of grammar, structure, and citation checks.

[1057] An "email address" is one of the means of communication associated with a user's account, and is an address used to receive information such as improvement suggestions.

[1058] The present invention is a system that allows users to upload a draft of a paper and receive optimal improvement suggestions using automatic proofreading and an emotion engine. Specific embodiments will be described step by step below.

[1059] Hardware and software used

[1060] User devices: computers, smartphones, tablets, etc. Through these devices, users upload drafts and view improvement suggestions.

[1061] Server: A remote computer that stores drafts, analyzes them, and generates improvement suggestions.

[1062] Emotion engine: Software or hardware that analyzes a user's facial expressions and voice in real time to recognize their emotional state. Examples include facial recognition technology and voice analysis technology.

[1063] AI Engine: An artificial intelligence program that checks grammar, structure, and citations. Examples include grammar analysis tools (e.g., Grammarly API) and machine learning models (e.g., BERT, GPT-3).

[1064] Data processing and calculation

[1065] User uploads draft

[1066] The user selects a draft of the paper from the device and uploads it to the server, which then transmits the data to the server using HTTP or HTTPS protocols.

[1067] The server receives and saves the draft

[1068] The server receives and stores the uploaded drafts, checking the integrity of the files and saving them in the appropriate folders.

[1069] Emotion recognition by emotion engine

[1070] The emotion engine analyzes the user's facial expressions and voice in real time to generate emotion data, which is then sent to a server via a REST API or similar and stored.

[1071] Grammar check by AI engine

[1072] The server passes the saved draft to an AI engine that analyzes it for grammatical errors. It uses grammar analysis tools to list the mistakes and suggest corrections.

[1073] Structural check using AI engine

[1074] The AI ​​engine analyzes the structure of a paper and generates suggestions for consistency and logic. For example, if a paragraph is unnaturally connected, it will suggest, "Merge this paragraph with the previous one."

[1075] Citation check by AI engine

[1076] The server uses an AI engine to check whether the citation format is correct and generate suggestions for corrections, such as "Please correct the citation according to APA style."

[1077] Generate comprehensive improvement suggestions

[1078] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks. It adjusts the wording and order of the suggestions based on data from the emotion engine. For example, it uses gentler wording when the user is feeling stressed.

[1079] Submit an improvement suggestion

[1080] The server sends the generated improvement suggestions to the user's device, either via email or as a dashboard display.

[1081] Review and apply user improvement suggestions

[1082] The user can review the improvement suggestions received through their device and apply any necessary corrections. The emotion engine also monitors the user's emotional state and displays supportive messages such as "Please stay calm and proceed."

[1083] Specific examples

[1084] A user uploads a draft of a research paper to the system. If the emotion engine detects that the user is nervous, it may display the message, "Relax and proceed. We'll help you." The server receives the draft and checks it for grammar, structure, and citations. The engine finds the error, "He go to the library." It generates a suggestion to correct it to, "He goes to the library." Furthermore, if the user is feeling fatigued, the suggestion may be simplified, with a simple suggestion such as, "The introduction is short; please add more detail."

[1085] Prompt Sentence Examples

[1086] "Generate timely emotional support messages for stressed users who upload their paper drafts."

[1087] "Write a concise suggestion for improving the paper structure for a user who is experiencing fatigue."

[1088] In this way, this system automatically proofreads papers while taking into account the user's emotional state and provides optimal improvement suggestions, thereby improving the quality of papers while reducing user stress.

[1089] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1090] Step 1:

[1091] User uploads draft

[1092] Input: The user selects the paper draft (e.g., a text file) on the file selection screen of the terminal and clicks the upload button.

[1093] Processing: The terminal sends the user's selected draft file to the server using HTTP or HTTPS protocol.

[1094] Output: A draft file is sent to the server.

[1095] Step 2:

[1096] The server receives and saves the draft

[1097] Input: The server receives the draft file sent from the terminal.

[1098] Processing: Saving the received file in a specific folder and checking the file integrity, for example, whether the file is corrupted and whether it was transferred completely.

[1099] Output: The draft file is saved on the server.

[1100] Step 3:

[1101] The emotion engine recognizes the user's emotions in real time and sends them to the server.

[1102] Input: Facial and voice data when users upload their drafts.

[1103] Processing: The emotion engine uses facial expression recognition software and voice analysis tools to analyze the user's emotional state in real time. The analysis results are converted into data and sent to a server using a REST API or similar.

[1104] Output: The user's emotional data (e.g., tension, stress, fatigue, etc.) is sent to the server.

[1105] Step 4:

[1106] The server's AI engine starts grammar checking

[1107] Input: Draft file saved on the server.

[1108] Processing: The server calls a grammar analysis tool (e.g., Grammarly API) to analyze the draft for grammar errors. It detects grammar errors and generates correction suggestions for each one.

[1109] Output: A list of grammar errors and suggested fixes for them.

[1110] Step 5:

[1111] The server's AI engine begins structure checks

[1112] Input: Draft file saved on the server.

[1113] Processing: The AI ​​engine analyzes the overall structure of the draft and generates suggestions for improvement regarding consistency and logic. For example, if a paragraph is not connected properly, it will suggest, "Merge this paragraph with the previous one."

[1114] Output: A list of structural errors and suggestions for improving them.

[1115] Step 6:

[1116] The server's AI engine starts checking quotes

[1117] Input: Draft file saved on the server.

[1118] Processing: The AI ​​engine analyzes the citations in the draft, checking whether they follow the proper formatting and generating correction suggestions if there are any deficiencies.

[1119] Output: A list of citation errors and suggested fixes.

[1120] Step 7:

[1121] Generate comprehensive improvement suggestions

[1122] Input: The results of grammar, structure, and citation checks, as well as user sentiment data sent from the sentiment engine.

[1123] Processing: The server integrates the results of each check and adjusts the wording and order of the improvement suggestions based on the emotional data. For example, if the user is feeling stressed, the suggestions will be presented in a gentler way and in an order that will reduce the burden.

[1124] Output: Comprehensive improvement suggestions.

[1125] Step 8:

[1126] The server sends improvement suggestions to the user's device

[1127] Input: Overall improvement suggestions.

[1128] Processing: The server sends the generated improvement suggestions to the user's email address or dashboard.

[1129] Output: Improvement suggestions that can be viewed on the user's device.

[1130] Step 9:

[1131] Review and apply user improvement suggestions

[1132] Input: Improvement suggestions received from the server.

[1133] Processing: The user reviews the received improvement suggestions and applies them to the draft if necessary. The emotion engine continues to monitor the user's emotional state and displays supportive messages such as "Keep calm and proceed."

[1134] Output: A draft with the corrections applied.

[1135] (Application example 2)

[1136] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1137] In production sites such as factories, employees are required to work efficiently while avoiding excessive stress and fatigue. However, current technology makes it difficult to monitor employees' emotional states in real time and provide appropriate feedback and improvement suggestions accordingly. In addition, there is a lack of means to adjust work suggestions based on employees' emotional states, making it a challenge to improve work efficiency while managing employee stress.

[1138] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1139] In this invention, the server includes: means for a user to upload a draft of a paper from a terminal; means for the server to receive and store the uploaded draft; means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; means for the server to analyze the structure of the paper and generate improvement suggestions; means for the server to check the accuracy and format of citations and generate correction suggestions; means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; means for the user to review and apply the improvement suggestions received; means for recognizing the user's emotional state using an emotion engine and adjusting the interface and the expression method of the suggestions based on that state; means for monitoring work progress in real time and generating feedback messages based on the emotion engine; and means for adjusting the priority and expression method of the improvement suggestions based on the emotional state. This makes it possible to provide appropriate feedback and improvement suggestions in real time that take into account the emotional state of employees, thereby improving work efficiency and managing stress at the same time.

