System

Abstract

A system is provided.SOLUTION: A system comprising: means for uploading an existing contract; means for importing a slide-format presentation; means for extracting text from the existing contract and the slide-format presentation; means for integrating the extracted text information to generate a draft of a memorandum contract; and means for previewing the generated draft to a user.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] Traditionally, creating and editing contracts has required a huge amount of time and effort. In particular, it has been extremely difficult to integrate different types of documents (existing contracts and slide presentations) and generate a consistent memorandum of understanding. For this reason, there is a need to improve the efficiency and accuracy of document creation. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for generating a draft memorandum of understanding contract by integrating the extracted text information, and means for displaying a preview of the generated draft to a user. Furthermore, by adding an online editor that allows a user to edit the generated draft and means for outputting the edited draft as a final version, contract creation can be made more flexible and efficient.

[0006] An "existing contract" is a document that describes the contents of a contract that has already been created.

[0007] A "slide presentation" is a document that presents information in the form of a slide show, typically in a presentation format that includes both visuals and text.

[0008] "Means for uploading" refers to the mechanism used by users to send files from their own devices to the server.

[0009] "Means of importing" refers to the mechanism by which external data or documents are brought into the system.

[0010] "Text extraction methods" refers to techniques and tools used to extract text data from documents, slides, etc.

[0011] "Integration methods" refers to techniques or processes that bring together data or text obtained from different sources and reconstruct it into a unified format or document.

[0012] "Means for generating a draft" refers to the process or technology used to automatically create a preliminary document based on input data or information.

[0013] The "means for displaying a preview" refers to a mechanism for displaying a generated document so that the user can check its contents before finalizing it.

[0014] "Online editor means" refers to an interface or tool provided to a user to edit a document over the Internet.

[0015] "Means for outputting as a final version" refers to a mechanism that allows a user to save or download the document they have edited and reviewed in its final format (usually PDF or Word format).

[0016] "OCR Method" means a technique or tool that uses optical character recognition technology to extract text data from a scan or image.

[0017] "API means" refers to a mechanism for obtaining or providing data from external systems or services using an application program interface. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The present invention relates to a system for automatically generating a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation. This system operates through the interaction of a server, a terminal, and a user.

[0040] 1. Importing data

[0041] User: Upload an existing contract from their device. In this case, the contract will be provided in PDF or Word format.

[0042] User: Access the server and log in to their Google account. After logging in, select a Google Slides presentation and import it.

[0043] 2. Data Analysis

[0044] Server: After receiving an existing contract, it uses OCR technology to extract the text from the contract, or if it is in Word format, it analyzes the text directly.

[0045] Server: Extract text content from each slide of the slide presentation using the Google Slides API, thereby obtaining the main points of the proposal.

[0046] 3. Data integration and organization

[0047] Server: Identify key contract clauses extracted from existing contracts (e.g., "contract term" and "payment terms") and correlate them with content from slide presentations.

[0048] Server: Based on a standard contract template, this data is arranged in an orderly manner to generate a consistent structure for the memorandum contract.

[0049] 4. Generate a draft

[0050] Server: Automatically generate draft MOUs based on the data integration results, ensuring that the drafts are consistent and include all required contract clauses.

[0051] Server: Previews the generated draft to the user, allowing the user to check the draft and make initial revisions.

[0052] 5. User confirmation and correction

[0053] User: Check the preview of the draft and make any necessary revisions using the online editor.

[0054] Server: Saves the user's edits and updates the final draft of the MOU.

[0055] 6. Final output

[0056] User: Once they are happy with the draft, they request a final output.

[0057] Server: Generates the final MOU in PDF or Word format and provides the user with a download link.

[0058] Specific examples

[0059] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in Google Slides format. Import these files and extract information about the "contract period" from ContractA. Next, obtain important information such as "payment terms" from ProposalB.

[0060] The server integrates this information into an existing contract template to generate a draft memorandum of understanding (MOU), at which point it provides a preview to the user, who can then confirm and modify the content to create the final MOU.

[0061] The present invention significantly streamlines the contract creation process, reducing errors and shortening work time. By using this system, the effort required for contract creation is reduced and professional documents can be generated quickly.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0065] Step 2:

[0066] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[0067] Step 3:

[0068] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[0069] Step 4:

[0070] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0071] Step 5:

[0072] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extract the contents of the contract as text data.

[0073] Step 6:

[0074] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0075] Step 7:

[0076] Server: Analyzes and correlates key contract terms (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[0077] Step 8:

[0078] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0079] Step 9:

[0080] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0081] Step 10:

[0082] User: Check the preview of the draft and, if necessary, make corrections using the online editor.

[0083] Step 11:

[0084] User: Review the revised draft and request the final version to be generated.

[0085] Step 12:

[0086] Server: Generates the final version of the MOU in PDF or Word format, reflecting the user's modifications, and provides the user with a download link.

[0087] Step 13:

[0088] Users: Download the final MOU from the download link provided.

[0089] Example 1

[0090] 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."

[0091] The traditional contract drafting process was time-consuming and labor-intensive, involving numerous manual tasks. Creating consistent contracts while referencing different formats (e.g., PDF contracts and slide presentations) often required a high level of expertise. Furthermore, there was a risk of overlooking important contract clauses and the risk of human error. This made it difficult to draft contracts efficiently and accurately.

[0092] 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.

[0093] In this invention, the server includes means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for generating a draft memorandum of understanding contract by integrating the extracted text information, means for previewing the generated draft to a user, means for identifying important contract clauses in the existing contract through text analysis, means for associating the information extracted from the slide presentation with the contract clauses, and means for arranging the contract clauses based on a specified contract template. This automates the contract creation process and enables efficient and accurate generation of memorandum of understanding contracts.

[0094] An "existing contract" is a document that describes the contents of a contract that has already been created, and is generally provided in PDF or Word format.

[0095] A "slide presentation" is a document for conveying information that consists of multiple slides and places emphasis on visuals.

[0096] "Means of text extraction" refers to technologies and methods for extracting textual information from digital documents, including analysis using OCR technology and APIs.

[0097] A "draft memorandum of understanding agreement" is a template or draft of the final agreement, the contents of which will later be reviewed and revised to become the final version.

[0098] "Means for displaying a preview" refers to a function or technology that allows a user to visually check a draft or document before editing.

[0099] "Text analysis" is a technology that uses natural language processing technology to analyze text within a document and extract and organize specific information.

[0100] "Contractual clauses" are specific conditions and provisions set forth in a contract, and are an important part of the contract that contains the requirements necessary for the performance of the contract.

[0101] A "template" is a model that predetermines the structure and format of a document or data, and provides a standardized format.

[0102] "Online Editor" means software or an application for creating and editing documents over the Internet.

[0103] The "final version" is the completed document that the user has checked and corrected and that is finally output.

[0104] The present invention relates to a system for automatically generating a draft memorandum of understanding (MOU) from an existing contract and a slide presentation. The system operates through the interaction of a server, a terminal, and a user, and includes the following components:

[0105] Importing Data

[0106] First, users upload an existing contract from their device to the server. The contract is provided in PDF or Word format. Using the web interface, users click the "Select File" button to upload the contract file.

[0107] Next, the user accesses the server and logs in to their Google account. After successfully logging in, the user selects and imports a presentation from Google Slides.

[0108] Data analysis

[0109] The server analyzes the received existing contract using OCR technology (for example, Google Cloud Vision API) and extracts the text within the contract. If the contract is in Word format, the server analyzes the text directly. The server also uses Google Slides API to extract the text of each slide from a slide presentation. This allows the main points of the proposal to be obtained.

[0110] Data Integration and Configuration

[0111] The server first identifies key contract clauses, such as "contract term" and "payment terms," ​​from text extracted from existing contracts using natural language processing (NLP). The server then associates the content from the presentation with the contract clauses. This association is based on a predefined contract template. The server then arranges the integrated data in an orderly fashion and generates a draft structure for the MOU.

[0112] Generate and preview a draft

[0113] The server automatically generates a draft MOU based on the data integration results. The draft is then checked for consistency, completeness, and inclusion of all required contract clauses. The server then displays a preview of the draft to the user, who can then review the draft and make initial revisions using an online editor.

[0114] User verification and correction

[0115] The user checks the previewed draft and makes any necessary corrections using the online editor. The server saves the user's edits and updates the draft of the MOU.

[0116] Final output

[0117] Once the user is satisfied with the draft, they request the final output, and the server generates the final MOU in PDF or Word format and provides the user with a download link.

[0118] Specific examples

[0119] For example, consider the case where a user uploads ContractA.pdf and imports ProposalB from Google Slides. The server extracts the "Contract Period" information from ContractA and the "Payment Terms" from ProposalB. The server combines this information and generates a draft based on a template. The user checks the content in a preview, makes any necessary corrections, and then requests the output of the final version. Finally, the server provides the final PDF.

[0120] Prompt example

[0121] Examples of prompts that use generative AI models include:

[0122] "Please describe a program that extracts key contract clauses from existing contracts and Google Slides proposals and automatically creates a draft integrated memorandum of understanding."

[0123] This system will significantly streamline the contract creation process, reducing errors and shortening work time.

[0124] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0125] Step 1:

[0126] The user uploads an existing contract from the terminal to the server. The user clicks the "Select File" button in the web interface, selects the contract (e.g., ContractA.pdf), and uploads it. The input is the existing contract file, and the output is the contract file saved on the server.

[0127] Step 2:

[0128] A user accesses the server and logs in to their Google account. After logging in, the user selects a Google Slides presentation (e.g., Proposal B) and imports it. The input is the Google account information and the Google Slides link, and the output is a presentation file saved on the server.

[0129] Step 3:

[0130] The server analyzes the uploaded existing contract using OCR technology (e.g., Google Cloud Vision API) and extracts the text. OCR is used for PDF format, and text is analyzed directly for Word format. The input is the existing contract file, and the output is the extracted text data.

[0131] Step 4:

[0132] The server uses the Google Slides API to extract the text of each slide from a slide presentation. The input is the Google Slides data, and the output is the extracted text data of the slide.

[0133] Step 5:

[0134] The server identifies important contract terms (e.g., "contract term," "payment terms," ​​etc.) from the extracted text data using natural language processing (NLP) techniques (e.g., spaCy and BERT). The input is the extracted text data, and the output is a list of important contract terms.

[0135] Step 6:

[0136] The server associates the text content obtained from the presentation with the contract terms. It matches the contract terms with the key points in the presentation that are highly relevant. The input is a list of contract terms and the text data of the presentation, and the output is the integrated data.

[0137] Step 7:

[0138] The server arranges the integrated data in order based on a specified contract template and generates a draft, where the input is the integrated data and the contract template, and the output is a draft memorandum of understanding contract.

[0139] Step 8:

[0140] The server then previews the generated draft to the user. The preview is done on a web interface. The input is the draft MOU and the output is the previewed draft.

[0141] Step 9:

[0142] The user checks the previewed draft and makes any necessary corrections using the online editor. The user edits the draft content and saves it. The input is the previewed draft and the user's corrections, and the output is the corrected draft.

[0143] Step 10:

[0144] The server saves the user's edits and updates the final draft of the MOU. The input is the user-modified draft and the output is the final draft.

[0145] Step 11:

[0146] When the user is satisfied with the draft, he or she requests the final output by clicking the "Generate Final" button. The input is the revised draft and the request for the final output, and the output is a notification of the request to the server.

[0147] Step 12:

[0148] The server generates the final MOU agreement in PDF or Word format and provides a download link to the user. The input is the final revised draft, and the output is the generated PDF or Word agreement and a download link.

[0149] (Application example 1)

[0150] 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."

[0151] With the conventional contract drafting method, it was difficult for store staff to provide customers with a draft of the contract quickly and accurately, resulting in problems such as reduced work efficiency and errors.In addition, there was a lack of a way for staff to confirm and revise the contents of the contract in real time while interacting with the customer, making it difficult to improve the quality of customer service.

[0152] 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.

[0153] In this invention, the server includes means for uploading existing documents, means for importing presentation materials, means for extracting character data from the existing documents and the presentation materials, means for previewing the generated draft to the user on a display device, and means for using a wearable device as the display device, thereby enabling store staff to generate, check, and revise draft contracts in real time while interacting with customers, and to quickly provide the final version.

[0154] "Existing Document" refers to a previously created contract or document that is being uploaded.

[0155] An "uploading means" is a method for submitting an existing document to the system.

[0156] "Presentation materials" refers to presentation documents that present information or content in the form of slides.

[0157] "Means of importing" refers to a method for importing data from outside into the system.

[0158] "Character data" refers to character information such as alphabets and kanji characters extracted from documents and presentations.

[0159] "Means of extraction" refers to a method for extracting the necessary information from the data.

[0160] "Draft" refers to a draft of the Agreement before it is finalized.

[0161] "Means of generation" refers to the method for creating new documents or information based on data.

[0162] The "means for displaying a preview" is a method for displaying the generated draft so that the user can check it.

[0163] A "display device" is a device that visually presents information.

[0164] "Wearable device" refers to a hardware device that is worn by a user.

[0165] An "online editing tool" is a method for editing documents over the Internet.

[0166] The "final version" is the version that has been edited and is output as an official document.

[0167] "Character recognition technology" refers to the technology that recognizes character information from images, etc., and converts it into digital text.

[0168] "Application programming interface means" refers to a program interface for linking with other software or services.

[0169] The present invention relates to a system for automatically generating a draft document using an existing document and presentation materials, which operates through the interaction of a server, a terminal, a display device, and a user.

[0170] 1. System Configuration

[0171] The system mainly includes the following elements:

[0172] server

[0173] Terminal

[0174] display device

[0175] User

[0176] server

[0177] The server has the following functions:

[0178] A means for uploading existing documents: Allows users to upload existing documents from their terminals to the server.

[0179] A way to import presentations: Allow users to import presentations from Google Slides or other formats.

[0180] Methods for extracting character data: Extract text from existing documents using OCR technology. Also extract text from presentation materials using API.

[0181] A method for generating a draft: Character data extracted from existing documents and presentation materials is integrated to generate a draft of the document.

[0182] Means for preview display: The generated draft is previewed to the user so that the user can visually check it through a wearable device (e.g., smart glasses).

[0183] Terminal

[0184] A terminal is a device that users use to upload existing documents or presentation materials, preview drafts, and edit them. Terminals can be PCs or smartphones.

[0185] display device

[0186] Wearable devices such as smart glasses are used as display devices, allowing staff to check and amend contracts in real time while interacting with customers.

[0187] User

[0188] Users are store staff and document creators. They use their terminals to upload existing documents and presentation materials, preview the generated drafts, edit them, and output the final version.

[0189] Specific system behavior

[0190] The server analyzes existing documents using OCR technology and presentation materials using API means. It then integrates the analyzed text data and automatically generates draft documents such as contracts and product information sheets. The generated draft is previewed to the user via a wearable device such as smart glasses. The user can then use online editing tools to check the draft and make any necessary corrections. The final document is output in PDF or Word format.

[0191] Hardware and software used

[0192] Hardware: Smart glasses (e.g., Google Glass (registered trademark))

[0193] Software: Python, Tesseract OCR, Google Slides API, python-docx

[0194] Specific examples

[0195] For example, when signing up for a new credit card in-store, the smart glasses can take a photo of the existing contract and load it into a promotional document in Google Slides format. Based on this information, a draft contract can be automatically generated and the customer can review and make amendments. Once the amendments are complete, the final contract can be exported and provided on the spot.

[0196] Prompt Sentence Examples

[0197] "Just take a photo of the contract with the smart glasses. Then enter the Google Slides presentation ID. The system will automatically generate a draft contract."

[0198] Such a system can reduce the workload of staff and provide fast and accurate service to customers.

[0199] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0200] Step 1: Upload an existing document

[0201] A user uses a terminal to upload an existing document to a server.

[0202] Input: Existing document (PDF or Word format)

[0203] Output: Existing documents stored on the server

[0204] Specific operation: The user operates the terminal interface to select an existing document and click the upload button. The server saves the uploaded file in the specified folder.

[0205] Step 2: Import your presentation

[0206] A user uses a terminal to import presentation materials into the server.

[0207] Input: Presentation materials (Google Slides format slide ID)

[0208] Output: Presentation data saved on the server

[0209] Specific operation: The user logs in to their Google account and enters the slide ID to import. The server retrieves and saves the presentation data from the specified slide ID using the Google Slides API.

[0210] Step 3: Extracting character data

[0211] The server extracts character data from existing documents and presentation materials.

[0212] Input: Existing documents, presentation materials

[0213] Output: Extracted character data

[0214] Specific operation: The server uses OCR technology to extract text from existing documents, and uses the Google Slides API to extract text from slides in presentation materials.

[0215] Step 4: Generate a draft

[0216] The server integrates the extracted character data to generate a draft document.

[0217] Input: Extracted character data

[0218] Output: Draft document

[0219] Specific operation: The server places the extracted text data in the appropriate location based on the existing contract template and integrates it. A draft document is generated based on the integrated data.

[0220] Step 5: Preview your draft

[0221] The server displays a preview of the generated draft to the user.

[0222] Input: Document draft

[0223] Output: Draft displayed in preview screen

[0224] Specific operation: The server renders the generated draft in HTML format and displays it on the user's device or smart glasses display.

[0225] Step 6: User Editing

[0226] The user edits the draft using online editing means.

[0227] Input: Document draft

[0228] Output: Edited draft

[0229] Specific operation: The user edits by tapping or clicking on the designated part on the preview screen. The server reflects and saves the user's edits in real time.

[0230] Step 7: Output the final version

[0231] The server outputs the edited draft as the final version.

[0232] Input: Edited draft

[0233] Output: Final document in PDF or Word format

[0234] Specific behavior: The server converts the edited draft into PDF or Word format and provides the user with a download link.

[0235] These processing steps enable the system to efficiently perform everything from automatic generation of contracts to previewing, editing, and outputting the final version.

