System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving and analyzing input information using natural language processing techniques; means for modifying and improving the grammar and style of generated sentences; means for providing improvement suggestions to a user and accepting user modifications; and means for storing and outputting final sentences in a specified format.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] In today's information-overloaded world, creating high-quality content targeted at specific expertise or specialized readers is crucial. However, many people struggle to quickly generate effective, polished writing due to time constraints or a lack of writing skills. Furthermore, existing writing support tools often only correct grammar or generate generic content, and are not sufficiently customized to meet individual needs or specialized requirements. Given this background, there is a need for a system that can efficiently generate high-quality writing without significant effort. [Means for solving the problem]

[0005] The present invention solves the above problems by the following means. First, it provides a means for receiving input information and analyzing it using natural language processing technology. Next, it includes a means for correcting and improving the grammar and style of the generated text. It also includes a means for providing improvement suggestions to the user and accepting corrections from the user. Finally, it provides a system including a means for saving the final text and outputting it in a specified format. In addition, it includes a means for extracting technical terms based on the characteristics of the target reader using natural language processing technology and a means for providing the generated text as multiple suggestions, making it possible to efficiently generate high-quality text that meets the user's needs.

[0006] "Input information" refers to information such as the theme, target audience, and technical terms that form the basis of the text provided by the user.

[0007] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0008] The "means of analysis" refers to the means of understanding the structure and content of a sentence based on input information and executing a process to set appropriate generation parameters.

[0009] "Generated sentences" are initial sentences created by an AI model based on input information.

[0010] "Means for correcting and improving grammar and style" refers to means for executing a process to detect and correct errors in grammar and style of expression in the generated text.

[0011] "Means for providing improvement suggestions" refers to means for notifying users of the results of corrections and improvements to grammar and style, and for providing options for further improvement.

[0012] "Means for accepting corrections from users" refers to the means for receiving additional corrections and feedback provided by users and adjusting the text again.

[0013] The "final text" is the text that is completed based on the user's corrections and improvements.

[0014] "Means for outputting in a specified format" refers to means for saving or outputting the completed document in a specific file format such as PDF or Word.

[0015] A "terminology extraction means" is a means for carrying out a process of identifying and extracting specific terminology used in a text based on the characteristics of the target audience.

[0016] The "means for providing multiple proposals" refers to a means for providing the generated sentences and revision suggestions to the user as multiple variations. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention is a system that enables users to efficiently create high-quality texts. The system utilizes a generative AI model to quickly and accurately generate texts that meet the user's needs and corrects grammar and style.

[0039] Explanation of program processing

[0040] User Input

[0041] The user uses a terminal to input information into the DocCraft Elite interface, such as the topic of the text and the characteristics of the target audience. This information can be specific, such as "The evolution and future of artificial intelligence" or "Academic audience with specialized knowledge." Once the input is complete, the user clicks the submit button to send the information to the server.

[0042] Sending input data

[0043] The device sends the data entered by the user to the server in real time, and the data is sent as an encrypted HTTP request during this communication process, ensuring security.

[0044] Analyzing input data

[0045] The server analyzes the received data and determines the necessary parameters. Specifically, it analyzes the theme and characteristics of the target audience using natural language processing technology and extracts the keywords and technical terms necessary for generating text.

[0046] Invoking a generative AI model

[0047] The server invokes a ChatGPT®-based generative AI model with specific parameters, which generates an initial sentence based on the user's input data.

[0048] Sentence generation

[0049] A generative AI model generates appropriate sentences based on user-provided information, such as an initial sentence like, "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0050] Text corrections and improvements

[0051] The server then reanalyzes the generated text and performs grammatical corrections and style improvements. This involves using natural language processing techniques to detect and correct grammatical errors. It also refines the expression based on style guidelines to improve the quality of the text. An example of a post-processing correction is, "Artificial intelligence (AI) has seen remarkable developments over the past few decades. This paper examines its evolution and future prospects in detail."

[0052] Providing improvement suggestions

[0053] The server sends the corrected and improved text and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further corrections.

[0054] User verification and correction

[0055] The user can check the proposed improvements sent from the server on their device and make additional adjustments as necessary, such as changing the word "evolution" to "progress."

[0056] Save and output the final text

[0057] The device saves the final text that the user has confirmed in local storage and can output the text in a specified format (e.g., PDF or Word file).

[0058] Specific examples

[0059] Writing an introduction for a research paper

[0060] 1. User input: A student (user) enters "research paper on the evolution and future of artificial intelligence" into the terminal and specifies "academic readers with specialized knowledge" as the target audience.

[0061] 2. Sending input data: The terminal sends the input data to the server.

[0062] 3. Parsing input data: The server parses the data and extracts the necessary keywords and parameters.

[0063] 4. Calling the generative AI model: The server calls the generative AI model and begins generating sentences.

[0064] 5. Sentence generation: The generative AI model creates initial sentences.

[0065] 6. Correcting and improving text: The server corrects the generated text based on grammar and style guidelines.

[0066] 7. Providing improvement suggestions: The server sends improvement suggestions to the student's device.

[0067] 8. User review and revision: Students review the proposal and make further revisions.

[0068] 9. Save and output the final text: The terminal saves the completed text in the specified format.

[0069] The above is a specific embodiment for carrying out the invention. This system enables users to efficiently generate high-quality professional documents and improve their quality.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] The user inputs the topic of the writing and the characteristics of the target audience into the device interface. Specifically, they input "a research paper about the evolution and future of artificial intelligence" or "an academic audience with specialized knowledge." Once the input is complete, they click the send button.

[0073] Step 2:

[0074] The device sends the data entered by the user to the server in real time, and the communication is secure because it is done using encrypted HTTP requests.

[0075] Step 3:

[0076] The server analyzes the received data, using natural language processing technology to analyze the theme and characteristics of the target audience, and extracts keywords and technical terms necessary for generating text.

[0077] Step 4:

[0078] The server invokes the generative AI model with specific parameters, including parameters based on the subject and target audience characteristics provided by the user.

[0079] Step 5:

[0080] Generative AI models generate initial sentences based on specified parameters, such as "The evolution of artificial intelligence (AI) has seen rapid development over the past few decades."

[0081] Step 6:

[0082] The server re-analyzes the generated text, correcting grammar and improving style, detecting grammatical errors and correcting them using dedicated correction algorithms, and refining the presentation based on style guidelines.

[0083] Step 7:

[0084] The server sends the corrected and improved sentences and multiple suggestions to the user's device, where the user can check the suggestions.

[0085] Step 8:

[0086] The user can check the proposed improvements on their device and make further corrections as necessary, for example, changing "evolution" to "progress."

[0087] Step 9:

[0088] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0089] This series of steps allows users to efficiently generate high-quality text and significantly improve its quality.

[0090] Example 1

[0091] 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."

[0092] Conventional text generation systems have had problems with the quality of the text they generate, especially when targeting specialized readers. Furthermore, correcting grammatical errors and improving style in the generated text requires a lot of time and effort. This makes it difficult for users to efficiently generate high-quality text.

[0093] 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.

[0094] In this invention, the server includes means for a user to provide input information such as the topic of the text and the characteristics of the target readers through a terminal, means for transmitting the input information to the server in real time, means for analyzing the input data using natural language processing technology and extracting necessary parameters, means for invoking a generative AI model and generating an initial text based on the user's input information, means for reanalyzing the generated text and correcting grammar and improving style, means for providing the corrected text and multiple suggestions to the user and accepting user corrections, and means for saving the final text and outputting it in a specified format. This enables a user to efficiently generate high-quality text and improve its quality.

[0095] "User" refers to an individual or corporation that provides input information from a terminal to generate text using this system.

[0096] A "terminal" is an electronic device used by a user to provide input information and communicate with a server. Examples include personal computers and smartphones.

[0097] "Server" means a computer system that receives data sent by a user, analyzes it, generates text using a generative AI model, corrects grammar and style, saves the final text, and outputs it in the specified format.

[0098] "Input information" refers to data such as the topic of the text and the characteristics of the target readers that the user provides through the terminal.

[0099] "Natural language processing technology" refers to technology for processing human language using a computer, and examples include text analysis and keyword extraction.

[0100] "Parameters" are data and settings required for sentence generation, which are analyzed and extracted by the server to be passed to the generative AI model.

[0101] A "generative AI model" is an algorithm or software that uses artificial intelligence techniques to generate sentences based on user prompts. Examples include ChatGPT.

[0102] A "prompt sentence" is text that is input into a generative AI model and serves as the basis for the model to generate sentences based on it.

[0103] "Grammar correction" is the process of detecting grammatical errors in the generated sentences and correcting them correctly.

[0104] "Style enhancement" is the process of refining and improving the expression and tone of the generated text.

[0105] A "suggestion" is a revised sentence or multiple variations that the server provides to the user, and is an option for the user to select and make revisions.

[0106] The "final text" is a text that has been finalized after the user has completed the revisions.

[0107] "Specified format" refers to the format in which the final document is to be saved or output, examples of which include PDF and Word files.

[0108] The system of the present invention is designed to enable users to efficiently create high-quality texts, utilizing generative AI models to quickly and accurately generate texts that meet the user's needs and correct grammar and style.

[0109] First, the user uses the terminal to provide input information such as the topic of the text and the characteristics of the target readers. This input information can be specific, such as "The evolution and future of artificial intelligence" or "Academic readers with specialized knowledge." Once the input is complete, the user clicks the send button, which sends the input information to the server.

[0110] The terminal transmits the data entered by the user to the server in real time. During this communication process, the data is sent as an encrypted HTTP request using TLS / SSL or other protocols, ensuring security.

[0111] The server analyzes the received data and determines the necessary parameters. Specifically, it uses natural language processing technology (such as SpaCy or NLTK) to analyze the subject and characteristics of the target audience and extract keywords and technical terms necessary for text generation.

[0112] The server then invokes a generative AI model (e.g., ChatGPT) with specific parameters, providing the model with a specific prompt, such as "Write a piece about the evolution and future of artificial intelligence for an academic audience with specialized knowledge."

[0113] A generative AI model generates initial sentences based on a given prompt. At this stage, the model leverages large amounts of training data to generate sentences with appropriate context and detail. For example, a generated sentence might be, "The evolution of artificial intelligence (AI) has seen rapid development over the past few decades."

[0114] The generated sentences are then re-analyzed on the server side. This process includes using a grammar checker (e.g., Grammarly or LanguageTool) to detect and correct grammatical errors. The process also refines the expression based on style guidelines to improve the quality of the sentences. Corrected examples are obtained, such as: "The development of artificial intelligence (AI) has been remarkable over the past few decades, and this paper examines its evolution and future prospects in detail."

[0115] The server then sends the revised and improved text and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further revisions. For example, the user may change "evolution" to "progress" or rearrange the order of sentences.

[0116] Finally, the text that the user has confirmed is saved to the device's local storage. It is also possible to output the text in a specified format (e.g., PDF or Word file). The user can then use the saved file in other applications.

[0117] As described above, the system of the present invention provides a specific means for users to efficiently generate high-quality text and improve that quality.

[0118] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0119] Step 1:

[0120] A user accesses the DocCraft Elite interface on a device, where they provide input information such as the topic of the article and the characteristics of the target audience. For example, they enter specific content such as "The evolution and future of artificial intelligence" or "Academic readers with specialized knowledge," and click the submit button. The input data includes the topic of the article and the target audience, and the output is encrypted request data.

[0121] Step 2:

[0122] The terminal transmits the data entered by the user to the server in real time. During this communication process, the input data is sent as an HTTP request using encryption technology such as TLS / SSL. The input is the data provided by the user, and the output is an encrypted HTTP request.

[0123] Step 3:

[0124] The server analyzes the received data. Specifically, it uses natural language processing technology (e.g., SpaCy or NLTK) to analyze the topic and characteristics of the target audience and extract keywords and technical terms necessary for text generation. The input is the data in the encrypted HTTP request, and the output is the analyzed keywords and parameters.

[0125] Step 4:

[0126] The server uses the obtained parameters to call a generative AI model (e.g., ChatGPT). At this time, it generates text to be passed to the generative AI model as a prompt. For example, a specific sentence such as "Please write a piece about the evolution and future of artificial intelligence for an academic audience with specialized knowledge" is input to the generative AI model. The input is the parsed parameters and the generated prompt, and the output is the initial sentence.

[0127] Step 5:

[0128] A generative AI model generates an initial sentence based on a given prompt. The model utilizes large-scale training data to generate sentences with appropriate context and details. A sentence such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades" is generated. The input is the prompt, and the output is the initial generated sentence.

[0129] Step 6:

[0130] The server re-analyzes the generated text. This process involves using a grammar checker (e.g., Grammarly or LanguageTool) to detect and correct grammatical errors. It also refines the expression based on style guidelines to improve the quality of the text. For example, it obtains a corrected example such as, "Artificial intelligence (AI) has developed significantly over the past few decades. This paper examines its evolution and future prospects in detail." The input is the initial generated text, and the output is the corrected text.

[0131] Step 7:

[0132] The server sends the corrected and improved sentences and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further corrections. The input is the corrected and improved sentences, and the output is the improvement suggestions provided to the user.

[0133] Step 8:

[0134] The user checks the proposed improvements on the device and makes additional corrections as necessary. For example, they make specific adjustments such as changing "evolution" to "progress" or rearranging the order of sentences. The input is the improvement proposal sent from the server, and the output is the final revised sentence.

[0135] Step 9:

[0136] The device saves the user's finalized text in local storage. It is also possible to output the text in a specified format (e.g., PDF or Word file). The user can use the saved file in other applications. The input is the final revised text, and the output is the text in the saved file format.

[0137] (Application example 1)

[0138] 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."

[0139] In the current content creation process, it is difficult to efficiently generate high-quality text based on a specific topic. In particular, correcting grammar and style, using technical terms based on the reader's characteristics, and providing suggestions for improvement to the user require a lot of time and effort. Therefore, there is a need for a support system that helps users create their own content quickly and accurately and improves the quality of the final text.

[0140] 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.

[0141] In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for generating initial sentences based on the input information using a generative AI model, means for correcting and improving the grammar and style of the generated sentences, means for providing multiple improvement suggestions to the user and accepting the user's corrections, and means for saving the final sentences and outputting them in a specified format, thereby enabling the user to quickly and efficiently create high-quality sentences based on a theme.

[0142] "Input information" refers to initial data such as the theme and characteristics of the target audience that the user provides to the system.

[0143] "Natural language processing technology" is a technology that uses computers to process and analyze language used by humans.

[0144] A "generative AI model" is an artificial intelligence model that automatically generates sentences based on input information provided by the user.

[0145] An "initial sentence" is the sentence that a generative AI model first generates based on input information.

[0146] "Grammar" refers to the rules and structure of language used to construct sentences.

[0147] "Style" is a particular method or characteristic of the presentation or presentation of writing.

[0148] "Correction and improvement" refers to the process of correcting grammatical and stylistic errors and inappropriate parts of the generated text to improve its quality.

[0149] The "multiple improvement suggestions" are multiple corrections or alternatives that are provided to the user for the generated text.

[0150] A "prompt sentence" is an instruction or input sentence given to a generative AI model when generating a specific sentence.

[0151] "Preservation" refers to recording the written work in a digital format so that it can be reused later.

[0152] "Specified format" refers to the particular digital file format in which the final document will be saved or output.

[0153] 1. System Overview

[0154] The system that realizes this application example generates high-quality text based on user input, corrects grammar and style, and suggests improvements, and then saves and outputs the final text. The system is mainly composed of a server and a user terminal, and operates in the following steps.

[0155] 2. Hardware and software used

[0156] Hardware

[0157] Server: Processes data and runs generative AI models. A server with a high-performance CPU and large memory capacity is desirable.

[0158] User device: Personal computer (PC), smartphone, tablet, head-mounted display, etc. Provides an interface for users to input information and check and correct the generated text.

[0159] software

[0160] Generative AI model: A natural language processing model such as the OpenAI (registered trademark) API. It generates sentences based on user input.

[0161] Encrypted communication protocols, such as HTTPS, that ensure the secure transmission of user-provided input data and generated text.

[0162] Data saving format: PDF, Word, etc. Used to save and output the final document in the format desired by the user.

[0163] 3. Data processing and calculation

[0164] Receiving and analyzing user-entered information

[0165] The user enters information into the device, such as the topic and characteristics of the target audience. This information might include, for example, "The evolution and future of artificial intelligence" or "Technology-savvy readers." The input data is sent to the server in real time via an encrypted HTTP request.

[0166] Initial sentence generation using a generative AI model

[0167] The server analyzes the received data and provides the extracted keywords and terminology to the generative AI model. The generative AI model uses natural language processing techniques, such as the OpenAI API, to generate initial sentences based on the provided information. For example, the prompt sentence could be "Write an article about the evolution of artificial intelligence for a tech-savvy audience."

[0168] Grammar and style fixes

[0169] The generated initial sentences are then analyzed again on the server, where natural language processing techniques are used to detect and correct grammatical errors and refine the sentences based on style guidelines, thereby improving the quality of the sentences.

[0170] Providing improvement suggestions

[0171] The server generates multiple suggestions for corrected and improved sentences and sends them to the user's device, where the user can review them and manually make additional corrections if necessary.

[0172] Save and output the final text

[0173] The finalized text is saved on the user's device in the format selected by the user (PDF or Word file).

[0174] 4. Specific Examples

[0175] Example of user input

[0176] Theme: "The Evolution of Artificial Intelligence"

[0177] Target audience: "Technical readers"

[0178] Prompt: "Write an article about the evolution of artificial intelligence for a tech-savvy audience."

[0179] In this way, users can quickly and efficiently create high-quality texts based on a theme.

[0180] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0181] Step 1:

[0182] The user uses a terminal to input information into the interface, such as the topic of the text and the characteristics of the target audience. Examples include "The evolution and future of artificial intelligence" and "Technology-savvy readers." By clicking the submit button, the input data is sent to the server in real time as an encrypted HTTP request. Input: Topic and characteristics of the target audience. Output: Transmission of encrypted input data.

[0183] Step 2:

[0184] The server analyzes the received data and extracts necessary parameters based on the input information using natural language processing technology. For example, if the topic is "The Evolution and Future of Artificial Intelligence," related keywords and technical terms are extracted. Input: Encrypted input data, Output: Analyzed parameters (keywords, technical terms).

[0185] Step 3:

[0186] The server uses the parsed parameters to provide a prompt to the generative AI model. For example, it generates a prompt such as "Write an article about the evolution of artificial intelligence for a tech-savvy audience." The generative AI model generates an initial sentence based on the provided information. Input: Parsed parameters, Output: Initial sentence.

[0187] Step 4:

[0188] The generated initial sentence is then re-analyzed by the server. Natural language processing techniques are used to detect and correct grammatical errors, and the sentence is refined based on style guidelines. This process improves the quality of the sentence. Input: Initial sentence, Output: Corrected and improved sentence.