[1140] "User" refers to a person who uses the system to upload a draft paper and receive suggestions for improvement.

[1141] "Terminal" refers to the device used by a User to upload a draft of their paper.

[1142] "Server" refers to a centralized computer system that receives and stores drafts uploaded by users and performs various analyses.

[1143] "AI Engine" refers to an artificial intelligence system installed on a server that detects grammatical errors and generates correction suggestions.

[1144] An "emotion engine" is a system that recognizes a user's emotional state in real time and adjusts the interface and presentation of suggestions based on that data.

[1145] "Grammar check" refers to the AI ​​engine's process of analyzing the sentence structure in the draft, detecting grammatical errors, and suggesting corrections.

[1146] "Structure" refers to the organization, arrangement, and development of paragraphs of an entire paper or document.

[1147] "Citations" refer to references within a paper to other studies or sources.

[1148] "Interface" refers to the operation screen and display method that allows users to interact with the system.

[1149] "Feedback message" refers to a message that is generated by the emotion engine based on the user's emotional state to support the progress of work and mood.

[1150] "Real-time monitoring" refers to instantly monitoring the progress of work and the user's emotional state, and responding immediately if necessary.

[1151] "Improvement suggestions" refer to corrections and suggestions regarding grammar, structure, citations, etc. that the AI ​​engine generates based on the analysis results.

[1152] This invention relates to a system that improves the work efficiency and mental health of employees in factory production. The system consists of four main components: smart glasses worn by the user, a server, an AI engine, and an emotion engine.

[1153] System configuration

[1154] 1. Users

[1155] The user is a factory worker who wears smart glasses to perform his / her work. The smart glasses are equipped with a camera, a display, and a network module.

[1156] 2. Smart Glasses

[1157] The smart glasses are equipped with a camera that captures the user's facial expressions and work status in real time. The emotion engine analyzes the user's emotional state and sends the results to the server. Feedback messages and improvement suggestions from the server are displayed on the display.

[1158] 3. Server

[1159] The server is the main hub for the following operations:

[1160] Receives and stores data uploaded by users.

[1161] An AI engine is used to perform grammar checks, structural analysis, and citation verification.

[1162] Use data from the emotion engine to tailor the wording of feedback messages and improvement suggestions.

[1163] The server is expected to be built on a general cloud computing environment (for example, AWS or Google Cloud Platform).

[1164] 4. AI Engine

[1165] The AI ​​engine is equipped with the technology to perform the following processes:

[1166] Grammar Check: Uses NLP (Natural Language Processing) techniques to detect grammatical errors and generate correction suggestions.

[1167] Structural analysis: Analyze the organization of an entire paper or document and generate improvement suggestions.

[1168] Citation Check: Checks the accuracy and format of citations in your paper and generates suggested revisions.

[1169] The AI ​​engine is developed using technologies such as TensorFlow and OpenCV.

[1170] 5. Emotion Engine

[1171] The emotion engine recognizes the user's emotional state and adjusts the presentation of the interface and suggestions based on that state.

[1172] Emotion analysis: Analyzes the user's facial expression data captured from the smart glasses camera to assess their emotional state.

[1173] Feedback generation: Generate appropriate feedback messages for users based on emotion data.

[1174] The emotion engine is built using, for example, the Affdex SDK.

[1175] Specific examples

[1176] Suppose an employee is performing assembly work. If the emotion engine recognizes the employee's fatigue, the smart glasses will display a message saying, "Please take a short break." If the AI ​​engine detects a mistake in the work, the smart glasses will display a suggestion saying, "The screws appear to be loose. Please check again." In this way, the system of the present invention can provide appropriate feedback and improvement suggestions in real time, taking into account the employee's emotional state.

[1177] Prompt Sentence Examples

[1178] Desired function: Support for assembly work in factories

[1179] Main features: Real-time monitoring of work content, recognition of emotional state, and provision of improvement suggestions

[1180] Technologies used: Sentiment analysis with Affdex SDK, working analysis with TensorFlow and OpenCV

[1181] Input data: facial expression data of employees, video data of their work

[1182] Output data: Feedback messages, improvement suggestions

[1183] Targeted effects: Improved work efficiency and quality, reduced employee stress

[1184] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1185] Step 1: User puts on smart glasses

[1186] A user puts on smart glasses to start work in the factory. The camera in the smart glasses captures the user's facial expressions and work status in real time. The input is the user's facial expression data and work video data, and the output is that these data are sent to the server.

[1187] Step 2: Emotional state analysis by the emotion engine

[1188] The server receives the facial expression data sent from the smart glasses. The emotion engine then analyzes it and evaluates the user's emotional state (e.g., fatigue, stress, or relaxation). The input is the facial expression data, and the output is the evaluation result of the emotional state. The emotion engine uses the Affdex SDK to analyze the facial expression data.

[1189] Step 3: Real-time operation monitoring

[1190] The server receives video data of the work sent from the smart glasses. The AI ​​engine analyzes the video data to check the progress of the work and detect errors and areas for improvement. The input is the video data, and the output is the work status and error detection results. The AI ​​engine performs analysis using TensorFlow and OpenCV.

[1191] Step 4: Generate feedback and improvement suggestions

[1192] The server integrates the emotional state evaluation results from the emotion engine and the work situation analysis results from the AI ​​engine. Then, based on the emotional state, it generates appropriate feedback messages and improvement suggestions for the user. The inputs are the emotional state evaluation results and the work situation analysis results, and the output is the feedback messages and improvement suggestions.

[1193] Step 5: Viewing feedback messages

[1194] The server sends the generated feedback messages and improvement suggestions to the smart glasses display. The user receives this feedback in real time and improves their work. The input is the feedback messages and improvement suggestions, and the output is the feedback displayed on the smart glasses display.

[1195] Step 6: User improvement and data feedback

[1196] The user improves their work based on the feedback from the smart glasses. The improved work data is again captured by the smart glasses' camera and sent to the server. The input is the improved work data, and the output is the data sent to the server. This feedback loop ensures that the latest data is always analyzed, leading to continuous work improvement.

[1197] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1198] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1199] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1200] [Fourth embodiment]

[1201] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1202] 7, a 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.

[1203] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1204] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1205] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1206] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1207] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1208] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1209] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1210] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1211] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1212] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1213] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1214] The present invention provides a system that allows a user to upload a draft of a paper, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the user. Specific embodiments for implementing the present invention are described in detail below.

[1215] System configuration

[1216] The system consists of three main components: users, devices, and a server. Users use their devices to upload drafts of their papers, receive suggestions for improvement, and review and revise them. The server receives and stores the uploaded drafts, checks grammar, structure, and citations using an AI engine, and generates suggestions for improvement and sends them to the users' devices.

[1217] Explanation of program processing

[1218] 1. User uploads a draft

[1219] Users log in to the system from their own devices, access the screen for uploading a paper draft, select a file, and click the upload button to send the draft to the server.

[1220] 2. The server receives the draft

[1221] The server receives the draft uploaded by the user, saves it in the specified directory, and checks the integrity of the file for proper processing.

[1222] 3. Grammar check by AI engine

[1223] The AI ​​engine in the server will then analyze the draft for grammatical errors, generating suggestions to correct, for example, the mistake "He go to the library." to "He goes to the library."

[1224] 4. Structure check using AI engine

[1225] The server's AI engine analyzes the structure of a paper (headings, paragraphs, sections, etc.) and checks the consistency of the entire paper. For example, if the introduction is too short, it will make suggestions such as, "The introduction is too short. We recommend adding more details."