[0236] 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.

[0237] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user.

[0238] 1. Importing data

[0239] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0240] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[0241] 2. Data Analysis

[0242] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[0243] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0244] 3. Data integration

[0245] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extract the contents of the contract as text data.

[0246] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0247] Server: Analyzes and correlates key contract terms (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[0248] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0249] 4. Generate and preview the draft

[0250] Server: Using the emotion engine, the server generates a draft memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server adjusts the wording and layout accordingly, taking into account the emotional information determined by the emotion engine.

[0251] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0252] 5. User confirmation and correction

[0253] User: Check the preview of the draft and use the online editor to revise it if necessary. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions.

[0254] Server: Saves the user's modifications and updates the final draft, taking into account the emotion engine data.

[0255] 6. Final output

[0256] User: Once they are happy with the draft, they request a final output.

[0257] Server: Generates the final MOU in PDF or Word format, reflecting the user's modifications and emotional data, and provides a download link to the user.

[0258] Specific examples

[0259] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in Google Slides format. Import these files and extract information about the "contract period" from ContractA. Next, obtain important information such as "payment terms" from ProposalB.

[0260] As the user reviews the contract on the preview screen, the emotion engine detects feelings of anxiety or doubt from the user's facial expressions and voice. Based on this emotion data, the server automatically changes the relevant part of the contract to more specific and clear wording and presents it to the user again. In this way, the content of the document is dynamically adjusted according to the user's emotions, providing an environment in which the user can review and revise the contract with confidence.

[0261] This system will not only significantly streamline the contract creation process and enable the rapid creation of accurate and professional documents, but will also provide a more satisfying user experience by taking user emotions into consideration. Utilizing emotion data is also expected to prevent important oversights.

[0262] The processing flow will be explained below.

[0263] Step 1:

[0264] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0265] Step 2:

[0266] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[0267] Step 3:

[0268] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[0269] Step 4:

[0270] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0271] Step 5:

[0272] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word), and extract the contents of the contract as text data.

[0273] Step 6:

[0274] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0275] Step 7:

[0276] Server: Analyzes and associates key contract clauses (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[0277] Step 8:

[0278] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0279] Step 9:

[0280] Server: Prepares the emotion engine and makes it possible to analyze the user's emotions in real time. This emotion engine reads the user's emotions through facial expressions and voice.

[0281] Step 10:

[0282] Server: A preview interface is generated and displayed to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0283] Step 11:

[0284] User: When reviewing a previewed draft, the emotion engine analyzes the user's emotional state (e.g., anxiety, doubt, satisfaction) in real time.

[0285] Step 12:

[0286] Server: Automatically adjusts the content or presentation of the contract as needed based on real-time sentiment data. For example, if the user is concerned about a particular clause, the document can be revised to explain that clause more clearly.

[0287] Step 13:

[0288] User: Improves the preview draft in the online editor while receiving feedback from the emotion engine.

[0289] Step 14:

[0290] Server: Updates the draft that the user has finalized with the final version of the memorandum of understanding, taking into account the emotional data.

[0291] Step 15:

[0292] User: Once satisfied with the draft, request a final output.

[0293] Step 16:

[0294] Server: Generates the final version of the memorandum contract in PDF or Word format, reflecting the user's modifications and emotional data, and provides the user with a download link.

[0295] Step 17:

[0296] User: Download the final MOU from the download link provided.

[0297] Example 2

[0298] 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."

[0299] In the conventional contract creation process, users had to individually review and edit the existing contract and the slide presentation, which required a huge amount of time and effort. Furthermore, if users had concerns or doubts about the content of the contract, there was a lack of a way to adjust the document while taking those concerns into account. This situation led to reduced efficiency in contract creation and user dissatisfaction.

[0300] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for incorporating suggestions and warnings based on the user's emotions into the draft using an emotion engine, and means for displaying a preview of the generated draft to the user. This enables quick and efficient creation of a contract that takes into account the user's anxieties and doubts.

[0301] "Existing contracts" are contract documents that have already been created and stored and are uploaded to the system in PDF or Word format.

[0302] A "slide presentation" is a presentation document consisting of a series of slides, primarily used in business and educational settings, that is imported from a user's Google account.

[0303] "Means for extracting text" refers to a method for extracting written data from contracts or presentations and converting it into text data for analysis.

[0304] The "means for integrating and generating a draft memorandum of understanding agreement" is a method for automatically generating an initial draft of an agreement by integrating multiple pieces of text information in a consistent manner.

[0305] An "emotion engine" is a technology that analyzes a user's facial expressions and voice, detects their emotional state, and reflects it in the content of a document.

[0306] The "means for displaying a preview" refers to a technique or method for displaying the generated draft on a screen so that the user can check it.

[0307] "Online editor means" refers to a tool or function that allows a user to edit text or document content in real time through an interface such as a browser.

[0308] "OCR technology" is an optical character recognition technology that reads characters from image data and analyzes them as text data.

[0309] "API technology" is an application program interface technology that is an interface that allows different software systems to exchange information with each other.

[0310] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user.

[0311] Importing Data

[0312] The user selects an existing contract (PDF or Word file) from their device and sends it to the server through the system's upload form. Next, the user logs in to their account on a browser, selects a slide presentation, and clicks the import button.

[0313] Data analysis

[0314] The server receives the uploaded existing contract file (PDF or Word) and stores it for analysis. Then, the server obtains access rights to the user's slides through the user's account authentication and downloads the specified presentation data using API technology.

[0315] Data integration

[0316] The server analyzes the existing contract file using OCR technology (for PDF) or direct text extraction (for Word) to extract the contract contents as text data. Next, the server uses API technology to extract text data from each slide of the imported slide presentation. The server then associates the key contract clauses (e.g., contract term, payment terms) extracted from the existing contract with key information from the slide presentation. Finally, the server integrates the extracted data based on a standard contract template to automatically generate a consistent and logical draft memorandum of understanding agreement.

[0317] Generate and preview a draft

[0318] The server uses an emotion engine to generate a draft of the memorandum contract that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server takes into account the emotional information determined by the emotion engine and adjusts the wording and layout accordingly. The generated draft is displayed as a preview to the user.

[0319] User verification and correction

[0320] The user checks the previewed draft and, if necessary, edits it using the online editor. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions. The server saves the user's edits and updates the final draft, incorporating the emotional data.

[0321] Final output

[0322] When the user is satisfied with the draft, they request the output of the final version. The server generates the final version of the MOU in PDF or Word format, reflecting the user's revisions and emotional data, and provides the user with a download link.

[0323] Specific examples

[0324] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in slide format. These files are imported, and information on the "contract period" is extracted from ContractA. Next, important points such as "payment terms" are obtained from ProposalB. As the user reviews the contents of the contract on the preview screen, the emotion engine detects feelings of anxiety or doubt from the user's facial expressions and voice. Based on the emotion data, the server automatically changes the relevant part of the contract to more specific and clear wording and presents it to the user again. In this way, the content of the document is dynamically adjusted according to the user's emotions, providing an environment in which the user can review and modify the contract with confidence.

[0325] This system will not only significantly streamline the contract creation process and enable the rapid creation of accurate and professional documents, but will also provide a more satisfying user experience by taking user emotions into consideration. Utilizing emotion data is also expected to prevent important oversights.

[0326] Example prompts for generative AI models

[0327] An example of a prompt is as follows:

[0328] "Please extract the contract period from the newly uploaded contract file (Contract A.pdf) and the payment terms from the sales proposal slide (Proposal B). Integrate them and generate a draft memorandum of understanding for the user to confirm. Please also reflect the user's sentiment data in real time."

[0329] This system streamlines the complex contract creation process and enables safe and secure document creation that takes users' feelings into consideration.

[0330] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0331] Step 1:

[0332] The user selects an existing contract (PDF or Word file) from their device and sends it to the server through the system's upload form. The input is the existing contract file selected by the user, and the output is that file saved on the server. Specifically, the user opens the system interface, clicks the "Select File" button, and selects and uploads the file from their local device.

[0333] Step 2:

[0334] A user logs in to their account on a browser, selects a slide presentation, and clicks the Import button. The input is the user's login information and the slide file, and the output is the slide file being imported to the server. Specifically, the user clicks the "Log in to Google Account" button, enters the required authentication information, and logs in. Then, the user selects the slide presentation and clicks the "Import" button.

[0335] Step 3:

[0336] The server receives the uploaded existing contract file and temporarily stores it for analysis. The input is the contract file uploaded by the user, and the output is that file stored in a directory for analysis. Specifically, the server detects when the file upload is complete and moves it to a specified directory.

[0337] Step 4:

[0338] The server obtains access to the slides through the user's account authentication and downloads the specified presentation data using API technology. The input is the user's authentication information and the slide presentation ID, and the output is the presentation data stored on the server. Specifically, the server authenticates the user using Google's OAuth and downloads the slide data via the Google Slides API.

[0339] Step 5:

[0340] The server analyzes the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data. The input is the existing contract file and the output is the contract's text data. Specifically, the server starts the OCR engine and performs text extraction on the PDF file. In the case of a Word file, the text data is read directly.

[0341] Step 6:

[0342] The server uses API technology to extract text data from each slide of the imported slide presentation. The input is the slide presentation data, and the output is the slide's text data. Specifically, the server uses the Google Slides API to extract the text content of each slide in order.

[0343] Step 7:

[0344] The server analyzes and correlates important contract terms (e.g., contract period, payment terms) extracted from existing contracts with key information from slide presentations. The input is the text data of the contract and the text data of the slides, and the output is an analysis result that correlates both sets of data. Specifically, the server uses natural language processing technology to analyze the text data and identify and match important keywords and phrases.

[0345] Step 8:

[0346] The server integrates the extracted data based on a standard contract template and automatically generates a consistent and logical draft memorandum of understanding contract. The input is the associated analysis results, and the output is a draft memorandum of understanding contract. Specifically, the server generates a draft based on a preset contract template, embedding important items.

[0347] Step 9:

[0348] The server uses the emotion engine to generate a draft memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. The input is the draft MOU and the user's emotion data, and the output is the finalized draft. Specifically, the server runs the emotion engine and adjusts the document according to the user's emotions.

[0349] Step 10:

[0350] The server previews the generated draft to the user. The input is the finalized draft, and the output is a preview screen displayed on the user's browser. Specifically, the server generates a preview interface and displays the draft to the user.

[0351] Step 11:

[0352] The user checks the previewed draft and, if necessary, edits it using the online editor. The input is the preview screen and the user's edits, and the output is the edited draft. Specifically, the user operates the online editor to edit the text and clicks the save button.

[0353] Step 12:

[0354] The server analyzes the user's emotional changes in real time and displays suggestions or warnings based on the user's emotions. The input is real-time emotional data, and the output is suggestions or warning messages. Specifically, the server continuously operates the emotion engine and provides the user with feedback based on their emotions.

[0355] Step 13:

[0356] The server saves the user's modifications and updates the final draft, which also reflects the emotion data. The input is the modified draft and the emotion data, and the output is the final draft. Specifically, the server generates and saves the final version of the memorandum of understanding that reflects the new information.

[0357] Step 14:

[0358] When the user is satisfied with the draft, they request output of the final version. The input is a preview screen containing the final draft, and the output is the output request. The specific action is that the user clicks the "Output Final Version" button.

[0359] Step 15:

[0360] The server generates a final version of the memorandum of understanding agreement in PDF or Word format that reflects the user's revisions and emotion data, and provides the user with a download link. The input is the final draft and the selection of the output format, and the output is the generation of a download link. Specifically, the server saves the generated document in the specified format and sends the link to the user.

[0361] (Application example 2)

[0362] 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."

[0363] Conventional contract creation systems, when combining existing contracts and presentation materials to generate memorandums of understanding, are unable to consider the user's feelings, potentially overlooking areas that may cause anxiety or doubt. Furthermore, if the created contract is difficult for users to understand, the risk of future problems increases. Furthermore, when reviewing contracts in transportation and traffic management, the limited working environment makes it difficult to properly review and revise the contents of the contract on the spot.

[0364] 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 uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for collecting user emotion data using an in-vehicle camera or microphone, means for automatically adjusting the content of the generated draft based on the collected emotion data, and means for displaying a preview of the generated draft to the user. This makes it possible to dynamically adjust the contract document taking emotion data into consideration when the user checks the content of the contract, providing an environment in which the user can check and modify the contract with peace of mind.

[0365] An "existing contract" is a contract that the user has created or received in the past, and is a document whose contents are used as the basis for a new contract to be created.

[0366] A "slide presentation" is a document created in the form of a slide show to provide information visually, and is particularly used in business negotiations and meetings.

[0367] "Text extraction means" means a technique or method for extracting digital text from an uploaded file.

[0368] The "means for integrating and generating a draft memorandum of understanding agreement" is a technique or method for combining the extracted text information with other related information to automatically generate a draft of a new agreement.

[0369] "Means for collecting user emotional data using an in-vehicle camera or microphone" refers to a device or method for obtaining the user's emotional state from their facial expressions and voice using a camera or microphone installed in the vehicle.

[0370] "Means for automatically adjusting the content of a draft generated based on collected emotional data" refers to a technique or method for automatically changing the content or structure of a document depending on the emotional state of the user.

[0371] The "preview display means" refers to a technique or method for visually displaying the generated draft so that the user can make final confirmation or corrections.

[0372] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user. Specific embodiments for carrying out the present invention are described below.

[0373] 1. Importing data

[0374] Terminal: The user selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0375] On the device: The user logs into their Google account on a browser, selects a slide presentation, and clicks the import button to send it to the server.

[0376] 2. Data Analysis

[0377] Server: The server receives the uploaded existing contract file (PDF or Word) and stores it for analysis.

[0378] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0379] 3. Data integration

[0380] Server: The server analyzes the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data.

[0381] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0382] Server: Analyzes and correlates key contract clauses extracted from existing contracts with key information from slide presentations.

[0383] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0384] 4. Generate and preview the draft

[0385] Server: Using the emotion engine, the server generates a draft of the memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server adjusts the wording and layout accordingly, taking into account the emotional information determined by the emotion engine.

[0386] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0387] 5. User confirmation and correction

[0388] On the device: The user previews the draft and edits it using the online editor. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions.

[0389] Server: Saves the user's modifications and updates the final draft, taking into account the emotion engine data.

[0390] 6. Final output

[0391] Terminal: When the user is satisfied with the draft, he or she requests a final output.

[0392] Server: Generates the final MOU in PDF or Word format, reflecting the user's modifications and emotional data, and provides a download link to the user.

[0393] The main technologies used in the above process include PyMuPDF (Fitz), Google Slides API, OpenCV, and a proprietary emotion recognition library. For example, if anxiety or anger is detected from the user's facial expression or voice while they are reviewing the contents of a contract, the wording in that section will be automatically changed to more specific and clearer language. This provides an environment where users can review and revise contracts with peace of mind.

[0394] Example prompt sentence:

[0395] When managing contracts for operating autonomous vehicles, please conduct image analysis to check whether the contract holder is showing any emotion such as anxiety or anger while reviewing the contract.

[0396] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0397] Step 1:

[0398] On the terminal: The user selects an existing contract (PDF or Word file) and sends it to the server through the system's upload form. The uploaded file is saved on the server.

[0399] Input: Existing contract (PDF or Word file)

[0400] Output: Agreement file saved on the server

[0401] Step 2:

[0402] On the device: The user logs in to their Google account on a browser, selects a slide presentation, and clicks the import button. The presentation data is sent to the server using the Google Slides API.

[0403] Input: Slide presentation

[0404] Output: Presentation data saved on the server

[0405] Step 3:

[0406] Server: The server analyzes the uploaded existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data.

[0407] Input: Agreement file stored on the server

[0408] Output: Extracted text data

[0409] Step 4:

[0410] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0411] Input: Presentation data stored on the server

[0412] Output: Extracted slide text data

[0413] Step 5:

[0414] Server: Integrates text data extracted from existing contracts and slide presentations, and automatically generates consistent and logical draft memorandum agreements based on standard contract templates.

[0415] Input: Extracted contract text data, slide text data

[0416] Output: Generated draft MOU agreement

[0417] Step 6:

[0418] Server: Collects user emotion data using in-car cameras or microphones, using facial recognition technology and voice emotion analysis technology.

[0419] Input: User's facial expression data, voice data

[0420] Output: Emotion data

[0421] Step 7:

[0422] Server: Automatically adjusts the content of the generated draft based on the collected sentiment data, specifically by changing the part where the user expresses anxiety or doubt to a clearer, more specific statement.

[0423] Input: Generated draft memorandum of understanding, sentiment data

[0424] Output: Draft of the adjusted MOU agreement

[0425] Step 8:

[0426] Terminal: Generates a preview interface and visually displays the adjusted draft to the user, who can then confirm the contents of the draft.

[0427] Input: Draft of adjusted MOU agreement

[0428] Output: Previewed draft

[0429] Step 9:

[0430] On the device: The user sees a preview of the draft and can edit it using the online editor.

[0431] Input: Previewed draft

[0432] Output: Draft revised by user

[0433] Step 10:

[0434] Server: Saves the user's modifications and updates the final draft taking into account the sentiment data.

[0435] Input: User-edited draft, emotion data

[0436] Output: Final draft

[0437] Step 11:

[0438] Terminal: The user requests the final output, and the server generates the final MOU in PDF or Word format and provides a download link to the user.

[0439] Input: Final Draft

[0440] Output: Final MOU (PDF or Word format) and download link

[0441] 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.

[0442] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<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.

[0443] 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.

[0444] [Second embodiment]

[0445] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0446] 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.

[0447] 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).

[0448] 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.

[0449] 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.

[0450] 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).

[0451] 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.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] 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."

[0457] The present invention relates to a system for automatically generating a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation. This system operates through the interaction of a server, a terminal, and a user.