[0189] Step 5:

[0190] The server generates multiple improvement suggestions based on the corrected and improved sentences and sends them to the user's terminal. The user checks these suggestions and manually makes additional corrections as needed. Input: corrected sentence, Output: multiple improvement suggestions.

[0191] Step 6:

[0192] The user checks the provided improvement suggestions on the device and modifies the text as necessary. The text that the user has finally confirmed can be saved on the device. It is also possible to save and output in a specified format (e.g. PDF or Word file). Input: Improvement suggestions and user modifications, Output: Final confirmed text.

[0193] Step 7:

[0194] The final text is saved in the format specified by the user (PDF or Word file). This allows users to efficiently create high-quality text and save it in various formats. Input: Final text, Output: Text saved in the specified format.

[0195] 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.

[0196] The present invention relates to a system for efficiently creating high-quality text, and in particular to a system that combines an emotion engine to enable text generation that takes into account the user's emotions. Specific embodiments of the present invention are described below.

[0197] Explanation of program processing

[0198] User Input

[0199] Users access the DocCraft Elite interface on their device and enter the topic and target audience characteristics for their writing, such as "Research paper on the evolution and future of artificial intelligence" or "Academic audience with specialized knowledge." Once the user has completed the input information, they click the submit button.

[0200] User Emotion Recognition

[0201] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. For example, it can estimate the user's emotions from input speed, typing strength, facial recognition cameras, etc.

[0202] Sending input data

[0203] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server using encrypted HTTP requests.

[0204] Input data and sentiment analysis

[0205] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also sets the parameters necessary for sentence generation, taking into account the emotional state provided by the emotional engine.

[0206] Invoking a generative AI model

[0207] The server invokes a generative AI model based on set parameters, which includes adjusting tone and style depending on the user's emotional state—for example, generating formal sentences in a calm emotional state and more energetic sentences in an excited emotional state.

[0208] Sentence generation

[0209] A generative AI model generates an initial sentence based on the specified parameters, such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0210] Text corrections and improvements

[0211] The server re-analyzes the generated text, correcting grammar and improving style. It detects grammatical errors and corrects them using a dedicated correction algorithm. It also adjusts the writing style by taking into account the emotional state provided by the emotion engine.

[0212] Providing improvement suggestions

[0213] The server sends the corrected and improved sentences and multiple suggestions to the user's device, where the user can check the suggestions.

[0214] User verification and correction

[0215] The user can check the improvement proposals sent from the server on their device and make further corrections as necessary, for example, by selecting the most appropriate expression according to the user's emotional state.

[0216] Save and output the final text

[0217] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0218] Specific examples

[0219] Writing an introduction for a research paper

[0220] 1. User input: A student (user) enters "research paper on the evolution and future of artificial intelligence" into the terminal and specifies "academic readers with specialized knowledge" as the target audience.

[0221] 2. User Emotion Recognition: The device's emotion engine analyzes the user's typing speed and facial expressions to estimate their emotional state. For example, if the user is excited, the device will adjust the tone of the text to be more energetic.

[0222] 3. Sending input data: The device sends the data and emotional state to the server.

[0223] 4. Input data and emotion analysis: The server analyzes the data and extracts necessary keywords and parameters. It also adjusts the response according to the user's emotional state.

[0224] 5. Calling the generative AI model: The server calls the generative AI model and begins generating sentences.

[0225] 6. Sentence generation: The generative AI model creates initial sentences.

[0226] 7. Correction and improvement of sentences: The server corrects the generated sentences based on grammar and emotional state.

[0227] 8. Providing improvement suggestions: The server sends improvement suggestions to the student's device.

[0228] 9. User review and correction: Students review the suggestions and make further corrections.

[0229] 10. Save and output the final text: The terminal saves the completed text in the specified format.

[0230] This series of processes enables users to efficiently generate high-quality, emotion-sensitive sentences and improve their quality.

[0231] The processing flow will be explained below.

[0232] Step 1:

[0233] The user inputs the topic of the writing and the characteristics of the target audience into the device interface. For example, they might input "The evolution and future of artificial intelligence" and specify "academic readers with specialized knowledge" as the target audience. Once they have completed the input, they click the send button.

[0234] Step 2:

[0235] The device's emotion engine analyzes the user's emotional state based on the content of their input, their input speed, their typing strength, and the facial recognition camera. The emotion engine obtains information such as whether the user is relaxed, excited, or stressed.

[0236] Step 3:

[0237] The device transmits the user-entered data and analyzed emotional state to the server in real time using encrypted HTTP requests.

[0238] Step 4:

[0239] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms for the article based on the topic and characteristics of the target audience. It also sets parameters for sentence generation, taking into account the emotional state provided by the emotional engine.

[0240] Step 5:

[0241] The server calls the generative AI model based on the set parameters and emotional information. For example, if the user is relaxed, it instructs the model to generate calm sentences, and if the user is excited, it instructs the model to generate energetic sentences.

[0242] Step 6:

[0243] A generative AI model generates an initial sentence based on specified parameters, such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0244] Step 7:

[0245] The server then re-analyzes the generated text, correcting grammar and improving style. It detects grammatical errors and corrects them using a dedicated correction algorithm. It also refines the expression based on style guidelines and adapts the writing style to suit the emotional state.

[0246] Step 8:

[0247] The server sends the corrected and improved sentences and multiple suggestions to the user's device, and the user can review and select the best sentence from the multiple options.

[0248] Step 9:

[0249] The user can check the proposed improvements sent from the server on their device and make any necessary adjustments. For example, they can change "evolution" to "progress." The system also selects the optimal expression based on the user's emotional state.

[0250] Step 10:

[0251] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0252] This series of steps allows users to efficiently generate high-quality, emotion-sensitive text and significantly improve its quality.

[0253] Example 2

[0254] 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."

[0255] In today's world, efficient and high-quality text creation is an important challenge. However, it is difficult to generate text while taking into account the user's emotional state using conventional technologies. Furthermore, to improve the quality of generated text, it is necessary to integrate natural language processing technology and emotion recognition technology. Unless these problems are resolved, it will be difficult to generate text that satisfies users.

[0256] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for analyzing the user's emotional state, means for setting parameters necessary for sentence generation based on the analyzed emotional state, means for calling a generation AI model and generating sentences based on specified parameters, means for correcting and improving the grammar and style of the generated sentences, means for providing improvement suggestions to the user and accepting user corrections, and means for saving the final sentences and outputting them in a specified format. This makes it possible to generate high-quality sentences that take the user's emotional state into consideration.

[0257] "Natural language processing technology" is a general term for technology that analyzes and generates language data, and is a means of performing semantic analysis of text, grammatical analysis, keyword extraction, etc.

[0258] "Emotional state" refers to the user's psychological and physiological state, and indicates emotions estimated from the user's input behavior, facial expressions, tone of voice, and the like.

[0259] "Parameters" are various setting items and values ​​that are set in text generation, and include the theme, tone, style, frequency of use of technical terms, and the like.

[0260] A "generative AI model" is an algorithm or model that uses machine learning or deep learning techniques to generate text, and is used to generate text from input data.

[0261] "Grammar and style correction and improvement" is a means of correcting grammatical errors in the generated text and adjusting and improving the writing style according to the user's requests and emotional state.

[0262] "Improvement suggestions" are alternatives or corrections presented to the generated or corrected text, and are intended as a reference for the user when making selections or corrections.

[0263] "Format" refers to the format and structure of a file, particularly the format used to save and output documents, such as PDF or Word files.

[0264] "Analysis means" refers to the technical means used to process input information to understand its meaning or to extract specific patterns from the data.

[0265] "Input information" refers to data or information that a user provides to the system, including, for example, the topic of the writing task and the characteristics of the target readers.

[0266] The "means for accepting user corrections" refers to a technical means for reflecting the corrections made by the user when the user makes additional corrections to the generated text or the proposed corrections.

[0267] "Storage and output means" means the technical means used to store the final document in local storage and output it in a specified format.

[0268] This invention is a system for efficiently creating high-quality text, and in particular, it enables text generation that takes into account the user's emotions by combining an emotion engine. Specific embodiments of this invention are described below.

[0269] User Input

[0270] Users access the system's interface using a terminal. They input the topic and target audience characteristics for the writing, such as "a research paper on the evolution and future of artificial intelligence" or "an academic audience with specialized knowledge." Once the user has completed the input information, they click the submit button.

[0271] User Emotion Recognition

[0272] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. For example, it can estimate the user's emotions from input speed, typing strength, and facial recognition cameras. Dedicated software and hardware (e.g., facial recognition cameras) are used for emotion recognition.

[0273] Sending input data

[0274] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server, where the communication is carried out using encrypted HTTP requests, ensuring data security.

[0275] Input data and sentiment analysis

[0276] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation. Technically, natural language processing libraries and APIs are used.

[0277] Invoking a generative AI model

[0278] The server invokes a generative AI model based on the set parameters, including the prompt text. The generative AI model also adjusts tone and style depending on the user's emotional state. For example, a calm emotional state generates more formal text, while an excited emotional state generates more energetic text.

[0279] Sentence generation

[0280] The generative AI model generates an initial sentence based on the specified parameters and prompt sentence. For example, the generated initial sentence might be something like, "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0281] Text corrections and improvements

[0282] The server then re-analyzes the generated text, correcting grammar and improving style. A dedicated correction algorithm detects and corrects grammatical errors. The server also adjusts the writing style by taking into account the emotional state provided by the emotion engine. For example, it corrects typos and changes the tone to be more energetic.

[0283] Providing improvement suggestions

[0284] The server sends the revised and improved text and multiple suggestions to the user's device, allowing the user to review the suggestions. For example, the server may present a "revised version of the problem" and an "improved style proposal."

[0285] User verification and correction

[0286] The user can check the proposed improvements sent from the server on their device and make further corrections as necessary. For example, they can make adjustments such as "changing the style to be more formal" or "adding specific keywords."

[0287] Save and output the final text

[0288] The device saves the final text in local storage and can output the text in a specified format, such as PDF or Word, according to the user's instructions.

[0289] Examples of concrete examples and prompts

[0290] For example, if a user is writing a "research paper on the evolution and future of artificial intelligence" and is targeting an "academic audience with specialized knowledge," they could use the following prompt:

[0291] "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades. In particular,..."

[0292] This series of processes enables users to efficiently generate high-quality, emotion-sensitive sentences and improve their quality.

[0293] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0294] Step 1: User Input

[0295] The user accesses the system's interface using a terminal and inputs the topic of the text they want to generate and the characteristics of the target audience. For example, they can input "research paper on the evolution and future of artificial intelligence" or "academic audience with specialized knowledge." By clicking the submit button, this data is saved on the terminal. This stores the input information within the system.

[0296] Step 2: Recognizing user emotions

[0297] The device analyzes the user's emotional state based on their input and interaction data. The emotion engine processes data from the input speed, typing strength, and facial recognition camera to estimate the user's emotional state. The resulting output is a message indicating whether the user is excited or calm.

[0298] Step 3: Submitting input data

[0299] The device sends the user's input data and the emotion recognition results to the server. The data is sent via an encrypted HTTP request, ensuring data security. The server receives this and proceeds to the next analysis step.

[0300] Step 4: Input data and sentiment analysis

[0301] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation. As a result of the analysis, the necessary keywords and emotional parameters are output.

[0302] Step 5: Invoke the generative AI model

[0303] The server calls the generative AI model based on the set parameters and begins generating sentences. A prompt sentence is also provided as input. The generative AI model generates initial sentences in a tone and style that reflects the user's emotional state. The initial sentences are then output.

[0304] Step 6: Sentence generation

[0305] The generative AI model generates an initial sentence based on the prompt and the set parameters. The generated sentence might be something like, "The evolution of artificial intelligence (AI) has made rapid progress over the past few decades." This is the output.

[0306] Step 7: Edit and improve your writing

[0307] The server then re-analyzes the generated text and corrects grammatical and stylistic errors. It uses a proprietary correction algorithm to detect errors and adjusts the writing style based on data from the emotion engine. The corrected text is then output.

[0308] Step 8: Providing suggestions for improvement

[0309] The server sends the revised and improved text and multiple suggestions to the user's device, where the user can review these suggestions. For example, the server outputs "revised version of the problem" and "improved style proposal."

[0310] Step 9: Verify and Modify Users

[0311] The user can then check the proposed improvements on the terminal and make further revisions as necessary, resulting in a final version of the text with more detailed revisions.

[0312] Step 10: Save and export the final document

[0313] The device saves the final text that the user has finalized in local storage. Then, based on the user's instructions, it outputs the text in a specified format, such as a PDF or Word file. The final text is saved and output in the specified format.

[0314] (Application example 2)

[0315] 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."

[0316] Conventional text generation systems have difficulty generating personalized content based on the user's emotional state, making them insufficient as a means for efficiently creating high-quality text. Furthermore, text that does not take emotions into account has the problem of being difficult to capture the interest of specific situations or target readers. Furthermore, there is a lack of technology for utilizing interactive devices to reflect emotional feedback in real time. Therefore, there is a need for text generation that reflects the user's emotions and for improving the quality of such text generation.

[0317] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for correcting and improving the grammar and style of the generated sentence, means for providing improvement suggestions to the user and accepting the user's corrections, and means for analyzing the user's emotional state using an interactive device, setting parameters based on the emotional information, and generating sentences according to the emotions using a generative AI model. This makes it possible to efficiently generate high-quality sentences that reflect the user's emotions and improve their quality.

[0318] "Input information" refers to data such as themes for writing and characteristics of the target readers that users provide to the system.

[0319] "Natural language processing technology" is a general term for algorithms and methods for analyzing, understanding, and generating human language, and refers to the technology used to analyze and generate sentences.

[0320] "Means for analyzing" refers to a method or apparatus for receiving input information and interpreting or analyzing it using natural language processing techniques.

[0321] "Means for correcting and improving" refers to methods and devices for checking the grammar and style of the generated text and correcting or optimizing it as necessary.

[0322] The "means for providing improvement suggestions" refers to a method or device for presenting candidates or suggested corrections to the generated sentence to the user and accepting confirmation or corrections.

[0323] "Storage means" refers to the method or device for recording the final text in a storage location such as local storage or the cloud.

[0324] "Means for outputting in a specified format" refers to a method or device for outputting the generated text in a specific format, such as a PDF or Word file.

[0325] "Interactive device" refers to a smartphone, tablet, or other interface that allows for real-time interaction with a user.

[0326] "Means for analyzing emotional states" refers to methods and devices for estimating and recognizing emotions based on information such as a user's facial expressions and voice.

[0327] "Means for setting parameters based on emotion information" refers to a method or device that determines setting values ​​for sentence generation taking into account the analyzed emotions.

[0328] "Generative AI model" refers to an algorithm or network model that uses artificial intelligence technology to automatically generate text.

[0329] "Means for generating sentences according to emotions" refers to a method or device that generates sentences with an appropriate tone and style based on the analyzed emotions.

[0330] This invention relates to a system for efficiently creating high-quality text that takes user emotions into consideration, particularly for realizing personalized text generation in content distribution services. This system includes receiving input information, analyzing it using natural language processing technology, correcting and improving the grammar and style of the generated text, providing improvement suggestions to the user, analyzing the emotional state using an interactive device, generating text according to the emotions using a generative AI model, and saving and outputting the final text.

[0331] First, the user accesses the system interface using a terminal and inputs the topic for writing and the characteristics of the target audience, such as "Hawaii travel experience" or "general readership." Once the user has completed the input information, they click the submit button.

[0332] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. Using the smartphone's camera and microphone, the system can estimate the user's emotions from their input speed, facial recognition camera data, and tone of voice. For example, if the system detects that the user is currently excited, that emotional information is transmitted to the system.

[0333] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server. Communication is performed using encrypted HTTP requests. The server analyzes the received data and emotional state and uses natural language processing technology to extract technical terms and keywords based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation.

[0334] The server then uses these parameters to call a generative AI model, which also adjusts tone and style based on the user's emotional state. For example, if the user is excited, the model will generate more energetic text.

[0335] The generated text undergoes a grammar check and style improvement process to further improve its quality. The server then sends the final improved text and several suggestions to the user's device. The user reviews the suggestions and makes further corrections as necessary. The user can then save the finalized text to local storage and output it in a specified format (e.g., PDF or Word file).

[0336] This system enables users to efficiently generate personalized, high-quality sentences that reflect their own emotions. An example of a specific prompt sentence is "Write an excited article about Hawaii travel experience for general readers." Using this prompt sentence, the generative AI model generates optimal sentences that take the user's emotions into consideration.

[0337] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0338] Step 1:

[0339] The user uses a terminal to access the system's interface and input the topic and target reader characteristics for the writing. The input information includes data such as "Hawaii travel experience" and "general reader." When the user completes the input information, the terminal accepts the click of a submit button. The input includes the topic and target reader information, and the output is sent to the system.

[0340] Step 2:

[0341] The emotion engine installed on the device analyzes the user's emotional state based on their input and interactions. It uses the smartphone's camera and microphone to collect input speed, facial recognition data, and tone of voice. Based on this data, the emotion engine estimates the user's emotion (e.g., excited, calm, etc.). The inputs are facial recognition data and tone of voice, and the output is the estimated emotional state.

[0342] Step 3:

[0343] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server using encrypted HTTP requests. The inputs are the theme, target audience information, and emotional state, and the output is this data sent to the server.

[0344] Step 4:

[0345] The server analyzes the received data (theme, target reader information, emotional state). It uses natural language processing technology to extract technical terms and keywords based on the characteristics of the theme and target reader. As a result of the analysis, parameters for detailed text generation are set. The input is the transmitted theme, target reader information, and emotional state, and the set parameters are obtained as the output.

[0346] Step 5:

[0347] The server calls the generative AI model based on the set parameters. Specifically, it adjusts the tone and style according to the user's emotional state and generates the initial sentence. The generative AI model uses a prompt sentence, such as "Write an excited article about Hawaii travel experience for general readers," to generate sentences that adapt to the emotion. The inputs are the set parameters and the prompt sentence, and the output is the initial generated sentence.

[0348] Step 6:

[0349] The generated text is then passed through a grammar checking and style improvement process on the server to improve its quality. Grammar errors are detected and corrected as necessary. The input is the initial generated text, and the output is the corrected and improved text.

[0350] Step 7:

[0351] The server sends the revised and improved sentences as multiple suggestions to the user's device. The user reviews these suggestions and makes any necessary revisions to finalize the sentence. The input is the revised and improved sentence, and the output is multiple suggestions that are provided to the user.

[0352] Step 8:

[0353] The user reviews the suggestions and makes any necessary revisions. The final text is saved on the device and output in the specified format (e.g., PDF or Word file). The input is the final text and format selected by the user, and the output is the final text saved in the specified format.