[1226] 5. Citation check using AI engine

[1227] The server's AI engine inspects citations in a paper to ensure they comply with a specific citation style. For example, if a citation does not follow APA style, it will suggest, "Your citation format should be revised to APA style."

[1228] 6. Generate and submit improvement suggestions

[1229] The server generates improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's device. The improvement suggestions are sent to the email address associated with the user's account or displayed on the user's dashboard when they log in to the system.

[1230] 7. Review and apply user improvement suggestions

[1231] The user reviews the improvement suggestions sent by the server, revises the draft as necessary, and re-edits the paper based on the reviewed suggestions to complete the final version.

[1232] Specific examples

[1233] For example, suppose a user uploads a draft of a research paper to the system. The draft contains grammatical errors, inconsistent structure, and incomplete citations. The server first checks for these issues using an AI engine, correcting "He go to the library" to "He goes to the library," noting that the introduction is too short, and generating suggestions for correcting citations that do not conform to APA style. These suggestions are then sent to the user, who can review and apply them to improve the quality of their paper.

[1234] As described above, the system of the present invention automatically proofreads papers, allowing researchers time to concentrate on their research and is extremely useful in improving the quality of papers.

[1235] The processing flow will be explained below.

[1236] Step 1:

[1237] A user uploads a draft of a paper using a terminal. The user opens the file selection screen, selects the draft file, and clicks the "Upload" button. This operation sends the draft file to the server.

[1238] Step 2:

[1239] The server saves the draft file received from the user in the specified directory, and checks the integrity of the file. After confirming that the file has been saved correctly, the server proceeds to the next processing step.

[1240] Step 3:

[1241] The server launches the AI ​​engine for grammar check. The server passes the saved draft file to the AI ​​engine, which analyzes it for grammatical errors. For example, it finds the sentence "He go to the library." and generates a suggestion to correct it to "He goes to the library."

[1242] Step 4:

[1243] The server uses an AI engine to check the structure of the paper. It analyzes the arrangement of headings, paragraphs, and sections in the draft to ensure consistency. For example, if the introduction is too short, it generates a suggestion that the introduction should be longer.

[1244] Step 5:

[1245] The server checks citations using an AI engine. It analyzes the citation format in the draft and checks whether it conforms to a specific citation style (e.g., APA style). If there are any deficiencies, it generates a suggestion to "revise the citation format to APA style."

[1246] Step 6:

[1247] The server generates improvement suggestions based on the results of the grammar, structure, and citation checks. Each suggestion is summarized in an easy-to-read report. The server prepares this report and moves on to the next step.

[1248] Step 7:

[1249] The server sends the generated improvement suggestions and reports to the user's device, either to the email address associated with the user's account or displayed on the dashboard when the user accesses the system.

[1250] Step 8:

[1251] The user reviews the improvement suggestions on their device. The user checks the received suggestions and modifies the draft as necessary. For example, they fix the problematic parts and add new content. Once the modifications are complete, the user saves the final version of the paper and, if necessary, uploads it back to the system.

[1252] The above is a specific processing flow in the system of the present invention.

[1253] Example 1

[1254] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1255] Conventional paper proofreading systems have the drawback of being time-consuming and labor-intensive, as they require manual checks of grammar, structure, and citations. Furthermore, they often fail to guarantee that proofreading conforms to a specific citation style or secure data transmission. Furthermore, the formats of improvement suggestions received by users are not standardized, making reviewing and applying them difficult.

[1256] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1257] In this invention, the server includes: a means for a user to upload a document draft from a terminal; a means for the server to receive and store the uploaded draft; a means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; a means for the server to analyze the document structure and generate improvement suggestions; a means for the server to check the accuracy and format of citations and generate correction suggestions; a means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; a means for the server to review and apply the improvement suggestions received by the user; a means for the server to use a hash function to verify integrity when receiving files; a means for the server to generate suggestions from the AI ​​engine in JSON format; a means for the server to securely transmit and receive data using the HTTPS protocol; and a means for the terminal to use editor software to review and apply the improvement suggestions. This enables automated and efficient paper proofreading, secure data transmission and reception, and the provision of unified improvement suggestions.

[1258] A "user" is a person who uploads draft documents from a terminal and has the role of reviewing and applying suggestions.

[1259] "Terminal" means an electronic device that a User uses to access the System, upload draft documents, and receive and review improvement suggestions.

[1260] The "server" is a device that has the function of storing drafts received from users, checking grammar, structure, and citations, generating improvement suggestions, and sending them to the user's terminal.

[1261] A "document draft" is an incomplete document that a user uploads to the system and that is checked for grammar, structure, and citations.

[1262] "Grammar checking" is the process of detecting grammar errors in a document and generating appropriate correction suggestions.

[1263] "AI Engine" refers to the artificial intelligence models and algorithms used to review documents and generate suggestions.

[1264] "Document structure" refers to the hierarchical and logical arrangement of the document as a whole, including headings, paragraphs, sections, etc.

[1265] "Accuracy of citations" means that citations within a document are based on appropriate sources and are expressed accurately.

[1266] "Citation formatting" refers to the proper citations in a document following a particular formatting style (e.g., APA style).

[1267] "Improvement suggestions" are recommendations for correcting and improving a document, generated based on the results of checks on grammar, structure, citations, etc.

[1268] A "hash function" is an algorithm used to verify the integrity of a file, generating a fixed-length output value (hash value) from input data.

[1269] "JSON" is a lightweight data interchange format for representing data in text form and is used to generate and transmit proposals.

[1270] The "HTTPS protocol" is a protocol used to send and receive data securely over the Internet and provides data encryption.

[1271] "Editor software" means application software that enables a user to create, edit, or modify documents.

[1272] The present invention relates to a system that allows users to upload drafts of their papers, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the users. Specific embodiments of the system are described below.

[1273] System configuration

[1274] The system consists of three main components: users, devices, and a server. Users use their devices to upload drafts of their papers, receive suggestions for improvement, and review and revise them. The server receives and stores the uploaded drafts, checks grammar, structure, and citations using an AI engine, and generates suggestions for improvement and sends them to the users' devices.

[1275] Hardware and software used

[1276] This system uses the following hardware and software:

[1277] Terminal: Electronic device (PC, tablet, smartphone, etc.) through which a user accesses the system

[1278] Server: The central computer that processes the data, stores the drafts, runs the AI ​​engine, and generates and sends proposals.

[1279] Software: The following software is used:

[1280] Web Browser: Used by users to access the system and upload drafts.

[1281] AI engine: Natural language processing libraries (e.g., spaCy or Grammarly API) and pre-trained models (e.g., BERT model)

[1282] Data transfer protocol: HTTPS protocol is used to encrypt and securely transmit data.

[1283] Data format: Improvement suggestions are generated in JSON format and sent to the user's device.

[1284] Detailed explanation of the process

[1285] First, a user logs in to the system using a web browser on their device and uploads a draft of their paper. The server receives the draft and saves it in a specified directory. At this time, the server verifies the integrity of the file using a hash function to confirm that the file has been received correctly.

[1286] The server then launches an AI engine to check the document's grammar. The AI ​​engine uses natural language processing libraries to detect grammatical errors and generate correction suggestions. Similarly, the AI ​​engine analyzes the document's structure, evaluating the consistency of headings, paragraphs, sections, etc., and generates improvement suggestions. In addition, the AI ​​engine checks the citation format to ensure it conforms to a specific citation style (e.g., APA style).