[0458] 1. Importing data

[0459] User: Upload an existing contract from their device. In this case, the contract will be provided in PDF or Word format.

[0460] User: Access the server and log in to their Google account. After logging in, select a Google Slides presentation and import it.

[0461] 2. Data Analysis

[0462] Server: After receiving an existing contract, it uses OCR technology to extract the text from the contract, or if it is in Word format, it analyzes the text directly.

[0463] Server: Extract text content from each slide of the slide presentation using the Google Slides API, thereby obtaining the main points of the proposal.

[0464] 3. Data integration and organization

[0465] Server: Identify key contract clauses extracted from existing contracts (e.g., "contract term" and "payment terms") and correlate them with content from slide presentations.

[0466] Server: Based on a standard contract template, this data is arranged in an orderly manner to generate a consistent structure for the memorandum contract.

[0467] 4. Generate a draft

[0468] Server: Automatically generate draft MOUs based on the data integration results, ensuring that the drafts are consistent and include all required contract clauses.

[0469] Server: Previews the generated draft to the user, allowing the user to check the draft and make initial revisions.

[0470] 5. User confirmation and correction

[0471] User: Check the preview of the draft and make any necessary revisions using the online editor.

[0472] Server: Saves the user's edits and updates the final draft of the MOU.

[0473] 6. Final output

[0474] User: Once they are happy with the draft, they request a final output.

[0475] Server: Generates the final MOU in PDF or Word format and provides the user with a download link.

[0476] Specific examples

[0477] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in Google Slides format. Import these files and extract information about the "contract period" from ContractA. Next, obtain important information such as "payment terms" from ProposalB.

[0478] The server integrates this information into an existing contract template to generate a draft memorandum of understanding (MOU), at which point it provides a preview to the user, who can then confirm and modify the content to create the final MOU.

[0479] The present invention significantly streamlines the contract creation process, reducing errors and shortening work time. By using this system, the effort required for contract creation is reduced and professional documents can be generated quickly.

[0480] The processing flow will be explained below.

[0481] Step 1:

[0482] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0483] Step 2:

[0484] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[0485] Step 3:

[0486] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[0487] Step 4:

[0488] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0489] Step 5:

[0490] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extract the contents of the contract as text data.

[0491] Step 6:

[0492] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0493] Step 7:

[0494] Server: Analyzes and correlates key contract terms (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[0495] Step 8:

[0496] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0497] Step 9:

[0498] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0499] Step 10:

[0500] User: Check the preview of the draft and, if necessary, make corrections using the online editor.

[0501] Step 11:

[0502] User: Review the revised draft and request the final version to be generated.

[0503] Step 12:

[0504] Server: Generates the final version of the MOU in PDF or Word format, reflecting the user's modifications, and provides the user with a download link.

[0505] Step 13:

[0506] Users: Download the final MOU from the download link provided.

[0507] Example 1

[0508] 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."

[0509] The traditional contract drafting process was time-consuming and labor-intensive, involving numerous manual tasks. Creating consistent contracts while referencing different formats (e.g., PDF contracts and slide presentations) often required a high level of expertise. Furthermore, there was a risk of overlooking important contract clauses and the risk of human error. This made it difficult to draft contracts efficiently and accurately.

[0510] 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.

[0511] In this invention, the server includes means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for generating a draft memorandum of understanding contract by integrating the extracted text information, means for previewing the generated draft to a user, means for identifying important contract clauses in the existing contract through text analysis, means for associating the information extracted from the slide presentation with the contract clauses, and means for arranging the contract clauses based on a specified contract template. This automates the contract creation process and enables efficient and accurate generation of memorandum of understanding contracts.

[0512] An "existing contract" is a document that describes the contents of a contract that has already been created, and is generally provided in PDF or Word format.

[0513] A "slide presentation" is a document for conveying information that consists of multiple slides and places emphasis on visuals.

[0514] "Means of text extraction" refers to technologies and methods for extracting textual information from digital documents, including analysis using OCR technology and APIs.

[0515] A "draft memorandum of understanding agreement" is a template or draft of the final agreement, the contents of which will later be reviewed and revised to become the final version.

[0516] "Means for displaying a preview" refers to a function or technology that allows a user to visually check a draft or document before editing.

[0517] "Text analysis" is a technology that uses natural language processing technology to analyze text within a document and extract and organize specific information.

[0518] "Contractual clauses" are specific conditions and provisions set forth in a contract, and are an important part of the contract that contains the requirements necessary for the performance of the contract.

[0519] A "template" is a model that predetermines the structure and format of a document or data, and provides a standardized format.

[0520] "Online Editor" means software or an application for creating and editing documents over the Internet.

[0521] The "final version" is the completed document that the user has checked and corrected and that is finally output.

[0522] The present invention relates to a system for automatically generating a draft memorandum of understanding (MOU) from an existing contract and a slide presentation. The system operates through the interaction of a server, a terminal, and a user, and includes the following components:

[0523] Importing Data

[0524] First, users upload an existing contract from their device to the server. The contract is provided in PDF or Word format. Using the web interface, users click the "Select File" button to upload the contract file.

[0525] Next, the user accesses the server and logs in to their Google account. After successfully logging in, the user selects and imports a presentation from Google Slides.

[0526] Data analysis

[0527] The server analyzes the received existing contract using OCR technology (for example, Google Cloud Vision API) and extracts the text within the contract. If the contract is in Word format, the server analyzes the text directly. The server also uses Google Slides API to extract the text of each slide from a slide presentation. This allows the main points of the proposal to be obtained.

[0528] Data Integration and Configuration

[0529] The server first identifies key contract clauses, such as "contract term" and "payment terms," ​​from text extracted from existing contracts using natural language processing (NLP). The server then associates the content from the presentation with the contract clauses. This association is based on a predefined contract template. The server then arranges the integrated data in an orderly fashion and generates a draft structure for the MOU.

[0530] Generate and preview a draft

[0531] The server automatically generates a draft MOU based on the data integration results. The draft is then checked for consistency, completeness, and inclusion of all required contract clauses. The server then displays a preview of the draft to the user, who can then review the draft and make initial revisions using an online editor.

[0532] User verification and correction

[0533] The user checks the previewed draft and makes any necessary corrections using the online editor. The server saves the user's edits and updates the draft of the MOU.

[0534] Final output

[0535] Once the user is satisfied with the draft, they request the final output, and the server generates the final MOU in PDF or Word format and provides the user with a download link.

[0536] Specific examples

[0537] For example, consider the case where a user uploads ContractA.pdf and imports ProposalB from Google Slides. The server extracts the "Contract Period" information from ContractA and the "Payment Terms" from ProposalB. The server combines this information and generates a draft based on a template. The user checks the content in a preview, makes any necessary corrections, and then requests the output of the final version. Finally, the server provides the final PDF.

[0538] Prompt example

[0539] Examples of prompts that use generative AI models include:

[0540] "Please describe a program that extracts key contract clauses from existing contracts and Google Slides proposals and automatically creates a draft integrated memorandum of understanding."

[0541] This system will significantly streamline the contract creation process, reducing errors and shortening work time.

[0542] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0543] Step 1:

[0544] The user uploads an existing contract from the terminal to the server. The user clicks the "Select File" button in the web interface, selects the contract (e.g., ContractA.pdf), and uploads it. The input is the existing contract file, and the output is the contract file saved on the server.

[0545] Step 2:

[0546] A user accesses the server and logs in to their Google account. After logging in, the user selects a Google Slides presentation (e.g., Proposal B) and imports it. The input is the Google account information and the Google Slides link, and the output is a presentation file saved on the server.

[0547] Step 3:

[0548] The server analyzes the uploaded existing contract using OCR technology (e.g., Google Cloud Vision API) and extracts the text. OCR is used for PDF format, and text is analyzed directly for Word format. The input is the existing contract file, and the output is the extracted text data.

[0549] Step 4:

[0550] The server uses the Google Slides API to extract the text of each slide from a slide presentation. The input is the Google Slides data, and the output is the extracted text data of the slide.

[0551] Step 5:

[0552] The server identifies important contract terms (e.g., "contract term," "payment terms," ​​etc.) from the extracted text data using natural language processing (NLP) techniques (e.g., spaCy and BERT). The input is the extracted text data, and the output is a list of important contract terms.

[0553] Step 6:

[0554] The server associates the text content obtained from the presentation with the contract terms. It matches the contract terms with the key points in the presentation that are highly relevant. The input is a list of contract terms and the text data of the presentation, and the output is the integrated data.

[0555] Step 7:

[0556] The server arranges the integrated data in order based on a specified contract template and generates a draft, where the input is the integrated data and the contract template, and the output is a draft memorandum of understanding contract.

[0557] Step 8:

[0558] The server then previews the generated draft to the user. The preview is done on a web interface. The input is the draft MOU and the output is the previewed draft.

[0559] Step 9:

[0560] The user checks the previewed draft and makes any necessary corrections using the online editor. The user edits the draft content and saves it. The input is the previewed draft and the user's corrections, and the output is the corrected draft.

[0561] Step 10:

[0562] The server saves the user's edits and updates the final draft of the MOU. The input is the user-modified draft and the output is the final draft.

[0563] Step 11:

[0564] When the user is satisfied with the draft, he or she requests the final output by clicking the "Generate Final" button. The input is the revised draft and the request for the final output, and the output is a notification of the request to the server.

[0565] Step 12:

[0566] The server generates the final MOU agreement in PDF or Word format and provides a download link to the user. The input is the final revised draft, and the output is the generated PDF or Word agreement and a download link.

[0567] (Application example 1)

[0568] 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."

[0569] With the conventional contract drafting method, it was difficult for store staff to provide customers with a draft of the contract quickly and accurately, resulting in problems such as reduced work efficiency and errors.In addition, there was a lack of a way for staff to confirm and revise the contents of the contract in real time while interacting with the customer, making it difficult to improve the quality of customer service.

[0570] 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.

[0571] In this invention, the server includes means for uploading existing documents, means for importing presentation materials, means for extracting character data from the existing documents and the presentation materials, means for previewing the generated draft to the user on a display device, and means for using a wearable device as the display device, thereby enabling store staff to generate, check, and revise draft contracts in real time while interacting with customers, and to quickly provide the final version.

[0572] "Existing Document" refers to a previously created contract or document that is being uploaded.

[0573] An "uploading means" is a method for submitting an existing document to the system.

[0574] "Presentation materials" refers to presentation documents that present information or content in the form of slides.

[0575] "Means of importing" refers to a method for importing data from outside into the system.

[0576] "Character data" refers to character information such as alphabets and kanji characters extracted from documents and presentations.

[0577] "Means of extraction" refers to a method for extracting the necessary information from the data.

[0578] "Draft" refers to a draft of the Agreement before it is finalized.

[0579] "Means of generation" refers to the method for creating new documents or information based on data.

[0580] The "means for displaying a preview" is a method for displaying the generated draft so that the user can check it.

[0581] A "display device" is a device that visually presents information.

[0582] "Wearable device" refers to a hardware device that is worn by a user.

[0583] An "online editing tool" is a method for editing documents over the Internet.

[0584] The "final version" is the version that has been edited and is output as an official document.

[0585] "Character recognition technology" refers to the technology that recognizes character information from images, etc., and converts it into digital text.

[0586] "Application programming interface means" refers to a program interface for linking with other software or services.

[0587] The present invention relates to a system for automatically generating a draft document using an existing document and presentation materials, which operates through the interaction of a server, a terminal, a display device, and a user.

[0588] 1. System Configuration

[0589] The system mainly includes the following elements:

[0590] server

[0591] Terminal

[0592] display device

[0593] User

[0594] server

[0595] The server has the following functions:

[0596] A means for uploading existing documents: Allows users to upload existing documents from their terminals to the server.

[0597] A way to import presentations: Allow users to import presentations from Google Slides or other formats.

[0598] Methods for extracting character data: Extract text from existing documents using OCR technology. Also extract text from presentation materials using API.

[0599] A method for generating a draft: Character data extracted from existing documents and presentation materials is integrated to generate a draft of the document.

[0600] Means for preview display: The generated draft is previewed to the user so that the user can visually check it through a wearable device (e.g., smart glasses).

[0601] Terminal

[0602] A terminal is a device that users use to upload existing documents or presentation materials, preview drafts, and edit them. Terminals can be PCs or smartphones.

[0603] display device

[0604] Wearable devices such as smart glasses are used as display devices, allowing staff to check and amend contracts in real time while interacting with customers.

[0605] User

[0606] Users are store staff and document creators. They use their terminals to upload existing documents and presentation materials, preview the generated drafts, edit them, and output the final version.

[0607] Specific system behavior

[0608] The server analyzes existing documents using OCR technology and presentation materials using API means. It then integrates the analyzed text data and automatically generates draft documents such as contracts and product information sheets. The generated draft is previewed to the user via a wearable device such as smart glasses. The user can then use online editing tools to check the draft and make any necessary corrections. The final document is output in PDF or Word format.

[0609] Hardware and software used

[0610] Hardware: Smart glasses (e.g., Google Glass)

[0611] Software: Python, Tesseract OCR, Google Slides API, python-docx

[0612] Specific examples

[0613] For example, when signing up for a new credit card in-store, the smart glasses can take a photo of the existing contract and load it into a promotional document in Google Slides format. Based on this information, a draft contract can be automatically generated and the customer can review and make amendments. Once the amendments are complete, the final contract can be exported and provided on the spot.

[0614] Prompt Sentence Examples

[0615] "Just take a photo of the contract with the smart glasses. Then enter the Google Slides presentation ID. The system will automatically generate a draft contract."

[0616] Such a system can reduce the workload of staff and provide fast and accurate service to customers.

[0617] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0618] Step 1: Upload an existing document

[0619] A user uses a terminal to upload an existing document to a server.

[0620] Input: Existing document (PDF or Word format)

[0621] Output: Existing documents stored on the server

[0622] Specific operation: The user operates the terminal interface to select an existing document and click the upload button. The server saves the uploaded file in the specified folder.

[0623] Step 2: Import your presentation

[0624] A user uses a terminal to import presentation materials into the server.

[0625] Input: Presentation materials (Google Slides format slide ID)

[0626] Output: Presentation data saved on the server

[0627] Specific operation: The user logs in to their Google account and enters the slide ID to import. The server retrieves and saves the presentation data from the specified slide ID using the Google Slides API.

[0628] Step 3: Extracting character data

[0629] The server extracts character data from existing documents and presentation materials.

[0630] Input: Existing documents, presentation materials

[0631] Output: Extracted character data

[0632] Specific operation: The server uses OCR technology to extract text from existing documents, and uses the Google Slides API to extract text from slides in presentation materials.

[0633] Step 4: Generate a draft

[0634] The server integrates the extracted character data to generate a draft document.

[0635] Input: Extracted character data

[0636] Output: Draft document

[0637] Specific operation: The server places the extracted text data in the appropriate location based on the existing contract template and integrates it. A draft document is generated based on the integrated data.

[0638] Step 5: Preview your draft

[0639] The server displays a preview of the generated draft to the user.

[0640] Input: Document draft

[0641] Output: Draft displayed in preview screen

[0642] Specific operation: The server renders the generated draft in HTML format and displays it on the user's device or smart glasses display.

[0643] Step 6: User Editing

[0644] The user edits the draft using online editing means.

[0645] Input: Document draft

[0646] Output: Edited draft

[0647] Specific operation: The user edits by tapping or clicking on the designated part on the preview screen. The server reflects and saves the user's edits in real time.

[0648] Step 7: Output the final version

[0649] The server outputs the edited draft as the final version.

[0650] Input: Edited draft

[0651] Output: Final document in PDF or Word format

[0652] Specific behavior: The server converts the edited draft into PDF or Word format and provides the user with a download link.

[0653] These processing steps enable the system to efficiently perform everything from automatic generation of contracts to previewing, editing, and outputting the final version.

[0654] 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.

[0655] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user.

[0656] 1. Importing data

[0657] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0658] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[0659] 2. Data Analysis

[0660] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[0661] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0662] 3. Data integration

[0663] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extract the contents of the contract as text data.

[0664] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0665] Server: Analyzes and correlates key contract terms (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[0666] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0667] 4. Generate and preview the draft

[0668] Server: Using the emotion engine, the server generates a draft memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server adjusts the wording and layout accordingly, taking into account the emotional information determined by the emotion engine.

[0669] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0670] 5. User confirmation and correction

[0671] User: Check the preview of the draft and use the online editor to revise it if necessary. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions.

[0672] Server: Saves the user's modifications and updates the final draft, taking into account the emotion engine data.

[0673] 6. Final output

[0674] User: Once they are happy with the draft, they request a final output.

[0675] Server: Generates the final MOU in PDF or Word format, reflecting the user's modifications and emotional data, and provides a download link to the user.

[0676] Specific examples

[0677] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in Google Slides format. Import these files and extract information about the "contract period" from ContractA. Next, obtain important information such as "payment terms" from ProposalB.

[0678] As the user reviews the contract on the preview screen, the emotion engine detects feelings of anxiety or doubt from the user's facial expressions and voice. Based on this emotion data, the server automatically changes the relevant part of the contract to more specific and clear wording and presents it to the user again. In this way, the content of the document is dynamically adjusted according to the user's emotions, providing an environment in which the user can review and revise the contract with confidence.

[0679] This system will not only significantly streamline the contract creation process and enable the rapid creation of accurate and professional documents, but will also provide a more satisfying user experience by taking user emotions into consideration. Utilizing emotion data is also expected to prevent important oversights.

[0680] The processing flow will be explained below.

[0681] Step 1:

[0682] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0683] Step 2:

[0684] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[0685] Step 3:

[0686] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[0687] Step 4:

[0688] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0689] Step 5:

[0690] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word), and extract the contents of the contract as text data.