[0354] 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.

[0355] 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 (registered trademark) (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.

[0356] 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.

[0357] [Second embodiment]

[0358] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0359] 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.

[0360] 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).

[0361] 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.

[0362] 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.

[0363] 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).

[0364] 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. 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.

[0365] 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.

[0366] 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.

[0367] 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.

[0368] 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.

[0369] 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."

[0370] This invention is a system that enables users to efficiently create high-quality texts. The system utilizes a generative AI model to quickly and accurately generate texts that meet the user's needs and corrects grammar and style.

[0371] Explanation of program processing

[0372] User Input

[0373] The user uses a terminal to input information into the DocCraft Elite interface, such as the topic of the text and the characteristics of the target audience. This information can be specific, such as "The evolution and future of artificial intelligence" or "Academic audience with specialized knowledge." Once the input is complete, the user clicks the submit button to send the information to the server.

[0374] Sending input data

[0375] The device sends the data entered by the user to the server in real time, and the data is sent as an encrypted HTTP request during this communication process, ensuring security.

[0376] Analyzing input data

[0377] The server analyzes the received data and determines the necessary parameters. Specifically, it analyzes the theme and characteristics of the target audience using natural language processing technology and extracts the keywords and technical terms necessary for generating text.

[0378] Invoking a generative AI model

[0379] The server invokes the ChatGPT-based generative AI model with specific parameters, which generates an initial sentence based on the user's input data.

[0380] Sentence generation

[0381] A generative AI model generates appropriate sentences based on user-provided information, such as an initial sentence like, "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0382] Text corrections and improvements

[0383] The server then reanalyzes the generated text and performs grammatical corrections and style improvements. This involves using natural language processing techniques to detect and correct grammatical errors. It also refines the expression based on style guidelines to improve the quality of the text. An example of a post-processing correction is, "Artificial intelligence (AI) has seen remarkable developments over the past few decades. This paper examines its evolution and future prospects in detail."

[0384] Providing improvement suggestions

[0385] The server sends the corrected and improved text and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further corrections.

[0386] User verification and correction

[0387] The user can check the proposed improvements sent from the server on their device and make additional adjustments as necessary, such as changing the word "evolution" to "progress."

[0388] Save and output the final text

[0389] The device saves the final text that the user has confirmed in local storage and can output the text in a specified format (e.g., PDF or Word file).

[0390] Specific examples

[0391] Writing an introduction for a research paper

[0392] 1. User input: A student (user) enters "research paper on the evolution and future of artificial intelligence" into the terminal and specifies "academic readers with specialized knowledge" as the target audience.

[0393] 2. Sending input data: The terminal sends the input data to the server.

[0394] 3. Parsing input data: The server parses the data and extracts the necessary keywords and parameters.

[0395] 4. Calling the generative AI model: The server calls the generative AI model and begins generating sentences.

[0396] 5. Sentence generation: The generative AI model creates initial sentences.

[0397] 6. Correcting and improving text: The server corrects the generated text based on grammar and style guidelines.

[0398] 7. Providing improvement suggestions: The server sends improvement suggestions to the student's device.

[0399] 8. User review and revision: Students review the proposal and make further revisions.

[0400] 9. Save and output the final text: The terminal saves the completed text in the specified format.

[0401] The above is a specific embodiment for carrying out the invention. This system enables users to efficiently generate high-quality professional documents and improve their quality.

[0402] The processing flow will be explained below.

[0403] Step 1:

[0404] The user inputs the topic of the writing and the characteristics of the target audience into the device interface. Specifically, they input "a research paper about the evolution and future of artificial intelligence" or "an academic audience with specialized knowledge." Once the input is complete, they click the send button.

[0405] Step 2:

[0406] The device sends the data entered by the user to the server in real time, and the communication is secure because it is done using encrypted HTTP requests.

[0407] Step 3:

[0408] The server analyzes the received data, using natural language processing technology to analyze the theme and characteristics of the target audience, and extracts keywords and technical terms necessary for generating text.

[0409] Step 4:

[0410] The server invokes the generative AI model with specific parameters, including parameters based on the subject and target audience characteristics provided by the user.

[0411] Step 5:

[0412] Generative AI models generate initial sentences based on specified parameters, such as "The evolution of artificial intelligence (AI) has seen rapid development over the past few decades."

[0413] Step 6:

[0414] The server re-analyzes the generated text, correcting grammar and improving style, detecting grammatical errors and correcting them using dedicated correction algorithms, and refining the presentation based on style guidelines.

[0415] Step 7:

[0416] The server sends the corrected and improved sentences and multiple suggestions to the user's device, where the user can check the suggestions.

[0417] Step 8:

[0418] The user can check the proposed improvements on their device and make further corrections as necessary, for example, changing "evolution" to "progress."

[0419] Step 9:

[0420] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0421] This series of steps allows users to efficiently generate high-quality text and significantly improve its quality.

[0422] Example 1

[0423] 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."

[0424] Conventional text generation systems have had problems with the quality of the text they generate, especially when targeting specialized readers. Furthermore, correcting grammatical errors and improving style in the generated text requires a lot of time and effort. This makes it difficult for users to efficiently generate high-quality text.

[0425] 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.

[0426] In this invention, the server includes means for a user to provide input information such as the topic of the text and the characteristics of the target readers through a terminal, means for transmitting the input information to the server in real time, means for analyzing the input data using natural language processing technology and extracting necessary parameters, means for invoking a generative AI model and generating an initial text based on the user's input information, means for reanalyzing the generated text and correcting grammar and improving style, means for providing the corrected text and multiple suggestions to the user and accepting user corrections, and means for saving the final text and outputting it in a specified format. This enables a user to efficiently generate high-quality text and improve its quality.

[0427] "User" refers to an individual or corporation that provides input information from a terminal to generate text using this system.

[0428] A "terminal" is an electronic device used by a user to provide input information and communicate with a server. Examples include personal computers and smartphones.

[0429] "Server" means a computer system that receives data sent by a user, analyzes it, generates text using a generative AI model, corrects grammar and style, saves the final text, and outputs it in the specified format.

[0430] "Input information" refers to data such as the topic of the text and the characteristics of the target readers that the user provides through the terminal.

[0431] "Natural language processing technology" refers to technology for processing human language using a computer, and examples include text analysis and keyword extraction.

[0432] "Parameters" are data and settings required for sentence generation, which are analyzed and extracted by the server to be passed to the generative AI model.

[0433] A "generative AI model" is an algorithm or software that uses artificial intelligence techniques to generate sentences based on user prompts. Examples include ChatGPT.

[0434] A "prompt sentence" is text that is input into a generative AI model and serves as the basis for the model to generate sentences based on it.

[0435] "Grammar correction" is the process of detecting grammatical errors in the generated sentences and correcting them correctly.

[0436] "Style enhancement" is the process of refining and improving the expression and tone of the generated text.

[0437] A "suggestion" is a revised sentence or multiple variations that the server provides to the user, and is an option for the user to select and make revisions.

[0438] The "final text" is a text that has been finalized after the user has completed the revisions.

[0439] "Specified format" refers to the format in which the final document is to be saved or output, examples of which include PDF and Word files.

[0440] The system of the present invention is designed to enable users to efficiently create high-quality texts, utilizing a generative AI model to quickly and accurately generate texts that meet the user's needs and correct grammar and style.

[0441] First, the user uses the terminal to provide input information such as the topic of the text and the characteristics of the target readers. This input information can be specific, such as "The evolution and future of artificial intelligence" or "Academic readers with specialized knowledge." Once the input is complete, the user clicks the send button, which sends the input information to the server.

[0442] The terminal transmits the data entered by the user to the server in real time. During this communication process, the data is sent as an encrypted HTTP request using TLS / SSL or other protocols, ensuring security.

[0443] The server analyzes the received data and determines the necessary parameters. Specifically, it uses natural language processing technology (such as SpaCy or NLTK) to analyze the subject and characteristics of the target audience and extract keywords and technical terms necessary for text generation.

[0444] The server then invokes a generative AI model (e.g., ChatGPT) with specific parameters, providing the model with a specific prompt, such as "Write a piece about the evolution and future of artificial intelligence for an academic audience with specialized knowledge."

[0445] A generative AI model generates initial sentences based on a given prompt. At this stage, the model leverages large amounts of training data to generate sentences with appropriate context and detail. For example, a generated sentence might be, "The evolution of artificial intelligence (AI) has seen rapid development over the past few decades."

[0446] The generated sentences are then re-analyzed on the server side. This process includes using a grammar checker (e.g., Grammarly or LanguageTool) to detect and correct grammatical errors. The process also refines the expression based on style guidelines to improve the quality of the sentences. Corrected examples are obtained, such as: "The development of artificial intelligence (AI) has been remarkable over the past few decades, and this paper examines its evolution and future prospects in detail."

[0447] The server then sends the revised and improved text and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further revisions. For example, the user may change "evolution" to "progress" or rearrange the order of sentences.

[0448] Finally, the text that the user has confirmed is saved to the device's local storage. It is also possible to output the text in a specified format (e.g., PDF or Word file). The user can then use the saved file in other applications.

[0449] As described above, the system of the present invention provides a specific means for users to efficiently generate high-quality text and improve that quality.

[0450] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0451] Step 1:

[0452] A user accesses the DocCraft Elite interface on a device, where they provide input information such as the topic of the article and the characteristics of the target audience. For example, they enter specific content such as "The evolution and future of artificial intelligence" or "Academic readers with specialized knowledge," and click the submit button. The input data includes the topic of the article and the target audience, and the output is encrypted request data.

[0453] Step 2:

[0454] The terminal transmits the data entered by the user to the server in real time. During this communication process, the input data is sent as an HTTP request using encryption technology such as TLS / SSL. The input is the data provided by the user, and the output is an encrypted HTTP request.

[0455] Step 3:

[0456] The server analyzes the received data. Specifically, it uses natural language processing technology (e.g., SpaCy or NLTK) to analyze the topic and characteristics of the target audience and extract keywords and technical terms necessary for text generation. The input is the data in the encrypted HTTP request, and the output is the analyzed keywords and parameters.

[0457] Step 4:

[0458] The server uses the obtained parameters to call a generative AI model (e.g., ChatGPT). At this time, it generates text to be passed to the generative AI model as a prompt. For example, a specific sentence such as "Please write a piece about the evolution and future of artificial intelligence for an academic audience with specialized knowledge" is input to the generative AI model. The input is the parsed parameters and the generated prompt, and the output is the initial sentence.

[0459] Step 5:

[0460] A generative AI model generates an initial sentence based on a given prompt. The model utilizes large-scale training data to generate sentences with appropriate context and details. A sentence such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades" is generated. The input is the prompt, and the output is the initial generated sentence.

[0461] Step 6:

[0462] The server re-analyzes the generated text. This process involves using a grammar checker (e.g., Grammarly or LanguageTool) to detect and correct grammatical errors. It also refines the expression based on style guidelines to improve the quality of the text. For example, it obtains a corrected example such as, "Artificial intelligence (AI) has developed significantly over the past few decades. This paper examines its evolution and future prospects in detail." The input is the initial generated text, and the output is the corrected text.

[0463] Step 7:

[0464] The server sends the corrected and improved sentences and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further corrections. The input is the corrected and improved sentences, and the output is the improvement suggestions provided to the user.

[0465] Step 8:

[0466] The user checks the proposed improvements on the device and makes additional corrections as necessary. For example, they make specific adjustments such as changing "evolution" to "progress" or rearranging the order of sentences. The input is the improvement proposal sent from the server, and the output is the final revised sentence.

[0467] Step 9:

[0468] The device saves the user's finalized text in local storage. It is also possible to output the text in a specified format (e.g., PDF or Word file). The user can use the saved file in other applications. The input is the final revised text, and the output is the text in the saved file format.

[0469] (Application example 1)

[0470] 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."

[0471] In the current content creation process, it is difficult to efficiently generate high-quality text based on a specific topic. In particular, correcting grammar and style, using technical terms based on the reader's characteristics, and providing suggestions for improvement to the user require a lot of time and effort. Therefore, there is a need for a support system that helps users create their own content quickly and accurately and improves the quality of the final text.

[0472] 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.

[0473] In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for generating initial sentences based on the input information using a generative AI model, means for correcting and improving the grammar and style of the generated sentences, means for providing multiple improvement suggestions to the user and accepting the user's corrections, and means for saving the final sentences and outputting them in a specified format, thereby enabling the user to quickly and efficiently create high-quality sentences based on a theme.

[0474] "Input information" refers to initial data such as the theme and characteristics of the target audience that the user provides to the system.

[0475] "Natural language processing technology" is a technology that uses computers to process and analyze language used by humans.

[0476] A "generative AI model" is an artificial intelligence model that automatically generates sentences based on input information provided by the user.

[0477] An "initial sentence" is the sentence that a generative AI model first generates based on input information.

[0478] "Grammar" refers to the rules and structure of language used to construct sentences.

[0479] "Style" is a particular method or characteristic of the presentation or presentation of writing.

[0480] "Correction and improvement" refers to the process of correcting grammatical and stylistic errors and inappropriate parts of the generated text to improve its quality.

[0481] The "multiple improvement suggestions" are multiple corrections or alternatives that are provided to the user for the generated text.

[0482] A "prompt sentence" is an instruction or input sentence given to a generative AI model when generating a specific sentence.

[0483] "Preservation" refers to recording the written work in a digital format so that it can be reused later.

[0484] "Specified format" refers to the particular digital file format in which the final document will be saved or output.

[0485] 1. System Overview

[0486] The system that realizes this application example generates high-quality text based on user input, corrects grammar and style, and suggests improvements, and then saves and outputs the final text. The system is mainly composed of a server and a user terminal, and operates in the following steps.

[0487] 2. Hardware and software used

[0488] Hardware

[0489] Server: Processes data and runs generative AI models. A server with a high-performance CPU and large memory capacity is desirable.

[0490] User device: Personal computer (PC), smartphone, tablet, head-mounted display, etc. Provides an interface for users to input information and check and correct the generated text.

[0491] software

[0492] Generative AI model: A natural language processing model such as the OpenAI API. It generates sentences based on user input.

[0493] Encrypted communication protocols, such as HTTPS, that ensure the secure transmission of user-provided input data and generated text.

[0494] Data saving format: PDF, Word, etc. Used to save and output the final document in the format desired by the user.

[0495] 3. Data processing and calculation

[0496] Receiving and analyzing user-entered information

[0497] The user enters information into the device, such as the topic and characteristics of the target audience. This information might include, for example, "The evolution and future of artificial intelligence" or "Technology-savvy readers." The input data is sent to the server in real time via an encrypted HTTP request.

[0498] Initial sentence generation using a generative AI model

[0499] The server analyzes the received data and provides the extracted keywords and terminology to the generative AI model. The generative AI model uses natural language processing techniques, such as the OpenAI API, to generate initial sentences based on the provided information. For example, the prompt sentence could be "Write an article about the evolution of artificial intelligence for a tech-savvy audience."

[0500] Grammar and style fixes

[0501] The generated initial sentences are then analyzed again on the server, where natural language processing techniques are used to detect and correct grammatical errors and refine the sentences based on style guidelines, thereby improving the quality of the sentences.

[0502] Providing improvement suggestions

[0503] The server generates multiple suggestions for corrected and improved sentences and sends them to the user's device, where the user can review them and manually make additional corrections if necessary.

[0504] Save and output the final text

[0505] The finalized text is saved on the user's device in the format selected by the user (PDF or Word file).

[0506] 4. Specific Examples

[0507] Example of user input

[0508] Theme: "The Evolution of Artificial Intelligence"

[0509] Target audience: "Technical readers"

[0510] Prompt: "Write an article about the evolution of artificial intelligence for a tech-savvy audience."

[0511] In this way, users can quickly and efficiently create high-quality texts based on a theme.

[0512] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0513] Step 1:

[0514] The user uses a terminal to input information into the interface, such as the topic of the text and the characteristics of the target audience. Examples include "The evolution and future of artificial intelligence" and "Technology-savvy readers." By clicking the submit button, the input data is sent to the server in real time as an encrypted HTTP request. Input: Topic and characteristics of the target audience. Output: Transmission of encrypted input data.

[0515] Step 2:

[0516] The server analyzes the received data and extracts necessary parameters based on the input information using natural language processing technology. For example, if the topic is "The Evolution and Future of Artificial Intelligence," related keywords and technical terms are extracted. Input: Encrypted input data, Output: Analyzed parameters (keywords, technical terms).

[0517] Step 3:

[0518] The server uses the parsed parameters to provide a prompt to the generative AI model. For example, it generates a prompt such as "Write an article about the evolution of artificial intelligence for a tech-savvy audience." The generative AI model generates an initial sentence based on the provided information. Input: Parsed parameters, Output: Initial sentence.

[0519] Step 4:

[0520] The generated initial sentence is then re-analyzed by the server. Natural language processing techniques are used to detect and correct grammatical errors, and the sentence is refined based on style guidelines. This process improves the quality of the sentence. Input: Initial sentence, Output: Corrected and improved sentence.

[0521] Step 5:

[0522] The server generates multiple improvement suggestions based on the corrected and improved sentences and sends them to the user's terminal. The user checks these suggestions and manually makes additional corrections as needed. Input: corrected sentence, Output: multiple improvement suggestions.

[0523] Step 6:

[0524] The user checks the provided improvement suggestions on the device and modifies the text as necessary. The text that the user has finally confirmed can be saved on the device. It is also possible to save and output in a specified format (e.g. PDF or Word file). Input: Improvement suggestions and user modifications, Output: Final confirmed text.

[0525] Step 7:

[0526] The final text is saved in the format specified by the user (PDF or Word file). This allows users to efficiently create high-quality text and save it in various formats. Input: Final text, Output: Text saved in the specified format.

[0527] 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.

[0528] The present invention relates to a system for efficiently creating high-quality text, and in particular to a system that combines an emotion engine to enable text generation that takes into account the user's emotions. Specific embodiments of the present invention are described below.

[0529] Explanation of program processing

[0530] User Input

[0531] Users access the DocCraft Elite interface on their device and enter the topic and target audience characteristics for their writing, such as "Research paper on the evolution and future of artificial intelligence" or "Academic audience with specialized knowledge." Once the user has completed the input information, they click the submit button.

[0532] User Emotion Recognition

[0533] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. For example, it can estimate the user's emotions from input speed, typing strength, facial recognition cameras, etc.

[0534] Sending input data

[0535] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server using encrypted HTTP requests.

[0536] Input data and sentiment analysis

[0537] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also sets the parameters necessary for sentence generation, taking into account the emotional state provided by the emotional engine.