[1287] Finally, the server compiles improvement suggestions based on the results of these checks and sends them to the user's device. The user reviews the improvement suggestions and revise the draft using dedicated editor software. Finally, the user improves the document based on the suggestions and finalizes it.

[1288] Specific examples

[1289] For example, if a user uploads a draft of a research paper containing the grammatical error "He go to the library," the server will use an AI engine to generate suggestions to correct this sentence to "He goes to the library." Furthermore, if the introduction is too short, the server will suggest, "The introduction is short, so we recommend adding more details," and if the citations do not conform to APA style, the server will suggest, "The citation format should be corrected to APA style." These suggestions are sent to the user in JSON format, who can review and revise the draft.

[1290] Specific prompt examples:

[1291] 1. Grammar error: 'He go to the library.' should be 'He goes to the library.'

[1292] 2. Inconsistent structure: The introduction is short, so the suggestion is, "The introduction is short, so we recommend adding more details."

[1293] 3. Incorrect citation: The citation format does not conform to APA style, so the suggestion is that "the citation format should be corrected to APA style."

[1294] As described above, the system of the present invention automatically proofreads papers, allowing researchers time to concentrate on their research and is extremely useful in improving the quality of papers.

[1295] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1296] Step 1:

[1297] A user uploads a draft of a paper

[1298] Input: The user uses the device's web browser to select a draft file of the paper (e.g., research paper.docx).

[1299] How it works: A user logs into the system, accesses the upload screen, selects a draft file, and clicks the upload button.

[1300] Output: The draft file is sent to the server.

[1301] Step 2:

[1302] The server receives and saves the draft

[1303] Input: Draft file submitted by user.

[1304] How it works: The server saves the received draft file in a specific directory, using a hash function to verify the integrity of the file.

[1305] Output: Draft files saved in a directory and their consistency check results.

[1306] Step 3:

[1307] The server checks the grammar using an AI engine

[1308] Input: Saved draft file.

[1309] How it works: The AI ​​engine on the server analyzes the document using natural language processing libraries (e.g., spaCy or Grammarly API). It detects grammatical errors in the draft and generates correction suggestions. For example, it generates a suggestion to change "He go to the library." to "He goes to the library."

[1310] Output: Grammar check results and suggested corrections.

[1311] Step 4:

[1312] The server checks the structure using an AI engine

[1313] Input: Saved draft file.

[1314] How it works: The server's AI engine uses trained models such as the BERT model to analyze the document structure (headings, paragraphs, sections, etc.) and check for consistency. For example, if the introduction is too short, it generates a suggestion such as "The introduction is short. We recommend adding more details."

[1315] Output: Results of the structure check and suggestions for improvement.

[1316] Step 5:

[1317] The server performs quote checking using an AI engine

[1318] Input: Saved draft file.

[1319] How it works: The server's AI engine uses rule-based NLP models and reference management software APIs (e.g., Zotero API) to check the accuracy of citation formatting. It checks whether the citation conforms to a specific citation style, such as APA style. For example, it generates a suggestion such as, "Your citation formatting should be corrected to APA style."

[1320] Output: Citation check results and suggested fixes.

[1321] Step 6:

[1322] The server generates and sends improvement suggestions

[1323] Input: Results of grammar checks, structure checks, and citation checks.

[1324] How it works: The server generates comprehensive improvement suggestions in JSON format based on the results of each check. The suggestions are sent to the user's device via HTTPS. When the user logs in to the system, the suggestions are displayed on the dashboard.

[1325] Output: Improvement suggestions sent to the user's device.

[1326] Step 7:

[1327] Users review and apply improvement suggestions

[1328] Input: Improvement suggestions sent by the server.

[1329] How it works: The user reviews the suggestions they receive and uses specialized editor software to revise the draft, for example by applying the provided grammar correction suggestions to revise the document.

[1330] Output: The modified draft file.

[1331] (Application example 1)

[1332] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1333] When content providers try to quickly generate high-quality documents, they face the problem of having to check grammar, structure, and citation formatting, which is time-consuming and laborious. It is also not easy to proofread documents to fit specific distribution formats. Therefore, there is a need for a method to efficiently proofread documents while maintaining the quality of the content.

[1334] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1335] In this invention, the server includes means for a user to upload a content draft from a terminal, means for the server to receive and store the uploaded draft, means for the server to call an AI engine for grammar check, detect grammatical errors, and generate correction suggestions, means for the server to analyze the structure of the content and generate improvement suggestions, means for the server to check the accuracy and format of citations and generate correction suggestions, means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal, and means for the user to review and apply the improvement suggestions received, thereby enabling content providers to efficiently create and distribute high-quality content.

[1336] Definitions of important words

[1337] "User" refers to the person who uploads draft content and receives suggested improvements for review and revision.

[1338] "Terminal" refers to a device used by a user to upload a content draft, and includes a smartphone, tablet, PC, etc.

[1339] "Server" means a central processing unit that receives and stores drafts of uploaded Content and performs grammar checks, structural analysis, and citation checks.

[1340] "AI engine" refers to a software system that uses artificial intelligence to detect grammatical errors and generate correction suggestions.

[1341] "Grammar checking" refers to the process of detecting grammatical errors in a content draft and making suggestions to fix them.

[1342] "Structural analysis" refers to the process of evaluating the logical organization of paragraphs, headings, sections, etc. throughout a content draft and making suggestions for improvement.

[1343] "Citation checking" refers to the process of reviewing citations in content for accuracy and formatting, and suggesting any necessary corrections.

[1344] "Improvement Suggestion" refers to a suggested revision of content that the server generates based on the results of grammar, structure, and citation checks and provides to the user.

[1345] "Distribution format" refers to the format or style required for a particular distribution channel or platform.

[1346] MODE FOR CARRYING OUT THE INVENTION

[1347] The present invention provides a system that allows users to upload drafts of content from devices such as smartphones, automatically checks the grammar, structure, and citations on a server, and generates and provides improvement suggestions to the user. Specific embodiments for implementing the present invention are described in detail below.

[1348] System configuration

[1349] The system includes the following components:

[1350] 1. User Device

[1351] A device used by a user, such as a smartphone, tablet, or PC, that is used to upload drafts and review improvement suggestions.

[1352] 2. Server

[1353] The server is a central processing unit that receives and stores uploaded drafts and checks grammar, structure, and citations using an AI engine. The server runs using Python and natural language processing libraries (e.g., NLTK, TensorFlow).

[1354] 3. AI Engine

[1355] The AI ​​engine is a software system for grammar error detection, structural analysis, and citation checking, which generates suggestions for correcting grammatical errors and improving structure and citations.

[1356] Explanation of program processing

[1357] 1. User uploads draft content

[1358] Users log in to the system from their own devices, access the screen for uploading draft content, select a file, and click the upload button to send the draft to the server.

[1359] 2. The server receives the draft

[1360] The server receives the draft uploaded by the user, saves it in the specified directory, and checks the integrity of the file for proper processing.

[1361] 3. Grammar, structure, and citation checks using an AI engine

[1362] The AI ​​engine on the server starts up and first performs grammatical analysis. Then it analyzes the overall structure of the content (paragraphs, headings, etc.), and finally checks the citation style. For example, it generates a suggestion to correct the mistake "He go to the library" to "He goes to the library." In terms of structure, if the introduction is short, it will suggest "We recommend adding more detail to the introduction." Also, if the citation does not follow a specific style, it will point out that "the citation format needs to be corrected."

[1363] 4. Generate and submit improvement suggestions

[1364] The server generates improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's device. The improvement suggestions are sent to the contact information associated with the user's account or displayed on the user's dashboard when they log in to the system.