[0691] Step 6:

[0692] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0693] Step 7:

[0694] Server: Analyzes and associates key contract clauses (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[0695] Step 8:

[0696] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0697] Step 9:

[0698] Server: Prepares the emotion engine and makes it possible to analyze the user's emotions in real time. This emotion engine reads the user's emotions through facial expressions and voice.

[0699] Step 10:

[0700] Server: A preview interface is generated and displayed to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0701] Step 11:

[0702] User: When reviewing a previewed draft, the emotion engine analyzes the user's emotional state (e.g., anxiety, doubt, satisfaction) in real time.

[0703] Step 12:

[0704] Server: Automatically adjusts the content or presentation of the contract as needed based on real-time sentiment data. For example, if the user is concerned about a particular clause, the document can be revised to explain that clause more clearly.

[0705] Step 13:

[0706] User: Improves the preview draft in the online editor while receiving feedback from the emotion engine.

[0707] Step 14:

[0708] Server: Updates the draft that the user has finalized with the final version of the memorandum of understanding, taking into account the emotional data.

[0709] Step 15:

[0710] User: Once satisfied with the draft, request a final output.

[0711] Step 16:

[0712] Server: Generates the final version of the memorandum contract in PDF or Word format, reflecting the user's modifications and emotional data, and provides the user with a download link.

[0713] Step 17:

[0714] User: Download the final MOU from the download link provided.

[0715] Example 2

[0716] 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."

[0717] In the conventional contract creation process, users had to individually review and edit the existing contract and the slide presentation, which required a huge amount of time and effort. Furthermore, if users had concerns or doubts about the content of the contract, there was a lack of a way to adjust the document while taking those concerns into account. This situation led to reduced efficiency in contract creation and user dissatisfaction.

[0718] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for incorporating suggestions and warnings based on the user's emotions into the draft using an emotion engine, and means for displaying a preview of the generated draft to the user. This enables quick and efficient creation of a contract that takes into account the user's anxieties and doubts.

[0719] "Existing contracts" are contract documents that have already been created and stored and are uploaded to the system in PDF or Word format.

[0720] A "slide presentation" is a presentation document consisting of a series of slides, primarily used in business and educational settings, that is imported from a user's Google account.

[0721] "Means for extracting text" refers to a method for extracting written data from contracts or presentations and converting it into text data for analysis.

[0722] The "means for integrating and generating a draft memorandum of understanding agreement" is a method for automatically generating an initial draft of an agreement by integrating multiple pieces of text information in a consistent manner.

[0723] An "emotion engine" is a technology that analyzes a user's facial expressions and voice, detects their emotional state, and reflects it in the content of a document.

[0724] The "means for displaying a preview" refers to a technique or method for displaying the generated draft on a screen so that the user can check it.

[0725] "Online editor means" refers to a tool or function that allows a user to edit text or document content in real time through an interface such as a browser.

[0726] "OCR technology" is an optical character recognition technology that reads characters from image data and analyzes them as text data.

[0727] "API technology" is an application program interface technology that is an interface that allows different software systems to exchange information with each other.

[0728] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user.

[0729] Importing Data

[0730] The user selects an existing contract (PDF or Word file) from their device and sends it to the server through the system's upload form. Next, the user logs in to their account on a browser, selects a slide presentation, and clicks the import button.

[0731] Data analysis

[0732] The server receives the uploaded existing contract file (PDF or Word) and stores it for analysis. Then, the server obtains access rights to the user's slides through the user's account authentication and downloads the specified presentation data using API technology.

[0733] Data integration

[0734] The server analyzes the existing contract file using OCR technology (for PDF) or direct text extraction (for Word) to extract the contract contents as text data. Next, the server uses API technology to extract text data from each slide of the imported slide presentation. The server then associates the key contract clauses (e.g., contract term, payment terms) extracted from the existing contract with key information from the slide presentation. Finally, the server integrates the extracted data based on a standard contract template to automatically generate a consistent and logical draft memorandum of understanding agreement.

[0735] Generate and preview a draft

[0736] The server uses an emotion engine to generate a draft of the memorandum contract that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server takes into account the emotional information determined by the emotion engine and adjusts the wording and layout accordingly. The generated draft is displayed as a preview to the user.

[0737] User verification and correction

[0738] The user checks the previewed draft and, if necessary, edits it using the online editor. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions. The server saves the user's edits and updates the final draft, incorporating the emotional data.

[0739] Final output

[0740] When the user is satisfied with the draft, they request the output of the final version. The server generates the final version of the MOU in PDF or Word format, reflecting the user's revisions and emotional data, and provides the user with a download link.

[0741] Specific examples

[0742] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in slide format. These files are imported, and information on the "contract period" is extracted from ContractA. Next, important points such as "payment terms" are obtained from ProposalB. As the user reviews the contents of the contract on the preview screen, the emotion engine detects feelings of anxiety or doubt from the user's facial expressions and voice. Based on the emotion data, the server automatically changes the relevant part of the contract to more specific and clear wording and presents it to the user again. In this way, the content of the document is dynamically adjusted according to the user's emotions, providing an environment in which the user can review and modify the contract with confidence.

[0743] This system will not only significantly streamline the contract creation process and enable the rapid creation of accurate and professional documents, but will also provide a more satisfying user experience by taking user emotions into consideration. Utilizing emotion data is also expected to prevent important oversights.

[0744] Example prompts for generative AI models

[0745] An example of a prompt is as follows:

[0746] "Please extract the contract period from the newly uploaded contract file (Contract A.pdf) and the payment terms from the sales proposal slide (Proposal B). Integrate them and generate a draft memorandum of understanding for the user to confirm. Please also reflect the user's sentiment data in real time."

[0747] This system streamlines the complex contract creation process and enables safe and secure document creation that takes users' feelings into consideration.

[0748] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0749] Step 1:

[0750] The user selects an existing contract (PDF or Word file) from their device and sends it to the server through the system's upload form. The input is the existing contract file selected by the user, and the output is that file saved on the server. Specifically, the user opens the system interface, clicks the "Select File" button, and selects and uploads the file from their local device.

[0751] Step 2:

[0752] A user logs in to their account on a browser, selects a slide presentation, and clicks the Import button. The input is the user's login information and the slide file, and the output is the slide file being imported to the server. Specifically, the user clicks the "Log in to Google Account" button, enters the required authentication information, and logs in. Then, the user selects the slide presentation and clicks the "Import" button.

[0753] Step 3:

[0754] The server receives the uploaded existing contract file and temporarily stores it for analysis. The input is the contract file uploaded by the user, and the output is that file stored in a directory for analysis. Specifically, the server detects when the file upload is complete and moves it to a specified directory.

[0755] Step 4:

[0756] The server obtains access to the slides through the user's account authentication and downloads the specified presentation data using API technology. The input is the user's authentication information and the slide presentation ID, and the output is the presentation data stored on the server. Specifically, the server authenticates the user using Google's OAuth and downloads the slide data via the Google Slides API.

[0757] Step 5:

[0758] The server analyzes the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data. The input is the existing contract file and the output is the contract's text data. Specifically, the server starts the OCR engine and performs text extraction on the PDF file. In the case of a Word file, the text data is read directly.

[0759] Step 6:

[0760] The server uses API technology to extract text data from each slide of the imported slide presentation. The input is the slide presentation data, and the output is the slide's text data. Specifically, the server uses the Google Slides API to extract the text content of each slide in order.

[0761] Step 7:

[0762] The server analyzes and correlates important contract terms (e.g., contract period, payment terms) extracted from existing contracts with key information from slide presentations. The input is the text data of the contract and the text data of the slides, and the output is an analysis result that correlates both sets of data. Specifically, the server uses natural language processing technology to analyze the text data and identify and match important keywords and phrases.

[0763] Step 8:

[0764] The server integrates the extracted data based on a standard contract template and automatically generates a consistent and logical draft memorandum of understanding contract. The input is the associated analysis results, and the output is a draft memorandum of understanding contract. Specifically, the server generates a draft based on a preset contract template, embedding important items.

[0765] Step 9:

[0766] The server uses the emotion engine to generate a draft memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. The input is the draft MOU and the user's emotion data, and the output is the finalized draft. Specifically, the server runs the emotion engine and adjusts the document according to the user's emotions.

[0767] Step 10:

[0768] The server previews the generated draft to the user. The input is the finalized draft, and the output is a preview screen displayed on the user's browser. Specifically, the server generates a preview interface and displays the draft to the user.

[0769] Step 11:

[0770] The user checks the previewed draft and, if necessary, edits it using the online editor. The input is the preview screen and the user's edits, and the output is the edited draft. Specifically, the user operates the online editor to edit the text and clicks the save button.

[0771] Step 12:

[0772] The server analyzes the user's emotional changes in real time and displays suggestions or warnings based on the user's emotions. The input is real-time emotional data, and the output is suggestions or warning messages. Specifically, the server continuously operates the emotion engine and provides the user with feedback based on their emotions.

[0773] Step 13:

[0774] The server saves the user's modifications and updates the final draft, which also reflects the emotion data. The input is the modified draft and the emotion data, and the output is the final draft. Specifically, the server generates and saves the final version of the memorandum of understanding that reflects the new information.

[0775] Step 14:

[0776] When the user is satisfied with the draft, they request output of the final version. The input is a preview screen containing the final draft, and the output is the output request. The specific action is that the user clicks the "Output Final Version" button.

[0777] Step 15:

[0778] The server generates a final version of the memorandum of understanding agreement in PDF or Word format that reflects the user's revisions and emotion data, and provides the user with a download link. The input is the final draft and the selection of the output format, and the output is the generation of a download link. Specifically, the server saves the generated document in the specified format and sends the link to the user.

[0779] (Application example 2)

[0780] 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."

[0781] Conventional contract creation systems, when combining existing contracts and presentation materials to generate memorandums of understanding, are unable to consider the user's feelings, potentially overlooking areas that may cause anxiety or doubt. Furthermore, if the created contract is difficult for users to understand, the risk of future problems increases. Furthermore, when reviewing contracts in transportation and traffic management, the limited working environment makes it difficult to properly review and revise the contents of the contract on the spot.

[0782] 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 uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for collecting user emotion data using an in-vehicle camera or microphone, means for automatically adjusting the content of the generated draft based on the collected emotion data, and means for displaying a preview of the generated draft to the user. This makes it possible to dynamically adjust the contract document taking emotion data into consideration when the user checks the content of the contract, providing an environment in which the user can check and modify the contract with peace of mind.

[0783] An "existing contract" is a contract that the user has created or received in the past, and is a document whose contents are used as the basis for a new contract to be created.

[0784] A "slide presentation" is a document created in the form of a slide show to provide information visually, and is particularly used in business negotiations and meetings.

[0785] "Text extraction means" means a technique or method for extracting digital text from an uploaded file.

[0786] The "means for integrating and generating a draft memorandum of understanding agreement" is a technique or method for combining the extracted text information with other related information to automatically generate a draft of a new agreement.

[0787] "Means for collecting user emotional data using an in-vehicle camera or microphone" refers to a device or method for obtaining the user's emotional state from their facial expressions and voice using a camera or microphone installed in the vehicle.

[0788] "Means for automatically adjusting the content of a draft generated based on collected emotional data" refers to a technique or method for automatically changing the content or structure of a document depending on the emotional state of the user.

[0789] The "preview display means" refers to a technique or method for visually displaying the generated draft so that the user can make final confirmation or corrections.

[0790] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user. Specific embodiments for carrying out the present invention are described below.

[0791] 1. Importing data

[0792] Terminal: The user selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0793] On the device: The user logs into their Google account on a browser, selects a slide presentation, and clicks the import button to send it to the server.

[0794] 2. Data Analysis

[0795] Server: The server receives the uploaded existing contract file (PDF or Word) and stores it for analysis.

[0796] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0797] 3. Data integration

[0798] Server: The server analyzes the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data.

[0799] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0800] Server: Analyzes and correlates key contract clauses extracted from existing contracts with key information from slide presentations.

[0801] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0802] 4. Generate and preview the draft

[0803] Server: Using the emotion engine, the server generates a draft of the memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server adjusts the wording and layout accordingly, taking into account the emotional information determined by the emotion engine.

[0804] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0805] 5. User confirmation and correction

[0806] On the device: The user previews the draft and edits it using the online editor. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions.

[0807] Server: Saves the user's modifications and updates the final draft, taking into account the emotion engine data.

[0808] 6. Final output

[0809] Terminal: When the user is satisfied with the draft, he or she requests a final output.

[0810] Server: Generates the final MOU in PDF or Word format, reflecting the user's modifications and emotional data, and provides a download link to the user.

[0811] The main technologies used in the above process include PyMuPDF (Fitz), Google Slides API, OpenCV, and a proprietary emotion recognition library. For example, if anxiety or anger is detected from the user's facial expression or voice while they are reviewing the contents of a contract, the wording in that section will be automatically changed to more specific and clearer language. This provides an environment where users can review and revise contracts with peace of mind.

[0812] Example prompt sentence:

[0813] When managing contracts for operating autonomous vehicles, please conduct image analysis to check whether the contract holder is showing any emotion such as anxiety or anger while reviewing the contract.

[0814] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0815] Step 1:

[0816] On the terminal: The user selects an existing contract (PDF or Word file) and sends it to the server through the system's upload form. The uploaded file is saved on the server.

[0817] Input: Existing contract (PDF or Word file)

[0818] Output: Agreement file saved on the server

[0819] Step 2:

[0820] On the device: The user logs in to their Google account on a browser, selects a slide presentation, and clicks the import button. The presentation data is sent to the server using the Google Slides API.

[0821] Input: Slide presentation

[0822] Output: Presentation data saved on the server

[0823] Step 3:

[0824] Server: The server analyzes the uploaded existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data.

[0825] Input: Agreement file stored on the server

[0826] Output: Extracted text data

[0827] Step 4:

[0828] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0829] Input: Presentation data stored on the server

[0830] Output: Extracted slide text data

[0831] Step 5:

[0832] Server: Integrates text data extracted from existing contracts and slide presentations, and automatically generates consistent and logical draft memorandum agreements based on standard contract templates.

[0833] Input: Extracted contract text data, slide text data

[0834] Output: Generated draft MOU agreement

[0835] Step 6:

[0836] Server: Collects user emotion data using in-car cameras or microphones, using facial recognition technology and voice emotion analysis technology.

[0837] Input: User's facial expression data, voice data

[0838] Output: Emotion data

[0839] Step 7:

[0840] Server: Automatically adjusts the content of the generated draft based on the collected sentiment data, specifically by changing the part where the user expresses anxiety or doubt to a clearer, more specific statement.

[0841] Input: Generated draft memorandum of understanding, sentiment data

[0842] Output: Draft of the adjusted MOU agreement

[0843] Step 8:

[0844] Terminal: Generates a preview interface and visually displays the adjusted draft to the user, who can then confirm the contents of the draft.

[0845] Input: Draft of adjusted MOU agreement

[0846] Output: Previewed draft

[0847] Step 9:

[0848] On the device: The user sees a preview of the draft and can edit it using the online editor.

[0849] Input: Previewed draft

[0850] Output: Draft revised by user

[0851] Step 10:

[0852] Server: Saves the user's modifications and updates the final draft taking into account the sentiment data.

[0853] Input: User-edited draft, emotion data

[0854] Output: Final draft

[0855] Step 11:

[0856] Terminal: The user requests the final output, and the server generates the final MOU in PDF or Word format and provides a download link to the user.

[0857] Input: Final Draft

[0858] Output: Final MOU (PDF or Word format) and download link

[0859] 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.

[0860] 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.

[0861] 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.

[0862] [Third embodiment]

[0863] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0864] 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.

[0865] 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).

[0866] 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.

[0867] 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.

[0868] 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).

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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."

[0875] The present invention relates to a system for automatically generating a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation. This system operates through the interaction of a server, a terminal, and a user.

[0876] 1. Importing data

[0877] User: Upload an existing contract from their device. In this case, the contract will be provided in PDF or Word format.

[0878] User: Access the server and log in to their Google account. After logging in, select a Google Slides presentation and import it.

[0879] 2. Data Analysis

[0880] Server: After receiving an existing contract, it uses OCR technology to extract the text from the contract, or if it is in Word format, it analyzes the text directly.

[0881] Server: Extract text content from each slide of the slide presentation using the Google Slides API, thereby obtaining the main points of the proposal.

[0882] 3. Data integration and organization

[0883] Server: Identify key contract clauses extracted from existing contracts (e.g., "contract term" and "payment terms") and correlate them with content from slide presentations.

[0884] Server: Based on a standard contract template, this data is arranged in an orderly manner to generate a consistent structure for the memorandum contract.

[0885] 4. Generate a draft

[0886] Server: Automatically generate draft MOUs based on the data integration results, ensuring that the drafts are consistent and include all required contract clauses.

[0887] Server: Previews the generated draft to the user, allowing the user to check the draft and make initial revisions.

[0888] 5. User confirmation and correction

[0889] User: Check the preview of the draft and make any necessary revisions using the online editor.

[0890] Server: Saves the user's edits and updates the final draft of the MOU.

[0891] 6. Final output

[0892] User: Once they are happy with the draft, they request a final output.

[0893] Server: Generates the final MOU in PDF or Word format and provides the user with a download link.

[0894] Specific examples

[0895] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in Google Slides format. Import these files and extract information about the "contract period" from ContractA. Next, obtain important information such as "payment terms" from ProposalB.

[0896] The server integrates this information into an existing contract template to generate a draft memorandum of understanding (MOU), at which point it provides a preview to the user, who can then confirm and modify the content to create the final MOU.

[0897] The present invention significantly streamlines the contract creation process, reducing errors and shortening work time. By using this system, the effort required for contract creation is reduced and professional documents can be generated quickly.

[0898] The processing flow will be explained below.

[0899] Step 1:

[0900] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[0901] Step 2:

[0902] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[0903] Step 3:

[0904] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[0905] Step 4:

[0906] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[0907] Step 5:

[0908] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extract the contents of the contract as text data.