[0538] Invoking a generative AI model

[0539] The server invokes a generative AI model based on set parameters, which includes adjusting tone and style depending on the user's emotional state—for example, generating formal sentences in a calm emotional state and more energetic sentences in an excited emotional state.

[0540] Sentence generation

[0541] A generative AI model generates an initial sentence based on the specified parameters, such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0542] Text corrections and improvements

[0543] The server re-analyzes the generated text, correcting grammar and improving style. It detects grammatical errors and corrects them using a dedicated correction algorithm. It also adjusts the writing style by taking into account the emotional state provided by the emotion engine.

[0544] Providing improvement suggestions

[0545] The server sends the corrected and improved sentences and multiple suggestions to the user's device, where the user can check the suggestions.

[0546] User verification and correction

[0547] The user can check the improvement proposals sent from the server on their device and make further corrections as necessary, for example, by selecting the most appropriate expression according to the user's emotional state.

[0548] Save and output the final text

[0549] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0550] Specific examples

[0551] Writing an introduction for a research paper

[0552] 1. User input: A student (user) enters "research paper on the evolution and future of artificial intelligence" into the terminal and specifies "academic readers with specialized knowledge" as the target audience.

[0553] 2. User Emotion Recognition: The device's emotion engine analyzes the user's typing speed and facial expressions to estimate their emotional state. For example, if the user is excited, the device will adjust the tone of the text to be more energetic.

[0554] 3. Sending input data: The device sends the data and emotional state to the server.

[0555] 4. Input data and emotion analysis: The server analyzes the data and extracts necessary keywords and parameters. It also adjusts the response according to the user's emotional state.

[0556] 5. Calling the generative AI model: The server calls the generative AI model and begins generating sentences.

[0557] 6. Sentence generation: The generative AI model creates initial sentences.

[0558] 7. Correction and improvement of sentences: The server corrects the generated sentences based on grammar and emotional state.

[0559] 8. Providing improvement suggestions: The server sends improvement suggestions to the student's device.

[0560] 9. User review and correction: Students review the suggestions and make further corrections.

[0561] 10. Save and output the final text: The terminal saves the completed text in the specified format.

[0562] This series of processes enables users to efficiently generate high-quality, emotion-sensitive sentences and improve their quality.

[0563] The processing flow will be explained below.

[0564] Step 1:

[0565] The user inputs the topic of the writing and the characteristics of the target audience into the device interface. For example, they might input "The evolution and future of artificial intelligence" and specify "academic readers with specialized knowledge" as the target audience. Once they have completed the input, they click the send button.

[0566] Step 2:

[0567] The device's emotion engine analyzes the user's emotional state based on the content of their input, their input speed, their typing strength, and the facial recognition camera. The emotion engine obtains information such as whether the user is relaxed, excited, or stressed.

[0568] Step 3:

[0569] The device transmits the user-entered data and analyzed emotional state to the server in real time using encrypted HTTP requests.

[0570] Step 4:

[0571] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms for the article based on the topic and characteristics of the target audience. It also sets parameters for sentence generation, taking into account the emotional state provided by the emotional engine.

[0572] Step 5:

[0573] The server calls the generative AI model based on the set parameters and emotional information. For example, if the user is relaxed, it instructs the model to generate calm sentences, and if the user is excited, it instructs the model to generate energetic sentences.

[0574] Step 6:

[0575] A generative AI model generates an initial sentence based on specified parameters, such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0576] Step 7:

[0577] The server then re-analyzes the generated text, correcting grammar and improving style. It detects grammatical errors and corrects them using a dedicated correction algorithm. It also refines the expression based on style guidelines and adapts the writing style to suit the emotional state.

[0578] Step 8:

[0579] The server sends the corrected and improved sentences and multiple suggestions to the user's device, and the user can review and select the best sentence from the multiple options.

[0580] Step 9:

[0581] The user can check the proposed improvements sent from the server on their device and make any necessary adjustments. For example, they can change "evolution" to "progress." The system also selects the optimal expression based on the user's emotional state.

[0582] Step 10:

[0583] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0584] This series of steps allows users to efficiently generate high-quality, emotion-sensitive text and significantly improve its quality.

[0585] Example 2

[0586] 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."

[0587] In today's world, efficient and high-quality text creation is an important challenge. However, it is difficult to generate text while taking into account the user's emotional state using conventional technologies. Furthermore, to improve the quality of generated text, it is necessary to integrate natural language processing technology and emotion recognition technology. Unless these problems are resolved, it will be difficult to generate text that satisfies users.

[0588] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for analyzing the user's emotional state, means for setting parameters necessary for sentence generation based on the analyzed emotional state, means for calling a generation AI model and generating sentences based on specified parameters, means for correcting and improving the grammar and style of the generated sentences, means for providing improvement suggestions to the user and accepting user corrections, and means for saving the final sentences and outputting them in a specified format. This makes it possible to generate high-quality sentences that take the user's emotional state into consideration.

[0589] "Natural language processing technology" is a general term for technology that analyzes and generates language data, and is a means of performing semantic analysis of text, grammatical analysis, keyword extraction, etc.

[0590] "Emotional state" refers to the user's psychological and physiological state, and indicates emotions estimated from the user's input behavior, facial expressions, tone of voice, and the like.

[0591] "Parameters" are various setting items and values ​​that are set in text generation, and include the theme, tone, style, frequency of use of technical terms, and the like.

[0592] A "generative AI model" is an algorithm or model that uses machine learning or deep learning techniques to generate text, and is used to generate text from input data.

[0593] "Grammar and style correction and improvement" is a means of correcting grammatical errors in the generated text and adjusting and improving the writing style according to the user's requests and emotional state.

[0594] "Improvement suggestions" are alternatives or corrections presented to the generated or corrected text, and are intended as a reference for the user when making selections or corrections.

[0595] "Format" refers to the format and structure of a file, particularly the format used to save and output documents, such as PDF or Word files.

[0596] "Analysis means" refers to the technical means used to process input information to understand its meaning or to extract specific patterns from the data.

[0597] "Input information" refers to data or information that a user provides to the system, including, for example, the topic of the writing task and the characteristics of the target readers.

[0598] The "means for accepting user corrections" refers to a technical means for reflecting the corrections made by the user when the user makes additional corrections to the generated text or the proposed corrections.

[0599] "Storage and output means" means the technical means used to store the final document in local storage and output it in a specified format.

[0600] This invention is a system for efficiently creating high-quality text, and in particular, it enables text generation that takes into account the user's emotions by combining an emotion engine. Specific embodiments of this invention are described below.

[0601] User Input

[0602] Users access the system's interface using a terminal. They input the topic and target audience characteristics for the writing, such as "a research paper on the evolution and future of artificial intelligence" or "an academic audience with specialized knowledge." Once the user has completed the input information, they click the submit button.

[0603] User Emotion Recognition

[0604] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. For example, it can estimate the user's emotions from input speed, typing strength, and facial recognition cameras. Dedicated software and hardware (e.g., facial recognition cameras) are used for emotion recognition.

[0605] Sending input data

[0606] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server, where the communication is carried out using encrypted HTTP requests, ensuring data security.

[0607] Input data and sentiment analysis

[0608] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation. Technically, natural language processing libraries and APIs are used.

[0609] Invoking a generative AI model

[0610] The server invokes a generative AI model based on the set parameters, including the prompt text. The generative AI model also adjusts tone and style depending on the user's emotional state. For example, a calm emotional state generates more formal text, while an excited emotional state generates more energetic text.

[0611] Sentence generation

[0612] The generative AI model generates an initial sentence based on the specified parameters and prompt sentence. For example, the generated initial sentence might be something like, "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0613] Text corrections and improvements

[0614] The server then re-analyzes the generated text, correcting grammar and improving style. A dedicated correction algorithm detects and corrects grammatical errors. The server also adjusts the writing style by taking into account the emotional state provided by the emotion engine. For example, it corrects typos and changes the tone to be more energetic.

[0615] Providing improvement suggestions

[0616] The server sends the revised and improved text and multiple suggestions to the user's device, allowing the user to review the suggestions. For example, the server may present a "revised version of the problem" and an "improved style proposal."

[0617] User verification and correction

[0618] The user can check the proposed improvements sent from the server on their device and make further corrections as necessary. For example, they can make adjustments such as "changing the style to be more formal" or "adding specific keywords."

[0619] Save and output the final text

[0620] The device saves the final text in local storage and can output the text in a specified format, such as PDF or Word, according to the user's instructions.

[0621] Examples of concrete examples and prompts

[0622] For example, if a user is writing a "research paper on the evolution and future of artificial intelligence" and is targeting an "academic audience with specialized knowledge," they could use the following prompt:

[0623] "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades. In particular,..."

[0624] This series of processes enables users to efficiently generate high-quality, emotion-sensitive sentences and improve their quality.

[0625] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0626] Step 1: User Input

[0627] The user accesses the system's interface using a terminal and inputs the topic of the text they want to generate and the characteristics of the target audience. For example, they can input "research paper on the evolution and future of artificial intelligence" or "academic audience with specialized knowledge." By clicking the submit button, this data is saved on the terminal. This stores the input information within the system.

[0628] Step 2: Recognizing user emotions

[0629] The device analyzes the user's emotional state based on their input and interaction data. The emotion engine processes data from the input speed, typing strength, and facial recognition camera to estimate the user's emotional state. The resulting output is a message indicating whether the user is excited or calm.

[0630] Step 3: Submitting input data

[0631] The device sends the user's input data and the emotion recognition results to the server. The data is sent via an encrypted HTTP request, ensuring data security. The server receives this and proceeds to the next analysis step.

[0632] Step 4: Input data and sentiment analysis

[0633] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation. As a result of the analysis, the necessary keywords and emotional parameters are output.

[0634] Step 5: Invoke the generative AI model

[0635] The server calls the generative AI model based on the set parameters and begins generating sentences. A prompt sentence is also provided as input. The generative AI model generates initial sentences in a tone and style that reflects the user's emotional state. The initial sentences are then output.

[0636] Step 6: Sentence generation

[0637] The generative AI model generates an initial sentence based on the prompt and the set parameters. The generated sentence might be something like, "The evolution of artificial intelligence (AI) has made rapid progress over the past few decades." This is the output.

[0638] Step 7: Edit and improve your writing

[0639] The server then re-analyzes the generated text and corrects grammatical and stylistic errors. It uses a proprietary correction algorithm to detect errors and adjusts the writing style based on data from the emotion engine. The corrected text is then output.

[0640] Step 8: Providing suggestions for improvement

[0641] The server sends the revised and improved text and multiple suggestions to the user's device, where the user can review these suggestions. For example, the server outputs "revised version of the problem" and "improved style proposal."

[0642] Step 9: Verify and Modify Users

[0643] The user can then check the proposed improvements on the terminal and make further revisions as necessary, resulting in a final version of the text with more detailed revisions.

[0644] Step 10: Save and export the final document

[0645] The device saves the final text that the user has finalized in local storage. Then, based on the user's instructions, it outputs the text in a specified format, such as a PDF or Word file. The final text is saved and output in the specified format.

[0646] (Application example 2)

[0647] 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."

[0648] Conventional text generation systems have difficulty generating personalized content based on the user's emotional state, making them insufficient as a means for efficiently creating high-quality text. Furthermore, text that does not take emotions into account has the problem of being difficult to capture the interest of specific situations or target readers. Furthermore, there is a lack of technology for utilizing interactive devices to reflect emotional feedback in real time. Therefore, there is a need for text generation that reflects the user's emotions and for improving the quality of such text generation.

[0649] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for correcting and improving the grammar and style of the generated sentence, means for providing improvement suggestions to the user and accepting the user's corrections, and means for analyzing the user's emotional state using an interactive device, setting parameters based on the emotional information, and generating sentences according to the emotions using a generative AI model. This makes it possible to efficiently generate high-quality sentences that reflect the user's emotions and improve their quality.

[0650] "Input information" refers to data such as themes for writing and characteristics of the target readers that users provide to the system.

[0651] "Natural language processing technology" is a general term for algorithms and methods for analyzing, understanding, and generating human language, and refers to the technology used to analyze and generate sentences.

[0652] "Means for analyzing" refers to a method or apparatus for receiving input information and interpreting or analyzing it using natural language processing techniques.

[0653] "Means for correcting and improving" refers to methods and devices for checking the grammar and style of the generated text and correcting or optimizing it as necessary.

[0654] The "means for providing improvement suggestions" refers to a method or device for presenting candidates or suggested corrections to the generated sentence to the user and accepting confirmation or corrections.

[0655] "Storage means" refers to the method or device for recording the final text in a storage location such as local storage or the cloud.

[0656] "Means for outputting in a specified format" refers to a method or device for outputting the generated text in a specific format, such as a PDF or Word file.

[0657] "Interactive device" refers to a smartphone, tablet, or other interface that allows for real-time interaction with a user.

[0658] "Means for analyzing emotional states" refers to methods and devices for estimating and recognizing emotions based on information such as a user's facial expressions and voice.

[0659] "Means for setting parameters based on emotion information" refers to a method or device that determines setting values ​​for sentence generation taking into account the analyzed emotions.

[0660] "Generative AI model" refers to an algorithm or network model that uses artificial intelligence technology to automatically generate text.

[0661] "Means for generating sentences according to emotions" refers to a method or device that generates sentences with an appropriate tone and style based on the analyzed emotions.

[0662] This invention relates to a system for efficiently creating high-quality text that takes user emotions into consideration, particularly for realizing personalized text generation in content distribution services. This system includes receiving input information, analyzing it using natural language processing technology, correcting and improving the grammar and style of the generated text, providing improvement suggestions to the user, analyzing the emotional state using an interactive device, generating text according to the emotions using a generative AI model, and saving and outputting the final text.

[0663] First, the user accesses the system interface using a terminal and inputs the topic for writing and the characteristics of the target audience, such as "Hawaii travel experience" or "general readership." Once the user has completed the input information, they click the submit button.

[0664] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. Using the smartphone's camera and microphone, the system can estimate the user's emotions from their input speed, facial recognition camera data, and tone of voice. For example, if the system detects that the user is currently excited, that emotional information is transmitted to the system.

[0665] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server. Communication is performed using encrypted HTTP requests. The server analyzes the received data and emotional state and uses natural language processing technology to extract technical terms and keywords based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation.

[0666] The server then uses these parameters to call a generative AI model, which also adjusts tone and style based on the user's emotional state. For example, if the user is excited, the model will generate more energetic text.

[0667] The generated text undergoes a grammar check and style improvement process to further improve its quality. The server then sends the final improved text and several suggestions to the user's device. The user reviews the suggestions and makes further corrections as necessary. The user can then save the finalized text to local storage and output it in a specified format (e.g., PDF or Word file).

[0668] This system enables users to efficiently generate personalized, high-quality sentences that reflect their own emotions. An example of a specific prompt sentence is "Write an excited article about Hawaii travel experience for general readers." Using this prompt sentence, the generative AI model generates optimal sentences that take the user's emotions into consideration.

[0669] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0670] Step 1:

[0671] The user uses a terminal to access the system's interface and input the topic and target reader characteristics for the writing. The input information includes data such as "Hawaii travel experience" and "general reader." When the user completes the input information, the terminal accepts the click of a submit button. The input includes the topic and target reader information, and the output is sent to the system.

[0672] Step 2:

[0673] The emotion engine installed on the device analyzes the user's emotional state based on their input and interactions. It uses the smartphone's camera and microphone to collect input speed, facial recognition data, and tone of voice. Based on this data, the emotion engine estimates the user's emotion (e.g., excited, calm, etc.). The inputs are facial recognition data and tone of voice, and the output is the estimated emotional state.

[0674] Step 3:

[0675] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server using encrypted HTTP requests. The inputs are the theme, target audience information, and emotional state, and the output is this data sent to the server.

[0676] Step 4:

[0677] The server analyzes the received data (theme, target reader information, emotional state). It uses natural language processing technology to extract technical terms and keywords based on the characteristics of the theme and target reader. As a result of the analysis, parameters for detailed text generation are set. The input is the transmitted theme, target reader information, and emotional state, and the set parameters are obtained as the output.

[0678] Step 5:

[0679] The server calls the generative AI model based on the set parameters. Specifically, it adjusts the tone and style according to the user's emotional state and generates the initial sentence. The generative AI model uses a prompt sentence, such as "Write an excited article about Hawaii travel experience for general readers," to generate sentences that adapt to the emotion. The inputs are the set parameters and the prompt sentence, and the output is the initial generated sentence.

[0680] Step 6:

[0681] The generated text is then passed through a grammar checking and style improvement process on the server to improve its quality. Grammar errors are detected and corrected as necessary. The input is the initial generated text, and the output is the corrected and improved text.

[0682] Step 7:

[0683] The server sends the revised and improved sentences as multiple suggestions to the user's device. The user reviews these suggestions and makes any necessary revisions to finalize the sentence. The input is the revised and improved sentence, and the output is multiple suggestions that are provided to the user.

[0684] Step 8:

[0685] The user reviews the suggestions and makes any necessary revisions. The final text is saved on the device and output in the specified format (e.g., PDF or Word file). The input is the final text and format selected by the user, and the output is the final text saved in the specified format.

[0686] 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.

[0687] 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.

[0688] 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.

[0689] [Third embodiment]

[0690] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0691] 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.

[0692] 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).

[0693] 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.

[0694] 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.

[0695] 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).

[0696] 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. 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.

[0697] 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.

[0698] 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.

[0699] 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.

[0700] 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.

[0701] 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."

[0702] This invention is a system that enables users to efficiently create high-quality texts. The system utilizes a generative AI model to quickly and accurately generate texts that meet the user's needs and corrects grammar and style.

[0703] Explanation of program processing

[0704] User Input

[0705] The user uses a terminal to input information into the DocCraft Elite interface, such as the topic of the text and the characteristics of the target audience. This information can be specific, such as "The evolution and future of artificial intelligence" or "Academic audience with specialized knowledge." Once the input is complete, the user clicks the submit button to send the information to the server.

[0706] Sending input data

[0707] The device sends the data entered by the user to the server in real time, and the data is sent as an encrypted HTTP request during this communication process, ensuring security.

[0708] Analyzing input data

[0709] The server analyzes the received data and determines the necessary parameters. Specifically, it analyzes the theme and characteristics of the target audience using natural language processing technology and extracts the keywords and technical terms necessary for generating text.

[0710] Invoking a generative AI model

[0711] The server invokes the ChatGPT-based generative AI model with specific parameters, which generates an initial sentence based on the user's input data.

[0712] Sentence generation

[0713] A generative AI model generates appropriate sentences based on user-provided information, such as an initial sentence like, "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0714] Text corrections and improvements

[0715] The server then reanalyzes the generated text and performs grammatical corrections and style improvements. This involves using natural language processing techniques to detect and correct grammatical errors. It also refines the expression based on style guidelines to improve the quality of the text. An example of a post-processing correction is, "Artificial intelligence (AI) has seen remarkable developments over the past few decades. This paper examines its evolution and future prospects in detail."