[1365] Specific examples

[1366] Suppose a user uploads a draft of a blog post to the system. The draft contains grammatical errors, inconsistent structure, and incomplete citations. The server first checks for these problems using an AI engine. Specifically, it generates suggestions to correct "He go to the library." to "He goes to the library.", suggests adding more detail to the short introduction, and further suggests correcting parts of the citation that do not comply with the syndication format. These suggestions are then sent to the user, who can review and apply them to improve the quality of the content.

[1367] Prompt Sentence Examples

[1368] Check the grammar, structure, and citations of blog posts uploaded by users and generate improvement suggestions as follows:

[1369] Grammar error: Change "He go to the library." to "He goes to the library."

[1370] Poor structure: "The introduction is short, so I suggest adding more details."

[1371] Incorrect citation: "Please correct your citation format."

[1372] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1373] Program processing flow

[1374] Step 1:

[1375] The user uploads a draft of content from the terminal. The input is the draft file specified by the user, and the output is the terminal sending the draft file to the server. When the user clicks the upload button, the draft file is sent from the terminal to the server.

[1376] Step 2:

[1377] The server receives the uploaded draft and saves it in the specified directory. The input is the draft file sent by the user, and the output is the draft file to be saved. The server first verifies the integrity of the draft file and saves it in the appropriate directory.

[1378] Step 3:

[1379] The server invokes the AI ​​engine to perform grammatical analysis of the draft. The input is the saved draft file, and the output is the results of grammatical error detection. The server inputs the saved draft file into the AI ​​engine and detects grammatical errors using a natural language processing library (NLTK). It generates a suggestion to correct the mistake "He go to the library." to "He goes to the library."

[1380] Step 4:

[1381] The server uses an AI engine to analyze the structure of the draft. The input is the saved draft file, and the output is structural improvement suggestions. The server evaluates the structure of the draft, including paragraphs, headings, and sections, to ensure consistency. For example, if the introduction is short, the server will make a suggestion such as, "We recommend adding more detail to the introduction."

[1382] Step 5:

[1383] The server uses an AI engine to check the citations in the draft. The input is the saved draft file, and the output is suggestions for correcting the citations and formatting. The server inspects the citations in the draft to ensure they conform to a specific style (e.g., APA style). If the citations do not follow the style, it suggests, "Your citation format needs to be revised."

[1384] Step 6:

[1385] The server generates improvement suggestions based on the results of each grammar, structure, and citation check and sends them to the user's device. The input is the check results from the AI ​​engine, and the output is the generated improvement suggestions. The server integrates the results of each check and generates improvement suggestions. These suggestions are then sent to the user's device and displayed on the dashboard or sent to the corresponding contact.

[1386] Step 7:

[1387] The user reviews and applies the improvement suggestions received. The input is the improvement suggestions sent from the server, and the output is the revised draft. The user checks the improvement suggestions on the terminal, adds necessary corrections to the draft, and re-edits it.

[1388] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1389] The present invention combines an emotion engine with a system for automatically proofreading a paper draft. This allows the system to recognize the user's emotional state and adjust the interface and the method of presenting improvement suggestions based on that state. Specific embodiments for implementing the present invention are described below.

[1390] System configuration

[1391] The system consists of four main components: the user, the device, the server, and the emotion engine. Users upload drafts of their papers via their devices, and the emotion engine recognizes their emotional state in real time. The server stores the received drafts and uses an AI engine to check grammar, structure, and citations, generating improvement suggestions. The emotion engine adjusts the interface and generates feedback messages based on the user's emotional data.

[1392] Explanation of program processing

[1393] 1. User uploads a draft

[1394] Using the terminal, the user selects the draft file from the file selection screen and clicks the upload button, which sends the file to the server.

[1395] During this process, the emotion engine analyzes the user's facial expressions and voice to recognize their current emotional state in real time.

[1396] 2. The server receives the draft

[1397] The server stores the uploaded draft and verifies the integrity of the file.

[1398] The emotion engine transmits the acquired emotion data to the server, which then stores the data.

[1399] 3. Grammar check by AI engine

[1400] The server's AI engine analyzes the draft for grammatical errors and generates correction suggestions.

[1401] The emotion engine adjusts the way suggestions are worded based on the user's emotional state, for example, using gentler language if the user is stressed.

[1402] 4. Structure check using AI engine

[1403] The server uses an AI engine to analyze the structure of the paper and generate suggestions regarding consistency and logic.

[1404] If the emotion engine determines that the user is tired, it will provide a concise summary of suggestions.

[1405] 5. Citation check using AI engine

[1406] The server's AI engine checks the citation format and generates appropriate correction suggestions.

[1407] The system adjusts which correction suggestions are given priority depending on the user's emotional state.

[1408] 6. Generate and submit improvement suggestions

[1409] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks, adjusting the wording and order of the suggestions taking into account data from the sentiment engine.

[1410] The final improvement proposals are sent to the user's device via the method selected by the user (email or dashboard display).

[1411] 7. Review and apply user improvement suggestions

[1412] The user receives and reviews the improvement suggestions via their device, while the emotion engine continues to monitor the user's emotional state and displays support messages as needed.

[1413] The user applies the suggested corrections and re-edits the draft, and the emotion engine supports the user in completing the final version while reducing stress.

[1414] Specific examples

[1415] Suppose a user uploads a draft of a research paper to the system. If the emotion engine detects that the user is nervous, it displays the message, "Relax and proceed. We'll help you." The server receives the draft and checks its grammar, structure, and citations. The engine finds an error in the sentence, "He go to the library." It generates a suggestion to correct it to, "He goes to the library." If the user is feeling even more fatigued, the suggestion is simplified and a simple suggestion such as, "The introduction is short, please add more details."

[1416] In this way, the system of the present invention automatically proofreads papers while taking into account the user's emotional state and provides optimal suggestions for improvement, helping researchers to write higher quality papers without feeling stressed.

[1417] The processing flow will be explained below.

[1418] Step 1:

[1419] The user uploads a draft of their paper using their device. They open a file selection screen and select the draft file. Then, by clicking the upload button, the selected file is sent to the server. At the same time, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their current emotional state.

[1420] Step 2:

[1421] The server saves the draft file received from the user in the specified directory and verifies the integrity of the file. After the file is saved correctly, the server saves the emotion data and proceeds to the next processing step.

[1422] Step 3:

[1423] The server launches the AI ​​engine to check grammar. The AI ​​engine reads the saved draft file and analyzes grammatical errors. For example, it finds the mistake "He go to the library." and generates a suggestion to correct it to "He goes to the library." If the emotion engine detects the user's stress, the AI ​​engine's output will use gentler expressions.

[1424] Step 4:

[1425] The server uses an AI engine to analyze the structure of the paper. It analyzes the arrangement of headings, paragraphs, and sections in the saved draft and checks for consistency. For example, it generates suggestions such as, "The introduction is short, so we recommend adding more details." If the emotion engine determines that the user is tired, it will display a concise summary of the suggestions.

[1426] Step 5:

[1427] The server uses an AI engine to check the accuracy and format of citations. It analyzes the citation format in the draft and checks whether it conforms to a specific citation style (e.g., APA style). If there are any deficiencies, it generates suggestions such as "Please revise the citation format to APA style." It prioritizes important revision suggestions based on the emotional state of the author.

[1428] Step 6:

[1429] The server generates improvement suggestions based on the results of grammar, structure, and citation checks. Each suggestion is summarized in an easy-to-read report. The wording and order of suggestions are adjusted taking into account data from the sentiment engine. If a user expressed negative sentiment during upload, subsequent suggestions may include encouraging content.