[0909] Step 6:

[0910] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[0911] Step 7:

[0912] Server: Analyzes and correlates key contract terms (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[0913] Step 8:

[0914] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[0915] Step 9:

[0916] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[0917] Step 10:

[0918] User: Check the preview of the draft and, if necessary, make corrections using the online editor.

[0919] Step 11:

[0920] User: Review the revised draft and request the final version to be generated.

[0921] Step 12:

[0922] Server: Generates the final version of the MOU in PDF or Word format, reflecting the user's modifications, and provides the user with a download link.

[0923] Step 13:

[0924] Users: Download the final MOU from the download link provided.

[0925] Example 1

[0926] 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."

[0927] The traditional contract drafting process was time-consuming and labor-intensive, involving numerous manual tasks. Creating consistent contracts while referencing different formats (e.g., PDF contracts and slide presentations) often required a high level of expertise. Furthermore, there was a risk of overlooking important contract clauses and the risk of human error. This made it difficult to draft contracts efficiently and accurately.

[0928] 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.

[0929] In this invention, the server includes means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for generating a draft memorandum of understanding contract by integrating the extracted text information, means for previewing the generated draft to a user, means for identifying important contract clauses in the existing contract through text analysis, means for associating the information extracted from the slide presentation with the contract clauses, and means for arranging the contract clauses based on a specified contract template. This automates the contract creation process and enables efficient and accurate generation of memorandum of understanding contracts.

[0930] An "existing contract" is a document that describes the contents of a contract that has already been created, and is generally provided in PDF or Word format.

[0931] A "slide presentation" is a document for conveying information that consists of multiple slides and places emphasis on visuals.

[0932] "Means of text extraction" refers to technologies and methods for extracting textual information from digital documents, including analysis using OCR technology and APIs.

[0933] A "draft memorandum of understanding agreement" is a template or draft of the final agreement, the contents of which will later be reviewed and revised to become the final version.

[0934] "Means for displaying a preview" refers to a function or technology that allows a user to visually check a draft or document before editing.

[0935] "Text analysis" is a technology that uses natural language processing technology to analyze text within a document and extract and organize specific information.

[0936] "Contractual clauses" are specific conditions and provisions set forth in a contract, and are an important part of the contract that contains the requirements necessary for the performance of the contract.

[0937] A "template" is a model that predetermines the structure and format of a document or data, and provides a standardized format.

[0938] "Online Editor" means software or an application for creating and editing documents over the Internet.

[0939] The "final version" is the completed document that the user has checked and corrected and that is finally output.

[0940] The present invention relates to a system for automatically generating a draft memorandum of understanding (MOU) from an existing contract and a slide presentation. The system operates through the interaction of a server, a terminal, and a user, and includes the following components:

[0941] Importing Data

[0942] First, users upload an existing contract from their device to the server. The contract is provided in PDF or Word format. Using the web interface, users click the "Select File" button to upload the contract file.

[0943] Next, the user accesses the server and logs in to their Google account. After successfully logging in, the user selects and imports a presentation from Google Slides.

[0944] Data analysis

[0945] The server analyzes the received existing contract using OCR technology (for example, Google Cloud Vision API) and extracts the text within the contract. If the contract is in Word format, the server analyzes the text directly. The server also uses Google Slides API to extract the text of each slide from a slide presentation. This allows the main points of the proposal to be obtained.

[0946] Data Integration and Configuration

[0947] The server first identifies key contract clauses, such as "contract term" and "payment terms," ​​from text extracted from existing contracts using natural language processing (NLP). The server then associates the content from the presentation with the contract clauses. This association is based on a predefined contract template. The server then arranges the integrated data in an orderly fashion and generates a draft structure for the MOU.

[0948] Generate and preview a draft

[0949] The server automatically generates a draft MOU based on the data integration results. The draft is then checked for consistency, completeness, and inclusion of all required contract clauses. The server then displays a preview of the draft to the user, who can then review the draft and make initial revisions using an online editor.

[0950] User verification and correction

[0951] The user checks the previewed draft and makes any necessary corrections using the online editor. The server saves the user's edits and updates the draft of the MOU.

[0952] Final output

[0953] Once the user is satisfied with the draft, they request the final output, and the server generates the final MOU in PDF or Word format and provides the user with a download link.

[0954] Specific examples

[0955] For example, consider the case where a user uploads ContractA.pdf and imports ProposalB from Google Slides. The server extracts the "Contract Period" information from ContractA and the "Payment Terms" from ProposalB. The server combines this information and generates a draft based on a template. The user checks the content in a preview, makes any necessary corrections, and then requests the output of the final version. Finally, the server provides the final PDF.

[0956] Prompt example

[0957] Examples of prompts that use generative AI models include:

[0958] "Please describe a program that extracts key contract clauses from existing contracts and Google Slides proposals and automatically creates a draft integrated memorandum of understanding."

[0959] This system will significantly streamline the contract creation process, reducing errors and shortening work time.

[0960] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0961] Step 1:

[0962] The user uploads an existing contract from the terminal to the server. The user clicks the "Select File" button in the web interface, selects the contract (e.g., ContractA.pdf), and uploads it. The input is the existing contract file, and the output is the contract file saved on the server.

[0963] Step 2:

[0964] A user accesses the server and logs in to their Google account. After logging in, the user selects a Google Slides presentation (e.g., Proposal B) and imports it. The input is the Google account information and the Google Slides link, and the output is a presentation file saved on the server.

[0965] Step 3:

[0966] The server analyzes the uploaded existing contract using OCR technology (e.g., Google Cloud Vision API) and extracts the text. OCR is used for PDF format, and text is analyzed directly for Word format. The input is the existing contract file, and the output is the extracted text data.

[0967] Step 4:

[0968] The server uses the Google Slides API to extract the text of each slide from a slide presentation. The input is the Google Slides data, and the output is the extracted text data of the slide.

[0969] Step 5:

[0970] The server identifies important contract terms (e.g., "contract term," "payment terms," ​​etc.) from the extracted text data using natural language processing (NLP) techniques (e.g., spaCy and BERT). The input is the extracted text data, and the output is a list of important contract terms.

[0971] Step 6:

[0972] The server associates the text content obtained from the presentation with the contract terms. It matches the contract terms with the key points in the presentation that are highly relevant. The input is a list of contract terms and the text data of the presentation, and the output is the integrated data.

[0973] Step 7:

[0974] The server arranges the integrated data in order based on a specified contract template and generates a draft, where the input is the integrated data and the contract template, and the output is a draft memorandum of understanding contract.

[0975] Step 8:

[0976] The server then previews the generated draft to the user. The preview is done on a web interface. The input is the draft MOU and the output is the previewed draft.

[0977] Step 9:

[0978] The user checks the previewed draft and makes any necessary corrections using the online editor. The user edits the draft content and saves it. The input is the previewed draft and the user's corrections, and the output is the corrected draft.

[0979] Step 10:

[0980] The server saves the user's edits and updates the final draft of the MOU. The input is the user-modified draft and the output is the final draft.

[0981] Step 11:

[0982] When the user is satisfied with the draft, he or she requests the final output by clicking the "Generate Final" button. The input is the revised draft and the request for the final output, and the output is a notification of the request to the server.

[0983] Step 12:

[0984] The server generates the final MOU agreement in PDF or Word format and provides a download link to the user. The input is the final revised draft, and the output is the generated PDF or Word agreement and a download link.

[0985] (Application example 1)

[0986] 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."

[0987] With the conventional contract drafting method, it was difficult for store staff to provide customers with a draft of the contract quickly and accurately, resulting in problems such as reduced work efficiency and errors.In addition, there was a lack of a way for staff to confirm and revise the contents of the contract in real time while interacting with the customer, making it difficult to improve the quality of customer service.

[0988] 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.

[0989] In this invention, the server includes means for uploading existing documents, means for importing presentation materials, means for extracting character data from the existing documents and the presentation materials, means for previewing the generated draft to the user on a display device, and means for using a wearable device as the display device, thereby enabling store staff to generate, check, and revise draft contracts in real time while interacting with customers, and to quickly provide the final version.

[0990] "Existing Document" refers to a previously created contract or document that is being uploaded.

[0991] An "uploading means" is a method for submitting an existing document to the system.

[0992] "Presentation materials" refers to presentation documents that present information or content in the form of slides.

[0993] "Means of importing" refers to a method for importing data from outside into the system.

[0994] "Character data" refers to character information such as alphabets and kanji characters extracted from documents and presentations.

[0995] "Means of extraction" refers to a method for extracting the necessary information from the data.

[0996] "Draft" refers to a draft of the Agreement before it is finalized.

[0997] "Means of generation" refers to the method for creating new documents or information based on data.

[0998] The "means for displaying a preview" is a method for displaying the generated draft so that the user can check it.

[0999] A "display device" is a device that visually presents information.

[1000] "Wearable device" refers to a hardware device that is worn by a user.

[1001] An "online editing tool" is a method for editing documents over the Internet.

[1002] The "final version" is the version that has been edited and is output as an official document.

[1003] "Character recognition technology" refers to the technology that recognizes character information from images, etc., and converts it into digital text.

[1004] "Application programming interface means" refers to a program interface for linking with other software or services.

[1005] The present invention relates to a system for automatically generating a draft document using an existing document and presentation materials, which operates through the interaction of a server, a terminal, a display device, and a user.

[1006] 1. System Configuration

[1007] The system mainly includes the following elements:

[1008] server

[1009] Terminal

[1010] display device

[1011] User

[1012] server

[1013] The server has the following functions:

[1014] A means for uploading existing documents: Allows users to upload existing documents from their terminals to the server.

[1015] A way to import presentations: Allow users to import presentations from Google Slides or other formats.

[1016] Methods for extracting character data: Extract text from existing documents using OCR technology. Also extract text from presentation materials using API.

[1017] A method for generating a draft: Character data extracted from existing documents and presentation materials is integrated to generate a draft of the document.

[1018] Means for preview display: The generated draft is previewed to the user so that the user can visually check it through a wearable device (e.g., smart glasses).

[1019] Terminal

[1020] A terminal is a device that users use to upload existing documents or presentation materials, preview drafts, and edit them. Terminals can be PCs or smartphones.

[1021] display device

[1022] Wearable devices such as smart glasses are used as display devices, allowing staff to check and amend contracts in real time while interacting with customers.

[1023] User

[1024] Users are store staff and document creators. They use their terminals to upload existing documents and presentation materials, preview the generated drafts, edit them, and output the final version.

[1025] Specific system behavior

[1026] The server analyzes existing documents using OCR technology and presentation materials using API means. It then integrates the analyzed text data and automatically generates draft documents such as contracts and product information sheets. The generated draft is previewed to the user via a wearable device such as smart glasses. The user can then use online editing tools to check the draft and make any necessary corrections. The final document is output in PDF or Word format.

[1027] Hardware and software used

[1028] Hardware: Smart glasses (e.g., Google Glass)

[1029] Software: Python, Tesseract OCR, Google Slides API, python-docx

[1030] Specific examples

[1031] For example, when signing up for a new credit card in-store, the smart glasses can take a photo of the existing contract and load it into a promotional document in Google Slides format. Based on this information, a draft contract can be automatically generated and the customer can review and make amendments. Once the amendments are complete, the final contract can be exported and provided on the spot.

[1032] Prompt Sentence Examples

[1033] "Just take a photo of the contract with the smart glasses. Then enter the Google Slides presentation ID. The system will automatically generate a draft contract."

[1034] Such a system can reduce the workload of staff and provide fast and accurate service to customers.

[1035] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1036] Step 1: Upload an existing document

[1037] A user uses a terminal to upload an existing document to a server.

[1038] Input: Existing document (PDF or Word format)

[1039] Output: Existing documents stored on the server

[1040] Specific operation: The user operates the terminal interface to select an existing document and click the upload button. The server saves the uploaded file in the specified folder.

[1041] Step 2: Import your presentation

[1042] A user uses a terminal to import presentation materials into the server.

[1043] Input: Presentation materials (Google Slides format slide ID)

[1044] Output: Presentation data saved on the server

[1045] Specific operation: The user logs in to their Google account and enters the slide ID to import. The server retrieves and saves the presentation data from the specified slide ID using the Google Slides API.

[1046] Step 3: Extracting character data

[1047] The server extracts character data from existing documents and presentation materials.

[1048] Input: Existing documents, presentation materials

[1049] Output: Extracted character data

[1050] Specific operation: The server uses OCR technology to extract text from existing documents, and uses the Google Slides API to extract text from slides in presentation materials.

[1051] Step 4: Generate a draft

[1052] The server integrates the extracted character data to generate a draft document.

[1053] Input: Extracted character data

[1054] Output: Draft document

[1055] Specific operation: The server places the extracted text data in the appropriate location based on the existing contract template and integrates it. A draft document is generated based on the integrated data.

[1056] Step 5: Preview your draft

[1057] The server displays a preview of the generated draft to the user.

[1058] Input: Document draft

[1059] Output: Draft displayed in preview screen

[1060] Specific operation: The server renders the generated draft in HTML format and displays it on the user's device or smart glasses display.

[1061] Step 6: User Editing

[1062] The user edits the draft using online editing means.

[1063] Input: Document draft

[1064] Output: Edited draft

[1065] Specific operation: The user edits by tapping or clicking on the designated part on the preview screen. The server reflects and saves the user's edits in real time.

[1066] Step 7: Output the final version

[1067] The server outputs the edited draft as the final version.

[1068] Input: Edited draft

[1069] Output: Final document in PDF or Word format

[1070] Specific behavior: The server converts the edited draft into PDF or Word format and provides the user with a download link.

[1071] These processing steps enable the system to efficiently perform everything from automatic generation of contracts to previewing, editing, and outputting the final version.

[1072] 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.

[1073] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user.

[1074] 1. Importing data

[1075] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[1076] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[1077] 2. Data Analysis

[1078] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[1079] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[1080] 3. Data integration

[1081] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extract the contents of the contract as text data.

[1082] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1083] Server: Analyzes and correlates key contract terms (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[1084] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[1085] 4. Generate and preview the draft

[1086] Server: Using the emotion engine, the server generates a draft memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server adjusts the wording and layout accordingly, taking into account the emotional information determined by the emotion engine.

[1087] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[1088] 5. User confirmation and correction

[1089] User: Check the preview of the draft and use the online editor to revise it if necessary. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions.

[1090] Server: Saves the user's modifications and updates the final draft, taking into account the emotion engine data.

[1091] 6. Final output

[1092] User: Once they are happy with the draft, they request a final output.

[1093] Server: Generates the final MOU in PDF or Word format, reflecting the user's modifications and emotional data, and provides a download link to the user.

[1094] Specific examples

[1095] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in Google Slides format. Import these files and extract information about the "contract period" from ContractA. Next, obtain important information such as "payment terms" from ProposalB.

[1096] As the user reviews the contract on the preview screen, the emotion engine detects feelings of anxiety or doubt from the user's facial expressions and voice. Based on this emotion data, the server automatically changes the relevant part of the contract to more specific and clear wording and presents it to the user again. In this way, the content of the document is dynamically adjusted according to the user's emotions, providing an environment in which the user can review and revise the contract with confidence.

[1097] This system will not only significantly streamline the contract creation process and enable the rapid creation of accurate and professional documents, but will also provide a more satisfying user experience by taking user emotions into consideration. Utilizing emotion data is also expected to prevent important oversights.

[1098] The processing flow will be explained below.

[1099] Step 1:

[1100] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[1101] Step 2:

[1102] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[1103] Step 3:

[1104] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[1105] Step 4:

[1106] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[1107] Step 5:

[1108] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word), and extract the contents of the contract as text data.

[1109] Step 6:

[1110] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1111] Step 7:

[1112] Server: Analyzes and associates key contract clauses (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[1113] Step 8:

[1114] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[1115] Step 9:

[1116] Server: Prepares the emotion engine and makes it possible to analyze the user's emotions in real time. This emotion engine reads the user's emotions through facial expressions and voice.

[1117] Step 10:

[1118] Server: A preview interface is generated and displayed to allow the user to preview the generated draft of the memorandum of understanding agreement.

[1119] Step 11:

[1120] User: When reviewing a previewed draft, the emotion engine analyzes the user's emotional state (e.g., anxiety, doubt, satisfaction) in real time.

[1121] Step 12:

[1122] Server: Automatically adjusts the content or presentation of the contract as needed based on real-time sentiment data. For example, if the user is concerned about a particular clause, the document can be revised to explain that clause more clearly.

[1123] Step 13:

[1124] User: Improves the preview draft in the online editor while receiving feedback from the emotion engine.

[1125] Step 14:

[1126] Server: Updates the draft that the user has finalized with the final version of the memorandum of understanding, taking into account the emotional data.

[1127] Step 15:

[1128] User: Once satisfied with the draft, request a final output.

[1129] Step 16:

[1130] Server: Generates the final version of the memorandum contract in PDF or Word format, reflecting the user's modifications and emotional data, and provides the user with a download link.

[1131] Step 17:

[1132] User: Download the final MOU from the download link provided.

[1133] Example 2

[1134] 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."

[1135] In the conventional contract creation process, users had to individually review and edit the existing contract and the slide presentation, which required a huge amount of time and effort. Furthermore, if users had concerns or doubts about the content of the contract, there was a lack of a way to adjust the document while taking those concerns into account. This situation led to reduced efficiency in contract creation and user dissatisfaction.

[1136] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for incorporating suggestions and warnings based on the user's emotions into the draft using an emotion engine, and means for displaying a preview of the generated draft to the user. This enables quick and efficient creation of a contract that takes into account the user's anxieties and doubts.

[1137] "Existing contracts" are contract documents that have already been created and stored and are uploaded to the system in PDF or Word format.

[1138] A "slide presentation" is a presentation document consisting of a series of slides, primarily used in business and educational settings, that is imported from a user's Google account.