[0716] Providing improvement suggestions

[0717] The server sends the corrected and improved text and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further corrections.

[0718] User verification and correction

[0719] The user can check the proposed improvements sent from the server on their device and make additional adjustments as necessary, such as changing the word "evolution" to "progress."

[0720] Save and output the final text

[0721] The device saves the final text that the user has confirmed in local storage and can output the text in a specified format (e.g., PDF or Word file).

[0722] Specific examples

[0723] Writing an introduction for a research paper

[0724] 1. User input: A student (user) enters "research paper on the evolution and future of artificial intelligence" into the terminal and specifies "academic readers with specialized knowledge" as the target audience.

[0725] 2. Sending input data: The terminal sends the input data to the server.

[0726] 3. Parsing input data: The server parses the data and extracts the necessary keywords and parameters.

[0727] 4. Calling the generative AI model: The server calls the generative AI model and begins generating sentences.

[0728] 5. Sentence generation: The generative AI model creates initial sentences.

[0729] 6. Correcting and improving text: The server corrects the generated text based on grammar and style guidelines.

[0730] 7. Providing improvement suggestions: The server sends improvement suggestions to the student's device.

[0731] 8. User review and revision: Students review the proposal and make further revisions.

[0732] 9. Save and output the final text: The terminal saves the completed text in the specified format.

[0733] The above is a specific embodiment for carrying out the invention. This system enables users to efficiently generate high-quality professional documents and improve their quality.

[0734] The processing flow will be explained below.

[0735] Step 1:

[0736] The user inputs the topic of the writing and the characteristics of the target audience into the device interface. Specifically, they input "a research paper about the evolution and future of artificial intelligence" or "an academic audience with specialized knowledge." Once the input is complete, they click the send button.

[0737] Step 2:

[0738] The device sends the data entered by the user to the server in real time, and the communication is secure because it is done using encrypted HTTP requests.

[0739] Step 3:

[0740] The server analyzes the received data, using natural language processing technology to analyze the theme and characteristics of the target audience, and extracts keywords and technical terms necessary for generating text.

[0741] Step 4:

[0742] The server invokes the generative AI model with specific parameters, including parameters based on the subject and target audience characteristics provided by the user.

[0743] Step 5:

[0744] Generative AI models generate initial sentences based on specified parameters, such as "The evolution of artificial intelligence (AI) has seen rapid development over the past few decades."

[0745] Step 6:

[0746] The server re-analyzes the generated text, correcting grammar and improving style, detecting grammatical errors and correcting them using dedicated correction algorithms, and refining the presentation based on style guidelines.

[0747] Step 7:

[0748] The server sends the corrected and improved sentences and multiple suggestions to the user's device, where the user can check the suggestions.

[0749] Step 8:

[0750] The user can check the proposed improvements on their device and make further corrections as necessary, for example, changing "evolution" to "progress."

[0751] Step 9:

[0752] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0753] This series of steps allows users to efficiently generate high-quality text and significantly improve its quality.

[0754] Example 1

[0755] 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."

[0756] Conventional text generation systems have had problems with the quality of the text they generate, especially when targeting specialized readers. Furthermore, correcting grammatical errors and improving style in the generated text requires a lot of time and effort. This makes it difficult for users to efficiently generate high-quality text.

[0757] 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.

[0758] In this invention, the server includes means for a user to provide input information such as the topic of the text and the characteristics of the target readers through a terminal, means for transmitting the input information to the server in real time, means for analyzing the input data using natural language processing technology and extracting necessary parameters, means for invoking a generative AI model and generating an initial text based on the user's input information, means for reanalyzing the generated text and correcting grammar and improving style, means for providing the corrected text and multiple suggestions to the user and accepting user corrections, and means for saving the final text and outputting it in a specified format. This enables a user to efficiently generate high-quality text and improve its quality.

[0759] "User" refers to an individual or corporation that provides input information from a terminal to generate text using this system.

[0760] A "terminal" is an electronic device used by a user to provide input information and communicate with a server. Examples include personal computers and smartphones.

[0761] "Server" means a computer system that receives data sent by a user, analyzes it, generates text using a generative AI model, corrects grammar and style, saves the final text, and outputs it in the specified format.

[0762] "Input information" refers to data such as the topic of the text and the characteristics of the target readers that the user provides through the terminal.

[0763] "Natural language processing technology" refers to technology for processing human language using a computer, and examples include text analysis and keyword extraction.

[0764] "Parameters" are data and settings required for sentence generation, which are analyzed and extracted by the server to be passed to the generative AI model.

[0765] A "generative AI model" is an algorithm or software that uses artificial intelligence techniques to generate sentences based on user prompts. Examples include ChatGPT.

[0766] A "prompt sentence" is text that is input into a generative AI model and serves as the basis for the model to generate sentences based on it.

[0767] "Grammar correction" is the process of detecting grammatical errors in the generated sentences and correcting them correctly.

[0768] "Style enhancement" is the process of refining and improving the expression and tone of the generated text.

[0769] A "suggestion" is a revised sentence or multiple variations that the server provides to the user, and is an option for the user to select and make revisions.

[0770] The "final text" is a text that has been finalized after the user has completed the revisions.

[0771] "Specified format" refers to the format in which the final document is to be saved or output, examples of which include PDF and Word files.

[0772] The system of the present invention is designed to enable users to efficiently create high-quality texts, utilizing a generative AI model to quickly and accurately generate texts that meet the user's needs and correct grammar and style.

[0773] First, the user uses the terminal to provide input information such as the topic of the text and the characteristics of the target readers. This input information can be specific, such as "The evolution and future of artificial intelligence" or "Academic readers with specialized knowledge." Once the input is complete, the user clicks the send button, which sends the input information to the server.

[0774] The terminal transmits the data entered by the user to the server in real time. During this communication process, the data is sent as an encrypted HTTP request using TLS / SSL or other protocols, ensuring security.

[0775] The server analyzes the received data and determines the necessary parameters. Specifically, it uses natural language processing technology (such as SpaCy or NLTK) to analyze the subject and characteristics of the target audience and extract keywords and technical terms necessary for text generation.

[0776] The server then invokes a generative AI model (e.g., ChatGPT) with specific parameters, providing the model with a specific prompt, such as "Write a piece about the evolution and future of artificial intelligence for an academic audience with specialized knowledge."

[0777] A generative AI model generates initial sentences based on a given prompt. At this stage, the model leverages large amounts of training data to generate sentences with appropriate context and detail. For example, a generated sentence might be, "The evolution of artificial intelligence (AI) has seen rapid development over the past few decades."

[0778] The generated sentences are then re-analyzed on the server side. This process includes using a grammar checker (e.g., Grammarly or LanguageTool) to detect and correct grammatical errors. The process also refines the expression based on style guidelines to improve the quality of the sentences. Corrected examples are obtained, such as: "The development of artificial intelligence (AI) has been remarkable over the past few decades, and this paper examines its evolution and future prospects in detail."

[0779] The server then sends the revised and improved text and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further revisions. For example, the user may change "evolution" to "progress" or rearrange the order of sentences.

[0780] Finally, the text that the user has confirmed is saved to the device's local storage. It is also possible to output the text in a specified format (e.g., PDF or Word file). The user can then use the saved file in other applications.

[0781] As described above, the system of the present invention provides a specific means for users to efficiently generate high-quality text and improve that quality.

[0782] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0783] Step 1:

[0784] A user accesses the DocCraft Elite interface on a device, where they provide input information such as the topic of the article and the characteristics of the target audience. For example, they enter specific content such as "The evolution and future of artificial intelligence" or "Academic readers with specialized knowledge," and click the submit button. The input data includes the topic of the article and the target audience, and the output is encrypted request data.

[0785] Step 2:

[0786] The terminal transmits the data entered by the user to the server in real time. During this communication process, the input data is sent as an HTTP request using encryption technology such as TLS / SSL. The input is the data provided by the user, and the output is an encrypted HTTP request.

[0787] Step 3:

[0788] The server analyzes the received data. Specifically, it uses natural language processing technology (e.g., SpaCy or NLTK) to analyze the topic and characteristics of the target audience and extract keywords and technical terms necessary for text generation. The input is the data in the encrypted HTTP request, and the output is the analyzed keywords and parameters.

[0789] Step 4:

[0790] The server uses the obtained parameters to call a generative AI model (e.g., ChatGPT). At this time, it generates text to be passed to the generative AI model as a prompt. For example, a specific sentence such as "Please write a piece about the evolution and future of artificial intelligence for an academic audience with specialized knowledge" is input to the generative AI model. The input is the parsed parameters and the generated prompt, and the output is the initial sentence.

[0791] Step 5:

[0792] A generative AI model generates an initial sentence based on a given prompt. The model utilizes large-scale training data to generate sentences with appropriate context and details. A sentence such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades" is generated. The input is the prompt, and the output is the initial generated sentence.

[0793] Step 6:

[0794] The server re-analyzes the generated text. This process involves using a grammar checker (e.g., Grammarly or LanguageTool) to detect and correct grammatical errors. It also refines the expression based on style guidelines to improve the quality of the text. For example, it obtains a corrected example such as, "Artificial intelligence (AI) has developed significantly over the past few decades. This paper examines its evolution and future prospects in detail." The input is the initial generated text, and the output is the corrected text.

[0795] Step 7:

[0796] The server sends the corrected and improved sentences and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further corrections. The input is the corrected and improved sentences, and the output is the improvement suggestions provided to the user.

[0797] Step 8:

[0798] The user checks the proposed improvements on the device and makes additional corrections as necessary. For example, they make specific adjustments such as changing "evolution" to "progress" or rearranging the order of sentences. The input is the improvement proposal sent from the server, and the output is the final revised sentence.

[0799] Step 9:

[0800] The device saves the user's finalized text in local storage. It is also possible to output the text in a specified format (e.g., PDF or Word file). The user can use the saved file in other applications. The input is the final revised text, and the output is the text in the saved file format.

[0801] (Application example 1)

[0802] 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."

[0803] In the current content creation process, it is difficult to efficiently generate high-quality text based on a specific topic. In particular, correcting grammar and style, using technical terms based on the reader's characteristics, and providing suggestions for improvement to the user require a lot of time and effort. Therefore, there is a need for a support system that helps users create their own content quickly and accurately and improves the quality of the final text.

[0804] 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.

[0805] In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for generating initial sentences based on the input information using a generative AI model, means for correcting and improving the grammar and style of the generated sentences, means for providing multiple improvement suggestions to the user and accepting the user's corrections, and means for saving the final sentences and outputting them in a specified format, thereby enabling the user to quickly and efficiently create high-quality sentences based on a theme.

[0806] "Input information" refers to initial data such as the theme and characteristics of the target audience that the user provides to the system.

[0807] "Natural language processing technology" is a technology that uses computers to process and analyze language used by humans.

[0808] A "generative AI model" is an artificial intelligence model that automatically generates sentences based on input information provided by the user.

[0809] An "initial sentence" is the sentence that a generative AI model first generates based on input information.

[0810] "Grammar" refers to the rules and structure of language used to construct sentences.

[0811] "Style" is a particular method or characteristic of the presentation or presentation of writing.

[0812] "Correction and improvement" refers to the process of correcting grammatical and stylistic errors and inappropriate parts of the generated text to improve its quality.

[0813] The "multiple improvement suggestions" are multiple corrections or alternatives that are provided to the user for the generated text.

[0814] A "prompt sentence" is an instruction or input sentence given to a generative AI model when generating a specific sentence.

[0815] "Preservation" refers to recording the written work in a digital format so that it can be reused later.

[0816] "Specified format" refers to the particular digital file format in which the final document will be saved or output.

[0817] 1. System Overview

[0818] The system that realizes this application example generates high-quality text based on user input, corrects grammar and style, and suggests improvements, and then saves and outputs the final text. The system is mainly composed of a server and a user terminal, and operates in the following steps.

[0819] 2. Hardware and software used

[0820] Hardware

[0821] Server: Processes data and runs generative AI models. A server with a high-performance CPU and large memory capacity is desirable.

[0822] User device: Personal computer (PC), smartphone, tablet, head-mounted display, etc. Provides an interface for users to input information and check and correct the generated text.

[0823] software

[0824] Generative AI model: A natural language processing model such as the OpenAI API. It generates sentences based on user input.

[0825] Encrypted communication protocols, such as HTTPS, that ensure the secure transmission of user-provided input data and generated text.

[0826] Data saving format: PDF, Word, etc. Used to save and output the final document in the format desired by the user.

[0827] 3. Data processing and calculation

[0828] Receiving and analyzing user-entered information

[0829] The user enters information into the device, such as the topic and characteristics of the target audience. This information might include, for example, "The evolution and future of artificial intelligence" or "Technology-savvy readers." The input data is sent to the server in real time via an encrypted HTTP request.

[0830] Initial sentence generation using a generative AI model

[0831] The server analyzes the received data and provides the extracted keywords and terminology to the generative AI model. The generative AI model uses natural language processing techniques, such as the OpenAI API, to generate initial sentences based on the provided information. For example, the prompt sentence could be "Write an article about the evolution of artificial intelligence for a tech-savvy audience."

[0832] Grammar and style fixes

[0833] The generated initial sentences are then analyzed again on the server, where natural language processing techniques are used to detect and correct grammatical errors and refine the sentences based on style guidelines, thereby improving the quality of the sentences.

[0834] Providing improvement suggestions

[0835] The server generates multiple suggestions for corrected and improved sentences and sends them to the user's device, where the user can review them and manually make additional corrections if necessary.

[0836] Save and output the final text

[0837] The finalized text is saved on the user's device in the format selected by the user (PDF or Word file).

[0838] 4. Specific Examples

[0839] Example of user input

[0840] Theme: "The Evolution of Artificial Intelligence"

[0841] Target audience: "Technical readers"

[0842] Prompt: "Write an article about the evolution of artificial intelligence for a tech-savvy audience."

[0843] In this way, users can quickly and efficiently create high-quality texts based on a theme.

[0844] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0845] Step 1:

[0846] The user uses a terminal to input information into the interface, such as the topic of the text and the characteristics of the target audience. Examples include "The evolution and future of artificial intelligence" and "Technology-savvy readers." By clicking the submit button, the input data is sent to the server in real time as an encrypted HTTP request. Input: Topic and characteristics of the target audience. Output: Transmission of encrypted input data.

[0847] Step 2:

[0848] The server analyzes the received data and extracts necessary parameters based on the input information using natural language processing technology. For example, if the topic is "The Evolution and Future of Artificial Intelligence," related keywords and technical terms are extracted. Input: Encrypted input data, Output: Analyzed parameters (keywords, technical terms).

[0849] Step 3:

[0850] The server uses the parsed parameters to provide a prompt to the generative AI model. For example, it generates a prompt such as "Write an article about the evolution of artificial intelligence for a tech-savvy audience." The generative AI model generates an initial sentence based on the provided information. Input: Parsed parameters, Output: Initial sentence.

[0851] Step 4:

[0852] The generated initial sentence is then re-analyzed by the server. Natural language processing techniques are used to detect and correct grammatical errors, and the sentence is refined based on style guidelines. This process improves the quality of the sentence. Input: Initial sentence, Output: Corrected and improved sentence.

[0853] Step 5:

[0854] The server generates multiple improvement suggestions based on the corrected and improved sentences and sends them to the user's terminal. The user checks these suggestions and manually makes additional corrections as needed. Input: corrected sentence, Output: multiple improvement suggestions.

[0855] Step 6:

[0856] The user checks the provided improvement suggestions on the device and modifies the text as necessary. The text that the user has finally confirmed can be saved on the device. It is also possible to save and output in a specified format (e.g. PDF or Word file). Input: Improvement suggestions and user modifications, Output: Final confirmed text.

[0857] Step 7:

[0858] The final text is saved in the format specified by the user (PDF or Word file). This allows users to efficiently create high-quality text and save it in various formats. Input: Final text, Output: Text saved in the specified format.

[0859] 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.

[0860] The present invention relates to a system for efficiently creating high-quality text, and in particular to a system that combines an emotion engine to enable text generation that takes into account the user's emotions. Specific embodiments of the present invention are described below.

[0861] Explanation of program processing

[0862] User Input

[0863] Users access the DocCraft Elite interface on their device and enter the topic and target audience characteristics for their writing, such as "Research paper on the evolution and future of artificial intelligence" or "Academic audience with specialized knowledge." Once the user has completed the input information, they click the submit button.

[0864] User Emotion Recognition

[0865] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. For example, it can estimate the user's emotions from input speed, typing strength, facial recognition cameras, etc.

[0866] Sending input data

[0867] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server using encrypted HTTP requests.

[0868] Input data and sentiment analysis

[0869] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also sets the parameters necessary for sentence generation, taking into account the emotional state provided by the emotional engine.

[0870] Invoking a generative AI model

[0871] The server invokes a generative AI model based on set parameters, which includes adjusting tone and style depending on the user's emotional state—for example, generating formal sentences in a calm emotional state and more energetic sentences in an excited emotional state.

[0872] Sentence generation

[0873] A generative AI model generates an initial sentence based on the specified parameters, such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0874] Text corrections and improvements

[0875] The server re-analyzes the generated text, correcting grammar and improving style. It detects grammatical errors and corrects them using a dedicated correction algorithm. It also adjusts the writing style by taking into account the emotional state provided by the emotion engine.

[0876] Providing improvement suggestions

[0877] The server sends the corrected and improved sentences and multiple suggestions to the user's device, where the user can check the suggestions.

[0878] User verification and correction

[0879] The user can check the improvement proposals sent from the server on their device and make further corrections as necessary, for example, by selecting the most appropriate expression according to the user's emotional state.

[0880] Save and output the final text

[0881] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0882] Specific examples

[0883] Writing an introduction for a research paper

[0884] 1. User input: A student (user) types "research paper on the evolution and future of artificial intelligence" into the terminal and specifies "academic readers with specialized knowledge" as the target audience.

[0885] 2. User Emotion Recognition: The device's emotion engine analyzes the user's typing speed and facial expressions to estimate their emotional state. For example, if the user is excited, the device will adjust the tone of the text to be more energetic.

[0886] 3. Sending input data: The device sends the data and emotional state to the server.

[0887] 4. Input data and emotion analysis: The server analyzes the data and extracts necessary keywords and parameters. It also adjusts the response according to the user's emotional state.

[0888] 5. Calling the generative AI model: The server calls the generative AI model and begins generating sentences.

[0889] 6. Sentence generation: The generative AI model creates initial sentences.

[0890] 7. Correction and improvement of sentences: The server corrects the generated sentences based on grammar and emotional state.

[0891] 8. Providing improvement suggestions: The server sends improvement suggestions to the student's device.