[1430] Step 7:

[1431] The server sends the generated improvement proposals and reports to the user's device either via email address associated with the user's account or displayed on the user's dashboard when they log in to the system. The tone of the proposals and the content of the message are adapted based on the emotional data.

[1432] Step 8:

[1433] The user reviews the improvement suggestions on their device. They confirm the suggestions and revise the draft based on them. The emotion engine monitors the user's emotional state during the review and displays encouraging or supportive messages as needed. For example, if the user is confused, the engine displays a message such as, "Don't worry, we'll provide advice as needed."

[1434] The above is a specific processing flow in the system of the present invention.

[1435] Example 2

[1436] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1437] While conventional paper proofreading systems can check grammar and structure, they have a problem in that they cannot make suggestions that take into account the user's emotional state. This causes problems such as users feeling stressed during the proofreading process and not being able to effectively utilize the suggestions for improvement.

[1438] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1439] In this invention, the server includes means for an emotion engine to recognize a user's emotion in real time and transmit that data to the server, means for the emotion engine to adjust the expression method and order of improvement suggestions based on the user's emotion data, and means for the server to generate comprehensive improvement suggestions based on the results of grammar, structure, and citation checks and transmit them to the user's terminal. This makes it possible to provide optimal improvement suggestions that take the user's emotional state into consideration.

[1440] "User" means any person or entity that uses the System to upload drafts of papers and receive suggestions for improvement.

[1441] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet.

[1442] "Server" means a remote computer that receives and stores uploaded drafts, performs various checks, and generates and submits improvement suggestions.

[1443] An "emotion engine" is software or hardware that analyzes a user's facial expressions and voice in real time to recognize their emotional state.

[1444] An "AI engine" is an artificial intelligence program that checks grammar, structure, and citations and generates suggestions for improvement.

[1445] "Grammar check" refers to the process of detecting grammatical errors in an uploaded draft and making correction suggestions.

[1446] A "structural check" is a process of analyzing the overall structure and logic of a paper and making suggestions for improvement regarding consistency and points of argument.

[1447] "Citation checking" is the process of verifying that citations in a paper are accurate and follow proper formatting, and making suggested revisions.

[1448] "Improvement Suggestions" are suggestions for improving the quality of a user's draft, generated based on the results of grammar, structure, and citation checks.

[1449] An "email address" is one of the communication methods associated with a user's account, and is an address used to receive information such as improvement suggestions.

[1450] The present invention is a system that allows users to upload a draft of a paper and receive optimal improvement suggestions using automatic proofreading and an emotion engine. Specific embodiments will be described step by step below.

[1451] Hardware and software used

[1452] User devices: computers, smartphones, tablets, etc. Through these devices, users upload drafts and view improvement suggestions.

[1453] Server: A remote computer that stores drafts, analyzes them, and generates improvement suggestions.

[1454] Emotion engine: Software or hardware that analyzes a user's facial expressions and voice in real time to recognize their emotional state. Examples include facial recognition technology and voice analysis technology.

[1455] AI Engine: An artificial intelligence program that checks grammar, structure, and citations. Examples include grammar analysis tools (e.g., Grammarly API) and machine learning models (e.g., BERT, GPT-3).

[1456] Data processing and calculation

[1457] User uploads draft

[1458] The user selects a draft of the paper from the device and uploads it to the server, which then transmits the data to the server using HTTP or HTTPS protocols.

[1459] The server receives and saves the draft

[1460] The server receives and stores the uploaded drafts, checking the integrity of the files and saving them in the appropriate folders.

[1461] Emotion recognition by emotion engine

[1462] The emotion engine analyzes the user's facial expressions and voice in real time to generate emotion data, which is then sent to a server via a REST API or similar and stored.

[1463] Grammar check by AI engine

[1464] The server passes the saved draft to an AI engine that analyzes it for grammatical errors. It uses grammar analysis tools to list the mistakes and suggest corrections.

[1465] Structural check using AI engine

[1466] The AI ​​engine analyzes the structure of a paper and generates suggestions for consistency and logic. For example, if a paragraph is unnaturally connected, it will suggest, "Merge this paragraph with the previous one."

[1467] Citation check by AI engine

[1468] The server uses an AI engine to check whether the citation format is correct and generate suggestions for corrections, such as "Please correct the citation according to APA style."

[1469] Generate comprehensive improvement suggestions

[1470] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks. It adjusts the wording and order of the suggestions based on data from the emotion engine. For example, it uses gentler wording when the user is feeling stressed.

[1471] Submit an improvement suggestion

[1472] The server sends the generated improvement suggestions to the user's device, either via email or as a dashboard display.

[1473] Review and apply user improvement suggestions

[1474] The user can review the improvement suggestions received through their device and apply any necessary corrections. The emotion engine also monitors the user's emotional state and displays supportive messages such as "Please stay calm and proceed."

[1475] Specific examples

[1476] A user uploads a draft of a research paper to the system. If the emotion engine detects that the user is nervous, it may display the message, "Relax and proceed. We'll help you." The server receives the draft and checks it for grammar, structure, and citations. The engine finds the error, "He go to the library." It generates a suggestion to correct it to, "He goes to the library." Furthermore, if the user is feeling fatigued, the suggestion may be simplified, with a simple suggestion such as, "The introduction is short; please add more detail."

[1477] Prompt Sentence Examples

[1478] "Generate timely emotional support messages for stressed users who upload their paper drafts."

[1479] "Write a concise suggestion for improving the paper structure for a user who is experiencing fatigue."

[1480] In this way, this system automatically proofreads papers while taking into account the user's emotional state and provides optimal improvement suggestions, thereby improving the quality of papers while reducing user stress.

[1481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1482] Step 1:

[1483] User uploads draft

[1484] Input: The user selects the paper draft (e.g., a text file) on the file selection screen of the terminal and clicks the upload button.

[1485] Processing: The terminal sends the user's selected draft file to the server using HTTP or HTTPS protocol.

[1486] Output: A draft file is sent to the server.

[1487] Step 2:

[1488] The server receives and saves the draft

[1489] Input: The server receives the draft file sent from the terminal.

[1490] Processing: Saving the received file in a specific folder and checking the file integrity, for example, whether the file is corrupted and whether it was transferred completely.

[1491] Output: The draft file is saved on the server.

[1492] Step 3:

[1493] The emotion engine recognizes the user's emotions in real time and sends them to the server.

[1494] Input: Facial and voice data when users upload their drafts.

[1495] Processing: The emotion engine uses facial expression recognition software and voice analysis tools to analyze the user's emotional state in real time. The analysis results are converted into data and sent to a server using a REST API or similar.

[1496] Output: The user's emotional data (e.g., tension, stress, fatigue, etc.) is sent to the server.

[1497] Step 4:

[1498] The server's AI engine starts grammar checking

[1499] Input: Draft file saved on the server.

[1500] Processing: The server calls a grammar analysis tool (e.g., Grammarly API) to analyze the draft for grammar errors. It detects grammar errors and generates correction suggestions for each one.

[1501] Output: A list of grammar errors and suggested fixes for them.

[1502] Step 5:

[1503] The server's AI engine begins structure checks

[1504] Input: Draft file saved on the server.

[1505] Processing: The AI ​​engine analyzes the overall structure of the draft and generates suggestions for improvement regarding consistency and logic. For example, if a paragraph is not connected properly, it will suggest, "Merge this paragraph with the previous one."

[1506] Output: A list of structural errors and suggestions for improving them.

[1507] Step 6:

[1508] The server's AI engine starts checking quotes

[1509] Input: Draft file saved on the server.