[1139] "Means for extracting text" refers to a method for extracting written data from contracts or presentations and converting it into text data for analysis.

[1140] The "means for integrating and generating a draft memorandum of understanding agreement" is a method for automatically generating an initial draft of an agreement by integrating multiple pieces of text information in a consistent manner.

[1141] An "emotion engine" is a technology that analyzes a user's facial expressions and voice, detects their emotional state, and reflects it in the content of a document.

[1142] The "means for displaying a preview" refers to a technique or method for displaying the generated draft on a screen so that the user can check it.

[1143] "Online editor means" refers to a tool or function that allows a user to edit text or document content in real time through an interface such as a browser.

[1144] "OCR technology" is an optical character recognition technology that reads characters from image data and analyzes them as text data.

[1145] "API technology" is an application program interface technology that is an interface that allows different software systems to exchange information with each other.

[1146] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user.

[1147] Importing Data

[1148] The user selects an existing contract (PDF or Word file) from their device and sends it to the server through the system's upload form. Next, the user logs in to their account on a browser, selects a slide presentation, and clicks the import button.

[1149] Data analysis

[1150] The server receives the uploaded existing contract file (PDF or Word) and stores it for analysis. Then, the server obtains access rights to the user's slides through the user's account authentication and downloads the specified presentation data using API technology.

[1151] Data integration

[1152] The server analyzes the existing contract file using OCR technology (for PDF) or direct text extraction (for Word) to extract the contract contents as text data. Next, the server uses API technology to extract text data from each slide of the imported slide presentation. The server then associates the key contract clauses (e.g., contract term, payment terms) extracted from the existing contract with key information from the slide presentation. Finally, the server integrates the extracted data based on a standard contract template to automatically generate a consistent and logical draft memorandum of understanding agreement.

[1153] Generate and preview a draft

[1154] The server uses an emotion engine to generate a draft of the memorandum contract that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server takes into account the emotional information determined by the emotion engine and adjusts the wording and layout accordingly. The generated draft is displayed as a preview to the user.

[1155] User verification and correction

[1156] The user checks the previewed draft and, if necessary, edits it using the online editor. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions. The server saves the user's edits and updates the final draft, incorporating the emotional data.

[1157] Final output

[1158] When the user is satisfied with the draft, they request the output of the final version. The server generates the final version of the MOU in PDF or Word format, reflecting the user's revisions and emotional data, and provides the user with a download link.

[1159] Specific examples

[1160] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in slide format. These files are imported, and information on the "contract period" is extracted from ContractA. Next, important points such as "payment terms" are obtained from ProposalB. As the user reviews the contents of the contract on the preview screen, the emotion engine detects feelings of anxiety or doubt from the user's facial expressions and voice. Based on the emotion data, the server automatically changes the relevant part of the contract to more specific and clear wording and presents it to the user again. In this way, the content of the document is dynamically adjusted according to the user's emotions, providing an environment in which the user can review and modify the contract with confidence.

[1161] This system will not only significantly streamline the contract creation process and enable the rapid creation of accurate and professional documents, but will also provide a more satisfying user experience by taking user emotions into consideration. Utilizing emotion data is also expected to prevent important oversights.

[1162] Example prompts for generative AI models

[1163] An example of a prompt is as follows:

[1164] "Please extract the contract period from the newly uploaded contract file (Contract A.pdf) and the payment terms from the sales proposal slide (Proposal B). Integrate them and generate a draft memorandum of understanding for the user to confirm. Please also reflect the user's sentiment data in real time."

[1165] This system streamlines the complex contract creation process and enables safe and secure document creation that takes users' feelings into consideration.

[1166] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1167] Step 1:

[1168] The user selects an existing contract (PDF or Word file) from their device and sends it to the server through the system's upload form. The input is the existing contract file selected by the user, and the output is that file saved on the server. Specifically, the user opens the system interface, clicks the "Select File" button, and selects and uploads the file from their local device.

[1169] Step 2:

[1170] A user logs in to their account on a browser, selects a slide presentation, and clicks the Import button. The input is the user's login information and the slide file, and the output is the slide file being imported to the server. Specifically, the user clicks the "Log in to Google Account" button, enters the required authentication information, and logs in. Then, the user selects the slide presentation and clicks the "Import" button.

[1171] Step 3:

[1172] The server receives the uploaded existing contract file and temporarily stores it for analysis. The input is the contract file uploaded by the user, and the output is that file stored in a directory for analysis. Specifically, the server detects when the file upload is complete and moves it to a specified directory.

[1173] Step 4:

[1174] The server obtains access to the slides through the user's account authentication and downloads the specified presentation data using API technology. The input is the user's authentication information and the slide presentation ID, and the output is the presentation data stored on the server. Specifically, the server authenticates the user using Google's OAuth and downloads the slide data via the Google Slides API.

[1175] Step 5:

[1176] The server analyzes the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data. The input is the existing contract file and the output is the contract's text data. Specifically, the server starts the OCR engine and performs text extraction on the PDF file. In the case of a Word file, the text data is read directly.

[1177] Step 6:

[1178] The server uses API technology to extract text data from each slide of the imported slide presentation. The input is the slide presentation data, and the output is the slide's text data. Specifically, the server uses the Google Slides API to extract the text content of each slide in order.

[1179] Step 7:

[1180] The server analyzes and correlates important contract terms (e.g., contract period, payment terms) extracted from existing contracts with key information from slide presentations. The input is the text data of the contract and the text data of the slides, and the output is an analysis result that correlates both sets of data. Specifically, the server uses natural language processing technology to analyze the text data and identify and match important keywords and phrases.

[1181] Step 8:

[1182] The server integrates the extracted data based on a standard contract template and automatically generates a consistent and logical draft memorandum of understanding contract. The input is the associated analysis results, and the output is a draft memorandum of understanding contract. Specifically, the server generates a draft based on a preset contract template, embedding important items.

[1183] Step 9:

[1184] The server uses the emotion engine to generate a draft memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. The input is the draft MOU and the user's emotion data, and the output is the finalized draft. Specifically, the server runs the emotion engine and adjusts the document according to the user's emotions.

[1185] Step 10:

[1186] The server previews the generated draft to the user. The input is the finalized draft, and the output is a preview screen displayed on the user's browser. Specifically, the server generates a preview interface and displays the draft to the user.

[1187] Step 11:

[1188] The user checks the previewed draft and, if necessary, edits it using the online editor. The input is the preview screen and the user's edits, and the output is the edited draft. Specifically, the user operates the online editor to edit the text and clicks the save button.

[1189] Step 12:

[1190] The server analyzes the user's emotional changes in real time and displays suggestions or warnings based on the user's emotions. The input is real-time emotional data, and the output is suggestions or warning messages. Specifically, the server continuously operates the emotion engine and provides the user with feedback based on their emotions.

[1191] Step 13:

[1192] The server saves the user's modifications and updates the final draft, which also reflects the emotion data. The input is the modified draft and the emotion data, and the output is the final draft. Specifically, the server generates and saves the final version of the memorandum of understanding that reflects the new information.

[1193] Step 14:

[1194] When the user is satisfied with the draft, they request output of the final version. The input is a preview screen containing the final draft, and the output is the output request. The specific action is that the user clicks the "Output Final Version" button.

[1195] Step 15:

[1196] The server generates a final version of the memorandum of understanding agreement in PDF or Word format that reflects the user's revisions and emotion data, and provides the user with a download link. The input is the final draft and the selection of the output format, and the output is the generation of a download link. Specifically, the server saves the generated document in the specified format and sends the link to the user.

[1197] (Application example 2)

[1198] 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."

[1199] Conventional contract creation systems, when combining existing contracts and presentation materials to generate memorandums of understanding, are unable to consider the user's feelings, potentially overlooking areas that may cause anxiety or doubt. Furthermore, if the created contract is difficult for users to understand, the risk of future problems increases. Furthermore, when reviewing contracts in transportation and traffic management, the limited working environment makes it difficult to properly review and revise the contents of the contract on the spot.

[1200] 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 uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for collecting user emotion data using an in-vehicle camera or microphone, means for automatically adjusting the content of the generated draft based on the collected emotion data, and means for displaying a preview of the generated draft to the user. This makes it possible to dynamically adjust the contract document taking emotion data into consideration when the user checks the content of the contract, providing an environment in which the user can check and modify the contract with peace of mind.

[1201] An "existing contract" is a contract that the user has created or received in the past, and is a document whose contents are used as the basis for a new contract to be created.

[1202] A "slide presentation" is a document created in the form of a slide show to provide information visually, and is particularly used in business negotiations and meetings.

[1203] "Text extraction means" means a technique or method for extracting digital text from an uploaded file.

[1204] The "means for integrating and generating a draft memorandum of understanding agreement" is a technique or method for combining the extracted text information with other related information to automatically generate a draft of a new agreement.

[1205] "Means for collecting user emotional data using an in-vehicle camera or microphone" refers to a device or method for obtaining the user's emotional state from their facial expressions and voice using a camera or microphone installed in the vehicle.

[1206] "Means for automatically adjusting the content of a draft generated based on collected emotional data" refers to a technique or method for automatically changing the content or structure of a document depending on the emotional state of the user.

[1207] The "preview display means" refers to a technique or method for visually displaying the generated draft so that the user can make final confirmation or corrections.

[1208] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user. Specific embodiments for carrying out the present invention are described below.

[1209] 1. Importing data

[1210] Terminal: The user selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[1211] On the device: The user logs into their Google account on a browser, selects a slide presentation, and clicks the import button to send it to the server.

[1212] 2. Data Analysis

[1213] Server: The server receives the uploaded existing contract file (PDF or Word) and stores it for analysis.

[1214] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[1215] 3. Data integration

[1216] Server: The server analyzes the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data.

[1217] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1218] Server: Analyzes and correlates key contract clauses extracted from existing contracts with key information from slide presentations.

[1219] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[1220] 4. Generate and preview the draft

[1221] Server: Using the emotion engine, the server generates a draft of the memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server adjusts the wording and layout accordingly, taking into account the emotional information determined by the emotion engine.

[1222] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[1223] 5. User confirmation and correction

[1224] On the device: The user previews the draft and edits it using the online editor. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions.

[1225] Server: Saves the user's modifications and updates the final draft, taking into account the emotion engine data.

[1226] 6. Final output

[1227] Terminal: When the user is satisfied with the draft, he or she requests a final output.

[1228] Server: Generates the final MOU in PDF or Word format, reflecting the user's modifications and emotional data, and provides a download link to the user.

[1229] The main technologies used in the above process include PyMuPDF (Fitz), Google Slides API, OpenCV, and a proprietary emotion recognition library. For example, if anxiety or anger is detected from the user's facial expression or voice while they are reviewing the contents of a contract, the wording in that section will be automatically changed to more specific and clearer language. This provides an environment where users can review and revise contracts with peace of mind.

[1230] Example prompt sentence:

[1231] When managing contracts for operating autonomous vehicles, please conduct image analysis to check whether the contract holder is showing any emotion such as anxiety or anger while reviewing the contract.

[1232] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1233] Step 1:

[1234] On the terminal: The user selects an existing contract (PDF or Word file) and sends it to the server through the system's upload form. The uploaded file is saved on the server.

[1235] Input: Existing contract (PDF or Word file)

[1236] Output: Agreement file saved on the server

[1237] Step 2:

[1238] On the device: The user logs in to their Google account on a browser, selects a slide presentation, and clicks the import button. The presentation data is sent to the server using the Google Slides API.

[1239] Input: Slide presentation

[1240] Output: Presentation data saved on the server

[1241] Step 3:

[1242] Server: The server analyzes the uploaded existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data.

[1243] Input: Agreement file stored on the server

[1244] Output: Extracted text data

[1245] Step 4:

[1246] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1247] Input: Presentation data stored on the server

[1248] Output: Extracted slide text data

[1249] Step 5:

[1250] Server: Integrates text data extracted from existing contracts and slide presentations, and automatically generates consistent and logical draft memorandum agreements based on standard contract templates.

[1251] Input: Extracted contract text data, slide text data

[1252] Output: Generated draft MOU agreement

[1253] Step 6:

[1254] Server: Collects user emotion data using in-car cameras or microphones, using facial recognition technology and voice emotion analysis technology.

[1255] Input: User's facial expression data, voice data

[1256] Output: Emotion data

[1257] Step 7:

[1258] Server: Automatically adjusts the content of the generated draft based on the collected sentiment data, specifically by changing the part where the user expresses anxiety or doubt to a clearer, more specific statement.

[1259] Input: Generated draft memorandum of understanding, sentiment data

[1260] Output: Draft of the adjusted MOU agreement

[1261] Step 8:

[1262] Terminal: Generates a preview interface and visually displays the adjusted draft to the user, who can then confirm the contents of the draft.

[1263] Input: Draft of adjusted MOU agreement

[1264] Output: Previewed draft

[1265] Step 9:

[1266] On the device: The user sees a preview of the draft and can edit it using the online editor.

[1267] Input: Previewed draft

[1268] Output: Draft revised by user

[1269] Step 10:

[1270] Server: Saves the user's modifications and updates the final draft taking into account the sentiment data.

[1271] Input: User-edited draft, emotion data

[1272] Output: Final draft

[1273] Step 11:

[1274] Terminal: The user requests the final output, and the server generates the final MOU in PDF or Word format and provides a download link to the user.

[1275] Input: Final Draft

[1276] Output: Final MOU (PDF or Word format) and download link

[1277] 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.

[1278] 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.

[1279] 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.

[1280] [Fourth embodiment]

[1281] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1282] 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.

[1283] 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).

[1284] 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.

[1285] 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.

[1286] 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).

[1287] 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.

[1288] 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.

[1289] 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.

[1290] 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.

[1291] 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.

[1292] 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.

[1293] 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."

[1294] The present invention relates to a system for automatically generating a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation. This system operates through the interaction of a server, a terminal, and a user.

[1295] 1. Importing data

[1296] User: Upload an existing contract from their device. In this case, the contract will be provided in PDF or Word format.

[1297] User: Access the server and log in to their Google account. After logging in, select a Google Slides presentation and import it.

[1298] 2. Data Analysis

[1299] Server: After receiving an existing contract, it uses OCR technology to extract the text from the contract, or if it is in Word format, it analyzes the text directly.

[1300] Server: Extract text content from each slide of the slide presentation using the Google Slides API, thereby obtaining the main points of the proposal.

[1301] 3. Data integration and organization

[1302] Server: Identify key contract clauses extracted from existing contracts (e.g., "contract term" and "payment terms") and correlate them with content from slide presentations.

[1303] Server: Based on a standard contract template, this data is arranged in an orderly manner to generate a consistent structure for the memorandum contract.

[1304] 4. Generate a draft

[1305] Server: Automatically generate draft MOUs based on the data integration results, ensuring that the drafts are consistent and include all required contract clauses.

[1306] Server: Previews the generated draft to the user, allowing the user to check the draft and make initial revisions.

[1307] 5. User confirmation and correction

[1308] User: Check the preview of the draft and make any necessary revisions using the online editor.

[1309] Server: Saves the user's edits and updates the final draft of the MOU.

[1310] 6. Final output

[1311] User: Once they are happy with the draft, they request a final output.

[1312] Server: Generates the final MOU in PDF or Word format and provides the user with a download link.

[1313] Specific examples

[1314] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in Google Slides format. Import these files and extract information about the "contract period" from ContractA. Next, obtain important information such as "payment terms" from ProposalB.

[1315] The server integrates this information into an existing contract template to generate a draft memorandum of understanding (MOU), at which point it provides a preview to the user, who can then confirm and modify the content to create the final MOU.

[1316] The present invention significantly streamlines the contract creation process, reducing errors and shortening work time. By using this system, the effort required for contract creation is reduced and professional documents can be generated quickly.

[1317] The processing flow will be explained below.

[1318] Step 1:

[1319] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[1320] Step 2:

[1321] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[1322] Step 3:

[1323] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[1324] Step 4:

[1325] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[1326] Step 5:

[1327] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extract the contents of the contract as text data.

[1328] Step 6:

[1329] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1330] Step 7:

[1331] Server: Analyzes and correlates key contract terms (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[1332] Step 8:

[1333] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[1334] Step 9:

[1335] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[1336] Step 10:

[1337] User: Check the preview of the draft and, if necessary, make corrections using the online editor.

[1338] Step 11:

[1339] User: Review the revised draft and request the final version to be generated.

[1340] Step 12:

[1341] Server: Generates the final version of the MOU in PDF or Word format, reflecting the user's modifications, and provides the user with a download link.

[1342] Step 13:

[1343] Users: Download the final MOU from the download link provided.

[1344] Example 1

[1345] 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."

[1346] The traditional contract drafting process was time-consuming and labor-intensive, involving numerous manual tasks. Creating consistent contracts while referencing different formats (e.g., PDF contracts and slide presentations) often required a high level of expertise. Furthermore, there was a risk of overlooking important contract clauses and the risk of human error. This made it difficult to draft contracts efficiently and accurately.

[1347] 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.

[1348] In this invention, the server includes means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for generating a draft memorandum of understanding contract by integrating the extracted text information, means for previewing the generated draft to a user, means for identifying important contract clauses in the existing contract through text analysis, means for associating the information extracted from the slide presentation with the contract clauses, and means for arranging the contract clauses based on a specified contract template. This automates the contract creation process and enables efficient and accurate generation of memorandum of understanding contracts.

[1349] An "existing contract" is a document that describes the contents of a contract that has already been created, and is generally provided in PDF or Word format.

[1350] A "slide presentation" is a document for conveying information that consists of multiple slides and places emphasis on visuals.

[1351] "Means of text extraction" refers to technologies and methods for extracting textual information from digital documents, including analysis using OCR technology and APIs.

[1352] A "draft memorandum of understanding agreement" is a template or draft of the final agreement, the contents of which will later be reviewed and revised to become the final version.

[1353] "Means for displaying a preview" refers to a function or technology that allows a user to visually check a draft or document before editing.