[0892] 9. User review and correction: Students review the suggestions and make further corrections.

[0893] 10. Save and output the final text: The terminal saves the completed text in the specified format.

[0894] This series of processes enables users to efficiently generate high-quality, emotion-sensitive sentences and improve their quality.

[0895] The processing flow will be explained below.

[0896] Step 1:

[0897] The user inputs the topic of the writing and the characteristics of the target audience into the device interface. For example, they might input "The evolution and future of artificial intelligence" and specify "academic readers with specialized knowledge" as the target audience. Once they have completed the input, they click the send button.

[0898] Step 2:

[0899] The device's emotion engine analyzes the user's emotional state based on the content of their input, their input speed, their typing strength, and the facial recognition camera. The emotion engine obtains information such as whether the user is relaxed, excited, or stressed.

[0900] Step 3:

[0901] The device transmits the user-entered data and analyzed emotional state to the server in real time using encrypted HTTP requests.

[0902] Step 4:

[0903] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms for the article based on the topic and characteristics of the target audience. It also sets parameters for sentence generation, taking into account the emotional state provided by the emotional engine.

[0904] Step 5:

[0905] The server calls the generative AI model based on the set parameters and emotional information. For example, if the user is relaxed, it instructs the model to generate calm sentences, and if the user is excited, it instructs the model to generate energetic sentences.

[0906] Step 6:

[0907] A generative AI model generates an initial sentence based on specified parameters, such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0908] Step 7:

[0909] The server then re-analyzes the generated text, correcting grammar and improving style. It detects grammatical errors and corrects them using a dedicated correction algorithm. It also refines the expression based on style guidelines and adapts the writing style to suit the emotional state.

[0910] Step 8:

[0911] The server sends the corrected and improved sentences and multiple suggestions to the user's device, and the user can review and select the best sentence from the multiple options.

[0912] Step 9:

[0913] The user can check the proposed improvements sent from the server on their device and make any necessary adjustments. For example, they can change "evolution" to "progress." The system also selects the optimal expression based on the user's emotional state.

[0914] Step 10:

[0915] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[0916] This series of steps allows users to efficiently generate high-quality, emotion-sensitive text and significantly improve its quality.

[0917] Example 2

[0918] 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."

[0919] In today's world, efficient and high-quality text creation is an important challenge. However, it is difficult to generate text while taking into account the user's emotional state using conventional technologies. Furthermore, to improve the quality of generated text, it is necessary to integrate natural language processing technology and emotion recognition technology. Unless these problems are resolved, it will be difficult to generate text that satisfies users.

[0920] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for analyzing the user's emotional state, means for setting parameters necessary for sentence generation based on the analyzed emotional state, means for calling a generation AI model and generating sentences based on specified parameters, means for correcting and improving the grammar and style of the generated sentences, means for providing improvement suggestions to the user and accepting user corrections, and means for saving the final sentences and outputting them in a specified format. This makes it possible to generate high-quality sentences that take the user's emotional state into consideration.

[0921] "Natural language processing technology" is a general term for technology that analyzes and generates language data, and is a means of performing semantic analysis of text, grammatical analysis, keyword extraction, etc.

[0922] "Emotional state" refers to the user's psychological and physiological state, and indicates emotions estimated from the user's input behavior, facial expressions, tone of voice, and the like.

[0923] "Parameters" are various setting items and values ​​that are set in text generation, and include the theme, tone, style, frequency of use of technical terms, and the like.

[0924] A "generative AI model" is an algorithm or model that uses machine learning or deep learning techniques to generate text, and is used to generate text from input data.

[0925] "Grammar and style correction and improvement" is a means of correcting grammatical errors in the generated text and adjusting and improving the writing style according to the user's requests and emotional state.

[0926] "Improvement suggestions" are alternatives or corrections presented to the generated or corrected text, and are intended as a reference for the user when making selections or corrections.

[0927] "Format" refers to the format and structure of a file, particularly the format used to save and output documents, such as PDF or Word files.

[0928] "Analysis means" refers to the technical means used to process input information to understand its meaning or to extract specific patterns from the data.

[0929] "Input information" refers to data or information that a user provides to the system, including, for example, the topic of the writing task and the characteristics of the target readers.

[0930] The "means for accepting user corrections" refers to a technical means for reflecting the corrections made by the user when the user makes additional corrections to the generated text or the proposed corrections.

[0931] "Storage and output means" means the technical means used to store the final document in local storage and output it in a specified format.

[0932] This invention is a system for efficiently creating high-quality text, and in particular, it enables text generation that takes into account the user's emotions by combining an emotion engine. Specific embodiments of this invention are described below.

[0933] User Input

[0934] Users access the system's interface using a terminal. They input the topic and target audience characteristics for the writing, such as "a research paper on the evolution and future of artificial intelligence" or "an academic audience with specialized knowledge." Once the user has completed the input information, they click the submit button.

[0935] User Emotion Recognition

[0936] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. For example, it can estimate the user's emotions from input speed, typing strength, and facial recognition cameras. Dedicated software and hardware (e.g., facial recognition cameras) are used for emotion recognition.

[0937] Sending input data

[0938] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server, where the communication is carried out using encrypted HTTP requests, ensuring data security.

[0939] Input data and sentiment analysis

[0940] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation. Technically, natural language processing libraries and APIs are used.

[0941] Invoking a generative AI model

[0942] The server invokes a generative AI model based on the set parameters, including the prompt text. The generative AI model also adjusts tone and style depending on the user's emotional state. For example, a calm emotional state generates more formal text, while an excited emotional state generates more energetic text.

[0943] Sentence generation

[0944] The generative AI model generates an initial sentence based on the specified parameters and prompt sentence. For example, the generated initial sentence might be something like, "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[0945] Text corrections and improvements

[0946] The server then re-analyzes the generated text, correcting grammar and improving style. A dedicated correction algorithm detects and corrects grammatical errors. The server also adjusts the writing style by taking into account the emotional state provided by the emotion engine. For example, it corrects typos and changes the tone to be more energetic.

[0947] Providing improvement suggestions

[0948] The server sends the revised and improved text and multiple suggestions to the user's device, allowing the user to review the suggestions. For example, the server may present a "revised version of the problem" and an "improved style proposal."

[0949] User verification and correction

[0950] The user can check the proposed improvements sent from the server on their device and make further corrections as necessary. For example, they can make adjustments such as "changing the style to be more formal" or "adding specific keywords."

[0951] Save and output the final text

[0952] The device saves the final text in local storage and can output the text in a specified format, such as PDF or Word, according to the user's instructions.

[0953] Examples of concrete examples and prompts

[0954] For example, if a user is writing a "research paper on the evolution and future of artificial intelligence" and is targeting an "academic audience with specialized knowledge," they could use the following prompt:

[0955] "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades. In particular,..."

[0956] This series of processes enables users to efficiently generate high-quality, emotion-sensitive sentences and improve their quality.

[0957] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0958] Step 1: User Input

[0959] The user accesses the system's interface using a terminal and inputs the topic of the text they want to generate and the characteristics of the target audience. For example, they can input "research paper on the evolution and future of artificial intelligence" or "academic audience with specialized knowledge." By clicking the submit button, this data is saved on the terminal. This stores the input information within the system.

[0960] Step 2: Recognizing user emotions

[0961] The device analyzes the user's emotional state based on their input and interaction data. The emotion engine processes data from the input speed, typing strength, and facial recognition camera to estimate the user's emotional state. The resulting output is a message indicating whether the user is excited or calm.

[0962] Step 3: Submitting input data

[0963] The device sends the user's input data and the emotion recognition results to the server. The data is sent via an encrypted HTTP request, ensuring data security. The server receives this and proceeds to the next analysis step.

[0964] Step 4: Input data and sentiment analysis

[0965] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation. As a result of the analysis, the necessary keywords and emotional parameters are output.

[0966] Step 5: Invoke the generative AI model

[0967] The server calls the generative AI model based on the set parameters and begins generating sentences. A prompt sentence is also provided as input. The generative AI model generates initial sentences in a tone and style that reflects the user's emotional state. The initial sentences are then output.

[0968] Step 6: Sentence generation

[0969] The generative AI model generates an initial sentence based on the prompt and the set parameters. The generated sentence might be something like, "The evolution of artificial intelligence (AI) has made rapid progress over the past few decades." This is the output.

[0970] Step 7: Edit and improve your writing

[0971] The server then re-analyzes the generated text and corrects grammatical and stylistic errors. It uses a proprietary correction algorithm to detect errors and adjusts the writing style based on data from the emotion engine. The corrected text is then output.

[0972] Step 8: Providing suggestions for improvement

[0973] The server sends the revised and improved text and multiple suggestions to the user's device, where the user can review these suggestions. For example, the server outputs "revised version of the problem" and "improved style proposal."

[0974] Step 9: Verify and Modify Users

[0975] The user can then check the proposed improvements on the terminal and make further revisions as necessary, resulting in a final version of the text with more detailed revisions.

[0976] Step 10: Save and export the final document

[0977] The device saves the final text that the user has finalized in local storage. Then, based on the user's instructions, it outputs the text in a specified format, such as a PDF or Word file. The final text is saved and output in the specified format.

[0978] (Application example 2)

[0979] 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."

[0980] Conventional text generation systems have difficulty generating personalized content based on the user's emotional state, making them insufficient as a means for efficiently creating high-quality text. Furthermore, text that does not take emotions into account has the problem of being difficult to capture the interest of specific situations or target readers. Furthermore, there is a lack of technology for utilizing interactive devices to reflect emotional feedback in real time. Therefore, there is a need for text generation that reflects the user's emotions and for improving the quality of such text generation.

[0981] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for correcting and improving the grammar and style of the generated sentence, means for providing improvement suggestions to the user and accepting the user's corrections, and means for analyzing the user's emotional state using an interactive device, setting parameters based on the emotional information, and generating sentences according to the emotions using a generative AI model. This makes it possible to efficiently generate high-quality sentences that reflect the user's emotions and improve their quality.

[0982] "Input information" refers to data such as themes for writing and characteristics of the target readers that users provide to the system.

[0983] "Natural language processing technology" is a general term for algorithms and methods for analyzing, understanding, and generating human language, and refers to the technology used to analyze and generate sentences.

[0984] "Means for analyzing" refers to a method or apparatus for receiving input information and interpreting or analyzing it using natural language processing techniques.

[0985] "Means for correcting and improving" refers to methods and devices for checking the grammar and style of the generated text and correcting or optimizing it as necessary.

[0986] The "means for providing improvement suggestions" refers to a method or device for presenting candidates or suggested corrections to the generated sentence to the user and accepting confirmation or corrections.

[0987] "Storage means" refers to the method or device for recording the final text in a storage location such as local storage or the cloud.

[0988] "Means for outputting in a specified format" refers to a method or device for outputting the generated text in a specific format, such as a PDF or Word file.

[0989] "Interactive device" refers to a smartphone, tablet, or other interface that allows for real-time interaction with a user.

[0990] "Means for analyzing emotional states" refers to methods and devices for estimating and recognizing emotions based on information such as a user's facial expressions and voice.

[0991] "Means for setting parameters based on emotion information" refers to a method or device that determines setting values ​​for sentence generation taking into account the analyzed emotions.

[0992] "Generative AI model" refers to an algorithm or network model that uses artificial intelligence technology to automatically generate text.

[0993] "Means for generating sentences according to emotions" refers to a method or device that generates sentences with an appropriate tone and style based on the analyzed emotions.

[0994] This invention relates to a system for efficiently creating high-quality text that takes user emotions into consideration, particularly for realizing personalized text generation in content distribution services. This system includes receiving input information, analyzing it using natural language processing technology, correcting and improving the grammar and style of the generated text, providing improvement suggestions to the user, analyzing the emotional state using an interactive device, generating text according to the emotions using a generative AI model, and saving and outputting the final text.

[0995] First, the user accesses the system interface using a terminal and inputs the topic for writing and the characteristics of the target audience, such as "Hawaii travel experience" or "general readership." Once the user has completed the input information, they click the submit button.

[0996] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. Using the smartphone's camera and microphone, the system can estimate the user's emotions from their input speed, facial recognition camera data, and tone of voice. For example, if the system detects that the user is currently excited, that emotional information is transmitted to the system.

[0997] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server. Communication is performed using encrypted HTTP requests. The server analyzes the received data and emotional state and uses natural language processing technology to extract technical terms and keywords based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation.

[0998] The server then uses these parameters to call a generative AI model, which also adjusts tone and style based on the user's emotional state. For example, if the user is excited, the model will generate more energetic text.

[0999] The generated text undergoes a grammar check and style improvement process to further improve its quality. The server then sends the final improved text and several suggestions to the user's device. The user reviews the suggestions and makes further corrections as necessary. The user can then save the finalized text to local storage and output it in a specified format (e.g., PDF or Word file).

[1000] This system enables users to efficiently generate personalized, high-quality sentences that reflect their own emotions. An example of a specific prompt sentence is "Write an excited article about Hawaii travel experience for general readers." Using this prompt sentence, the generative AI model generates optimal sentences that take the user's emotions into consideration.

[1001] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1002] Step 1:

[1003] The user uses a terminal to access the system's interface and input the topic and target reader characteristics for the writing. The input information includes data such as "Hawaii travel experience" and "general reader." When the user completes the input information, the terminal accepts the click of a submit button. The input includes the topic and target reader information, and the output is sent to the system.

[1004] Step 2:

[1005] The emotion engine installed on the device analyzes the user's emotional state based on their input and interactions. It uses the smartphone's camera and microphone to collect input speed, facial recognition data, and tone of voice. Based on this data, the emotion engine estimates the user's emotion (e.g., excited, calm, etc.). The inputs are facial recognition data and tone of voice, and the output is the estimated emotional state.

[1006] Step 3:

[1007] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server using encrypted HTTP requests. The inputs are the theme, target audience information, and emotional state, and the output is this data sent to the server.

[1008] Step 4:

[1009] The server analyzes the received data (theme, target reader information, emotional state). It uses natural language processing technology to extract technical terms and keywords based on the characteristics of the theme and target reader. As a result of the analysis, parameters for detailed text generation are set. The input is the transmitted theme, target reader information, and emotional state, and the set parameters are obtained as the output.

[1010] Step 5:

[1011] The server calls the generative AI model based on the set parameters. Specifically, it adjusts the tone and style according to the user's emotional state and generates the initial sentence. The generative AI model uses a prompt sentence, such as "Write an excited article about Hawaii travel experience for general readers," to generate sentences that adapt to the emotion. The inputs are the set parameters and the prompt sentence, and the output is the initial generated sentence.

[1012] Step 6:

[1013] The generated text is then passed through a grammar checking and style improvement process on the server to improve its quality. Grammar errors are detected and corrected as necessary. The input is the initial generated text, and the output is the corrected and improved text.

[1014] Step 7:

[1015] The server sends the revised and improved sentences as multiple suggestions to the user's device. The user reviews these suggestions and makes any necessary revisions to finalize the sentence. The input is the revised and improved sentence, and the output is multiple suggestions that are provided to the user.

[1016] Step 8:

[1017] The user reviews the suggestions and makes any necessary revisions. The final text is saved on the device and output in the specified format (e.g., PDF or Word file). The input is the final text and format selected by the user, and the output is the final text saved in the specified format.

[1018] 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.

[1019] 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.

[1020] 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.

[1021] [Fourth embodiment]

[1022] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1023] 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.

[1024] 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).

[1025] 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.

[1026] 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.

[1027] 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).

[1028] 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. 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.

[1029] 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.

[1030] 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.

[1031] 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.

[1032] 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.

[1033] 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.

[1034] 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."

[1035] This invention is a system that enables users to efficiently create high-quality texts. The system utilizes a generative AI model to quickly and accurately generate texts that meet the user's needs and corrects grammar and style.

[1036] Explanation of program processing

[1037] User Input

[1038] The user uses a terminal to input information into the DocCraft Elite interface, such as the topic of the text and the characteristics of the target audience. This information can be specific, such as "The evolution and future of artificial intelligence" or "Academic audience with specialized knowledge." Once the input is complete, the user clicks the submit button to send the information to the server.

[1039] Sending input data

[1040] The device sends the data entered by the user to the server in real time, and the data is sent as an encrypted HTTP request during this communication process, ensuring security.

[1041] Analyzing input data

[1042] The server analyzes the received data and determines the necessary parameters. Specifically, it analyzes the theme and characteristics of the target audience using natural language processing technology and extracts the keywords and technical terms necessary for generating text.

[1043] Invoking a generative AI model

[1044] The server invokes the ChatGPT-based generative AI model with specific parameters, which generates an initial sentence based on the user's input data.

[1045] Sentence generation

[1046] A generative AI model generates appropriate sentences based on user-provided information, such as an initial sentence like, "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[1047] Text corrections and improvements

[1048] The server then reanalyzes the generated text and performs grammatical corrections and style improvements. This involves using natural language processing techniques to detect and correct grammatical errors. It also refines the expression based on style guidelines to improve the quality of the text. An example of a post-processing correction is, "Artificial intelligence (AI) has seen remarkable developments over the past few decades. This paper examines its evolution and future prospects in detail."

[1049] Providing improvement suggestions

[1050] The server sends the corrected and improved text and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further corrections.

[1051] User verification and correction

[1052] The user can check the proposed improvements sent from the server on their device and make additional adjustments as necessary, such as changing the word "evolution" to "progress."

[1053] Save and output the final text

[1054] The device saves the final text that the user has confirmed in local storage and can output the text in a specified format (e.g., PDF or Word file).

[1055] Specific examples

[1056] Writing an introduction for a research paper

[1057] 1. User input: A student (user) enters "research paper on the evolution and future of artificial intelligence" into the terminal and specifies "academic readers with specialized knowledge" as the target audience.

[1058] 2. Sending input data: The terminal sends the input data to the server.

[1059] 3. Parsing input data: The server parses the data and extracts the necessary keywords and parameters.

[1060] 4. Calling the generative AI model: The server calls the generative AI model and begins generating sentences.

[1061] 5. Sentence generation: The generative AI model creates initial sentences.

[1062] 6. Correcting and improving text: The server corrects the generated text based on grammar and style guidelines.

[1063] 7. Providing improvement suggestions: The server sends improvement suggestions to the student's device.

[1064] 8. User review and revision: Students review the proposal and make further revisions.

[1065] 9. Save and output the final text: The terminal saves the completed text in the specified format.

[1066] The above is a specific embodiment for carrying out the invention. This system enables users to efficiently generate high-quality professional documents and improve their quality.

[1067] The processing flow will be explained below.

[1068] Step 1:

[1069] The user inputs the topic of the writing and the characteristics of the target audience into the device interface. Specifically, they input "a research paper about the evolution and future of artificial intelligence" or "an academic audience with specialized knowledge." Once the input is complete, they click the send button.