[1510] Processing: The AI ​​engine analyzes the citations in the draft, checking whether they follow the proper formatting and generating correction suggestions if there are any deficiencies.

[1511] Output: A list of citation errors and suggested fixes.

[1512] Step 7:

[1513] Generate comprehensive improvement suggestions

[1514] Input: The results of grammar, structure, and citation checks, as well as user sentiment data sent from the sentiment engine.

[1515] Processing: The server integrates the results of each check and adjusts the wording and order of the improvement suggestions based on the emotional data. For example, if the user is feeling stressed, the suggestions will be presented in a gentler way and in an order that will reduce the burden.

[1516] Output: Comprehensive improvement suggestions.

[1517] Step 8:

[1518] The server sends improvement suggestions to the user's device

[1519] Input: Overall improvement suggestions.

[1520] Processing: The server sends the generated improvement suggestions to the user's email address or dashboard.

[1521] Output: Improvement suggestions that can be viewed on the user's device.

[1522] Step 9:

[1523] Review and apply user improvement suggestions

[1524] Input: Improvement suggestions received from the server.

[1525] Processing: The user reviews the received improvement suggestions and applies them to the draft if necessary. The emotion engine continues to monitor the user's emotional state and displays supportive messages such as "Keep calm and proceed."

[1526] Output: A draft with the corrections applied.

[1527] (Application example 2)

[1528] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1529] In production sites such as factories, employees are required to work efficiently while avoiding excessive stress and fatigue. However, current technology makes it difficult to monitor employees' emotional states in real time and provide appropriate feedback and improvement suggestions accordingly. In addition, there is a lack of means to adjust work suggestions based on employees' emotional states, making it difficult to improve work efficiency while managing employee stress.

[1530] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1531] In this invention, the server includes: means for a user to upload a draft of a paper from a terminal; means for the server to receive and store the uploaded draft; means for the server to invoke an AI engine for grammar checks, detect grammatical errors, and generate correction suggestions; means for the server to analyze the structure of the paper and generate improvement suggestions; means for the server to check the accuracy and format of citations and generate correction suggestions; means for the server to generate improvement suggestions based on the results of the grammar, structure, and citation checks and send them to the user's terminal; means for the user to review and apply the improvement suggestions received; means for recognizing the user's emotional state using an emotion engine and adjusting the interface and the expression method of the suggestions based on that state; means for monitoring work progress in real time and generating feedback messages based on the emotion engine; and means for adjusting the priority and expression method of the improvement suggestions based on the emotional state. This makes it possible to provide appropriate feedback and improvement suggestions in real time that take into account the emotional state of employees, thereby improving work efficiency and managing stress at the same time.

[1532] "User" refers to a person who uses the system to upload a draft paper and receive suggestions for improvement.

[1533] "Terminal" refers to the device used by a User to upload a draft of their paper.

[1534] "Server" refers to a centralized computer system that receives and stores drafts uploaded by users and performs various analyses.

[1535] "AI Engine" refers to an artificial intelligence system installed on a server that detects grammatical errors and generates correction suggestions.

[1536] An "emotion engine" is a system that recognizes a user's emotional state in real time and adjusts the interface and presentation of suggestions based on that data.

[1537] "Grammar check" refers to the AI ​​engine's process of analyzing the sentence structure in the draft, detecting grammatical errors, and suggesting corrections.

[1538] "Structure" refers to the organization, arrangement, and development of paragraphs of an entire paper or document.

[1539] "Citations" refer to references within a paper to other studies or sources.

[1540] "Interface" refers to the operation screen and display method that allows users to interact with the system.

[1541] "Feedback message" refers to a message that the emotion engine generates based on the user's emotional state to support the progress of work and mood.

[1542] "Real-time monitoring" refers to instantly monitoring the progress of work and the user's emotional state, and responding immediately if necessary.

[1543] "Improvement suggestions" refer to corrections and suggestions regarding grammar, structure, citations, etc. that the AI ​​engine generates based on the analysis results.

[1544] This invention relates to a system that improves the work efficiency and mental health of employees in factory production. The system consists of four main components: smart glasses worn by the user, a server, an AI engine, and an emotion engine.

[1545] System configuration

[1546] 1. Users

[1547] The user is a factory worker who wears smart glasses to perform his / her work. The smart glasses are equipped with a camera, a display, and a network module.

[1548] 2. Smart Glasses

[1549] The smart glasses are equipped with a camera that captures the user's facial expressions and work status in real time. The emotion engine analyzes the user's emotional state and sends the results to the server. Feedback messages and improvement suggestions from the server are displayed on the display.

[1550] 3. Server

[1551] The server is the main hub for the following operations:

[1552] Receive and store data uploaded by users.

[1553] An AI engine is used to perform grammar checks, structural analysis, and citation verification.

[1554] Use data from the emotion engine to tailor the wording of feedback messages and improvement suggestions.

[1555] The server is expected to be built on a general cloud computing environment (for example, AWS or Google Cloud Platform).

[1556] 4. AI Engine

[1557] The AI ​​engine is equipped with the technology to perform the following processes:

[1558] Grammar Check: Uses NLP (Natural Language Processing) techniques to detect grammatical errors and generate correction suggestions.

[1559] Structural analysis: Analyze the organization of an entire paper or document and generate improvement suggestions.

[1560] Citation Check: Checks the accuracy and format of citations in your paper and generates suggested revisions.

[1561] The AI ​​engine is developed using technologies such as TensorFlow and OpenCV.

[1562] 5. Emotion Engine

[1563] The emotion engine recognizes the user's emotional state and adjusts the presentation of the interface and suggestions based on that state.

[1564] Emotion analysis: Analyzes the user's facial expression data captured from the smart glasses camera to assess their emotional state.

[1565] Feedback generation: Generate appropriate feedback messages for users based on emotion data.

[1566] The emotion engine is built using, for example, the Affdex SDK.

[1567] Specific examples

[1568] Suppose an employee is performing assembly work. If the emotion engine recognizes the employee's fatigue, the smart glasses will display a message saying, "Please take a short break." If the AI ​​engine detects a mistake in the work, the smart glasses will display a suggestion saying, "The screws appear to be loose. Please check them again." In this way, the system of the present invention can provide appropriate feedback and improvement suggestions in real time, taking into account the employee's emotional state.

[1569] Prompt Sentence Examples

[1570] Desired function: Support for assembly work in factories

[1571] Main features: Real-time monitoring of work content, recognition of emotional state, and provision of improvement suggestions

[1572] Technologies used: Sentiment analysis with Affdex SDK, working analysis with TensorFlow and OpenCV

[1573] Input data: facial expression data of employees, video data of their work

[1574] Output data: Feedback messages, improvement suggestions

[1575] Targeted effects: Improved work efficiency and quality, reduced employee stress

[1576] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1577] Step 1: User puts on smart glasses

[1578] A user puts on smart glasses to start work in the factory. The camera in the smart glasses captures the user's facial expressions and work status in real time. The input is the user's facial expression data and work video data, and the output is that these data are sent to the server.

[1579] Step 2: Emotional state analysis by the emotion engine

[1580] The server receives the facial expression data sent from the smart glasses. The emotion engine then analyzes it and evaluates the user's emotional state (e.g., fatigue, stress, or relaxation). The input is the facial expression data, and the output is the evaluation result of the emotional state. The emotion engine uses the Affdex SDK to analyze the facial expression data.

[1581] Step 3: Real-time operation monitoring

[1582] The server receives video data of the work sent from the smart glasses. The AI ​​engine analyzes the video data to check the progress of the work and detect errors and areas for improvement. The input is the video data, and the output is the work status and error detection results. The AI ​​engine performs analysis using TensorFlow and OpenCV.