[1354] "Text analysis" is a technology that uses natural language processing technology to analyze text within a document and extract and organize specific information.

[1355] "Contractual clauses" are specific conditions and provisions set forth in a contract, and are an important part of the contract that contains the requirements necessary for the performance of the contract.

[1356] A "template" is a model that predetermines the structure and format of a document or data, and provides a standardized format.

[1357] "Online Editor" means software or an application for creating and editing documents over the Internet.

[1358] The "final version" is the completed document that the user has checked and corrected and that is finally output.

[1359] The present invention relates to a system for automatically generating a draft memorandum of understanding (MOU) from an existing contract and a slide presentation. The system operates through the interaction of a server, a terminal, and a user, and includes the following components:

[1360] Importing Data

[1361] First, users upload an existing contract from their device to the server. The contract is provided in PDF or Word format. Using the web interface, users click the "Select File" button to upload the contract file.

[1362] Next, the user accesses the server and logs in to their Google account. After successfully logging in, the user selects and imports a presentation from Google Slides.

[1363] Data analysis

[1364] The server analyzes the received existing contract using OCR technology (for example, Google Cloud Vision API) and extracts the text within the contract. If the contract is in Word format, the server analyzes the text directly. The server also uses Google Slides API to extract the text of each slide from a slide presentation. This allows the main points of the proposal to be obtained.

[1365] Data Integration and Configuration

[1366] The server first identifies key contract clauses, such as "contract term" and "payment terms," ​​from text extracted from existing contracts using natural language processing (NLP). The server then associates the content from the presentation with the contract clauses. This association is based on a predefined contract template. The server then arranges the integrated data in an orderly fashion and generates a draft structure for the MOU.

[1367] Generate and preview a draft

[1368] The server automatically generates a draft MOU based on the data integration results. The draft is then checked for consistency, completeness, and inclusion of all required contract clauses. The server then displays a preview of the draft to the user, who can then review the draft and make initial revisions using an online editor.

[1369] User verification and correction

[1370] The user checks the previewed draft and makes any necessary corrections using the online editor. The server saves the user's edits and updates the draft of the MOU.

[1371] Final output

[1372] Once the user is satisfied with the draft, they request the final output, and the server generates the final MOU in PDF or Word format and provides the user with a download link.

[1373] Specific examples

[1374] For example, consider the case where a user uploads ContractA.pdf and imports ProposalB from Google Slides. The server extracts the "Contract Period" information from ContractA and the "Payment Terms" from ProposalB. The server combines this information and generates a draft based on a template. The user checks the content in a preview, makes any necessary corrections, and then requests the output of the final version. Finally, the server provides the final PDF.

[1375] Prompt example

[1376] Examples of prompts that use generative AI models include:

[1377] "Please describe a program that extracts key contract clauses from existing contracts and Google Slides proposals and automatically creates a draft integrated memorandum of understanding."

[1378] This system will significantly streamline the contract creation process, reducing errors and shortening work time.

[1379] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1380] Step 1:

[1381] The user uploads an existing contract from the terminal to the server. The user clicks the "Select File" button in the web interface, selects the contract (e.g., ContractA.pdf), and uploads it. The input is the existing contract file, and the output is the contract file saved on the server.

[1382] Step 2:

[1383] A user accesses the server and logs in to their Google account. After logging in, the user selects a Google Slides presentation (e.g., Proposal B) and imports it. The input is the Google account information and the Google Slides link, and the output is a presentation file saved on the server.

[1384] Step 3:

[1385] The server analyzes the uploaded existing contract using OCR technology (e.g., Google Cloud Vision API) and extracts the text. OCR is used for PDF format, and text is analyzed directly for Word format. The input is the existing contract file, and the output is the extracted text data.

[1386] Step 4:

[1387] The server uses the Google Slides API to extract the text of each slide from a slide presentation. The input is the Google Slides data, and the output is the extracted text data of the slide.

[1388] Step 5:

[1389] The server identifies important contract terms (e.g., "contract term," "payment terms," ​​etc.) from the extracted text data using natural language processing (NLP) techniques (e.g., spaCy and BERT). The input is the extracted text data, and the output is a list of important contract terms.

[1390] Step 6:

[1391] The server associates the text content obtained from the presentation with the contract terms. It matches the contract terms with the key points in the presentation that are highly relevant. The input is a list of contract terms and the text data of the presentation, and the output is the integrated data.

[1392] Step 7:

[1393] The server arranges the integrated data in order based on a specified contract template and generates a draft, where the input is the integrated data and the contract template, and the output is a draft memorandum of understanding contract.

[1394] Step 8:

[1395] The server then previews the generated draft to the user. The preview is done on a web interface. The input is the draft MOU and the output is the previewed draft.

[1396] Step 9:

[1397] The user checks the previewed draft and makes any necessary corrections using the online editor. The user edits the draft content and saves it. The input is the previewed draft and the user's corrections, and the output is the corrected draft.

[1398] Step 10:

[1399] The server saves the user's edits and updates the final draft of the MOU. The input is the user-modified draft and the output is the final draft.

[1400] Step 11:

[1401] When the user is satisfied with the draft, he or she requests the final output by clicking the "Generate Final" button. The input is the revised draft and the request for the final output, and the output is a notification of the request to the server.

[1402] Step 12:

[1403] The server generates the final MOU agreement in PDF or Word format and provides a download link to the user. The input is the final revised draft, and the output is the generated PDF or Word agreement and a download link.

[1404] (Application example 1)

[1405] 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."

[1406] With the conventional contract drafting method, it was difficult for store staff to provide customers with a draft of the contract quickly and accurately, resulting in problems such as reduced work efficiency and errors.In addition, there was a lack of a way for staff to confirm and revise the contents of the contract in real time while interacting with the customer, making it difficult to improve the quality of customer service.

[1407] 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.

[1408] In this invention, the server includes means for uploading existing documents, means for importing presentation materials, means for extracting character data from the existing documents and the presentation materials, means for previewing the generated draft to the user on a display device, and means for using a wearable device as the display device, thereby enabling store staff to generate, check, and revise draft contracts in real time while interacting with customers, and to quickly provide the final version.

[1409] "Existing Document" refers to a previously created contract or document that is being uploaded.

[1410] An "uploading means" is a method for submitting an existing document to the system.

[1411] "Presentation materials" refers to presentation documents that present information or content in the form of slides.

[1412] "Means of importing" refers to a method for importing data from outside into the system.

[1413] "Character data" refers to character information such as alphabets and kanji characters extracted from documents and presentations.

[1414] "Means of extraction" refers to a method for extracting the necessary information from the data.

[1415] "Draft" refers to a draft of the Agreement before it is finalized.

[1416] "Means of generation" refers to the method for creating new documents or information based on data.

[1417] The "means for displaying a preview" is a method for displaying the generated draft so that the user can check it.

[1418] A "display device" is a device that visually presents information.

[1419] "Wearable device" refers to a hardware device that is worn by a user.

[1420] An "online editing tool" is a method for editing documents over the Internet.

[1421] The "final version" is the version that has been edited and is output as an official document.

[1422] "Character recognition technology" refers to the technology that recognizes character information from images, etc., and converts it into digital text.

[1423] "Application programming interface means" refers to a program interface for linking with other software or services.

[1424] The present invention relates to a system for automatically generating a draft document using an existing document and presentation materials, which operates through the interaction of a server, a terminal, a display device, and a user.

[1425] 1. System Configuration

[1426] The system mainly includes the following elements:

[1427] server

[1428] Terminal

[1429] display device

[1430] User

[1431] server

[1432] The server has the following functions:

[1433] A means for uploading existing documents: Allows users to upload existing documents from their terminals to the server.

[1434] A way to import presentations: Allow users to import presentations from Google Slides or other formats.

[1435] Methods for extracting character data: Extract text from existing documents using OCR technology. Also extract text from presentation materials using API.

[1436] A method for generating a draft: Character data extracted from existing documents and presentation materials is integrated to generate a draft of the document.

[1437] Means for preview display: The generated draft is previewed to the user so that the user can visually check it through a wearable device (e.g., smart glasses).

[1438] Terminal

[1439] A terminal is a device that users use to upload existing documents or presentation materials, preview drafts, and edit them. Terminals can be PCs or smartphones.

[1440] display device

[1441] Wearable devices such as smart glasses are used as display devices, allowing staff to check and amend contracts in real time while interacting with customers.

[1442] User

[1443] Users are store staff and document creators. They use their terminals to upload existing documents and presentation materials, preview the generated drafts, edit them, and output the final version.

[1444] Specific system behavior

[1445] The server analyzes existing documents using OCR technology and presentation materials using API means. It then integrates the analyzed text data and automatically generates draft documents such as contracts and product information sheets. The generated draft is previewed to the user via a wearable device such as smart glasses. The user can then use online editing tools to check the draft and make any necessary corrections. The final document is output in PDF or Word format.

[1446] Hardware and software used

[1447] Hardware: Smart glasses (e.g., Google Glass)

[1448] Software: Python, Tesseract OCR, Google Slides API, python-docx

[1449] Specific examples

[1450] For example, when signing up for a new credit card in-store, the smart glasses can take a photo of the existing contract and load it into a promotional document in Google Slides format. Based on this information, a draft contract can be automatically generated and the customer can review and make amendments. Once the amendments are complete, the final contract can be exported and provided on the spot.

[1451] Prompt Sentence Examples

[1452] "Just take a photo of the contract with the smart glasses. Then enter the Google Slides presentation ID. The system will automatically generate a draft contract."

[1453] Such a system can reduce the workload of staff and provide fast and accurate service to customers.

[1454] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1455] Step 1: Upload an existing document

[1456] A user uses a terminal to upload an existing document to a server.

[1457] Input: Existing document (PDF or Word format)

[1458] Output: Existing documents stored on the server

[1459] Specific operation: The user operates the terminal interface to select an existing document and click the upload button. The server saves the uploaded file in the specified folder.

[1460] Step 2: Import your presentation

[1461] A user uses a terminal to import presentation materials into the server.

[1462] Input: Presentation materials (Google Slides format slide ID)

[1463] Output: Presentation data saved on the server

[1464] Specific operation: The user logs in to their Google account and enters the slide ID to import. The server retrieves and saves the presentation data from the specified slide ID using the Google Slides API.

[1465] Step 3: Extracting character data

[1466] The server extracts character data from existing documents and presentation materials.

[1467] Input: Existing documents, presentation materials

[1468] Output: Extracted character data

[1469] Specific operation: The server uses OCR technology to extract text from existing documents, and uses the Google Slides API to extract text from slides in presentation materials.

[1470] Step 4: Generate a draft

[1471] The server integrates the extracted character data to generate a draft document.

[1472] Input: Extracted character data

[1473] Output: Draft document

[1474] Specific operation: The server places the extracted text data in the appropriate location based on the existing contract template and integrates it. A draft document is generated based on the integrated data.

[1475] Step 5: Preview your draft

[1476] The server displays a preview of the generated draft to the user.

[1477] Input: Document draft

[1478] Output: Draft displayed in preview screen

[1479] Specific operation: The server renders the generated draft in HTML format and displays it on the user's device or smart glasses display.

[1480] Step 6: User Editing

[1481] The user edits the draft using online editing means.

[1482] Input: Document draft

[1483] Output: Edited draft

[1484] Specific operation: The user edits by tapping or clicking on the designated part on the preview screen. The server reflects and saves the user's edits in real time.

[1485] Step 7: Output the final version

[1486] The server outputs the edited draft as the final version.

[1487] Input: Edited draft

[1488] Output: Final document in PDF or Word format

[1489] Specific behavior: The server converts the edited draft into PDF or Word format and provides the user with a download link.

[1490] These processing steps enable the system to efficiently perform everything from automatic generation of contracts to previewing, editing, and outputting the final version.

[1491] 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.

[1492] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user.

[1493] 1. Importing data

[1494] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[1495] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[1496] 2. Data Analysis

[1497] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[1498] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[1499] 3. Data integration

[1500] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extract the contents of the contract as text data.

[1501] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1502] Server: Analyzes and correlates key contract terms (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[1503] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[1504] 4. Generate and preview the draft

[1505] Server: Using the emotion engine, the server generates a draft memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server adjusts the wording and layout accordingly, taking into account the emotional information determined by the emotion engine.

[1506] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[1507] 5. User confirmation and correction

[1508] User: Check the preview of the draft and use the online editor to revise it if necessary. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions.

[1509] Server: Saves the user's modifications and updates the final draft, taking into account the emotion engine data.

[1510] 6. Final output

[1511] User: Once they are happy with the draft, they request a final output.

[1512] Server: Generates the final MOU in PDF or Word format, reflecting the user's modifications and emotional data, and provides a download link to the user.

[1513] Specific examples

[1514] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in Google Slides format. Import these files and extract information about the "contract period" from ContractA. Next, obtain important information such as "payment terms" from ProposalB.

[1515] As the user reviews the contract on the preview screen, the emotion engine detects feelings of anxiety or doubt from the user's facial expressions and voice. Based on this emotion data, the server automatically changes the relevant part of the contract to more specific and clear wording and presents it to the user again. In this way, the content of the document is dynamically adjusted according to the user's emotions, providing an environment in which the user can review and revise the contract with confidence.

[1516] This system will not only significantly streamline the contract creation process and enable the rapid creation of accurate and professional documents, but will also provide a more satisfying user experience by taking user emotions into consideration. Utilizing emotion data is also expected to prevent important oversights.

[1517] The processing flow will be explained below.

[1518] Step 1:

[1519] User: Selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[1520] Step 2:

[1521] User: Log in to their Google account in a browser, select a slide presentation, and then click the Import button.

[1522] Step 3:

[1523] Server: Receives uploaded existing contract files (PDF or Word) and stores the files for analysis.

[1524] Step 4:

[1525] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[1526] Step 5:

[1527] Server: Analyze the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word), and extract the contents of the contract as text data.

[1528] Step 6:

[1529] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1530] Step 7:

[1531] Server: Analyzes and associates key contract clauses (e.g., contract duration, payment terms) extracted from existing contracts with key information from slide presentations.

[1532] Step 8:

[1533] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[1534] Step 9:

[1535] Server: Prepares the emotion engine and makes it possible to analyze the user's emotions in real time. This emotion engine reads the user's emotions through facial expressions and voice.

[1536] Step 10:

[1537] Server: A preview interface is generated and displayed to allow the user to preview the generated draft of the memorandum of understanding agreement.

[1538] Step 11:

[1539] User: When reviewing a previewed draft, the emotion engine analyzes the user's emotional state (e.g., anxiety, doubt, satisfaction) in real time.

[1540] Step 12:

[1541] Server: Automatically adjusts the content or presentation of the contract as needed based on real-time sentiment data. For example, if the user is concerned about a particular clause, the document can be revised to explain that clause more clearly.

[1542] Step 13:

[1543] User: Improves the preview draft in the online editor while receiving feedback from the emotion engine.

[1544] Step 14:

[1545] Server: Updates the draft that the user has finalized with the final version of the memorandum of understanding, taking into account the emotional data.

[1546] Step 15:

[1547] User: Once satisfied with the draft, request a final output.

[1548] Step 16:

[1549] Server: Generates the final version of the memorandum contract in PDF or Word format, reflecting the user's modifications and emotional data, and provides the user with a download link.

[1550] Step 17:

[1551] User: Download the final MOU from the download link provided.

[1552] Example 2

[1553] 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."

[1554] In the conventional contract creation process, users had to individually review and edit the existing contract and the slide presentation, which required a huge amount of time and effort. Furthermore, if users had concerns or doubts about the content of the contract, there was a lack of a way to adjust the document while taking those concerns into account. This situation led to reduced efficiency in contract creation and user dissatisfaction.

[1555] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for incorporating suggestions and warnings based on the user's emotions into the draft using an emotion engine, and means for displaying a preview of the generated draft to the user. This enables quick and efficient creation of a contract that takes into account the user's anxieties and doubts.

[1556] "Existing contracts" are contract documents that have already been created and stored and are uploaded to the system in PDF or Word format.

[1557] A "slide presentation" is a presentation document consisting of a series of slides, primarily used in business and educational settings, that is imported from a user's Google account.

[1558] "Means for extracting text" refers to a method for extracting written data from contracts or presentations and converting it into text data for analysis.

[1559] The "means for integrating and generating a draft memorandum of understanding agreement" is a method for automatically generating an initial draft of an agreement by integrating multiple pieces of text information in a consistent manner.

[1560] An "emotion engine" is a technology that analyzes a user's facial expressions and voice, detects their emotional state, and reflects it in the content of a document.

[1561] The "means for displaying a preview" refers to a technique or method for displaying the generated draft on a screen so that the user can check it.

[1562] "Online editor means" refers to a tool or function that allows a user to edit text or document content in real time through an interface such as a browser.

[1563] "OCR technology" is an optical character recognition technology that reads characters from image data and analyzes them as text data.

[1564] "API technology" is an application program interface technology that is an interface that allows different software systems to exchange information with each other.

[1565] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user.

[1566] Importing Data

[1567] The user selects an existing contract (PDF or Word file) from their device and sends it to the server through the system's upload form. Next, the user logs in to their account on a browser, selects a slide presentation, and clicks the import button.

[1568] Data analysis

[1569] The server receives the uploaded existing contract file (PDF or Word) and stores it for analysis. Then, the server obtains access rights to the user's slides through the user's account authentication and downloads the specified presentation data using API technology.

[1570] Data integration

[1571] The server analyzes the existing contract file using OCR technology (for PDF) or direct text extraction (for Word) to extract the contract contents as text data. Next, the server uses API technology to extract text data from each slide of the imported slide presentation. The server then associates the key contract clauses (e.g., contract term, payment terms) extracted from the existing contract with key information from the slide presentation. Finally, the server integrates the extracted data based on a standard contract template to automatically generate a consistent and logical draft memorandum of understanding agreement.