[1070] Step 2:

[1071] The device sends the data entered by the user to the server in real time, and the communication is secure because it is done using encrypted HTTP requests.

[1072] Step 3:

[1073] The server analyzes the received data, using natural language processing technology to analyze the theme and characteristics of the target audience, and extracts keywords and technical terms necessary for generating text.

[1074] Step 4:

[1075] The server invokes the generative AI model with specific parameters, including parameters based on the subject and target audience characteristics provided by the user.

[1076] Step 5:

[1077] Generative AI models generate initial sentences based on specified parameters, such as "The evolution of artificial intelligence (AI) has seen rapid development over the past few decades."

[1078] Step 6:

[1079] The server re-analyzes the generated text, correcting grammar and improving style, detecting grammatical errors and correcting them using dedicated correction algorithms, and refining the presentation based on style guidelines.

[1080] Step 7:

[1081] The server sends the corrected and improved sentences and multiple suggestions to the user's device, where the user can check the suggestions.

[1082] Step 8:

[1083] The user can check the proposed improvements on their device and make further corrections as necessary, for example, changing "evolution" to "progress."

[1084] Step 9:

[1085] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[1086] This series of steps allows users to efficiently generate high-quality text and significantly improve its quality.

[1087] Example 1

[1088] 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."

[1089] Conventional text generation systems have had problems with the quality of the text they generate, especially when targeting specialized readers. Furthermore, correcting grammatical errors and improving style in the generated text requires a lot of time and effort. This makes it difficult for users to efficiently generate high-quality text.

[1090] 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.

[1091] In this invention, the server includes means for a user to provide input information such as the topic of the text and the characteristics of the target readers through a terminal, means for transmitting the input information to the server in real time, means for analyzing the input data using natural language processing technology and extracting necessary parameters, means for invoking a generative AI model and generating an initial text based on the user's input information, means for reanalyzing the generated text and correcting grammar and improving style, means for providing the corrected text and multiple suggestions to the user and accepting user corrections, and means for saving the final text and outputting it in a specified format. This enables a user to efficiently generate high-quality text and improve its quality.

[1092] "User" refers to an individual or corporation that provides input information from a terminal to generate text using this system.

[1093] A "terminal" is an electronic device used by a user to provide input information and communicate with a server. Examples include personal computers and smartphones.

[1094] "Server" means a computer system that receives data sent by a user, analyzes it, generates text using a generative AI model, corrects grammar and style, saves the final text, and outputs it in the specified format.

[1095] "Input information" refers to data such as the topic of the text and the characteristics of the target readers that the user provides through the terminal.

[1096] "Natural language processing technology" refers to technology for processing human language using a computer, and examples include text analysis and keyword extraction.

[1097] "Parameters" are data and settings required for sentence generation, which are analyzed and extracted by the server to be passed to the generative AI model.

[1098] A "generative AI model" is an algorithm or software that uses artificial intelligence techniques to generate sentences based on user prompts. Examples include ChatGPT.

[1099] A "prompt sentence" is text that is input into a generative AI model and serves as the basis for the model to generate sentences based on it.

[1100] "Grammar correction" is the process of detecting grammatical errors in the generated sentences and correcting them correctly.

[1101] "Style enhancement" is the process of refining and improving the expression and tone of the generated text.

[1102] A "suggestion" is a revised sentence or multiple variations that the server provides to the user, and is an option for the user to select and make revisions.

[1103] The "final text" is a text that has been finalized after the user has completed the revisions.

[1104] "Specified format" refers to the format in which the final document is to be saved or output, examples of which include PDF and Word files.

[1105] The system of the present invention is designed to enable users to efficiently create high-quality texts, utilizing a generative AI model to quickly and accurately generate texts that meet the user's needs and correct grammar and style.

[1106] First, the user uses the terminal to provide input information such as the topic of the text and the characteristics of the target readers. This input information can be specific, such as "The evolution and future of artificial intelligence" or "Academic readers with specialized knowledge." Once the input is complete, the user clicks the send button, which sends the input information to the server.

[1107] The terminal transmits the data entered by the user to the server in real time. During this communication process, the data is sent as an encrypted HTTP request using TLS / SSL or other protocols, ensuring security.

[1108] The server analyzes the received data and determines the necessary parameters. Specifically, it uses natural language processing technology (such as SpaCy or NLTK) to analyze the subject and characteristics of the target audience and extract keywords and technical terms necessary for text generation.

[1109] The server then invokes a generative AI model (e.g., ChatGPT) with specific parameters, providing the model with a specific prompt, such as "Write a piece about the evolution and future of artificial intelligence for an academic audience with specialized knowledge."

[1110] A generative AI model generates initial sentences based on a given prompt. At this stage, the model leverages large amounts of training data to generate sentences with appropriate context and detail. For example, a generated sentence might be, "The evolution of artificial intelligence (AI) has seen rapid development over the past few decades."

[1111] The generated sentences are then re-analyzed on the server side. This process includes using a grammar checker (e.g., Grammarly or LanguageTool) to detect and correct grammatical errors. The process also refines the expression based on style guidelines to improve the quality of the sentences. Corrected examples are obtained, such as: "The development of artificial intelligence (AI) has been remarkable over the past few decades, and this paper examines its evolution and future prospects in detail."

[1112] The server then sends the revised and improved text and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further revisions. For example, the user may change "evolution" to "progress" or rearrange the order of sentences.

[1113] Finally, the text that the user has confirmed is saved to the device's local storage. It is also possible to output the text in a specified format (e.g., PDF or Word file). The user can then use the saved file in other applications.

[1114] As described above, the system of the present invention provides a specific means for users to efficiently generate high-quality text and improve that quality.

[1115] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1116] Step 1:

[1117] A user accesses the DocCraft Elite interface on a device, where they provide input information such as the topic of the article and the characteristics of the target audience. For example, they enter specific content such as "The evolution and future of artificial intelligence" or "Academic readers with specialized knowledge," and click the submit button. The input data includes the topic of the article and the target audience, and the output is encrypted request data.

[1118] Step 2:

[1119] The terminal transmits the data entered by the user to the server in real time. During this communication process, the input data is sent as an HTTP request using encryption technology such as TLS / SSL. The input is the data provided by the user, and the output is an encrypted HTTP request.

[1120] Step 3:

[1121] The server analyzes the received data. Specifically, it uses natural language processing technology (e.g., SpaCy or NLTK) to analyze the topic and characteristics of the target audience and extract keywords and technical terms necessary for text generation. The input is the data in the encrypted HTTP request, and the output is the analyzed keywords and parameters.

[1122] Step 4:

[1123] The server uses the obtained parameters to call a generative AI model (e.g., ChatGPT). At this time, it generates text to be passed to the generative AI model as a prompt. For example, a specific sentence such as "Please write a piece about the evolution and future of artificial intelligence for an academic audience with specialized knowledge" is input to the generative AI model. The input is the parsed parameters and the generated prompt, and the output is the initial sentence.

[1124] Step 5:

[1125] A generative AI model generates an initial sentence based on a given prompt. The model utilizes large-scale training data to generate sentences with appropriate context and details. A sentence such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades" is generated. The input is the prompt, and the output is the initial generated sentence.

[1126] Step 6:

[1127] The server re-analyzes the generated text. This process involves using a grammar checker (e.g., Grammarly or LanguageTool) to detect and correct grammatical errors. It also refines the expression based on style guidelines to improve the quality of the text. For example, it obtains a corrected example such as, "Artificial intelligence (AI) has developed significantly over the past few decades. This paper examines its evolution and future prospects in detail." The input is the initial generated text, and the output is the corrected text.

[1128] Step 7:

[1129] The server sends the corrected and improved sentences and multiple suggestions to the user's device, allowing the user to review the suggested improvements and make further corrections. The input is the corrected and improved sentences, and the output is the improvement suggestions provided to the user.

[1130] Step 8:

[1131] The user checks the proposed improvements on the device and makes additional corrections as necessary. For example, they make specific adjustments such as changing "evolution" to "progress" or rearranging the order of sentences. The input is the improvement proposal sent from the server, and the output is the final revised sentence.

[1132] Step 9:

[1133] The device saves the user's finalized text in local storage. It is also possible to output the text in a specified format (e.g., PDF or Word file). The user can use the saved file in other applications. The input is the final revised text, and the output is the text in the saved file format.

[1134] (Application example 1)

[1135] 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."

[1136] In the current content creation process, it is difficult to efficiently generate high-quality text based on a specific topic. In particular, correcting grammar and style, using technical terms based on the reader's characteristics, and providing suggestions for improvement to the user require a lot of time and effort. Therefore, there is a need for a support system that helps users create their own content quickly and accurately and improves the quality of the final text.

[1137] 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.

[1138] In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for generating initial sentences based on the input information using a generative AI model, means for correcting and improving the grammar and style of the generated sentences, means for providing multiple improvement suggestions to the user and accepting the user's corrections, and means for saving the final sentences and outputting them in a specified format, thereby enabling the user to quickly and efficiently create high-quality sentences based on a theme.

[1139] "Input information" refers to initial data such as the theme and characteristics of the target audience that the user provides to the system.

[1140] "Natural language processing technology" is a technology that uses computers to process and analyze language used by humans.

[1141] A "generative AI model" is an artificial intelligence model that automatically generates sentences based on input information provided by the user.

[1142] An "initial sentence" is the sentence that a generative AI model first generates based on input information.

[1143] "Grammar" refers to the rules and structure of language used to construct sentences.

[1144] "Style" is a particular method or characteristic of the presentation or presentation of writing.

[1145] "Correction and improvement" refers to the process of correcting grammatical and stylistic errors and inappropriate parts of the generated text to improve its quality.

[1146] The "multiple improvement suggestions" are multiple corrections or alternatives that are provided to the user for the generated text.

[1147] A "prompt sentence" is an instruction or input sentence given to a generative AI model when generating a specific sentence.

[1148] "Preservation" refers to recording the written work in a digital format so that it can be reused later.

[1149] "Specified format" refers to the particular digital file format in which the final document will be saved or output.

[1150] 1. System Overview

[1151] The system that realizes this application example generates high-quality text based on user input, corrects grammar and style, and suggests improvements, and then saves and outputs the final text. The system is mainly composed of a server and a user terminal, and operates in the following steps.

[1152] 2. Hardware and software used

[1153] Hardware

[1154] Server: Processes data and runs generative AI models. A server with a high-performance CPU and large memory capacity is desirable.

[1155] User device: Personal computer (PC), smartphone, tablet, head-mounted display, etc. Provides an interface for users to input information and check and correct the generated text.

[1156] software

[1157] Generative AI model: A natural language processing model such as the OpenAI API. It generates sentences based on user input.

[1158] Encrypted communication protocols, such as HTTPS, that ensure the secure transmission of user-provided input data and generated text.

[1159] Data saving format: PDF, Word, etc. Used to save and output the final document in the format desired by the user.

[1160] 3. Data processing and calculation

[1161] Receiving and analyzing user-entered information

[1162] The user enters information into the device, such as the topic and characteristics of the target audience. This information might include, for example, "The evolution and future of artificial intelligence" or "Technology-savvy readers." The input data is sent to the server in real time via an encrypted HTTP request.

[1163] Initial sentence generation using a generative AI model

[1164] The server analyzes the received data and provides the extracted keywords and terminology to the generative AI model. The generative AI model uses natural language processing techniques, such as the OpenAI API, to generate initial sentences based on the provided information. For example, the prompt sentence could be "Write an article about the evolution of artificial intelligence for a tech-savvy audience."

[1165] Grammar and style fixes

[1166] The generated initial sentences are then analyzed again on the server, where natural language processing techniques are used to detect and correct grammatical errors and refine the sentences based on style guidelines, thereby improving the quality of the sentences.

[1167] Providing improvement suggestions

[1168] The server generates multiple suggestions for corrected and improved sentences and sends them to the user's device, where the user can review them and manually make additional corrections if necessary.

[1169] Save and output the final text

[1170] The finalized text is saved on the user's device in the format selected by the user (PDF or Word file).

[1171] 4. Specific Examples

[1172] Example of user input

[1173] Theme: "The Evolution of Artificial Intelligence"

[1174] Target audience: "Technical readers"

[1175] Prompt: "Write an article about the evolution of artificial intelligence for a tech-savvy audience."

[1176] In this way, users can quickly and efficiently create high-quality texts based on a theme.

[1177] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1178] Step 1:

[1179] The user uses a terminal to input information into the interface, such as the topic of the text and the characteristics of the target audience. Examples include "The evolution and future of artificial intelligence" and "Technology-savvy readers." By clicking the submit button, the input data is sent to the server in real time as an encrypted HTTP request. Input: Topic and characteristics of the target audience. Output: Transmission of encrypted input data.

[1180] Step 2:

[1181] The server analyzes the received data and extracts necessary parameters based on the input information using natural language processing technology. For example, if the topic is "The Evolution and Future of Artificial Intelligence," related keywords and technical terms are extracted. Input: Encrypted input data, Output: Analyzed parameters (keywords, technical terms).

[1182] Step 3:

[1183] The server uses the parsed parameters to provide a prompt to the generative AI model. For example, it generates a prompt such as "Write an article about the evolution of artificial intelligence for a tech-savvy audience." The generative AI model generates an initial sentence based on the provided information. Input: Parsed parameters, Output: Initial sentence.

[1184] Step 4:

[1185] The generated initial sentence is then re-analyzed by the server. Natural language processing techniques are used to detect and correct grammatical errors, and the sentence is refined based on style guidelines. This process improves the quality of the sentence. Input: Initial sentence, Output: Corrected and improved sentence.

[1186] Step 5:

[1187] The server generates multiple improvement suggestions based on the corrected and improved sentences and sends them to the user's terminal. The user checks these suggestions and manually makes additional corrections as needed. Input: corrected sentence, Output: multiple improvement suggestions.

[1188] Step 6:

[1189] The user checks the provided improvement suggestions on the device and modifies the text as necessary. The text that the user has finally confirmed can be saved on the device. It is also possible to save and output in a specified format (e.g. PDF or Word file). Input: Improvement suggestions and user modifications, Output: Final confirmed text.

[1190] Step 7:

[1191] The final text is saved in the format specified by the user (PDF or Word file). This allows users to efficiently create high-quality text and save it in various formats. Input: Final text, Output: Text saved in the specified format.

[1192] 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.

[1193] The present invention relates to a system for efficiently creating high-quality text, and in particular to a system that combines an emotion engine to enable text generation that takes into account the user's emotions. Specific embodiments of the present invention are described below.

[1194] Explanation of program processing

[1195] User Input

[1196] Users access the DocCraft Elite interface on their device and enter the topic and target audience characteristics for their writing, such as "Research paper on the evolution and future of artificial intelligence" or "Academic audience with specialized knowledge." Once the user has completed the input information, they click the submit button.

[1197] User Emotion Recognition

[1198] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. For example, it can estimate the user's emotions from input speed, typing strength, facial recognition cameras, etc.

[1199] Sending input data

[1200] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server using encrypted HTTP requests.

[1201] Input data and sentiment analysis

[1202] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also sets the parameters necessary for sentence generation, taking into account the emotional state provided by the emotional engine.

[1203] Invoking a generative AI model

[1204] The server invokes a generative AI model based on set parameters, which includes adjusting tone and style depending on the user's emotional state—for example, generating formal sentences in a calm emotional state and more energetic sentences in an excited emotional state.

[1205] Sentence generation

[1206] A generative AI model generates an initial sentence based on the specified parameters, such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[1207] Text corrections and improvements

[1208] The server re-analyzes the generated text, correcting grammar and improving style. It detects grammatical errors and corrects them using a dedicated correction algorithm. It also adjusts the writing style by taking into account the emotional state provided by the emotion engine.

[1209] Providing improvement suggestions

[1210] The server sends the corrected and improved sentences and multiple suggestions to the user's device, where the user can check the suggestions.

[1211] User verification and correction

[1212] The user can check the improvement proposals sent from the server on their device and make further corrections as necessary, for example, by selecting the most appropriate expression according to the user's emotional state.

[1213] Save and output the final text

[1214] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[1215] Specific examples

[1216] Writing an introduction for a research paper

[1217] 1. User input: A student (user) enters "research paper on the evolution and future of artificial intelligence" into the terminal and specifies "academic readers with specialized knowledge" as the target audience.

[1218] 2. User Emotion Recognition: The device's emotion engine analyzes the user's typing speed and facial expressions to estimate their emotional state. For example, if the user is excited, the device will adjust the tone of the text to be more energetic.

[1219] 3. Sending input data: The device sends the data and emotional state to the server.

[1220] 4. Input data and emotion analysis: The server analyzes the data and extracts necessary keywords and parameters. It also adjusts the response according to the user's emotional state.

[1221] 5. Calling the generative AI model: The server calls the generative AI model and begins generating sentences.

[1222] 6. Sentence generation: The generative AI model creates initial sentences.

[1223] 7. Correction and improvement of sentences: The server corrects the generated sentences based on grammar and emotional state.

[1224] 8. Providing improvement suggestions: The server sends improvement suggestions to the student's device.

[1225] 9. User review and correction: Students review the suggestions and make further corrections.

[1226] 10. Save and output the final text: The terminal saves the completed text in the specified format.

[1227] This series of processes enables users to efficiently generate high-quality, emotion-sensitive sentences and improve their quality.

[1228] The processing flow will be explained below.

[1229] Step 1:

[1230] The user inputs the topic of the writing and the characteristics of the target audience into the device interface. For example, they might input "The evolution and future of artificial intelligence" and specify "academic readers with specialized knowledge" as the target audience. Once they have completed the input, they click the send button.

[1231] Step 2:

[1232] The device's emotion engine analyzes the user's emotional state based on the content of their input, their input speed, their typing strength, and the facial recognition camera. The emotion engine obtains information such as whether the user is relaxed, excited, or stressed.

[1233] Step 3:

[1234] The device transmits the user-entered data and analyzed emotional state to the server in real time using encrypted HTTP requests.

[1235] Step 4:

[1236] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms for the article based on the topic and characteristics of the target audience. It also sets parameters for sentence generation, taking into account the emotional state provided by the emotional engine.

[1237] Step 5:

[1238] The server calls the generative AI model based on the set parameters and emotional information. For example, if the user is relaxed, it instructs the model to generate calm sentences, and if the user is excited, it instructs the model to generate energetic sentences.

[1239] Step 6:

[1240] A generative AI model generates an initial sentence based on specified parameters, such as "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[1241] Step 7:

[1242] The server then re-analyzes the generated text, correcting grammar and improving style. It detects grammatical errors and corrects them using a dedicated correction algorithm. It also refines the expression based on style guidelines and adapts the writing style to suit the emotional state.