[1583] Step 4: Generate feedback and improvement suggestions

[1584] The server integrates the emotional state evaluation results from the emotion engine and the work situation analysis results from the AI ​​engine. Then, based on the emotional state, it generates appropriate feedback messages and improvement suggestions for the user. The inputs are the emotional state evaluation results and the work situation analysis results, and the output is the feedback messages and improvement suggestions.

[1585] Step 5: Viewing feedback messages

[1586] The server sends the generated feedback messages and improvement suggestions to the smart glasses display. The user receives this feedback in real time and improves their work. The input is the feedback messages and improvement suggestions, and the output is the feedback displayed on the smart glasses display.

[1587] Step 6: User improvement and data feedback

[1588] The user improves their work based on the feedback from the smart glasses. The improved work data is again captured by the smart glasses' camera and sent to the server. The input is the improved work data, and the output is the data sent to the server. This feedback loop ensures that the latest data is always analyzed, leading to continuous work improvement.

[1589] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1590] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1591] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1592] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1593] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1594] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1595] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1596] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1597] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1598] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1599] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1600] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1601] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1602] 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.

[1603] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1604] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1605] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1606] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1607] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1608] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1609] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1610] The following is further disclosed regarding the above embodiment.

[1611] (Claim 1)

[1612] A means for users to upload drafts of their papers from their devices;

[1613] a means for the server to receive and store the uploaded draft;

[1614] A server calls an AI engine for grammar checking, detects grammatical errors, and generates correction suggestions;

[1615] a means for the server to analyze the structure of the paper and generate improvement suggestions;

[1616] a means for the server to verify the accuracy and format of the citation and generate suggested corrections;

[1617] A means for the server to generate improvement suggestions based on the results of grammar, structure, and citation checks and send them to the user's terminal;

[1618] Includes a means for users to review and apply improvement suggestions received

[1619] system.

[1620] (Claim 2)

[1621] 10. The system of claim 1, wherein the server includes means for proofreading the paper based on a particular academic journal format and generating suggestions.

[1622] (Claim 3)

[1623] 2. The system of claim 1, wherein the server includes means for sending improvement suggestions to an email address corresponding to the user's account.

[1624] "Example 1"

[1625] (Claim 1)

[1626] a means for a user to upload a draft document from a terminal;

[1627] a means for the server to receive and store the uploaded draft;

[1628] A server calls an AI engine for grammar checking, detects grammatical errors, and generates correction suggestions;

[1629] a means for the server to analyze the structure of the document and generate improvement suggestions;

[1630] a means for the server to verify the accuracy and format of the citation and generate suggested corrections;

[1631] A means for the server to generate improvement suggestions based on the results of grammar, structure, and citation checks and send them to the user's terminal;

[1632] A means for users to review and apply the improvement suggestions received;

[1633] A means for using a hash function to verify the integrity of the file when it is received by the server;

[1634] A means for the server to generate AI engine suggestions in JSON format;

[1635] A means for the server to send and receive data securely using the HTTPS protocol;

[1636] a means for the terminal to use editor software to review and apply the improvement suggestions;

[1637] A system including:

[1638] (Claim 2)

[1639] 10. The system of claim 1, wherein the server includes means for proofreading the document based on a particular academic journal format and generating suggestions.

[1640] (Claim 3)

[1641] 10. The system of claim 1, wherein the server includes means for sending improvement suggestions to an email address corresponding to the user's account.

[1642] "Application Example 1"

[1643] Rewritten claims

[1644] (Claim 1)

[1645] a means for a user to upload draft content from a device;

[1646] a means for the server to receive and store the uploaded draft;

[1647] A server calls an AI engine for grammar checking, detects grammatical errors, and generates correction suggestions;

[1648] a means for the server to analyze the structure of the content and generate improvement suggestions;

[1649] a means for the server to verify the accuracy and format of the citation and generate suggested corrections;

[1650] A means for the server to generate improvement suggestions based on the results of grammar, structure, and citation checks and send them to the user's terminal;

[1651] Includes a means for users to review and apply improvement suggestions received

[1652] system.

[1653] (Claim 2)

[1654] 10. The system of claim 1, wherein the server includes means for proofreading content based on a format for a particular delivery format and generating suggestions.

[1655] (Claim 3)

[1656] 10. The system of claim 1, wherein the server includes means for sending improvement suggestions to a contact corresponding to the user's account.

[1657] "Example 2: Combining Emotion Engines"

[1658] (Claim 1)

[1659] A means for users to upload drafts of their papers from their devices;

[1660] a means for the terminal to transmit the uploaded draft to the server;

[1661] a means for the server to receive and store the uploaded draft;

[1662] A means for the emotion engine to recognize the user's emotion in real time and transmit the data to a server;

[1663] A server calls an AI engine for grammar checking, detects grammatical errors, and generates correction suggestions;

[1664] A means for the server to analyze the structure of a paper and generate improvement suggestions regarding consistency and logic;

[1665] a means for the server to verify the accuracy and format of the citation and generate suggested corrections;

[1666] A means for the emotion engine to adjust the expression method and order of improvement suggestions based on the user's emotion data;

[1667] The server generates comprehensive improvement suggestions based on the results of grammar, structure, and citation checks and sends them to the user's terminal;

[1668] Includes a means for users to review and apply improvement suggestions received

[1669] system.

[1670] (Claim 2)

[1671] 10. The system of claim 1, wherein the server includes means for proofreading the paper based on a particular academic journal format and generating suggestions.

[1672] (Claim 3)

[1673] 10. The system of claim 1, wherein the server includes means for sending improvement suggestions to an email address corresponding to the user's account.

[1674] "Application example 2 when combining emotion engines"

[1675] (Claim 1)

[1676] A means for users to upload drafts of their papers from their devices;

[1677] a means for the server to receive and store the uploaded draft;

[1678] A server calls an AI engine for grammar checking, detects grammatical errors, and generates correction suggestions;

[1679] a means for the server to analyze the structure of the paper and generate improvement suggestions;

[1680] a means for the server to verify the accuracy and format of the citation and generate suggested corrections;

[1681] A means for the server to generate improvement suggestions based on the results of grammar, structure, and citation checks and send them to the user's terminal;

[1682] A means for users to review and apply the improvement suggestions received;

[1683] a means for recognizing a user's emotional state through an emotion engine and adjusting the presentation of the interface and suggestions based on that state;

[1684] a means for monitoring the work progress in real time and generating feedback messages based on an emotion engine;

[1685] A means by which improvement suggestions are prioritized and presented based on emotional state;

[1686] A system including:

[1687] (Claim 2)

[1688] 10. The system of claim 1, wherein the server includes means for proofreading the paper based on a particular academic journal format and generating suggestions.

[1689] (Claim 3)

[1690] 2. The system of claim 1, wherein the server includes means for sending improvement suggestions to an email address corresponding to the user's account. [Explanation of symbols]

[1691] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to upload drafts of their papers from their devices; a means for the server to receive and store the uploaded draft; A server calls an AI engine for grammar checking, detects grammatical errors, and generates correction suggestions; a means for the server to analyze the structure of the paper and generate improvement suggestions; a means for the server to verify the accuracy and format of the citation and generate suggested corrections; A means for the server to generate improvement suggestions based on the results of grammar, structure, and citation checks and send them to the user's terminal; Includes a means for users to review and apply improvement suggestions received system.

2. 10. The system of claim 1, wherein the server includes means for proofreading the paper based on the format of a particular academic journal and generating suggestions.

3. 2. The system of claim 1, wherein the server includes means for sending improvement suggestions to an email address corresponding to the user's account.

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