[1572] Generate and preview a draft

[1573] The server uses an emotion engine to generate a draft of the memorandum contract that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server takes into account the emotional information determined by the emotion engine and adjusts the wording and layout accordingly. The generated draft is displayed as a preview to the user.

[1574] User verification and correction

[1575] The user checks the previewed draft and, if necessary, edits it using the online editor. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions. The server saves the user's edits and updates the final draft, incorporating the emotional data.

[1576] Final output

[1577] When the user is satisfied with the draft, they request the output of the final version. The server generates the final version of the MOU in PDF or Word format, reflecting the user's revisions and emotional data, and provides the user with a download link.

[1578] Specific examples

[1579] For example, suppose a user uploads an existing contract (e.g., ContractA.pdf) and also has a sales proposal (e.g., ProposalB) saved in slide format. These files are imported, and information on the "contract period" is extracted from ContractA. Next, important points such as "payment terms" are obtained from ProposalB. As the user reviews the contents of the contract on the preview screen, the emotion engine detects feelings of anxiety or doubt from the user's facial expressions and voice. Based on the emotion data, the server automatically changes the relevant part of the contract to more specific and clear wording and presents it to the user again. In this way, the content of the document is dynamically adjusted according to the user's emotions, providing an environment in which the user can review and modify the contract with confidence.

[1580] This system will not only significantly streamline the contract creation process and enable the rapid creation of accurate and professional documents, but will also provide a more satisfying user experience by taking user emotions into consideration. Utilizing emotion data is also expected to prevent important oversights.

[1581] Example prompts for generative AI models

[1582] An example of a prompt is as follows:

[1583] "Please extract the contract period from the newly uploaded contract file (Contract A.pdf) and the payment terms from the sales proposal slide (Proposal B). Integrate them and generate a draft memorandum of understanding for the user to confirm. Please also reflect the user's sentiment data in real time."

[1584] This system streamlines the complex contract creation process and enables safe and secure document creation that takes users' feelings into consideration.

[1585] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1586] Step 1:

[1587] The user selects an existing contract (PDF or Word file) from their device and sends it to the server through the system's upload form. The input is the existing contract file selected by the user, and the output is that file saved on the server. Specifically, the user opens the system interface, clicks the "Select File" button, and selects and uploads the file from their local device.

[1588] Step 2:

[1589] A user logs in to their account on a browser, selects a slide presentation, and clicks the Import button. The input is the user's login information and the slide file, and the output is the slide file being imported to the server. Specifically, the user clicks the "Log in to Google Account" button, enters the required authentication information, and logs in. Then, the user selects the slide presentation and clicks the "Import" button.

[1590] Step 3:

[1591] The server receives the uploaded existing contract file and temporarily stores it for analysis. The input is the contract file uploaded by the user, and the output is that file stored in a directory for analysis. Specifically, the server detects when the file upload is complete and moves it to a specified directory.

[1592] Step 4:

[1593] The server obtains access to the slides through the user's account authentication and downloads the specified presentation data using API technology. The input is the user's authentication information and the slide presentation ID, and the output is the presentation data stored on the server. Specifically, the server authenticates the user using Google's OAuth and downloads the slide data via the Google Slides API.

[1594] Step 5:

[1595] The server analyzes the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data. The input is the existing contract file and the output is the contract's text data. Specifically, the server starts the OCR engine and performs text extraction on the PDF file. In the case of a Word file, the text data is read directly.

[1596] Step 6:

[1597] The server uses API technology to extract text data from each slide of the imported slide presentation. The input is the slide presentation data, and the output is the slide's text data. Specifically, the server uses the Google Slides API to extract the text content of each slide in order.

[1598] Step 7:

[1599] The server analyzes and correlates important contract terms (e.g., contract period, payment terms) extracted from existing contracts with key information from slide presentations. The input is the text data of the contract and the text data of the slides, and the output is an analysis result that correlates both sets of data. Specifically, the server uses natural language processing technology to analyze the text data and identify and match important keywords and phrases.

[1600] Step 8:

[1601] The server integrates the extracted data based on a standard contract template and automatically generates a consistent and logical draft memorandum of understanding contract. The input is the associated analysis results, and the output is a draft memorandum of understanding contract. Specifically, the server generates a draft based on a preset contract template, embedding important items.

[1602] Step 9:

[1603] The server uses the emotion engine to generate a draft memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. The input is the draft MOU and the user's emotion data, and the output is the finalized draft. Specifically, the server runs the emotion engine and adjusts the document according to the user's emotions.

[1604] Step 10:

[1605] The server previews the generated draft to the user. The input is the finalized draft, and the output is a preview screen displayed on the user's browser. Specifically, the server generates a preview interface and displays the draft to the user.

[1606] Step 11:

[1607] The user checks the previewed draft and, if necessary, edits it using the online editor. The input is the preview screen and the user's edits, and the output is the edited draft. Specifically, the user operates the online editor to edit the text and clicks the save button.

[1608] Step 12:

[1609] The server analyzes the user's emotional changes in real time and displays suggestions or warnings based on the user's emotions. The input is real-time emotional data, and the output is suggestions or warning messages. Specifically, the server continuously operates the emotion engine and provides the user with feedback based on their emotions.

[1610] Step 13:

[1611] The server saves the user's modifications and updates the final draft, which also reflects the emotion data. The input is the modified draft and the emotion data, and the output is the final draft. Specifically, the server generates and saves the final version of the memorandum of understanding that reflects the new information.

[1612] Step 14:

[1613] When the user is satisfied with the draft, they request output of the final version. The input is a preview screen containing the final draft, and the output is the output request. The specific action is that the user clicks the "Output Final Version" button.

[1614] Step 15:

[1615] The server generates a final version of the memorandum of understanding agreement in PDF or Word format that reflects the user's revisions and emotion data, and provides the user with a download link. The input is the final draft and the selection of the output format, and the output is the generation of a download link. Specifically, the server saves the generated document in the specified format and sends the link to the user.

[1616] (Application example 2)

[1617] 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."

[1618] Conventional contract creation systems, when combining existing contracts and presentation materials to generate memorandums of understanding, are unable to consider the user's feelings, potentially overlooking areas that may cause anxiety or doubt. Furthermore, if the created contract is difficult for users to understand, the risk of future problems increases. Furthermore, when reviewing contracts in transportation and traffic management, the limited working environment makes it difficult to properly review and revise the contents of the contract on the spot.

[1619] 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 uploading an existing contract, means for importing a slide presentation, means for extracting text from the existing contract and the slide presentation, means for collecting user emotion data using an in-vehicle camera or microphone, means for automatically adjusting the content of the generated draft based on the collected emotion data, and means for displaying a preview of the generated draft to the user. This makes it possible to dynamically adjust the contract document taking emotion data into consideration when the user checks the content of the contract, providing an environment in which the user can check and modify the contract with peace of mind.

[1620] An "existing contract" is a contract that the user has created or received in the past, and is a document whose contents are used as the basis for a new contract to be created.

[1621] A "slide presentation" is a document created in the form of a slide show to provide information visually, and is particularly used in business negotiations and meetings.

[1622] "Text extraction means" means a technique or method for extracting digital text from an uploaded file.

[1623] The "means for integrating and generating a draft memorandum of understanding agreement" is a technique or method for combining the extracted text information with other related information to automatically generate a draft of a new agreement.

[1624] "Means for collecting user emotional data using an in-vehicle camera or microphone" refers to a device or method for obtaining the user's emotional state from their facial expressions and voice using a camera or microphone installed in the vehicle.

[1625] "Means for automatically adjusting the content of a draft generated based on collected emotional data" refers to a technique or method for automatically changing the content or structure of a document depending on the emotional state of the user.

[1626] The "preview display means" refers to a technique or method for visually displaying the generated draft so that the user can make final confirmation or corrections.

[1627] The present invention relates to a system that automatically generates a draft of a memorandum of understanding (MOU) using an existing contract and a slide presentation, and combines it with an emotion engine that recognizes the user's emotions. This system operates through the interaction of a server, a terminal, and a user. Specific embodiments for carrying out the present invention are described below.

[1628] 1. Importing data

[1629] Terminal: The user selects an existing contract (PDF or Word file) from the terminal and sends it to the server via the system's upload form.

[1630] On the device: The user logs into their Google account on a browser, selects a slide presentation, and clicks the import button to send it to the server.

[1631] 2. Data Analysis

[1632] Server: The server receives the uploaded existing contract file (PDF or Word) and stores it for analysis.

[1633] Server: Obtains access to the user's Google Slides through Google account authentication, and downloads the specified presentation data using the Google Slides API.

[1634] 3. Data integration

[1635] Server: The server analyzes the existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data.

[1636] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1637] Server: Analyzes and correlates key contract clauses extracted from existing contracts with key information from slide presentations.

[1638] Server: Based on a standard contract template, the extracted data is integrated and a consistent and logical draft of the memorandum of understanding contract is automatically generated.

[1639] 4. Generate and preview the draft

[1640] Server: Using the emotion engine, the server generates a draft of the memorandum of understanding (MOU) that includes suggestions and warnings based on the user's emotions. As the user reviews the draft, the server adjusts the wording and layout accordingly, taking into account the emotional information determined by the emotion engine.

[1641] Server: Generates and displays a preview interface to allow the user to preview the generated draft of the memorandum of understanding agreement.

[1642] 5. User confirmation and correction

[1643] On the device: The user previews the draft and edits it using the online editor. The emotion engine analyzes the user's emotional changes in real time and displays suggestions and warnings based on the user's emotions.

[1644] Server: Saves the user's modifications and updates the final draft, taking into account the emotion engine data.

[1645] 6. Final output

[1646] Terminal: When the user is satisfied with the draft, he or she requests a final output.

[1647] Server: Generates the final MOU in PDF or Word format, reflecting the user's modifications and emotional data, and provides a download link to the user.

[1648] The main technologies used in the above process include PyMuPDF (Fitz), Google Slides API, OpenCV, and a proprietary emotion recognition library. For example, if anxiety or anger is detected from the user's facial expression or voice while they are reviewing the contents of a contract, the wording in that section will be automatically changed to more specific and clearer language. This provides an environment where users can review and revise contracts with peace of mind.

[1649] Example prompt sentence:

[1650] When managing contracts for operating autonomous vehicles, please conduct image analysis to check whether the contract holder is showing any emotion such as anxiety or anger while reviewing the contract.

[1651] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1652] Step 1:

[1653] On the terminal: The user selects an existing contract (PDF or Word file) and sends it to the server through the system's upload form. The uploaded file is saved on the server.

[1654] Input: Existing contract (PDF or Word file)

[1655] Output: Agreement file saved on the server

[1656] Step 2:

[1657] On the device: The user logs in to their Google account on a browser, selects a slide presentation, and clicks the import button. The presentation data is sent to the server using the Google Slides API.

[1658] Input: Slide presentation

[1659] Output: Presentation data saved on the server

[1660] Step 3:

[1661] Server: The server analyzes the uploaded existing contract file using OCR technology (in the case of PDF) or direct text extraction (in the case of Word) and extracts the contents of the contract as text data.

[1662] Input: Agreement file stored on the server

[1663] Output: Extracted text data

[1664] Step 4:

[1665] Server: Use the Google Slides API to extract text data from each slide in the imported Slides presentation.

[1666] Input: Presentation data stored on the server

[1667] Output: Extracted slide text data

[1668] Step 5:

[1669] Server: Integrates text data extracted from existing contracts and slide presentations, and automatically generates consistent and logical draft memorandum agreements based on standard contract templates.

[1670] Input: Extracted contract text data, slide text data

[1671] Output: Generated draft MOU agreement

[1672] Step 6:

[1673] Server: Collects user emotion data using in-car cameras or microphones, using facial recognition technology and voice emotion analysis technology.

[1674] Input: User's facial expression data, voice data

[1675] Output: Emotion data

[1676] Step 7:

[1677] Server: Automatically adjusts the content of the generated draft based on the collected sentiment data, specifically by changing the part where the user expresses anxiety or doubt to a clearer, more specific statement.

[1678] Input: Generated draft memorandum of understanding, sentiment data

[1679] Output: Draft of the adjusted MOU agreement

[1680] Step 8:

[1681] Terminal: Generates a preview interface and visually displays the adjusted draft to the user, who can then confirm the contents of the draft.

[1682] Input: Draft of adjusted MOU agreement

[1683] Output: Previewed draft

[1684] Step 9:

[1685] On the device: The user sees a preview of the draft and can edit it using the online editor.

[1686] Input: Previewed draft

[1687] Output: Draft revised by user

[1688] Step 10:

[1689] Server: Saves the user's modifications and updates the final draft taking into account the sentiment data.

[1690] Input: User-edited draft, emotion data

[1691] Output: Final draft

[1692] Step 11:

[1693] Terminal: The user requests the final output, and the server generates the final MOU in PDF or Word format and provides a download link to the user.

[1694] Input: Final Draft

[1695] Output: Final MOU (PDF or Word format) and download link

[1696] 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.

[1697] 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.

[1698] 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.

[1699] 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.

[1700] 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.

[1701] 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.

[1702] 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).

[1703] 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.

[1704] 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."

[1705] 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.

[1706] 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).

[1707] 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.

[1708] 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.

[1709] 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.

[1710] 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.

[1711] 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.

[1712] 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.

[1713] 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.

[1714] 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.

[1715] 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.

[1716] 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.

[1717] The following is further disclosed regarding the above embodiment.

[1718] (Claim 1)

[1719] A means to upload existing contracts;

[1720] A means to import slide presentations;

[1721] means for extracting text from the existing contract and the slide presentation;

[1722] means for integrating the extracted text information to generate a draft memorandum of understanding agreement;

[1723] The system further includes means for displaying a preview of the generated draft to a user.

[1724] (Claim 2)

[1725] online editor means for enabling a user to edit the generated draft;

[1726] 10. The system of claim 1, further comprising means for outputting the edited draft as a final version.

[1727] (Claim 3)

[1728] A means for analyzing the existing contract using an OCR means;

[1729] 10. The system of claim 1, further comprising means for parsing said slide presentation using API means.

[1730] "Example 1"

[1731] (Claim 1)

[1732] A means to upload existing contracts;

[1733] A means to import slide presentations;

[1734] means for extracting text from the existing contract and the slide presentation;

[1735] means for integrating the extracted text information to generate a draft memorandum of understanding agreement;

[1736] means for displaying a preview of the generated draft to a user;

[1737] A method for identifying important contract clauses in existing contracts through text analysis;

[1738] means for associating information extracted from the slide presentation with contract terms;

[1739] A system including a means for placing contract clauses based on defined contract templates.

[1740] (Claim 2)

[1741] online editor means for enabling a user to edit the generated draft;

[1742] 10. The system of claim 1, further comprising means for outputting the edited draft as a final version.

[1743] (Claim 3)

[1744] A means for analyzing the existing contract using an OCR means;

[1745] 10. The system of claim 1, further comprising means for parsing said slide presentation using API means.

[1746] "Application Example 1"

[1747] (Claim 1)

[1748] a means to upload existing documents;

[1749] A means to import presentation materials;

[1750] means for extracting character data from the existing document and the presentation material;

[1751] means for integrating the extracted character data to generate a draft of a document;

[1752] means for displaying a preview of the generated draft to a user through a display device;

[1753] A system including means for using a wearable device as a display device.

[1754] (Claim 2)

[1755] online editing means that allow a user to edit the generated draft;

[1756] 10. The system of claim 1, further comprising means for outputting the edited draft as a final version.

[1757] (Claim 3)

[1758] means for analyzing the existing document using character recognition technology;

[1759] 10. The system of claim 1, further comprising means for parsing the presentation material using application programming interface means.

[1760] "Example 2: Combining Emotion Engines"

[1761] (Claim 1)

[1762] A means to upload existing contracts;

[1763] A means to import slide presentations;

[1764] means for extracting text from the existing contract and the slide presentation;

[1765] means for integrating the extracted text information to generate a draft memorandum of understanding agreement;

[1766] A means for including suggestions and warnings in the draft based on the user's emotions using an emotion engine;

[1767] The system further includes means for displaying a preview of the generated draft to a user.

[1768] (Claim 2)

[1769] online editor means for enabling a user to edit the generated draft;

[1770] 10. The system of claim 1, further comprising means for outputting the edited draft as a final version.

[1771] (Claim 3)

[1772] A means for analyzing the existing contract using OCR technology;

[1773] 10. The system of claim 1, further comprising means for analyzing the slide presentation using API technology.

[1774] "Application example 2 when combining emotion engines"

[1775] (Claim 1)

[1776] A means to upload existing contracts;

[1777] A means to import slide presentations;

[1778] means for extracting text from the existing contract and the slide presentation;

[1779] means for integrating the extracted text information to generate a draft memorandum of understanding agreement;

[1780] means for collecting user emotion data using an in-car camera or microphone;

[1781] means for automatically adjusting the content of the generated draft based on the collected emotion data;

[1782] The system further includes means for displaying a preview of the generated draft to a user.

[1783] (Claim 2)

[1784] online editor means for enabling a user to edit the generated draft;

[1785] 10. The system of claim 1, further comprising means for outputting the edited draft as a final version.

[1786] (Claim 3)

[1787] A means for analyzing the existing contract using an OCR means;

[1788] 10. The system of claim 1, further comprising means for parsing said slide presentation using API means. [Explanation of symbols]

[1789] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means to upload existing contracts; A means to import slide presentations; means for extracting text from the existing contract and the slide presentation; means for integrating the extracted text information to generate a draft memorandum of understanding agreement; The system further includes means for displaying a preview of the generated draft to a user.

2. online editor means for enabling a user to edit the generated draft; 2. The system of claim 1, further comprising means for outputting the edited draft as a final version.

3. A means for analyzing the existing contract using an OCR means; 10. The system of claim 1, further comprising means for parsing said slide presentation using API means.

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