[1243] Step 8:

[1244] The server sends the corrected and improved sentences and multiple suggestions to the user's device, and the user can review and select the best sentence from the multiple options.

[1245] Step 9:

[1246] The user can check the proposed improvements sent from the server on their device and make any necessary adjustments. For example, they can change "evolution" to "progress." The system also selects the optimal expression based on the user's emotional state.

[1247] Step 10:

[1248] The device saves the final text that the user has confirmed in local storage. It is also possible to output the text in a specified format (PDF or Word file).

[1249] This series of steps allows users to efficiently generate high-quality, emotion-sensitive text and significantly improve its quality.

[1250] Example 2

[1251] 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."

[1252] In today's world, efficient and high-quality text creation is an important challenge. However, it is difficult to generate text while taking into account the user's emotional state using conventional technologies. Furthermore, to improve the quality of generated text, it is necessary to integrate natural language processing technology and emotion recognition technology. Unless these problems are resolved, it will be difficult to generate text that satisfies users.

[1253] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for analyzing the user's emotional state, means for setting parameters necessary for sentence generation based on the analyzed emotional state, means for calling a generation AI model and generating sentences based on specified parameters, means for correcting and improving the grammar and style of the generated sentences, means for providing improvement suggestions to the user and accepting user corrections, and means for saving the final sentences and outputting them in a specified format. This makes it possible to generate high-quality sentences that take the user's emotional state into consideration.

[1254] "Natural language processing technology" is a general term for technology that analyzes and generates language data, and is a means of performing semantic analysis of text, grammatical analysis, keyword extraction, etc.

[1255] "Emotional state" refers to the user's psychological and physiological state, and indicates emotions estimated from the user's input behavior, facial expressions, tone of voice, and the like.

[1256] "Parameters" are various setting items and values ​​that are set in text generation, and include the theme, tone, style, frequency of use of technical terms, and the like.

[1257] A "generative AI model" is an algorithm or model that uses machine learning or deep learning techniques to generate text, and is used to generate text from input data.

[1258] "Grammar and style correction and improvement" is a means of correcting grammatical errors in the generated text and adjusting and improving the writing style according to the user's requests and emotional state.

[1259] "Improvement suggestions" are alternatives or corrections presented to the generated or corrected text, and are intended as a reference for the user when making selections or corrections.

[1260] "Format" refers to the format and structure of a file, particularly the format used to save and output documents, such as PDF or Word files.

[1261] "Analysis means" refers to the technical means used to process input information to understand its meaning or to extract specific patterns from the data.

[1262] "Input information" refers to data or information that a user provides to the system, including, for example, the topic of the writing task and the characteristics of the target readers.

[1263] The "means for accepting user corrections" refers to a technical means for reflecting the corrections made by the user when the user makes additional corrections to the generated text or the proposed corrections.

[1264] "Storage and output means" means the technical means used to store the final document in local storage and output it in a specified format.

[1265] This invention is a system for efficiently creating high-quality text, and in particular, it enables text generation that takes into account the user's emotions by combining an emotion engine. Specific embodiments of this invention are described below.

[1266] User Input

[1267] Users access the system's interface using a terminal. They input the topic and target audience characteristics for the writing, such as "a research paper on the evolution and future of artificial intelligence" or "an academic audience with specialized knowledge." Once the user has completed the input information, they click the submit button.

[1268] User Emotion Recognition

[1269] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. For example, it can estimate the user's emotions from input speed, typing strength, and facial recognition cameras. Dedicated software and hardware (e.g., facial recognition cameras) are used for emotion recognition.

[1270] Sending input data

[1271] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server, where the communication is carried out using encrypted HTTP requests, ensuring data security.

[1272] Input data and sentiment analysis

[1273] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation. Technically, natural language processing libraries and APIs are used.

[1274] Invoking a generative AI model

[1275] The server invokes a generative AI model based on the set parameters, including the prompt text. The generative AI model also adjusts tone and style depending on the user's emotional state. For example, a calm emotional state generates more formal text, while an excited emotional state generates more energetic text.

[1276] Sentence generation

[1277] The generative AI model generates an initial sentence based on the specified parameters and prompt sentence. For example, the generated initial sentence might be something like, "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades."

[1278] Text corrections and improvements

[1279] The server then re-analyzes the generated text, correcting grammar and improving style. A dedicated correction algorithm detects and corrects grammatical errors. The server also adjusts the writing style by taking into account the emotional state provided by the emotion engine. For example, it corrects typos and changes the tone to be more energetic.

[1280] Providing improvement suggestions

[1281] The server sends the revised and improved text and multiple suggestions to the user's device, allowing the user to review the suggestions. For example, the server may present a "revised version of the problem" and an "improved style proposal."

[1282] User verification and correction

[1283] The user can check the proposed improvements sent from the server on their device and make further corrections as necessary. For example, they can make adjustments such as "changing the style to be more formal" or "adding specific keywords."

[1284] Save and output the final text

[1285] The device saves the final text in local storage and can output the text in a specified format, such as PDF or Word, according to the user's instructions.

[1286] Examples of concrete examples and prompts

[1287] For example, if a user is writing a "research paper on the evolution and future of artificial intelligence" and is targeting an "academic audience with specialized knowledge," they could use the following prompt:

[1288] "The evolution of artificial intelligence (AI) has progressed rapidly over the past few decades. In particular,..."

[1289] This series of processes enables users to efficiently generate high-quality, emotion-sensitive sentences and improve their quality.

[1290] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1291] Step 1: User Input

[1292] The user accesses the system's interface using a terminal and inputs the topic of the text they want to generate and the characteristics of the target audience. For example, they can input "research paper on the evolution and future of artificial intelligence" or "academic audience with specialized knowledge." By clicking the submit button, this data is saved on the terminal. This stores the input information within the system.

[1293] Step 2: Recognizing user emotions

[1294] The device analyzes the user's emotional state based on their input and interaction data. The emotion engine processes data from the input speed, typing strength, and facial recognition camera to estimate the user's emotional state. The resulting output is a message indicating whether the user is excited or calm.

[1295] Step 3: Submitting input data

[1296] The device sends the user's input data and the emotion recognition results to the server. The data is sent via an encrypted HTTP request, ensuring data security. The server receives this and proceeds to the next analysis step.

[1297] Step 4: Input data and sentiment analysis

[1298] The server analyzes the received data and emotional state. It uses natural language processing technology to extract keywords and technical terms based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation. As a result of the analysis, the necessary keywords and emotional parameters are output.

[1299] Step 5: Invoke the generative AI model

[1300] The server calls the generative AI model based on the set parameters and begins generating sentences. A prompt sentence is also provided as input. The generative AI model generates initial sentences in a tone and style that reflects the user's emotional state. The initial sentences are then output.

[1301] Step 6: Sentence generation

[1302] The generative AI model generates an initial sentence based on the prompt and the set parameters. The generated sentence might be something like, "The evolution of artificial intelligence (AI) has made rapid progress over the past few decades." This is the output.

[1303] Step 7: Edit and improve your writing

[1304] The server then re-analyzes the generated text and corrects grammatical and stylistic errors. It uses a proprietary correction algorithm to detect errors and adjusts the writing style based on data from the emotion engine. The corrected text is then output.

[1305] Step 8: Providing suggestions for improvement

[1306] The server sends the revised and improved text and multiple suggestions to the user's device, where the user can review these suggestions. For example, the server outputs "revised version of the problem" and "improved style proposal."

[1307] Step 9: Verify and Modify Users

[1308] The user can then check the proposed improvements on the terminal and make further revisions as necessary, resulting in a final version of the text with more detailed revisions.

[1309] Step 10: Save and export the final document

[1310] The device saves the final text that the user has finalized in local storage. Then, based on the user's instructions, it outputs the text in a specified format, such as a PDF or Word file. The final text is saved and output in the specified format.

[1311] (Application example 2)

[1312] 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."

[1313] Conventional text generation systems have difficulty generating personalized content based on the user's emotional state, making them insufficient as a means for efficiently creating high-quality text. Furthermore, text that does not take emotions into account has the problem of being difficult to capture the interest of specific situations or target readers. Furthermore, there is a lack of technology for utilizing interactive devices to reflect emotional feedback in real time. Therefore, there is a need for text generation that reflects the user's emotions and for improving the quality of such text generation.

[1314] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input information and analyzing it using natural language processing technology, means for correcting and improving the grammar and style of the generated sentence, means for providing improvement suggestions to the user and accepting the user's corrections, and means for analyzing the user's emotional state using an interactive device, setting parameters based on the emotional information, and generating sentences according to the emotions using a generative AI model. This makes it possible to efficiently generate high-quality sentences that reflect the user's emotions and improve their quality.

[1315] "Input information" refers to data such as themes for writing and characteristics of the target readers that users provide to the system.

[1316] "Natural language processing technology" is a general term for algorithms and methods for analyzing, understanding, and generating human language, and refers to the technology used to analyze and generate sentences.

[1317] "Means for analyzing" refers to a method or apparatus for receiving input information and interpreting or analyzing it using natural language processing techniques.

[1318] "Means for correcting and improving" refers to methods and devices for checking the grammar and style of the generated text and correcting or optimizing it as necessary.

[1319] The "means for providing improvement suggestions" refers to a method or device for presenting candidates or suggested corrections to the generated sentence to the user and accepting confirmation or corrections.

[1320] "Storage means" refers to the method or device for recording the final text in a storage location such as local storage or the cloud.

[1321] "Means for outputting in a specified format" refers to a method or device for outputting the generated text in a specific format, such as a PDF or Word file.

[1322] "Interactive device" refers to a smartphone, tablet, or other interface that allows for real-time interaction with a user.

[1323] "Means for analyzing emotional states" refers to methods and devices for estimating and recognizing emotions based on information such as a user's facial expressions and voice.

[1324] "Means for setting parameters based on emotion information" refers to a method or device that determines setting values ​​for sentence generation taking into account the analyzed emotions.

[1325] "Generative AI model" refers to an algorithm or network model that uses artificial intelligence technology to automatically generate text.

[1326] "Means for generating sentences according to emotions" refers to a method or device that generates sentences with an appropriate tone and style based on the analyzed emotions.

[1327] This invention relates to a system for efficiently creating high-quality text that takes user emotions into consideration, particularly for realizing personalized text generation in content distribution services. This system includes receiving input information, analyzing it using natural language processing technology, correcting and improving the grammar and style of the generated text, providing improvement suggestions to the user, analyzing the emotional state using an interactive device, generating text according to the emotions using a generative AI model, and saving and outputting the final text.

[1328] First, the user accesses the system interface using a terminal and inputs the topic for writing and the characteristics of the target audience, such as "Hawaii travel experience" or "general readership." Once the user has completed the input information, they click the submit button.

[1329] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and interactions. Using the smartphone's camera and microphone, the system can estimate the user's emotions from their input speed, facial recognition camera data, and tone of voice. For example, if the system detects that the user is currently excited, that emotional information is transmitted to the system.

[1330] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server. Communication is performed using encrypted HTTP requests. The server analyzes the received data and emotional state and uses natural language processing technology to extract technical terms and keywords based on the theme and characteristics of the target audience. It also takes into account the emotional state provided by the emotion engine and sets the parameters necessary for sentence generation.

[1331] The server then uses these parameters to call a generative AI model, which also adjusts tone and style based on the user's emotional state. For example, if the user is excited, the model will generate more energetic text.

[1332] The generated text undergoes a grammar check and style improvement process to further improve its quality. The server then sends the final improved text and several suggestions to the user's device. The user reviews the suggestions and makes further corrections as necessary. The user can then save the finalized text to local storage and output it in a specified format (e.g., PDF or Word file).

[1333] This system enables users to efficiently generate personalized, high-quality sentences that reflect their own emotions. An example of a specific prompt sentence is "Write an excited article about Hawaii travel experience for general readers." Using this prompt sentence, the generative AI model generates optimal sentences that take the user's emotions into consideration.

[1334] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1335] Step 1:

[1336] The user uses a terminal to access the system's interface and input the topic and target reader characteristics for the writing. The input information includes data such as "Hawaii travel experience" and "general reader." When the user completes the input information, the terminal accepts the click of a submit button. The input includes the topic and target reader information, and the output is sent to the system.

[1337] Step 2:

[1338] The emotion engine installed on the device analyzes the user's emotional state based on their input and interactions. It uses the smartphone's camera and microphone to collect input speed, facial recognition data, and tone of voice. Based on this data, the emotion engine estimates the user's emotion (e.g., excited, calm, etc.). The inputs are facial recognition data and tone of voice, and the output is the estimated emotional state.

[1339] Step 3:

[1340] The device sends the data entered by the user and the emotional state analyzed by the emotion engine to the server using encrypted HTTP requests. The inputs are the theme, target audience information, and emotional state, and the output is this data sent to the server.

[1341] Step 4:

[1342] The server analyzes the received data (theme, target reader information, emotional state). It uses natural language processing technology to extract technical terms and keywords based on the characteristics of the theme and target reader. As a result of the analysis, parameters for detailed text generation are set. The input is the transmitted theme, target reader information, and emotional state, and the set parameters are obtained as the output.

[1343] Step 5:

[1344] The server calls the generative AI model based on the set parameters. Specifically, it adjusts the tone and style according to the user's emotional state and generates the initial sentence. The generative AI model uses a prompt sentence, such as "Write an excited article about Hawaii travel experience for general readers," to generate sentences that adapt to the emotion. The inputs are the set parameters and the prompt sentence, and the output is the initial generated sentence.

[1345] Step 6:

[1346] The generated text is then passed through a grammar checking and style improvement process on the server to improve its quality. Grammar errors are detected and corrected as necessary. The input is the initial generated text, and the output is the corrected and improved text.

[1347] Step 7:

[1348] The server sends the revised and improved sentences as multiple suggestions to the user's device. The user reviews these suggestions and makes any necessary revisions to finalize the sentence. The input is the revised and improved sentence, and the output is multiple suggestions that are provided to the user.

[1349] Step 8:

[1350] The user reviews the suggestions and makes any necessary revisions. The final text is saved on the device and output in the specified format (e.g., PDF or Word file). The input is the final text and format selected by the user, and the output is the final text saved in the specified format.

[1351] 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.

[1352] 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.

[1353] 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.

[1354] 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.

[1355] 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.

[1356] 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.

[1357] 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).

[1358] 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.

[1359] 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."

[1360] 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.

[1361] 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).

[1362] 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.

[1363] 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.

[1364] 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.

[1365] 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.

[1366] 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.

[1367] 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.

[1368] 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.

[1369] 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.

[1370] 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.

[1371] 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.

[1372] The following is further disclosed regarding the above embodiment.

[1373] (Claim 1)

[1374] means for receiving input information and analyzing it using natural language processing technology;

[1375] A means to correct and improve the grammar and style of the generated text;

[1376] a means for providing user improvement suggestions and accepting user corrections;

[1377] A means to save the final text and output it in a specified format;

[1378] A system including:

[1379] (Claim 2)

[1380] 10. The system of claim 1, further comprising means for extracting terminology based on target audience characteristics using natural language processing techniques.

[1381] (Claim 3)

[1382] The system of claim 1 , further comprising: means for providing the generated sentences as a plurality of suggestions.

[1383] "Example 1"

[1384] (Claim 1)

[1385] A means for the user to provide input information such as the topic of the text and the characteristics of the target audience through a terminal;

[1386] means for transmitting input information to a server in real time;

[1387] A means for the server to analyze input data using natural language processing technology and extract necessary parameters;

[1388] A means for invoking a generative AI model to generate initial sentences based on user input;

[1389] A means to reanalyze the generated text and make grammatical corrections or style improvements;

[1390] a means for providing the user with a revised text or multiple suggestions and accepting the user's revisions;

[1391] A means to save the final text and output it in a specified format;

[1392] A system including:

[1393] (Claim 2)

[1394] 10. The system of claim 1, wherein the server further comprises means for extracting terminology based on characteristics of the target audience using natural language processing techniques.

[1395] (Claim 3)

[1396] The system of claim 1 , further comprising: means for providing the generated sentences as a plurality of suggestions.

[1397] "Application Example 1"

[1398] (Claim 1)

[1399] means for receiving input information and analyzing it using natural language processing technology;

[1400] A means for generating initial sentences based on input information using a generative AI model;

[1401] A means to correct and improve the grammar and style of the generated text;

[1402] a means for providing the user with multiple improvement suggestions and accepting user modifications;

[1403] A means to save the final text and output it in a specified format;

[1404] A system including:

[1405] (Claim 2)

[1406] and means for extracting technical terms based on the characteristics of the target audience using natural language processing techniques.

[1407] 10. The system of claim 1.

[1408] (Claim 3)

[1409] The system further includes means for generating prompt sentences for various themes and automatically generating sentences based on input information.

[1410] 10. The system of claim 1.

[1411] "Example 2: Combining Emotion Engines"

[1412] (Claim 1)

[1413] means for receiving input information and analyzing it using natural language processing technology;

[1414] means for analyzing the emotional state of a user;

[1415] a means for setting parameters necessary for sentence generation based on the analyzed emotional state;

[1416] A means for invoking a generative AI model to generate sentences based on specified parameters;

[1417] A means to correct and improve the grammar and style of the generated text;

[1418] a means for providing user improvement suggestions and accepting user corrections;

[1419] A means to save the final text and output it in a specified format;

[1420] A system including:

[1421] (Claim 2)

[1422] 10. The system of claim 1, further comprising means for extracting terminology based on target audience characteristics using natural language processing techniques.

[1423] (Claim 3)

[1424] The system of claim 1 , further comprising: means for providing the generated sentences as a plurality of suggestions.

[1425] "Application example 2 when combining emotion engines"

[1426] (Claim 1)

[1427] means for receiving input information and analyzing it using natural language processing technology;

[1428] A means to correct and improve the grammar and style of the generated text;

[1429] a means for providing user improvement suggestions and accepting user corrections;

[1430] A means to save the final text and output it in a specified format;

[1431] A means for analyzing the emotional state of a user using an interactive device, setting parameters based on the emotional information, and generating sentences according to the emotions using a generative AI model;

[1432] A system including:

[1433] (Claim 2)

[1434] 10. The system of claim 1, further comprising means for extracting terminology based on target audience characteristics using natural language processing techniques.

[1435] (Claim 3)

[1436] The system of claim 1 , further comprising: means for providing the generated sentences as a plurality of suggestions. [Explanation of symbols]

[1437] 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. means for receiving input information and analyzing it using natural language processing technology; A means for correcting and improving the grammar and style of the generated text; a means for providing user improvement suggestions and accepting user corrections; A means to save the final text and output it in a specified format; A system including:

2. The system of claim 1 , further comprising means for extracting terminology based on target audience characteristics using natural language processing techniques.

3. The system of claim 1 , further comprising: means for providing the generated sentences as a plurality of suggestions.

Images